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coronavirus origin | 1 | Virus–Host Coevolution with a Focus on Animal and Human DNA Viruses | Viruses have been infecting their host cells since the dawn of life, and this extremely long-term coevolution gave rise to some surprising consequences for the entire tree of life. It is hypothesised that viruses might have contributed to the formation of the first cellular life form, or that even the eukaryotic cell nucleus originates from an infection by a coated virus. The continuous struggle between viruses and their hosts to maintain at least a constant fitness level led to the development of an unceasing arms race, where weapons are often shuttled between the participants. In this literature review we try to give a short insight into some general consequences or traits of virus–host coevolution, and after this we zoom in to the viral clades of adenoviruses, herpesviruses, nucleo-cytoplasmic large DNA viruses, polyomaviruses and, finally, circoviruses. | 33fs6exl |
coronavirus origin | 1 | Origins of MERS-CoV, and lessons for 2019-nCoV | gyj5213f |
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coronavirus origin | 1 | The Origin and Evolution of Viruses | The lecture covers three main topics: (i) Viruses: properties, place in the living world, and possible origin; (ii) Molecular basis of viral variability and evolution; and (iii) Evolution of viral pathogenicity and emerging viral infections. | gy8d8285 |
coronavirus origin | 1 | Diversity of Coronaviruses in Bats: Insights Into Origin of SARS Coronavirus | 6foz003n |
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coronavirus origin | 1 | Intraspecies diversity of SARS-like coronaviruses in Rhinolophus sinicus and its implications for the origin of SARS coronaviruses in humans. | The Chinese rufous horseshoe bat (Rhinolophus sinicus) has been suggested to carry the direct ancestor of severe acute respiratory syndrome (SARS) coronavirus (SCoV), and the diversity of SARS-like CoVs (SLCoV) within this Rhinolophus species is therefore worth investigating. Here, we demonstrate the remarkable diversity of SLCoVs in R. sinicus and identify a strain with the same pattern of phylogenetic incongruence (i.e. an indication of recombination) as reported previously in another SLCoV strain. Moreover, this strain possesses a distinctive 579 nt deletion in the nsp3 region that was also found in a human SCoV from the late-phase epidemic. Phylogenetic analysis of the Orf1 region suggested that the human SCoVs are phylogenetically closer to SLCoVs in R. sinicus than to SLCoVs in other Rhinolophus species. These findings reveal a closer evolutionary linkage between SCoV in humans and SLCoVs in R. sinicus, defining the scope of surveillance to search for the direct ancestor of human SCoVs. | 0t2a5500 |
coronavirus origin | 1 | Evidence for an Ancestral Association of Human Coronavirus 229E with Bats. | UNLABELLED We previously showed that close relatives of human coronavirus 229E (HCoV-229E) exist in African bats. The small sample and limited genomic characterizations have prevented further analyses so far. Here, we tested 2,087 fecal specimens from 11 bat species sampled in Ghana for HCoV-229E-related viruses by reverse transcription-PCR (RT-PCR). Only hipposiderid bats tested positive. To compare the genetic diversity of bat viruses and HCoV-229E, we tested historical isolates and diagnostic specimens sampled globally over 10 years. Bat viruses were 5- and 6-fold more diversified than HCoV-229E in the RNA-dependent RNA polymerase (RdRp) and spike genes. In phylogenetic analyses, HCoV-229E strains were monophyletic and not intermixed with animal viruses. Bat viruses formed three large clades in close and more distant sister relationships. A recently described 229E-related alpaca virus occupied an intermediate phylogenetic position between bat and human viruses. According to taxonomic criteria, human, alpaca, and bat viruses form a single CoV species showing evidence for multiple recombination events. HCoV-229E and the alpaca virus showed a major deletion in the spike S1 region compared to all bat viruses. Analyses of four full genomes from 229E-related bat CoVs revealed an eighth open reading frame (ORF8) located at the genomic 3' end. ORF8 also existed in the 229E-related alpaca virus. Reanalysis of HCoV-229E sequences showed a conserved transcription regulatory sequence preceding remnants of this ORF, suggesting its loss after acquisition of a 229E-related CoV by humans. These data suggested an evolutionary origin of 229E-related CoVs in hipposiderid bats, hypothetically with camelids as intermediate hosts preceding the establishment of HCoV-229E. IMPORTANCE The ancestral origins of major human coronaviruses (HCoVs) likely involve bat hosts. Here, we provide conclusive genetic evidence for an evolutionary origin of the common cold virus HCoV-229E in hipposiderid bats by analyzing a large sample of African bats and characterizing several bat viruses on a full-genome level. Our evolutionary analyses show that animal and human viruses are genetically closely related, can exchange genetic material, and form a single viral species. We show that the putative host switches leading to the formation of HCoV-229E were accompanied by major genomic changes, including deletions in the viral spike glycoprotein gene and loss of an open reading frame. We reanalyze a previously described genetically related alpaca virus and discuss the role of camelids as potential intermediate hosts between bat and human viruses. The evolutionary history of HCoV-229E likely shares important characteristics with that of the recently emerged highly pathogenic Middle East respiratory syndrome (MERS) coronavirus. | n2o7iiew |
coronavirus origin | 1 | Animal source of the coronavirus continues to elude scientists. | 4mtnqfqw |
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coronavirus origin | 1 | Severe Acute Respiratory Syndrome (SARS) Coronavirus ORF8 Protein Is Acquired from SARS-Related Coronavirus from Greater Horseshoe Bats through Recombination. | UNLABELLED Despite the identification of horseshoe bats as the reservoir of severe acute respiratory syndrome (SARS)-related coronaviruses (SARSr-CoVs), the origin of SARS-CoV ORF8, which contains the 29-nucleotide signature deletion among human strains, remains obscure. Although two SARS-related Rhinolophus sinicus bat CoVs (SARSr-Rs-BatCoVs) previously detected in Chinese horseshoe bats (Rhinolophus sinicus) in Yunnan, RsSHC014 and Rs3367, possessed 95% genome identities to human and civet SARSr-CoVs, their ORF8 protein exhibited only 32.2 to 33% amino acid identities to that of human/civet SARSr-CoVs. To elucidate the origin of SARS-CoV ORF8, we sampled 348 bats of various species in Yunnan, among which diverse alphacoronaviruses and betacoronaviruses, including potentially novel CoVs, were identified, with some showing potential interspecies transmission. The genomes of two betacoronaviruses, SARSr-Rf-BatCoV YNLF_31C and YNLF_34C, from greater horseshoe bats (Rhinolophus ferrumequinum), possessed 93% nucleotide identities to human/civet SARSr-CoV genomes. Although these two betacoronaviruses displayed lower similarities than SARSr-Rs-BatCoV RsSHC014 and Rs3367 in S protein to civet SARSr-CoVs, their ORF8 proteins demonstrated exceptionally high (80.4 to 81.3%) amino acid identities to that of human/civet SARSr-CoVs, compared to SARSr-BatCoVs from other horseshoe bats (23.2 to 37.3%). Potential recombination events were identified around ORF8 between SARSr-Rf-BatCoVs and SARSr-Rs-BatCoVs, leading to the generation of civet SARSr-CoVs. The expression of ORF8 subgenomic mRNA suggested that the ORF8 protein may be functional in SARSr-Rf-BatCoVs. The high Ka/Ks ratio among human SARS-CoVs compared to that among SARSr-BatCoVs supported that ORF8 is under strong positive selection during animal-to-human transmission. Molecular clock analysis using ORF1ab showed that SARSr-Rf-BatCoV YNLF_31C and YNLF_34C diverged from civet/human SARSr-CoVs in approximately 1990. SARS-CoV ORF8 originated from SARSr-CoVs of greater horseshoe bats through recombination, which may be important for animal-to-human transmission. IMPORTANCE Although horseshoe bats are the primary reservoir of SARS-related coronaviruses (SARSr-CoVs), it is still unclear how these bat viruses have evolved to cross the species barrier to infect civets and humans. Most human SARS-CoV epidemic strains contain a signature 29-nucleotide deletion in ORF8, compared to civet SARSr-CoVs, suggesting that ORF8 may be important for interspecies transmission. However, the origin of SARS-CoV ORF8 remains obscure. In particular, SARSr-Rs-BatCoVs from Chinese horseshoe bats (Rhinolophus sinicus) exhibited <40% amino acid identities to human/civet SARS-CoV in the ORF8 protein. We detected diverse alphacoronaviruses and betacoronaviruses among various bat species in Yunnan, China, including two SARSr-Rf-BatCoVs from greater horseshoe bats that possessed ORF8 proteins with exceptionally high amino acid identities to that of human/civet SARSr-CoVs. We demonstrated recombination events around ORF8 between SARSr-Rf-BatCoVs and SARSr-Rs-BatCoVs, leading to the generation of civet SARSr-CoVs. Our findings offer insight into the evolutionary origin of SARS-CoV ORF8 protein, which was likely acquired from SARSr-CoVs of greater horseshoe bats through recombination. | phlxsez8 |
coronavirus origin | 1 | COVID-19-A Novel Zoonotic Disease: A Review of the Disease, the Virus, and Public Health Measures. | A cluster of cases of pneumonia of unknown etiology emerged in Wuhan, China, at the end of December 2019. The cluster was largely associated with a seafood and animal market. A novel Betacoronavirus was quickly identified as the causative agent, and it is shown to be related genetically to SARS-CoV and other bat-borne SARS-related Betacoronaviruses. The number of cases increased rapidly and spread to other provinces in China, as well as to another 4 countries. To help control the spread of the virus, a "cordon sanitaire" was instituted for Wuhan on January 23, 2020, and subsequently extended to other cities in Hubei Province, and the outbreak declared a Public Health Emergency of International Concern by the Director General of the World Health Organization on January 30, 2020. The virus was named SARS-CoV-2 by the International Committee for the Taxonomy of Viruses, and the disease it causes was named COVID-19 by the World Health Organization. This article described the evolution of the outbreak, and the known properties of the novel virus, SARS-CoV-2 and the clinical disease it causes, and the major public health measures being used to help control it's spread. These measures include social distancing, intensive surveillance and quarantining of cases, contact tracing and isolation, cancellation of mass gatherings, and community containment. The virus is the third zoonotic coronavirus, after SARS-CoV and MERS-CoV, but appears to be the only one with pandemic potential. However, a number of important properties of the virus are still not well understood, and there is an urgent need to learn more about its transmission dynamics, its spectrum of clinical severity, its wildlife origin, and its genetic stability. In addition, more research is needed on possible interventions, particularly therapeutic and vaccines. | qkl2yiqa |
coronavirus origin | 1 | COVID-19: animals, veterinary and zoonotic links. | Coronavirus disease 2019 (COVID-19), has spread over 210 countries and territories beyond China shortly. On February 29, 2020, the World Health Organization (WHO) denoted it in a high-risk category, and on March 11, 2020, this virus was designated pandemic, after its declaration being a Public Health International Emergency on January 30, 2020. World over high efforts are being made to counter and contain this virus. The COVID-19 outbreak once again proves the potential of the animal-human interface to act as the primary source of emerging zoonotic diseases. Even though the circumstantial evidence suggests the possibility of an initial zoonotic emergence, it is too early to confirm the role of intermediate hosts such as snakes, pangolins, turtles, and other wild animals in the origin of SARS-CoV-2, in addition to bats, the natural hosts of multiple coronaviruses such as SARS-CoV and MERS-CoV. The lessons learned from past episodes of MERS-CoV and SARS-CoV are being exploited to retort this virus. Best efforts are being taken up by worldwide nations to implement effective diagnosis, strict vigilance, heightened surveillance, and monitoring, along with adopting appropriate preventive and control strategies. Identifying the possible zoonotic emergence and the exact mechanism responsible for its initial transmission will help us to design and implement appropriate preventive barriers against the further transmission of SARS-CoV-2. This review discusses in brief about the COVID-19/SARS-CoV-2 with a particular focus on the role of animals, the veterinary and associated zoonotic links along with prevention and control strategies based on One-health approaches. | 3uvuo4sf |
coronavirus origin | 1 | Global genetic patterns reveal host tropism versus cross-taxon transmission of bat Betacoronaviruses | Emerging infectious diseases due to coronavirus (CoV) infections have received significant global attention in the past decade and have been linked to bats as the original source. The diversity, distribution, and host associations of bat CoVs were investigated to assess their potential for zoonotic transmission. Phylogenetic, network, and principal coordinate analysis confirmed the classification of betacoronaviruses (BetaCoVs) into five groups (2A to 2E) and a potentially novel group, with further division of 2D into five subgroups. The genetic co-clustering of BetaCoVs among closely related bats reflects host taxon-specificity with each bat family as the host for a specific BetaCoV group, potentially a natural barrier against random transmission. The divergent pathway of BetaCoV and host evolution suggests that the viruses were introduced just prior to bat dispersal and speciation. As such, deviant patterns were observed such as for 2D-IV, wherein cross-taxon transmission due to overlap in bat habitats and geographic range among genetically divergent African bat hosts could have played a strong role on their shared CoV lineages. In fact, a few bat taxa especially the subfamily Pteropodinae were shown to host diverse groups of BetaCoVs. Therefore, ecological imbalances that disturb bat distribution may lead to loss of host specificity through cross-taxon transmission and multi-CoV infection. Hence, initiatives that minimize the destruction of wildlife habitats and limit wildlife-livestock-human interfaces are encouraged to help maintain the natural state of bat BetaCoVs in the wild. Importance Bat Betacoronaviruses (BetaCoVs) pose a significant threat to global public health and have been implicated in several epidemics such as the recent pandemic by severe acute respiratory syndrome coronavirus 2. Here, we show that bat BetaCoVs are predominantly host-specific, which could be a natural barrier against infection of other host types. However, a strong overlap in bat habitat and geographic range may facilitate viral transmission to unrelated hosts, and a few bat families have already been shown to host multi-CoV variants. We predict that continued disturbances on the ecological balance may eventually lead to loss of host specificity. When combined with enhanced wildlife-livestock-human interfaces, spillover to humans may be further facilitated. We should therefore start to define the ecological mechanisms surrounding zoonotic events. Global surveillance should be expanded and strengthened to assess the complete picture of bat coronavirus diversity and distribution and their potential to cause spillover infections. | d8n9711b |
coronavirus origin | 1 | 2019 Novel Coronavirus Disease Outbreak and Molecular Genetic Characteristics of Severe Acute Respiratory Syndrome-coronavirus-2 | The 2019 novel coronavirus disease (COVID-19) outbreaks that emerged in Wuhan city, Hubei province, have led to a formidable number of confirmed cases that resulted in >5,700 deaths globally, including 143 countries in all 6 continents. The World Health Organization declared a Public Health Emergency of International Concern with a very high level of global risk assessment. Severe acute respiratory syndrome (SARS)-coronavirus-2 (SARS-CoV-2), the agent of COVID-19, has >79% nucleotide sequence homology to SARS-CoV; therefore, both belong to the genus betacoronavirus and subgenus sarbecovirus. The S1 domains of the two appeared to share the cellular receptor ACE2, but revealed a much higher S1-ACE2 binding affinity. As seen in many other human coronaviruses, SARS-CoV-2 also shows respiratory infection, but the basic reproductive number (R0) in transmission and the clinical latency are quite dissimilar from those of SARS-or MERS-CoVs. Many scientists infer that the time point of cross-barrier transfer from bats to mediate animals or to humans should be a rather recent event based on the full-length genome analyses obtained from the very first patients. Copy-choice polymerization, which often leads to a significant genome recombination rate in most coronaviruses, predicts the continued emergence of novel coronaviruses. | 9a475qhj |
coronavirus origin | 1 | Predicting wildlife hosts of betacoronaviruses for SARS-CoV-2 sampling prioritization | Despite massive investment in research on reservoirs of emerging pathogens, it remains difficult to rapidly identify the wildlife origins of novel zoonotic viruses. Viral surveillance is costly but rarely optimized using model-guided prioritization strategies, and predictions from a single model may be highly uncertain. Here, we generate an ensemble of eight network- and trait-based statistical models that predict mammal-virus associations, and we use model predictions to develop a set of priority recommendations for sampling potential bat reservoirs and intermediate hosts for SARS-CoV-2 and related betacoronaviruses. We find over 200 bat species globally could be undetected hosts of betacoronaviruses. Although over a dozen species of Asian horseshoe bats (Rhinolophus spp.) are known to harbor SARS-like coronaviruses, we find at least two thirds of betacoronavirus reservoirs in this bat genus might still be undetected. Although identification of other probable mammal reservoirs is likely beyond existing predictive capacity, some of our findings are surprisingly plausible; for example, several civet and pangolin species were highlighted as high-priority species for viral sampling. Our results should not be over-interpreted as novel information about the plausibility or likelihood of SARS-CoV-2’s ultimate origin, but rather these predictions could help guide sampling for novel potentially zoonotic viruses; immunological research to characterize key receptors (e.g., ACE2) and identify mechanisms of viral tolerance; and experimental infections to quantify competence of suspected host species. | 9q5zckir |
coronavirus origin | 1 | The origin of SARS-CoV-2 in Istanbul: Sequencing findings from the epicenter of the pandemic in Turkey | OBJECTIVE: Turkey is one of the latest countries that COVID-19 disease was reported, with the first case on March 11, 2020, and since then, Istanbul became the epicenter of the pandemic in Turkey Here, we reveal sequences of the virus isolated from three different patients with various clinical presentations METHODS: Nasopharyngeal swab specimens of the patients were tested positive for the COVID-19 by qRT-PCR Viral RNA extraction was performed from the same swab samples Amplicon based libraries were prepared and sequenced using the Illumina NextSeq platform Raw sequencing data were processed for variant calling and generating near-complete genome sequences All three genomes were evaluated and compared with other worldwide isolates RESULTS: The patients showed various clinics (an asymptomatic patient, patient with mild disease, and with severe pulmonary infiltration) Amplicon-based next-generation sequencing approach successfully applied to generate near-complete genomes with an average depth of 2 616 All three viral genomes carried the D614G variant (G clade according to GISAID classification) with implications for the origin of a spread first through China to Europe then to Istanbul CONCLUSION: Here, we report the viral genomes circulating in Istanbul for the first time Further sequencing of the virus isolates may enable us to understand variations in disease presentation and association with viral factors if there is any In addition, the sequencing of more viral genomes will delineate the spread of disease and will guide and ease the necessary measures taken to stem the spread of the novel coronavirus | 9mrtic2k |
coronavirus origin | 1 | Animal origins of SARS coronavirus: possible links with the international trade in small carnivores. | The search for animal host origins of severe acute respiratory syndrome (SARS) coronavirus has so far remained focused on wildlife markets, restaurants and farms within China. A significant proportion of this wildlife enters China through an expanding regional network of illegal, international wildlife trade. We present the case for extending the search for ancestral coronaviruses and their hosts across international borders into countries such as Vietnam and Lao People's Democratic Republic, where the same guilds of species are found on sale in similar wildlife markets or food outlets. The three species that have so far been implicated, a viverrid, a mustelid and a canid, are part of a large suite of small carnivores distributed across this region currently overexploited by this international wildlife trade. A major lesson from SARS is that the underlying roots of newly emergent zoonotic diseases may lie in the parallel biodiversity crisis of massive species loss as a result of overexploitation of wild animal populations and the destruction of their natural habitats by increasing human populations. To address these dual threats to the long-term future of biodiversity, including man, requires a less anthropocentric and more interdisciplinary approach to problems that require the combined research expertise of ecologists, conservation biologists, veterinarians, epidemiologists, virologists, as well as human health professionals. | ur4eua83 |
coronavirus origin | 1 | Mosaic evolution of the severe acute respiratory syndrome coronavirus. | Severe acute respiratory syndrome (SARS) is a deadly form of pneumonia caused by a novel coronavirus, a viral family responsible for mild respiratory tract infections in a wide variety of animals including humans, pigs, cows, mice, cats, and birds. Analyses to date have been unable to identify the precise origin of the SARS coronavirus. We used Bayesian, neighbor-joining, and split decomposition phylogenetic techniques on the SARS virus replicase, surface spike, matrix, and nucleocapsid proteins to reveal the evolutionary origin of this recently emerging infectious agent. The analyses support a mammalian-like origin for the replicase protein, an avian-like origin for the matrix and nucleocapsid proteins, and a mammalian-avian mosaic origin for the host-determining spike protein. A bootscan recombination analysis of the spike gene revealed high nucleotide identity between the SARS virus and a feline infectious peritonitis virus throughout the gene, except for a 200- base-pair region of high identity to an avian sequence. These data support the phylogenetic analyses and suggest a possible past recombination event between mammalian-like and avian-like parent viruses. This event occurred near a region that has been implicated to be the human receptor binding site and may have been directly responsible for the switch of host of the SARS coronavirus from animals to humans. | 8ccl9aui |
coronavirus origin | 1 | Evidence of the recombinant origin of a bat severe acute respiratory syndrome (SARS)-like coronavirus and its implications on the direct ancestor of SARS coronavirus. | Bats have been identified as the natural reservoir of severe acute respiratory syndrome (SARS)-like and SARS coronaviruses (SLCoV and SCoV). However, previous studies suggested that none of the currently sampled bat SLCoVs is the descendant of the direct ancestor of SCoV, based on their relatively distant phylogenetic relationship. In this study, evidence of the recombinant origin of the genome of a bat SLCoV is demonstrated. We identified a potential recombination breakpoint immediately after the consensus intergenic sequence between open reading frame 1 and the S coding region, suggesting the replication intermediates may participate in the recombination event, as previously speculated for other CoVs. Phylogenetic analysis of its parental regions suggests the presence of an uncharacterized SLCoV lineage that is phylogenetically closer to SCoVs than any of the currently sampled bat SLCoVs. Using various Bayesian molecular-clock models, interspecies transfer of this SLCoV lineage from bats to the amplifying host (e.g., civets) was estimated to have happened a median of 4.08 years before the SARS outbreak. Based on this relatively short window period, we speculate that this uncharacterized SLCoV lineage may contain the direct ancestor of SCoV. This study sheds light on the possible host bat species of the direct ancestor of SCoV, providing valuable information on the scope and focus of surveillance for the origin of SCoV. | 6zfmjq9p |
coronavirus origin | 1 | SARS coronavirus without reservoir originated from an unnatural evolution, experienced the reverse evolution, and finally disappeared in the world. | jdpxu0ef |
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coronavirus origin | 1 | [Source of the COVID-19 pandemic: ecology and genetics of coronaviruses (Betacoronavirus: Coronaviridae) SARS-CoV, SARS-CoV-2 (subgenus Sarbecovirus), and MERS-CoV (subgenus Merbecovirus).] | Since the early 2000s, three novel zooanthroponous coronaviruses (Betacoronavirus) have emerged. The first outbreak of infection (SARS) caused by SARS-CoV virus occurred in the fall of 2002 in China (Guangdong Province). A second outbreak (MERS) associated with the new MERS-CoV virus appeared in Saudi Arabia in autumn 2012. The third epidemic, which turned into a COVID-19 pandemic caused by SARS-CoV-2 virus, emerged in China (Hubei Province) in the autumn 2019. This review focuses on ecological and genetic aspects that lead to the emergence of new human zoanthroponous coronaviruses. The main mechanism of adaptation of zoonotic betacoronaviruses to humans is to changes in the receptor-binding domain of surface protein (S), as a result of which it gains the ability to bind human cellular receptors of epithelial cells in respiratory and gastrointestinal tract. This process is caused by the high genetic diversity and variability combined with frequent recombination, during virus circulation in their natural reservoir - bats (Microchiroptera, Chiroptera). Appearance of SARS-CoV, SARS-CoV-2 (subgenus Sarbecovirus), and MERS (subgenus Merbecovirus) viruses is a result of evolutionary events occurring in bat populations with further transfer of viruses to the human directly or through the intermediate vertebrate hosts, ecologically connected with bats. This review is based on the report at the meeting «Coronavirus - a global challenge to science¼ of the Scientific Council «Life Science¼ of the Russian Academy of Science: Lvov D.K., Alkhovsky S.V., Burtseva E.I. COVID-19 pandemic sources: origin, biology and genetics of coronaviruses of SARS-CoV, SARS-CoV-2, MERS-CoV (Conference hall of Presidium of RAS, 14 Leninsky Prospect, Moscow, Russia. April 16, 2020). | ia3rct46 |
coronavirus origin | 1 | Novel human coronavirus (SARS-CoV-2): A lesson from animal coronaviruses | The recent pandemic caused by the novel human coronavirus, referrred to as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), not only is having a great impact on the health care systems and economies in all continents but it is also causing radical changes of common habits and life styles. The novel coronavirus (CoV) recognises, with high probability, a zoonotic origin but the role of animals in the SARS-CoV-2 epidemiology is still largely unknown. However, CoVs have been known in animals since several decades, so that veterinary coronavirologists have a great expertise on how to face CoV infections in animals, which could represent a model for SARS-CoV-2 infection in humans. In the present paper, we provide an up-to-date review of the literature currently available on animal CoVs, focusing on the molecular mechanisms that are responsible for the emergence of novel CoV strains with different antigenic, biologic and/or pathogenetic features. A full comprehension of the mechanisms driving the evolution of animal CoVs will help better understand the emergence, spreading, and evolution of SARS-CoV-2. | su8czd4x |
coronavirus origin | 1 | COVID-19: Epidemiology, Evolution, and Cross-Disciplinary Perspectives | The recent outbreak of COVID-19 in Wuhan turned into a public health emergency of international concern. With no antiviral drugs nor vaccines, and the presence of carriers without obvious symptoms, traditional public health intervention measures are significantly less effective. Here, we report the epidemiological and virological characteristics of the COVID-19 outbreak. Originated in bats, 2019-nCoV/ severe acute respiratory syndrome coronavirus (SARS-CoV)-2 likely experienced adaptive evolution in intermediate hosts before transfer to humans at a concentrated source of transmission. Similarities of receptor sequence binding to 2019-nCoV between humans and animals suggest a low species barrier for transmission of the virus to farm animals. We propose, based on the One Health model, that veterinarians and animal specialists should be involved in a cross-disciplinary collaboration in the fight against this epidemic. | oi0zsdtd |
coronavirus origin | 1 | Cross-species transmission of the newly identified coronavirus 2019-nCoV | The current outbreak of viral pneumonia in the city of Wuhan, China, was caused by a novel coronavirus designated 2019-nCoV by the World Health Organization, as determined by sequencing the viral RNA genome. Many initial patients were exposed to wildlife animals at the Huanan seafood wholesale market, where poultry, snake, bats, and other farm animals were also sold. To investigate possible virus reservoir, we have carried out comprehensive sequence analysis and comparison in conjunction with relative synonymous codon usage (RSCU) bias among different animal species based on the 2019-nCoV sequence. Results obtained from our analyses suggest that the 2019-nCoV may appear to be a recombinant virus between the bat coronavirus and an origin-unknown coronavirus. The recombination may occurred within the viral spike glycoprotein, which recognizes a cell surface receptor. Additionally, our findings suggest that 2019-nCoV has most similar genetic information with bat coronovirus and most similar codon usage bias with snake. Taken together, our results suggest that homologous recombination may occur and contribute to the 2019-nCoV cross-species transmission. | niytf3wo |
coronavirus origin | 1 | 2019_nCoV/SARS-CoV-2: rapid classification of betacoronaviruses and identification of Traditional Chinese Medicine as potential origin of zoonotic coronaviruses | The current outbreak of a novel severe acute respiratory syndrome-like coronavirus, 2019_nCoV (now named SARS-CoV-2), illustrated difficulties in identifying a novel coronavirus and its natural host, as the coding sequences of various Betacoronavirus species can be highly diverse. By means of whole-genome sequence comparisons, we demonstrate that the noncoding flanks of the viral genome can be used to correctly separate the recognized four betacoronavirus subspecies. The conservation would be sufficient to define target sequences that could, in theory, classify novel virus species into their subspecies. Only 253 upstream noncoding sequences of Sarbecovirus are sufficient to identify genetic similarities between species of this subgenus. Furthermore, it was investigated which bat species have commercial value in China, and would thus likely be handled for trading purposes. A number of coronavirus genomes have been published that were obtained from such bat species. These bats are used in Traditional Chinese Medicine, and their handling poses a potential risk to cause zoonotic coronavirus epidemics. SIGNIFICANCE AND IMPACT OF THE STUDY: The noncoding upstream and downstream flanks of coronavirus genomes allow for rapid classification of novel Betacoronavirus species and correct identification of genetic relationships. Although bats are the likely natural host of 2019_nCoV, the exact bat species that serves as the natural host of the virus remains as yet unknown. Chinese bat species with commercial value were identified as natural reservoirs of coronaviruses and are used in Traditional Chinese Medicine. Since their trading provides a potential risk for spreading zoonoses, a change in these practices is highly recommended. | ex7rta8f |
coronavirus origin | 1 | Spillover of SARS-CoV-2 into novel wild hosts in North America: A conceptual model for perpetuation of the pathogen | There is evidence that the current outbreak of the novel coronavirus SARS-CoV-2, which causes COVID-19, is of animal origin. As with a number of zoonotic pathogens, there is a risk of spillover into novel hosts. Here, we propose a hypothesized conceptual model that illustrates the mechanism whereby the SARS-CoV-2 could spillover from infected humans to naive wildlife hosts in North America. This proposed model is premised on transmission of SARS-CoV-2 from human feces through municipal waste water treatment plants into the natural aquatic environment where potential wildlife hosts become infected. We use the existing literature on human coronaviruses, including SARS CoV, to support the potential pathways and mechanisms in the conceptual model. Although we focus on North America, our conceptual model could apply to other parts of the globe as well. | lhh2b4r0 |
coronavirus origin | 1 | Origin and evolution of the 2019 novel coronavirus | xwi9pdd2 |
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coronavirus origin | 1 | Response to "Comments on "Homologous recombination within the spike glycoprotein of the newly identified coronavirus may boost cross-species transmission from snake to human" and "Codon bias analysis alone is uninformative for identifying host(s) of new virus" | We have recently reported for the first time that SARS-CoV-2 maybe a bat-originated coronavirus with a recombination occurred within the spike (S) protein gene based on phylogenetic and simplot analyses1 . These two conclusions are supported by findings recently reported by others and are well accepted in the field of SARS-CoV-2 research2-4 . This article is protected by copyright. All rights reserved. | 3x2psny9 |
coronavirus origin | 1 | Mystery deepens over animal source of coronavirus | 3840bxvn |
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coronavirus origin | 1 | A pneumonia outbreak associated with a new coronavirus of probable bat origin | Since the outbreak of severe acute respiratory syndrome (SARS) 18 years ago, a large number of SARS-related coronaviruses (SARSr-CoVs) have been discovered in their natural reservoir host, bats1-4. Previous studies have shown that some bat SARSr-CoVs have the potential to infect humans5-7. Here we report the identification and characterization of a new coronavirus (2019-nCoV), which caused an epidemic of acute respiratory syndrome in humans in Wuhan, China. The epidemic, which started on 12 December 2019, had caused 2,794 laboratory-confirmed infections including 80 deaths by 26 January 2020. Full-length genome sequences were obtained from five patients at an early stage of the outbreak. The sequences are almost identical and share 79.6% sequence identity to SARS-CoV. Furthermore, we show that 2019-nCoV is 96% identical at the whole-genome level to a bat coronavirus. Pairwise protein sequence analysis of seven conserved non-structural proteins domains show that this virus belongs to the species of SARSr-CoV. In addition, 2019-nCoV virus isolated from the bronchoalveolar lavage fluid of a critically ill patient could be neutralized by sera from several patients. Notably, we confirmed that 2019-nCoV uses the same cell entry receptor-angiotensin converting enzyme II (ACE2)-as SARS-CoV. | w53u5ive |
coronavirus origin | 1 | COVID-19 and veterinarians for one health, zoonotic- and reverse-zoonotic transmissions | A novel coronavirus emerged in human populations and spread rapidly to cause the global coronavirus disease 2019 pandemic. Although the origin of the associated virus (severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2]) remains unclear, genetic evidence suggests that bats are a reservoir host of the virus, and pangolins are a probable intermediate. SARS-CoV-2 has crossed the species barrier to infect humans and other animal species, and infected humans can facilitate reverse-zoonotic transmission to animals. Considering the rapidly changing interconnections among people, animals, and ecosystems, traditional roles of veterinarians should evolve to include transdisciplinary roles. | 3jgedokv |
coronavirus origin | 1 | Genomic variance of the 2019-nCoV coronavirus | There is a rising global concern for the recently emerged novel coronavirus (2019-nCoV). Full genomic sequences have been released by the worldwide scientific community in the last few weeks to understand the evolutionary origin and molecular characteristics of this virus. Taking advantage of all the genomic information currently available, we constructed a phylogenetic tree including also representatives of other coronaviridae, such as Bat coronavirus (BCoV) and severe acute respiratory syndrome. We confirm high sequence similarity (>99%) between all sequenced 2019-nCoVs genomes available, with the closest BCoV sequence sharing 96.2% sequence identity, confirming the notion of a zoonotic origin of 2019-nCoV. Despite the low heterogeneity of the 2019-nCoV genomes, we could identify at least two hypervariable genomic hotspots, one of which is responsible for a Serine/Leucine variation in the viral ORF8-encoded protein. Finally, we perform a full proteomic comparison with other coronaviridae, identifying key aminoacidic differences to be considered for antiviral strategies deriving from previous anti-coronavirus approaches. | uaoyounl |
coronavirus origin | 1 | Zoonotic origins of human coronaviruses | Mutation and adaptation have driven the co-evolution of coronaviruses (CoVs) and their hosts, including human beings, for thousands of years. Before 2003, two human CoVs (HCoVs) were known to cause mild illness, such as common cold. The outbreaks of severe acute respiratory syndrome (SARS) and the Middle East respiratory syndrome (MERS) have flipped the coin to reveal how devastating and life-threatening an HCoV infection could be. The emergence of SARS-CoV-2 in central China at the end of 2019 has thrusted CoVs into the spotlight again and surprised us with its high transmissibility but reduced pathogenicity compared to its sister SARS-CoV. HCoV infection is a zoonosis and understanding the zoonotic origins of HCoVs would serve us well. Most HCoVs originated from bats where they are non-pathogenic. The intermediate reservoir hosts of some HCoVs are also known. Identifying the animal hosts has direct implications in the prevention of human diseases. Investigating CoV-host interactions in animals might also derive important insight on CoV pathogenesis in humans. In this review, we present an overview of the existing knowledge about the seven HCoVs, with a focus on the history of their discovery as well as their zoonotic origins and interspecies transmission. Importantly, we compare and contrast the different HCoVs from a perspective of virus evolution and genome recombination. The current CoV disease 2019 (COVID-19) epidemic is discussed in this context. In addition, the requirements for successful host switches and the implications of virus evolution on disease severity are also highlighted. | dnla56uh |
coronavirus origin | 1 | Identification of a novel coronavirus causing severe pneumonia in human: a descriptive study | BACKGROUND: Human infections with zoonotic coronaviruses (CoVs), including severe acute respiratory syndrome (SARS)-CoV and Middle East respiratory syndrome (MERS)-CoV, have raised great public health concern globally. Here, we report a novel bat-origin CoV causing severe and fatal pneumonia in humans. METHODS: We collected clinical data and bronchoalveolar lavage (BAL) specimens from five patients with severe pneumonia from Wuhan Jinyintan Hospital, Hubei province, China. Nucleic acids of the BAL were extracted and subjected to next-generation sequencing. Virus isolation was carried out, and maximum-likelihood phylogenetic trees were constructed. RESULTS: Five patients hospitalized from December 18 to December 29, 2019 presented with fever, cough, and dyspnea accompanied by complications of acute respiratory distress syndrome. Chest radiography revealed diffuse opacities and consolidation. One of these patients died. Sequence results revealed the presence of a previously unknown ß-CoV strain in all five patients, with 99.8% to 99.9% nucleotide identities among the isolates. These isolates showed 79.0% nucleotide identity with the sequence of SARS-CoV (GenBank NC_004718) and 51.8% identity with the sequence of MERS-CoV (GenBank NC_019843). The virus is phylogenetically closest to a bat SARS-like CoV (SL-ZC45, GenBank MG772933) with 87.6% to 87.7% nucleotide identity, but is in a separate clade. Moreover, these viruses have a single intact open reading frame gene 8, as a further indicator of bat-origin CoVs. However, the amino acid sequence of the tentative receptor-binding domain resembles that of SARS-CoV, indicating that these viruses might use the same receptor. CONCLUSION: A novel bat-borne CoV was identified that is associated with severe and fatal respiratory disease in humans. | klzen04m |
coronavirus origin | 1 | Detection of novel coronaviruses in bats in Myanmar | The recent emergence of bat-borne zoonotic viruses warrants vigilant surveillance in their natural hosts. Of particular concern is the family of coronaviruses, which includes the causative agents of severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS), and most recently, Coronavirus Disease 2019 (COVID-19), an epidemic of acute respiratory illness originating from Wuhan, China in December 2019. Viral detection, discovery, and surveillance activities were undertaken in Myanmar to identify viruses in animals at high risk contact interfaces with people. Free-ranging bats were captured, and rectal and oral swabs and guano samples collected for coronaviral screening using broadly reactive consensus conventional polymerase chain reaction. Sequences from positives were compared to known coronaviruses. Three novel alphacoronaviruses, three novel betacoronaviruses, and one known alphacoronavirus previously identified in other southeast Asian countries were detected for the first time in bats in Myanmar. Ongoing land use change remains a prominent driver of zoonotic disease emergence in Myanmar, bringing humans into ever closer contact with wildlife, and justifying continued surveillance and vigilance at broad scales. | yon280y8 |
coronavirus origin | 1 | Possible Bat Origin of Severe Acute Respiratory Syndrome Coronavirus 2 | We showed that severe acute respiratory syndrome coronavirus 2 is probably a novel recombinant virus. Its genome is closest to that of severe acute respiratory syndrome-related coronaviruses from horseshoe bats, and its receptor-binding domain is closest to that of pangolin viruses. Its origin and direct ancestral viruses have not been identified. | kqqantwg |
coronavirus origin | 1 | Zoonotic origins of human coronavirus 2019 (HCoV-19 / SARS-CoV-2): why is this work important? | The ongoing pandemic of coronavirus disease 2019 (COVID-19), caused by infection with human coronavirus 2019 (HCoV-19 / SARS-CoV-2 / 2019-nCoV), is a global threat to the human population. Here, we briefly summarize the available data for the zoonotic origins of HCoV-19, with reference to the other two epidemics of highly virulent coronaviruses, SARS-CoV and MERS-CoV, which cause severe pneumonia in humans. We propose to intensify future efforts for tracing the origins of HCoV-19, which is a very important scientific question for the control and prevention of the pandemic. | 75773gwg |
coronavirus origin | 1 | Master Regulator Analysis of the SARS-CoV-2/Human Interactome | The recent epidemic outbreak of a novel human coronavirus called SARS-CoV-2 causing the respiratory tract disease COVID-19 has reached worldwide resonance and a global effort is being undertaken to characterize the molecular features and evolutionary origins of this virus. In this paper, we set out to shed light on the SARS-CoV-2/host receptor recognition, a crucial factor for successful virus infection. Based on the current knowledge of the interactome between SARS-CoV-2 and host cell proteins, we performed Master Regulator Analysis to detect which parts of the human interactome are most affected by the infection. We detected, amongst others, affected apoptotic and mitochondrial mechanisms, and a downregulation of the ACE2 protein receptor, notions that can be used to develop specific therapies against this new virus. | tvoxbi3q |
coronavirus origin | 1 | Coronaviruses: origin and evolution | jkejiuf2 |
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coronavirus origin | 1 | Mapping the genomic landscape & diversity of COVID-19 based on >3950 clinical isolates of SARS-CoV-2: Likely origin & transmission dynamics of isolates sequenced in India | q8dq3alv |
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coronavirus origin | 1 | Pangolins Harbor SARS-CoV-2-Related Coronaviruses | The pandemic of coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 has posed a severe threat to global public health. Yet, the origin of SARS-CoV-2 remains mysterious. Several recent studies (e.g., Lam et al.,Xiao et al.) identified SARS-CoV-2-related viruses in pangolins, providing novel insights into the evolution and diversity of SARS-CoV-2-related viruses. | pfv7q4v6 |
coronavirus origin | 1 | Genomic characterization and infectivity of a novel SARS-like coronavirus in Chinese bats | SARS coronavirus (SARS-CoV), the causative agent of the large SARS outbreak in 2003, originated in bats. Many SARS-like coronaviruses (SL-CoVs) have been detected in bats, particularly those that reside in China, Europe, and Africa. To further understand the evolutionary relationship between SARS-CoV and its reservoirs, 334 bats were collected from Zhoushan city, Zhejiang province, China, between 2015 and 2017. PCR amplification of the conserved coronaviral protein RdRp detected coronaviruses in 26.65% of bats belonging to this region, and this number was influenced by seasonal changes. Full genomic analyses of the two new SL-CoVs from Zhoushan (ZXC21 and ZC45) showed that their genomes were 29,732 nucleotides (nt) and 29,802 nt in length, respectively, with 13 open reading frames (ORFs). These results revealed 81% shared nucleotide identity with human/civet SARS CoVs, which was more distant than that observed previously for bat SL-CoVs in China. Importantly, using pathogenic tests, we found that the virus can reproduce and cause disease in suckling rats, and further studies showed that the virus-like particles can be observed in the brains of suckling rats by electron microscopy. Thus, this study increased our understanding of the genetic diversity of the SL-CoVs carried by bats and also provided a new perspective to study the possibility of cross-species transmission of SL-CoVs using suckling rats as an animal model. | vp1r00m9 |
coronavirus origin | 1 | The virus whose family expanded | The discovery of many new species of hepaciviruses and pegiviruses, which exhibit enormous genetic diversity, in wild rodent and bat populations might help us to understand the origins of the hepatitis C virus. | nw0jbs1s |
coronavirus origin | 1 | Comments to the predecessor of human SARS coronavirus in 2003–2004 epidemic | xa8b1nuo |
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coronavirus origin | 1 | 2019-nCoV in context: lessons learned? | oxs4o9xe |
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coronavirus origin | 1 | Host-related nucleotide composition and codon usage as driving forces in the recent evolution of the Astroviridae | Abstract The evolutionary history of the Astroviridae comprises the ancient separation between avian and mammalian astrovirus lineages followed by diversification among mammalian astroviruses. The latter process included several cross-species transmissions. We found that the recent, but not the ancient, evolution of astroviruses was associated with a switch in nucleotide composition and codon usage among non-human mammalian versus human/avian astroviruses. Virus and hosts phylogenies based on codon usage agreed with each other and matched the hosts' evolutionary emergence order. This recent switch in driving forces acting at the synonymous level points to the adaptation of codon usage by viruses to that of their hosts after cross-species transmissions. This is the first demonstration of nucleotide composition and codon usage being active driving forces during the recent evolutionary history of a virus group in the host–parasite system. | vlpdirjs |
coronavirus origin | 1 | Exceptional diversity and selection pressure on SARS-CoV and SARS-CoV-2 host receptor in bats compared to other mammals | Pandemics originating from pathogen transmission between animals and humans highlight the broader need to understand how natural hosts have evolved in response to emerging human pathogens and which groups may be susceptible to infection. Here, we investigate angiotensin-converting enzyme 2 (ACE2), the host protein bound by SARS-CoV and SARS-CoV-2. We find that the ACE2 gene is under strong selection pressure in bats, the group in which the progenitors of SARS-CoV and SARS-CoV-2 are hypothesized to have evolved, particularly in residues that contact SARS-CoV and SARS-CoV-2. We detect positive selection in non-bat mammals in ACE2 but in a smaller proportion of branches than in bats, without enrichment of selection in residues that contact SARS-CoV or SARS-CoV-2. Additionally, we evaluate similarity between humans and other species in residues that contact SARS-CoV or SARS-CoV-2, revealing potential susceptible species but also highlighting the difficulties of predicting spillover events. This work increases our understanding of the relationship between mammals, particularly bats, and coronaviruses, and provides data that can be used in functional studies of how host proteins are bound by SARS-CoV and SARS-CoV-2 strains. | ijsn8d7b |
coronavirus origin | 1 | Newly identified viral genomes in pangolins with fatal disease | Epizootic pathogens pose a major threat to many wildlife species, particularly in the context of rapidly changing environments. Pangolins (order Pholidota) are highly threatened mammals, in large part due to the trade in illegal wildlife. During July to August 2018 four sick wild pangolins (three Manis javanica and one Manis pentadactyla) exhibiting a variety of clinical symptoms were rescued by the Jinhua Wildlife Protection Station in Zhejiang province, China. Although three of these animals died, fortunately one recovered after 2 weeks of symptomatic treatment. Using meta-transcriptomics combined with reverse transcription polymerase chain reaction (RT-PCR), we identified two novel RNA viruses in two of the dead pangolins. Genomic analysis revealed that these viruses were most closely related to pestiviruses and coltiviruses, although still highly genetically distinct, with more than 48 and 25 per cent sequence divergence at the amino acid level, respectively. We named these Dongyang pangolin virus (DYPV) and Lishui pangolin virus (LSPV) based on the sampling site and hosts. Although coltiviruses (LSPV) are known to be transmitted by ticks, we found no evidence of LSPV in ticks sampled close to where the pangolins were collected. In addition, although DYPV was present in nymph ticks (Amblyomma javanense) collected from a diseased pangolin, they were not found in the local tick population. Epidemiological investigation revealed that both novel viruses might have been imported following the illegal international trade of pangolins. Hence, these data indicate that illegal wildlife trafficking not only threatens the status of pangolin populations, but may also spread epizootic pathogens. | h3imwhss |
coronavirus origin | 1 | Origins of major human infectious diseases | Many of the major human infectious diseases, including some now confined to humans and absent from animals, are ‘new’ ones that arose only after the origins of agriculture. Where did they come from? Why are they overwhelmingly of Old World origins? Here we show that answers to these questions are different for tropical and temperate diseases; for instance, in the relative importance of domestic animals and wild primates as sources. We identify five intermediate stages through which a pathogen exclusively infecting animals may become transformed into a pathogen exclusively infecting humans. We propose an initiative to resolve disputed origins of major diseases, and a global early warning system to monitor pathogens infecting individuals exposed to wild animals. SUPPLEMENTARY INFORMATION: The online version of this article (doi:10.1038/nature05775) contains supplementary material, which is available to authorized users. | a1chcrk8 |
coronavirus origin | 1 | A Mathematical Model of the Evolution and Spread of Pathogenic Coronaviruses from Natural Host to Human Host | Coronaviruses are highly transmissible and are pathogenic viruses of the 21(st) century worldwide. In general, these viruses are originated in bats or rodents. At the same time, the transmission of the infection to the human host is caused by domestic animals that represent in the habitat the intermediate host. In this study, we review the currently collected information about coronaviruses and establish a model of differential equations with piecewise constant arguments to discuss the spread of the infection from the natural host to the intermediate, and from them to the human host, while we focus on the potential spillover of bat-borne coronaviruses. The local stability of the positive equilibrium point of the model is considered via the Linearized Stability Theorem. Besides, we discuss global stability by employing an appropriate Lyapunov function. To analyze the outbreak in early detection, we incorporate the Allee effect at time t and obtain stability conditions for the dynamical behavior. Furthermore, it is shown that the model demonstrates the Neimark-Sacker Bifurcation. Finally, we conduct numerical simulations to support the theoretical findings. | afx977mr |
coronavirus origin | 1 | Common RNA replication signals exist among group 2 coronaviruses: evidence for in vivo recombination between animal and human coronavius molecules | Abstract 5′ and 3′ UTR sequences on the coronavirus genome are known to carry cis-acting elements for DI RNA replication and presumably also virus genome replication. 5′ UTR-adjacent coding sequences are also thought to harbor cis-acting elements. Here we have determined the 5′ UTR and adjacent 289-nt sequences, and 3′ UTR sequences, for six group 2 coronaviruses and have compared them to each other and to three previously reported group 2 members. Extensive regions of highly similar UTR sequences were found but small regions of divergence were also found indicating group 2 coronaviruses could be subdivided into those that are bovine coronavirus (BCoV)-like (BCoV, human respiratory coronavirus-OC43, human enteric coronavirus, porcine hemagglutinating encephalomyelitis virus, and equine coronavirus) and those that are murine hepatitis virus (MHV)-like (A59, 2, and JHM strains of MHV, puffinosis virus, and rat sialodacryoadenitis virus). The 3′ UTRs of BCoV and MHV have been previously shown to be interchangeable. Here, a reporter-containing BCoV DI RNA was shown to be replicated by all five BCoV-like helper viruses and by MHV-H2 (a human cell-adapted MHV strain), a representative of the MHV-like subgroup, demonstrating group 2 common 5′ and 3′ replication signaling elements. BCoV DI RNA, furthermore, acquired the leader of HCoV-OC43 by leader switching, demonstrating for the first time in vivo recombination between animal and human coronavirus molecules. These results indicate that common replication signaling elements exist among group 2 coronaviruses despite a two-cluster pattern within the group and imply there could exist a high potential for recombination among group members. | 2l4xxu3v |
coronavirus origin | 1 | Isolation and Characterization of 2019-nCoV-like Coronavirus from Malayan Pangolins | The outbreak of 2019-nCoV in the central Chinese city of Wuhan at the end of 2019 poses unprecedent public health challenges to both China and the rest world1. The new coronavirus shares high sequence identity to SARS-CoV and a newly identified bat coronavirus2. While bats may be the reservoir host for various coronaviruses, whether 2019-nCoV has other hosts is still ambiguous. In this study, one coronavirus isolated from Malayan pangolins showed 100%, 98.2%, 96.7% and 90.4% amino acid identity with 2019-nCoV in the E, M, N and S genes, respectively. In particular, the receptor-binding domain of the S protein of the Pangolin-CoV is virtually identical to that of 2019-nCoV, with one amino acid difference. Comparison of available genomes suggests 2019-nCoV might have originated from the recombination of a Pangolin-CoV-like virus with a Bat-CoV-RaTG13-like virus. Infected pangolins showed clinical signs and histopathological changes, and the circulating antibodies reacted with the S protein of 2019-nCoV. The isolation of a coronavirus that is highly related to 2019-nCoV in the pangolins suggests that these animals have the potential to act as the intermediate host of 2019-nCoV. The newly identified coronavirus in the most-trafficked mammal could represent a continuous threat to public health if wildlife trade is not effectively controlled. | mw0wb8a8 |
coronavirus response to weather changes | 2 | Effect modification of environmental factors on influenza-associated mortality: a time-series study in two Chinese cities | BACKGROUND: Environmental factors have been associated with transmission and survival of influenza viruses but no studies have ever explored the role of environmental factors on severity of influenza infection. METHODS: We applied a Poisson regression model to the mortality data of two Chinese metropolitan cities located within the subtropical zone, to calculate the influenza associated excess mortality risks during the periods with different levels of temperature and humidity. RESULTS: The results showed that high absolute humidity (measured by vapor pressure) was significantly (p < 0.05) associated with increased risks of all-cause and cardiorespiratory deaths, but not with increased risks of pneumonia and influenza deaths. The association between absolute humidity and mortality risks was found consistent among the two cities. An increasing pattern of influenza associated mortality risks was also found across the strata of low to high relative humidity, but the results were less consistent for temperature. CONCLUSIONS: These findings highlight the need for people with chronic cardiovascular and respiratory diseases to take extra caution against influenza during hot and humid days in the subtropics and tropics. | crla8vrj |
coronavirus response to weather changes | 2 | Nature of transmission of Covid19 in India | We examine available data on the number of individuals infected by the Covid-19 virus, across several different states in India, over the period January 30, 2020 to April 10, 2020. It is found that the growth of the number of infected individuals $N(t)$ can be modeled across different states with a simple linear function $N(t)=\gamma+\alpha t$ beyond the date when reasonable number of individuals were tested (and when a countrywide lockdown was imposed). The slope $\alpha$ is different for different states. Following recent work by Notari (arxiv:2003.12417), we then consider the dependency of the $\alpha$ for different states on the average maximum and minimum temperatures, the average relative humidity and the population density in each state. It turns out that like other countries, the parameter $\alpha$, which determines the rate of rise of the number of infected individuals, seems to have a weak correlation with the average maximum temperature of the state. In contrast, any significant variation of $\alpha$ with humidity or minimum temperature seems absent with almost no meaningful correlation. Expectedly, $\alpha$ increases (slightly) with increase in the population density of the states; however, the degree of correlation here too is negligible. These results seem to barely suggest that a natural cause like a hot summer (larger maximum temperatures) may contribute towards reducing the transmission of the virus, though the role of minimum temperature, humidity and population density remains somewhat obscure from the inferences which may be drawn from presently available data. | iv7dok0v |
coronavirus response to weather changes | 2 | Any contribution of the season change to the spread of covid-19 caused by sars-cov-2? | Background: Most people raise a similar concern during this tough time of the COVID-19 pandemic caused by SARS-CoV-2 infection regarding when this outbreak will come to end. A recent thorough-general study on the success of China dealing with COVID-19 outbreak has concluded to recommend the need for a multi-sectoral approach to prevent future outbreaks of emerging infectious diseases including for the still-occurring COVID-19 outbreak with the initiative for the highest interest of the health of mankind Discussion: The prevalence of SARS-CoV as the predecessor of SARS-CoV-2 has been concluded to be more suitable in spring than autumn and winter, with nothing prevalence in summer. No coincidence that SARS-CoV-2 infection has outbreak around the world from January 2020 to the present, April 2020, as ever predicted to reoccur based on its predecessor, SARS-CoV, that have prevalence been high since January, February, March, April, until early May 2003. As opposed to other seasons, summer has low atmospheric pressure as its exemption that provenly causes virus inactivation. Conclusions: The denotative nature of SARS-CoV-2 seems to reflect its predecessor, SARS-CoV, which begins nearing the end of the year and reaches its optimum hence in spring, thereafter, finally ends in summer. Low atmospheric pressure in the summer impresses that it is the potential cause of ending the outbreak by deactivating SARS-CoV-2, apart from the hot temperature of weather. The knowledge to be gained here is further closely correlated to the fact that coronavirus is able to have genetic recombination that may bring about new genotypes and, consequently, outbreaks later occurring. | q3tc522t |
coronavirus response to weather changes | 2 | An environmental determinant of viral respiratory disease | The evident seasonality of influenza suggests a significant role for weather and climate as one of several determinants of viral respiratory disease (VRD), including social determinants which play a major role in shaping these phenomena. Based on the current mechanistic understanding of how VRDs are transmitted by small droplets, we identify an environmental variable, Air Drying Capacity (ADC), as an atmospheric state-variable with significant and direct relevance to the transmission of VRD. ADC dictates the evolution and fate of droplets under given temperature and humidity conditions. The definition of this variable is rooted in the Maxwell theory of droplet evolution via coupled heat and mass transfer between droplets and the surrounding environment. We present the climatology of ADC, and compare its observed distribution in space and time to the observed prevalence of influenza and COVID-19 from extensive global data sets. Globally, large ADC values appear to significantly constrain the observed transmission and spread of VRD, consistent with the significant coherency of the observed seasonal cycles of ADC and influenza. Our results introduce a new environmental determinant, rooted in the mechanism of VRD transmission, with potential implications for explaining seasonality of influenza, and for describing how environmental conditions may impact to some degree the evolution of similar VRDs, such as COVID-19. | 24pp67fw |
coronavirus response to weather changes | 2 | Impact Of Temperature and Sunshine Duration on Daily New Cases and Death due to COVID-19 | Background: The coronavirus pandemic (COVID-19) control has now become a critical issue for public health. Many ecological factors are proven to influence the transmission and survival of the virus. In this study, we aim to determine the association of different climate factors with the spread and mortality due to COVID-19. Methods: The climate indicators included in the study were duration of sunshine, average minimum temperature and average maximum temperature, with cumulative confirmed cases, deceased and recovered cases. The data was performed for 138 different countries of the world, between January 2020 to May 2020. Both univariate and multivariate was performed for cumulative and month-wise analysis using SPSS software. Results: The average maximum temperature, and sunshine duration was significantly associated with COVID-19 confirmed cases, deceased and recovered. For every one degree increase in mean average temperature, the confirmed, deceased and recovered cases decreased by 2047(p=0.03), 157(p=0.016), 743 (p=0.005) individuals. The association remained significant even after adjusting for environmental such as sunshine duration as well as non-environmental variables. Average sunshine duration was inversely correlated with increase in daily new cases ({rho}= -2261) and deaths ({rho}= -0.2985). Conclusion: Higher average temperature and longer sunshine duration was strongly associated with COVID-19 cases and deaths in 138 countries. Hence the temperature is an important factor in SARS CoV-2 survival and this study will help in formulating better preventive measures to combat COVID-19 based on their climatic conditions. | t3e8bfnr |
coronavirus response to weather changes | 2 | Impact of Daily Weather on COVID-19 outbreak in India | The COVID-19 pandemic has outspread obstreperously in India. As of June 04, 2020, more than 2 lakh cases have been confirmed with a death rate of 2.81%. It has been noticed that, out of each 1000 tests, 53 result positively infected. In order to investigate the impact of weather conditions on daily transmission occurring in India, daily data of Maximum (TMax), Minimum (TMin), Mean (TMean) and Dew Point Temperature (TDew), Diurnal Temperature range (TRange), Average Relative Humidity, Range in Relative Humidity, and Wind Speed (WS) over 9 most affected cities are analysed in several time frames: weather of that day, 7, 10, 12, 14, 16 days before transmission. Spearman rank correlation (r) shows significant but low correlation with most of the weather parameters, however, comparatively better association exists on 14 days lag. Diurnal range in Temperature and Relative Humidity shows non-significant correlation. Analysis shows, COVID-19 cases likely to be increased with increasing air temperature, however role of humidity is not clear. Among weather parameters, Minimum Temperature was relatively better correlate than other. 80% of the total confirmed cases were registered when TMax, TMean, TMin, TRange, TDew, and WS on 12-16 days ago vary within a range of 33.6-41.3 deg C, 29.8-36.5 deg C, 24.8-30.4 deg C, 7.5-15.2 deg C, 18.7-23.6 deg C, and 4.2-5.75 m/s respectively, hence, it gives an idea of susceptible weather conditions for such transmission in India. Using Support Vector Machine based regression, the daily cases are profoundly estimated with more than 80% accuracy, which indicate that coronavirus transmission cannot be well linearly correlated with any single weather parameters, rather multivariate non-linear approach must be employed. Accounting lag of 12-16 days, the association found to be excellent, thus depict that there is an incubation period of 12-16 days for coronavirus transmission in Indian scenario. | uj8a09t3 |
coronavirus response to weather changes | 2 | Effect of Temperature on the Transmission of COVID-19: A Machine Learning Case Study in Spain | The novel coronavirus (COVID-19) has already spread to almost every country in the world and has infected over 3 million people. To understand the transmission mechanism of this highly contagious virus, it is necessary to study the potential factors, including meteorological conditions. Here, we present a machine learning approach to study the effect of temperature, humidity and wind speed on the number of infected people in the three most populous autonomous communities in Spain. We find that there is a moderate inverse correlation between temperature and the daily number of infections. This correlation manifests for temperatures recorded up to 6 days before the onset, which corresponds well to the known mean incubation period of COVID-19. We also show that the correlation for humidity and wind speed is not significant. | r9yrr45q |
coronavirus response to weather changes | 2 | Associations of ambient air pollutants and meteorological factors with COVID-19 transmission in 31 Chinese provinces: A time-series study | Background: Evidence regarding the effects of ambient air pollutants and meteorological factors on COVID-19 transmission is limited. Objectives: To explore the associations of air pollutants and meteorological factors with COVID-19 confirmed cases across 31 Chinese provinces during the outbreak period. Methods: The number of COVID-19 confirmed cases, air pollutant concentrations and meteorological factors in 31 Chinese provinces from January 25 to February 29, 2020 were extracted from authoritative electronic databases. The associations were estimated for a single-day lag (lag0-lag6) as well as moving averages lag (lag01-lag05) using generalized additive mixed models (GAMMs), adjusted for time trends, day of the week, holidays and meteorological variables. Region-specific analyses and meta-analysis were conducted in five selected regions with diverse air pollution levels and weather conditions. Nonlinear exposure-response analyses were performed. Results: We examined 77,578 COVID-19 confirmed cases across 31 Chinese provinces during the study period. An increase of each interquartile range in PM2.5, PM10, SO2, NO2, O3 and CO at lag4 corresponded to 1.40 (1.37-1.43), 1.35 (1.32-1.37), 1.01 (1.00-1.02), 1.08 (1.07-1.10), 1.28 (1.27-1.29) and 1.26 (1.24-1.28) odds ratios (ORs) of daily COVID-19 confirmed new cases, respectively. For 1 oc, 1% and 1 m/s increase in temperature, relative humidity and wind velocity, the ORs were 0.97 (0.97-0.98), 0.96 (0.96-0.97), and 0.94 (0.92-0.95), respectively. The estimates of PM2.5, PM10, NO2 and all meteorological factors remained statistically significant after meta-analysis for the five selected regions. The exposure-response relationships showed that higher concentrations of air pollutants and lower meteorological factors were associated with daily COVID-19 confirmed new cases increasing. Conclusions: Higher air pollutant concentrations and lower temperature, relative humidity and wind velocity may favor COVID-19 transmission. As summer months are arriving in the Northern Hemisphere, the environmental factors and implementation of public health control measures may play an optimistic role in controlling COVID-19 epidemic. | aqozmk1t |
coronavirus response to weather changes | 2 | The Association of Social Distancing, Population Density, and Temperature with the SARS-CoV-2 Instantaneous Reproduction Number in Counties Across the United States | Importance: The Covid-19 pandemic has been marked by considerable heterogeneity in outbreaks across the United States. Local factors that may be associated with variation in SARS-CoV-2 transmission have not been well studied. Objective: To examine the association of county-level factors with variation in the SARS-CoV-2 reproduction number over time. Design: Observational study Setting: 211 counties in 46 states and the District of Columbia between February 25, 2020 and April 23, 2020. Participants: Residents within the counties (55% of the US population) Exposures: Social distancing as measured by percent change in visits to non-essential businesses, population density, lagged daily wet bulb temperatures. Main Outcomes and Measures: The instantaneous reproduction number (Rt) which is the estimated number of cases generated by one case at a given time during the pandemic. Results: Median case incidence was 1185 cases and fatality rate was 43.7 deaths per 100,000 people for the top decile of 21 counties, nearly ten times the incidence and fatality rate in the lowest density quartile. Average Rt in the first two weeks was 5.7 (SD 2.5) in the top decile, compared to 3.1 (SD 1.2) in the lowest quartile. In multivariable analysis, a 50% decrease in visits to non-essential businesses was associated with a 57% decrease in Rt (95% confidence interval, 56% to 58%). Cumulative temperature effects over 4 to 10 days prior to case incidence were nonlinear; relative Rt decreased as temperatures warmed above 32F to 53F, which was the point of minimum Rt, then increased between 53F and 66F, at which point Rt began to decrease. At 55F, and with a 70% reduction in visits to non-essential business, 96% of counties were estimated to fall below a threshold Rt of 1.0, including 86% of counties among the top density decile and 98% of counties in the lowest density quartile. Conclusions and Relevance: Social distancing, lower population density, and temperate weather change were associated with a decreased SARS-Co-V-2 Rt in counties across the United States. These relationships can inform selective public policy planning in communities during the SARS-CoV-2 pandemic. | tqnwk4o6 |
coronavirus response to weather changes | 2 | Diverse local epidemics reveal the distinct effects of population density, demographics, climate, depletion of susceptibles, and intervention in the first wave of COVID-19 in the United States | The SARS-CoV-2 pandemic has caused significant mortality and morbidity worldwide, sparing almost no community. As the disease will likely remain a threat for years to come, an understanding of the precise influences of human demographics and settlement, as well as the dynamic factors of climate, susceptible depletion, and intervention, on the spread of localized epidemics will be vital for mounting an effective response. We consider the entire set of local epidemics in the United States; a broad selection of demographic, population density, and climate factors; and local mobility data, tracking social distancing interventions, to determine the key factors driving the spread and containment of the virus. Assuming first a linear model for the rate of exponential growth (or decay) in cases/mortality, we find that population-weighted density, humidity, and median age dominate the dynamics of growth and decline, once interventions are accounted for. A focus on distinct metropolitan areas suggests that some locales benefited from the timing of a nearly simultaneous nationwide shutdown, and/or the regional climate conditions in mid-March; while others suffered significant outbreaks prior to intervention. Using a first-principles model of the infection spread, we then develop predictions for the impact of the relaxation of social distancing and local climate conditions. A few regions, where a significant fraction of the population was infected, show evidence that the epidemic has partially resolved via depletion of the susceptible population (i.e., "herd immunity"), while most regions in the United States remain overwhelmingly susceptible. These results will be important for optimal management of intervention strategies, which can be facilitated using our online dashboard. | t70lnidk |
coronavirus response to weather changes | 2 | Correlation of the global spread of coronavirus disease-19 with atmospheric air temperature | Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an enveloped virus that may be sensitive to heat. We assessed whether the spread of coronavirus disease 2019 (COVID-19) correlates with air temperature. We also studied whether additional climate, geographical, and population variables were correlated. The total number of confirmed COVID-19 cases and mortality rates reported in each country between 1st Jan and 31st Mar 2020 were compared with the country's three-month average atmospheric air temperature, precipitation and latitude. Spearman's correlation coefficient (rs) was used to identify significant correlations. Our analysis included a total of 748,555 confirmed COVID-19 cases worldwide. The total number of patients with COVID-19 decreased with increasing atmospheric air temperature (rs = -0.54, 95%CI: [-0.64, -0.42]; P <0.001) and increased with an increasing latitude (rs =0.60, 95%CI: [0.48, 0.70]; P <0.001). Our findings justify further studies to examine the effect of air temperature on infectivity of SAR-CoV-2. | foha7ozb |
coronavirus response to weather changes | 2 | Temperature and Humidity Do Not Influence Global COVID-19 Incidence as Inferred from Causal Models | The relationship between meteorological factors such as temperature and humidity with COVID-19 incidence is still unclear after 6 months of the beginning of the pandemic. Some literature confirms the association of temperature with disease transmission while some oppose the same. This work intends to determine whether there is a causal association between temperature, humidity and Covid-19 cases. Three different causal models were used to capture stochastic, chaotic and symbolic natured time-series data and to provide a robust & unbiased analysis by constructing networks of causal relationships between the variables. Granger-Causality method, Transfer Entropy method & Convergent Cross-Mapping (CCM) was done on data from regions with different temperatures and cases greater than 50,000 as of 13th May 2020. From the Granger-Causality test we found that in only Canada, the United Kingdom, temperature and daily new infections are causally linked. The same results were obtained from Convergent Cross Mapping for India. Again using Granger-Causality test, we found that in Russia only, relative humidity is causally linked to daily new cases. Thus, a Generalized Additive Model with a smoothing spline function was fitted for these countries to understand the directionality. Using the combined results of the said models, we were able to conclude that there is no evidence of a causal association between temperature, humidity and Covid-19 cases. | 3yzxljjf |
coronavirus response to weather changes | 2 | Temperature and relative humidity are not major contributing factor on the occurrence of COVID-19 pandemic: An observational study in 57 countries | The world searching for hope has already experienced a huge loss of lives due to COVID-19 caused by SARS-CoV-2 started in Wuhan, China. There are speculations that climatic conditions can slowdown the transmission of COVID-19.Findings from the early outbreak indicated the possible association of air temperature and relative humidity in COVID-19 occurrence in China. Current study focused on whether climatic conditions(temperature and relative humidity)are having any influence in the occurrence of COVID-19 when the outbreak has been classified as pandemic. To determine the effect of daily average temperature and average relative humidity on log-transformed total daily cases of COVID-19, polynomial regression as a quadratic term and linear regression were done. Linear regression analysis was also carried out to explore the same effect on selected countries. Present study observed no correlation between the climatic conditions (the daily average temperature and relative humidity) and the number of cases of COVID-19. Similar result was found in relation between daily average temperature and average number of cases per day in country-wise analysis. However, about 93.5% cases of COVID-19 occurred between 10C to 160C and the average number of cases per day was lower in high temperature country than low temperature country with exceptions. The minimum effect of summer temperature may not be effective to control the pandemic rather need to apply the control measures of COVID-19. | 51k50ebv |
coronavirus response to weather changes | 2 | Impacts of regional climate on the COVID-19 pandemic | The COVID-19 pandemic has led to six million confirmed cases by May 31, 2020. Impacts of regional weather and climate on epidemics have been investigated but need further study with new methods. We combined the number of monthly confirmed new cases and death with month, latitude, temperature, humidity, rainfall, and sunshine ultraviolet (UV) to explore the climate impact on epidemics in 116 countries and territories with at least 1000 confirmed cases. Correlation and regression analyses were performed with Stata. Humid subtropical climate regions had the most confirmed COVID-19 cases (24.4%). The case mortality in temperate marine regions was the highest (11.6%). Case-weighted means of the latitude, monthly maximum temperature, relative humidity, rainfall, and sunshine UV were 36.7 degrees, 20.5, 63%, 63mm, and 53.5, respectively. The case mortality was 7.44% in cold regions but only 4.68% in hot regions, 7.14% in rainy regions but only 3.86% in rainless regions, and 7.40% in cloudy regions but only 4.64% in sunny regions. Monthly confirmed cases increase as the temperature, rainfall, and sunshine UV rise in cold regions (r=0.34, 0.26, 0.26, respectively), but no correlation in hot regions. Every 1 increase in monthly maximum temperature leads to an increase in the natural logarithm of monthly confirmed new cases by 2.4% in cold regions. Monthly confirmed cases increase as the temperature, rainfall, and sunshine UV rise in arid regions (r=0.29, 0.28, 0.26, respectively), but no correlation in humid regions. Monthly confirmed new cases increase as the temperature and sunshine UV rise in rainy regions (r=0.30, 0.29), but no correlation in rainless regions. Monthly confirmed new deaths increase as the temperature and sunshine UV rise in cloudy regions (r=0.30, 0.30), but no correlation in sunny regions. It is wise to escape from an epicenter full of miasma to a hot sunny place in dry season without pollution. As peaking in the spring depends on the climate, the peak will go in the summer. | k1l16pmm |
coronavirus response to weather changes | 2 | Climatic influence on the magnitude of COVID-19 outbreak: a stochastic model-based global analysis | This study examines the association between community transmission of COVID-19 cases and climatic predictors, considering travel information and annual parasite index across the three climatic zones, i.e., tropical, subtropical, and temperate. A Boosted Regression Tree model has been employed to understand the association between the COVID-19 cases. The results show that average temperature and average relative humidity are the major contributors in explaining the differentials of COVID-19 transmission in temperate and subtropical regions whereas the mean diurnal temperature range and temperature seasonality are the most significant determinants in tropical regions. The average temperature is the most influential factor affecting the number of COVID-19 cases in France, Turkey, the US, the UK, and Germany, and the cases decrease sharply above 10oC. Among the tropical countries, India found to be most affected by mean diurnal temperature, and Brazil fazed by temperature seasonality. Most of the temperate countries like France, USA, Turkey, UK, and Germany with an average temperature between 5-12oC had high number of COVID-19 cases. The findings are expected to add to the ongoing debates on the influence of climatic factors influencing the number of COVID-19 cases and could help researchers and policymakers to make appropriate decisions for preventing the spread. | ioyl1gla |
coronavirus response to weather changes | 2 | Early transmission of COVID-19 has an optimal temperature but late transmission decreases in warm climate | The COVID-19 novel virus, as an emerging highly pathogenic agent, has caused a pandemic. Revealing the influencing factors affecting transmission of COVID-19 is essential to take effective control measures. Several previous studies suggested that the spread of COVID-19 was likely associated with temperature and/or humidity. But, a recent extensive review indicated that conclusions on associations between climate and COVID-19 were elusive with high uncertainty due to caveats in most previous studies, such as limitations in time and space, data quality and confounding factors. In this study, by using a more extensive global dataset covering 578 time series from China, USA, Europe and the rest of the world, we show that climate show distinct impacts on early and late transmission of COVID-19 in the world after excluding the confounding factors. The early transmission ability of COVID-19 peaked around 6.3{degrees}C without or with little human intervention, but the later transmission ability was reduced in high temperature conditions under human intervention, probably driven by increased control efficiency of COVID-19. The transmission ability was positively associated with the founding population size of early reported cases and population size of a location. Our study suggested that with the coming summer seasons, the transmission risk of COVID-19 would increase in the high-latitude or high-altitude regions but decrease in low-latitude or low-altitude regions; human intervention is essential in containing the spread of COVID-19 around the world. | t4k5csgy |
coronavirus response to weather changes | 2 | Meteorological Conditions and Covid-19 in Large U.S. Cities | To determine whether prevalence of Coronavirus disease 2019 (Covid-19) is modulated by meteorological conditions, we herein conducted meta-regression of data in large U.S. cities. We selected 33 large U.S. cities with a population of >500,000. The integrated numbers of confirmed Covid-19 cases in the country to which the city belongs on 14 May 2020, the estimated population in 2019 in the country, and monthly meteorological conditions at the city for 4 months (from January to April 2020) were obtained. Meteorological conditions consisted of mean temperature (F), total precipitation (inch), mean wind speed (MPH), mean sky cover, and mean relative humidity (%). Monthly data for 4 months were averaged or integrated. The Covid-19 prevalence was defined as the integrated number of Covid-19 cases divided by the population. Random-effects meta-regression was performed by means of OpenMetaAnalyst. In a meta-regression graph, Covid-19 prevalence (plotted as the logarithm transformed prevalence on the y-axis) was depicted as a function of a given factor (plotted as a meteorological datum on the x-axis). A slope of the meta-regression line was significantly negative (coefficient, -0.069; P < 0.001) for the mean temperature and significantly positive for the mean wind speed (coefficient, 0.174; P = 0.027) and the sky cover (coefficient, 2.220; P = 0.023). In conclusion, lower temperature and higher wind speed/sky cover may be associated with higher Covid-19 prevalence, which should be confirmed by further epidemiological researches adjusting for various risk and protective factors (in addition to meteorological conditions) of Covid-19. | 7usv3ljo |
coronavirus response to weather changes | 2 | Study of the Dependence of Effective Reproduction Number of COVID-19 on the Temperature and Humidity: A Case Study with the Indian States | Corona Virus Disease 2019 (COVID-19) started in Wuhan province of China in November 2019 and within a short time, it was declared as a worldwide pandemic by World Health Organisation due to very fast worldwide spread of the virus. In the absence of any vaccine, various mitigation measures were used. In the past, the effect of temperature and humidity on the spread of the virus was studied for a very early phase of the data with mixed results. We are studying the impact of COVID-19 on the maximum temperature and relative humidity of a place using Indian states as test cases for SIR, SIRD, and SEIR models. We used a linear regression method to look for any dependency between effective reproduction number with maximum temperature and relative humidity. Most of the states show a correlation with the negative slope between the effective reproduction number with the maximum temperature and the relative humidity. It indicates that the effective reproduction number goes down as maximum temperature or relative humidity rise. But, the regression coefficient R2 is low for these correlations which means that the correlation is not strong. | n59q479q |
coronavirus response to weather changes | 2 | UV light influences covid-19 activity through big data: trade offs between northern subtropical, tropical, and southern subtropical countries | UV (ultraviolet) light is an important factor should be considered to predict coronavirus epidemic growth pace. UV is different from weather temperature since UV is electromagnetic wavelength from 10 nm to 400 nm in size, shorter than of visible lights. For some people, UV light can lead to cancer from unprotected sun exposure, however, for tropical people, which have been used to live in such condition, have resisted from negative effect high UV index. Moreover, UV has the capability to inactivate virus. This conclusion has been discussed deeply with biological experts. Although UV light has the ability to inactivate viruses, it may be meaningless in areas with high air pollution where UV light turns into heat. | odbi4yvz |
coronavirus response to weather changes | 2 | Warmer weather and global trends in the coronavirus COVID-19 | Predicting COVID-19 epidemic development in the upcoming warm season has attracted much attention in the hope of providing helps to fight the epidemic. It requires weather (environmental) factors to be included in prediction models, but there are few models to achieve it successfully. In this study, we proposed a new concept of environmental infection rate (RE), based on floating time of respiratory droplets in the air and inactivation rate of virus to solve the problem. More than half of the particles in the droplets can float in the atmosphere for 1-2 hours. The prediction results showed that high RE values (>3.5) are scattered around 30N in winter (Dec.-Feb.). As the weather warms, its distribution area expands and extends to higher latitudes of northern hemisphere, reaching its maximum in April, and then shrinking northward. These indicated that the spread of COVID-19 in most parts of the northern hemisphere is expected to decline after Apr., but the risks in high latitudes will remain high in May. In the south of southern hemisphere, the RE values tend to subside from Apr. to July. The high modeled RE values up to July, however, suggested that warmer weather will not stop COVID-19 from spreading. Public health intervention is needed to overcome the outbreak. | fj3a2y1o |
coronavirus response to weather changes | 2 | REGIONAL DETERMINANTS OF THE EXPANSION OF COVID-19 IN BRAZIL | Objective: This study investigates the regional differences in the occurrence of COVID-19 in Brazil and its relationship with climatic and demographic factors, for this, using data about identified cases of COVID-19 on Brazil from February 26 to April 04, 2020. Methods: A model using the Polynomial Regression with cubic adjustments of the number of days of contagion, demographic density, city population and climatic factors was designed to explain the spread of COVID-19 in Brazil. Main results: It was evidenced that temperature variation maintains a relationship with the reduction in the number of cases of COVID-19, but on a very small scale. With a simulation of 30 days of contagion, a variation of -0.9% was found for each increase of 1 C. Conclusion: Temperature, despite being an intervening factor in the variation in the number of COVID-19 cases, has a reduced magnitude effect. Cities with higher temperatures do not necessarily it is more protected from the SARS-CoV-2 than those with lower temperatures, however, strong statistical significance was found, this relationship deserves to be investigated in other tests with longer time series, wide and with especially non-linear data adjustments. | epa6m6nq |
coronavirus response to weather changes | 2 | No Evidence for Temperature-Dependence of the COVID-19 Epidemic | The pandemic of the COVID-19 disease extended from China across the north-temperate zone, and more recently to the tropics and southern hemisphere. We find no evidence that spread rates decline with temperatures above 20 oC, suggesting that the COVID-19 disease is unlikely to behave as a seasonal respiratory virus. | bnrmh1qs |
coronavirus response to weather changes | 2 | ICU admissions and in-hospital deaths linked to covid-19 in the Paris region are correlated with previously observed ambient temperature | OBJECTIVE To study the effect of weather on severity indicators of coronavirus disease 2019 (covid-19). DESIGN Ecological study. SETTING Paris region. POPULATION Severely ill patients with covid-19. MAIN OUTCOME MEASURES Daily covid-19-related intensive care unit (ICU) admission and in-hospital deaths in the Paris region, and the daily weather characteristics of Paris midtown. RESULTS Daily ICU admissions and in-hospital deaths were strongly and negatively correlated to ambient temperatures, with a time lag. The highest Pearson correlation coefficients and statistically significant P values were found 8 days before occurrence of ICU admissions and 15 days before deaths. CONCLUSIONS The study findings show a strong effect of previously observed ambient temperature that has an effect on severity indicators of covid-19. | gmlbbw9u |
coronavirus response to weather changes | 2 | Temperature dependence of COVID-19 transmission | The recent coronavirus pandemic follows in its early stages an almost exponential expansion, with the number of cases N reasonably well fit by N eαt, in many countries. We analyze the rate α in different countries, choosing as a starting point in each country the first day with 30 cases and fitting for the following 12 days, capturing thus the early exponential growth in a rather homogeneous way. We look for a link between the rate α and the average temperature T of each country, in the month of the epidemic growth. We analyze a {\it base} set of 42 countries, which developed the epidemic at an earlier stage, an {\it intermediate} set of 88 countries and an {\it extended} set of 125 countries, which developed the epidemic more recently. Fitting with a linear behavior α(T), we find increasing evidence in the three datasets for a decreasing growth rate as a function of T, at $99.66\%$C.L., $99.86\%$C.L. and $99.99995 \%$ C.L. ($p$-value $5 \cdot 10^{-7}$, or 5$\sigma$ detection) in the {\it base}, {\it intermediate} and {\it extended} dataset, respectively. The doubling time is expected to increase by $40\%\sim 50\%$, going from $5^\circ$ C to $25^\circ$ C. In the {\it base} set, going beyond a linear model, a peak at about $(7.7\pm 3.6)^\circ C$ seems to be present in the data, but such evidence disappears for the larger datasets. Moreover we have analyzed the possible existence of a bias: poor countries, typically located in warm regions, might have less intense testing. By excluding countries below a given GDP per capita from the dataset, we find that this affects our conclusions only slightly and only for the {\it extended} dataset. The significance always remains high, with a $p$-value of about $10^{-3}-10^{-4}$ or less. Our findings give hope that, for northern hemisphere countries, the growth rate should significantly decrease as a result of both warmer weather and lockdown policies. In general the propagation should be hopefully stopped by strong lockdown, testing and tracking policies, before the arrival of the next cold season. | 0oma7hdu |
coronavirus response to weather changes | 2 | Higher Air Temperature, Pressure, and Ultraviolet Are Associated with Less Covid-19 Incidence | A recent study from China suggests that high temperature and ultraviolet (UV) radiation cannot decrease the epidemics of Coronavirus disease 2019 (Covid-19). To determine whether COVID-19 incidence is modulated by meteorological factors, meta-regression of Japanese prefectural data was herein conducted. We extracted 1) cumulative numbers of confirmed Covid-19 patients in each Japanese prefecture from January to April 2020; 2) populations per 1-km2 inhabitable area in each prefecture in 2020; and 3) meteorological factors at each prefectural capital city from January to April 2020. Meteorological factors included monthly mean air temperature (degree Celsius), wind speed (m/s), sea level air pressure (hPa), relative humidity (%), and percentage of possible sunshine (%); monthly total of sunshine duration (h) and precipitation (mm); and monthly mean daily maximum ultraviolet (UV) index. To adjust for prefectural population density, we defined the incidence of Covid-19 as the cumulative number of Covid-19 patients divided by the population per 100-km2 inhabitable area. Random-effects meta-regression was performed, and its graph depicted Covid-19 incidence (plotted as the logarithm transformed incidence on the y-axis) as a function of a given meteorological factor (plotted on the x-axis). A slope of the meta-regression line was significantly negative as a function of the mean air temperature (coefficient, -0.127; P = 0.023), the mean sea level air pressure (coefficient, -0.351; P < 0.001), and the mean daily maximum UV index (coefficient, -0.001; P = 0.012) which indicated that Covid-19 incidence decreased significantly as air temperature, air pressure, and UV increased. In conclusion, higher air temperature, air pressure, and UV may be associated with less Covid-19 incidence. | 9nicryzs |
coronavirus response to weather changes | 2 | Weather variables impact on COVID-19 incidence | We test the hypothesis of COVID-19 contagion being influenced by meteorological parameters such as temperature or humidity. We analysed data at high spatial resolution (regions in Italy and counties in the USA) and found that while at low resolution this might seem the case, at higher resolution no correlation is found. Our results are consistent with a poor outdoors transmission of the disease. However, a possible indirect correlation between good weather and a decrease in disease spread may occur, as people spend longer time outdoors. | hadnxjeo |
coronavirus response to weather changes | 2 | Impact of weather on COVID-19 pandemic in Turkey | The coronavirus pandemic, which has numerous global implications, has led people to believe that nothing will be the same as before. The present day is dominated by studies on determining the factors that affect, taking preventive actions, and trying to find an effective treatment on top priority. Meteorological parameters are among the crucial factors affecting infectious diseases. The present study examines the correlation between weather and coronavirus disease 2019 (COVID-19) by considering nine cities in Turkey. In this regard, temperature (°C), dew point (°C), humidity (%), and wind speed (mph) are considered as parameters of weather. Research states that the incubation period of COVID-19 varies from 1â¯day to 14â¯days. Therefore, the effects of each parameter within 1, 3, 7, and 14â¯days are examined. In addition, the population is included as an effective parameter for evaluation. The analyses are conducted based on Spearman's correlation coefficients. The results showed that the highest correlations were observed for population, wind speed 14â¯days ago, and temperature on the day, respectively. The study results may guide authorities and decision-makers on taking specific measures for the cities. | ds3nmssp |
coronavirus response to weather changes | 2 | Investigation of effective climatology parameters on COVID-19 outbreak in Iran | SARS CoV-2 (COVID-19) Coronavirus cases are confirmed throughout the world and millions of people are being put into quarantine. A better understanding of the effective parameters in infection spreading can bring about a logical measurement toward COVID-19. The effect of climatic factors on spreading of COVID-19 can play an important role in the new Coronavirus outbreak. In this study, the main parameters, including the number of infected people with COVID-19, population density, intra-provincial movement, and infection days to end of the study period, average temperature, average precipitation, humidity, wind speed, and average solar radiation investigated to understand how can these parameters effects on COVID-19 spreading in Iran? The Partial correlation coefficient (PCC) and Sobol'-Jansen methods are used for analyzing the effect and correlation of variables with the COVID-19 spreading rate. The result of sensitivity analysis shows that the population density, intra-provincial movement have a direct relationship with the infection outbreak. Conversely, areas with low values of wind speed, humidity, and solar radiation exposure to a high rate of infection that support the virus's survival. The provinces such as Tehran, Mazandaran, Alborz, Gilan, and Qom are more susceptible to infection because of high population density, intra-provincial movements and high humidity rate in comparison with Southern provinces. | 15slu3kk |
coronavirus response to weather changes | 2 | Distribution of the SARS-CoV-2 Pandemic and Its Monthly Forecast Based on Seasonal Climate Patterns | This paper investigates whether the Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) pandemic could have been favored by specific weather conditions and other factors. It is found that the 2020 winter weather in the region of Wuhan (Hubei, Central China)-where the virus first broke out in December and spread widely from January to February 2020-was strikingly similar to that of the Northern Italian provinces of Milan, Brescia and Bergamo, where the pandemic broke out from February to March. The statistical analysis was extended to cover the United States of America, which overtook Italy and China as the country with the highest number of confirmed COronaVIrus Disease 19 (COVID-19) cases, and then to the entire world. The found correlation patterns suggest that the COVID-19 lethality significantly worsens (4 times on average) under weather temperatures between 4 ∘ C and 12 ∘ C and relative humidity between 60% and 80%. Possible co-factors such as median population age and air pollution were also investigated suggesting an important influence of the former but not of the latter, at least, on a synoptic scale. Based on these results, specific isotherm world maps were generated to locate, month by month, the world regions that share similar temperature ranges. From February to March, the 4-12 ∘ C isotherm zone extended mostly from Central China toward Iran, Turkey, West-Mediterranean Europe (Italy, Spain and France) up to the United State of America, optimally coinciding with the geographic regions most affected by the pandemic from February to March. It is predicted that in the spring, as the weather gets warm, the pandemic will likely worsen in northern regions (United Kingdom, Germany, East Europe, Russia and North America) while the situation will likely improve in the southern regions (Italy and Spain). However, in autumn, the pandemic could come back and affect the same regions again. The Tropical Zone and the entire Southern Hemisphere, but in restricted colder southern regions, could avoid a strong pandemic because of the sufficiently warm weather during the entire year and because of the lower median age of their population. Google-Earth-Pro interactive-maps covering the entire world are provided as supplementary files. | 04rbtmmi |
coronavirus response to weather changes | 2 | Statistical analysis of the impact of environmental temperature on the exponential growth rate of cases infected by COVID-19 | We perform a statistical analysis for understanding the effect of the environmental temperature on the exponential growth rate of the cases infected by COVID-19 for US and Italian regions. In particular, we analyze the datasets of regional infected cases, derive the growth rates for regions characterized by a readable exponential growth phase in their evolution spread curve and plot them against the environmental temperatures averaged within the same regions, derive the relationship between temperature and growth rate, and evaluate its statistical confidence. The results clearly support the first reported statistically significant relationship of negative correlation between the average environmental temperature and exponential growth rates of the infected cases. The critical temperature, which eliminates the exponential growth, and thus the COVID-19 spread in US regions, is estimated to be TC = 86.1 ± 4.3 F0. | q12b7uyr |
coronavirus response to weather changes | 2 | Asymmetric nexus between temperature and COVID-19 in the top ten affected provinces of China: A current application of quantile-on-quantile approach | The present study examines the asymmetrical effect of temperature on COVID-19 (Coronavirus Disease) from 22 January 2020 to 31 March 2020 in the 10 most affected provinces in China. This study used the Sim & Zhou' quantile-on-quantile (QQ) approach to analyze how the temperature quantities affect the different quantiles of COVID-19. Daily COVID-19 and, temperature data collected from the official websites of the Chinese National Health Commission and Weather Underground Company (WUC) respectively. Empirical results have shown that the relationship between temperature and COVID-19 is mostly positive for Hubei, Hunan, and Anhui, while mostly negative for Zhejiang and Shandong provinces. The remaining five provinces Guangdong, Henan, Jiangxi, Jiangsu, and Heilongjiang are showing the mixed trends. These differences among the provinces can be explained by the differences in the number of COVID-19 cases, temperature, and the province's overall hospital facilitations. The study concludes that maintaining a safe and comfortable atmosphere for patients while COVID-19 is being treated may be rational. | 3tow59gc |
coronavirus response to weather changes | 2 | Maximum Daily Temperature, Precipitation, Ultra-Violet Light and Rates of Transmission of SARS-Cov-2 in the United States | BACKGROUND: Previous reports have suggested that transmission of SARS-CoV-2 is reduced by higher temperatures and higher humidity. We analyzed case-data from the United States to investigate effects of temperature, precipitation, and UV Light on community transmission of SARS-CoV-2. METHODS: Daily reported cases of SARS-CoV-2 across the United States from 01/22/2020 to 04/03/2020 were analyzed. We used negative binomial regression modelling to investigate whether daily maximum temperature, precipitation, UV Index and the incidence 5 days later were related. We performed sensitivity analyses at 3 days, 7 days and 9 days to assess transmission lags. RESULTS: A maximum temperature greater than 52°F on a given day was associated with a lower rate of new cases at 5 days[IRR: 0.85(0.76,0.96)p=0.009]. Among observations with daily temperatures below 52°F, there was a significant inverse association between the maximum daily temperature and the rate of cases at 5 days [IRR 0.98(0.97,0.99)p=0.001]. The rate of new cases was predicted to be lower for theoretical states that maintained a stable maximum daily temperature above 52°F with a predicted 23-fewer cases per-million per-day by 25 days of the epidemic. A 1-unit higher UV index was associated with a lower rate at 5 days [IRR 0.97(0.95,0.99)p=0.004]. Precipitation was not associated with a greater rate of cases at 5 days [IRR 0.98(0.89,1.08)p=0.65]. CONCLUSION: The incidence of disease declines with increasing temperature up until 52°F and is lower at warmer versus cooler temperatures. However, the association between temperature and transmission is small and transmission is likely to remain high at warmer temperatures. | 7vwjcp53 |
coronavirus response to weather changes | 2 | The Weather Impacts the Outbreak of COVID-19 in Mainland China | Recent literature has suggested that climate conditions have considerably significant influences on the transmission of coronavirus COVID-19. However, there is a lack of comprehensive study that investigates the relationships between multiple weather factors and the development of COVID-19 pandemic while excluding the impact of social factors. In this paper, we study the relationships between six main weather factors and the infection statistics of COVID-19 on 250 cities in Mainland China. Our correlation analysis using weather and infection statistics indicates that all the studied weather factors are correlated with the spread of COVID-19, where precipitation shows the strongest correlation. We also build a weather-aware predictive model that forecasts the number of infected cases should there be a second wave of the outbreak in Mainland China. Our predicted results show that cities located in different geographical areas are likely to be challenged with the second wave of COVID-19 at very different time periods and the severity of the outbreak varies to a large degree, in correspondence with the varying weather conditions. | akb96git |
coronavirus response to weather changes | 2 | Anomalous atmospheric circulation favored the spread of COVID-19 in Europe | The current pandemic caused by the coronavirus SARS-CoV-2 is having negative health, social and economic consequences worldwide. In Europe, the pandemic started to develop strongly at the end of February and beginning of March 2020. It has subsequently spread over the continent, with special virulence in northern Italy and inland Spain. In this study we show that an unusual persistent anticyclonic situation prevailing in southwestern Europe during February 2020 (i.e. anomalously strong positive phase of the North Atlantic and Arctic Oscillations) could have resulted in favorable conditions, in terms of air temperature and humidity, in Italy and Spain for a quicker spread of the virus compared with the rest of the European countries. It seems plausible that the strong atmospheric stability and associated dry conditions that dominated in these regions may have favored the virus's propagation, by short-range droplet transmission as well as likely by long-range aerosol (airborne) transmission. | kpvxdhcu |
coronavirus response to weather changes | 2 | Evidence that high temperatures and intermediate relative humidity might favor the spread of COVID-19 in tropical climate: A case study for the most affected Brazilian cities | This study aimed to analyze how meteorological conditions such as temperature, humidity and rainfall can affect the spread of COVID-19 in five Brazilian (São Paulo, Rio de Janeiro, Brasília, Manaus and Fortaleza) cities. The cities selected were those with the largest number of confirmed cases considering data of April 13. Variables such as number of cumulative cases, new daily cases and contamination rate were employed for this study. Our results showed that higher mean temperatures and average relative humidity favored the COVID-19 transmission, differently from reports from coldest countries or periods of time under cool temperatures. Thus, considering the results obtained, intersectoral policies and actions are necessary, mainly in cities where the contamination rate is increasing rapidly. Thus, prevention and protection measures should be adopted in these cities aiming to reduce transmission and the possible collapse of the health system. | 5b9xjvwm |
coronavirus response to weather changes | 2 | Association between climate variables and global transmission oF SARS-CoV-2 | In this study, we aimed at analyzing the associations between transmission of and deaths caused by SARS-CoV-2 and meteorological variables, such as average temperature, minimum temperature, maximum temperature, and precipitation. Two outcome measures were considered, with the first aiming to study SARS-CoV-2 infections and the second aiming to study COVID-19 mortality. Daily data as well as data on SARS-CoV-2 infections and COVID-19 mortality obtained between December 1, 2019 and March 28, 2020 were collected from weather stations around the world. The country's population density and time of exposure to the disease were used as control variables. Finally, a month dummy variable was added. Daily data by country were analyzed using the panel data model. An increase in the average daily temperature by one degree Fahrenheit reduced the number of cases by approximately 6.4 cases/day. There was a negative correlation between the average temperature per country and the number of cases of SARS-CoV-2 infections. This association remained strong even with the incorporation of additional variables and controls (maximum temperature, average temperature, minimum temperature, and precipitation) and fixed country effects. There was a positive correlation between precipitation and SARS-CoV-2 transmission. Countries with higher rainfall measurements showed an increase in disease transmission. For each average inch/day, there was an increase of 56.01 cases/day. COVID-19 mortality showed no significant association with temperature. | aekywz71 |
coronavirus response to weather changes | 2 | Effects of temperature and humidity on the daily new cases and new deaths of COVID-19 in 166 countries | The coronavirus disease 2019 (COVID-19) pandemic is the defining global health crisis of our time and the greatest challenge facing the world. Meteorological parameters are reportedly crucial factors affecting respiratory infectious disease epidemics; however, the effect of meteorological parameters on COVID-19 remains controversial. This study investigated the effects of temperature and relative humidity on daily new cases and daily new deaths of COVID-19, which has useful implications for policymakers and the public. Daily data on meteorological conditions, new cases and new deaths of COVID-19 were collected for 166 countries (excluding China) as of March 27, 2020. Log-linear generalized additive model was used to analyze the effects of temperature and relative humidity on daily new cases and daily new deaths of COVID-19, with potential confounders controlled for, including wind speed, median age of the national population, Global Health Security Index, Human Development Index and population density. Our findings revealed that temperature and relative humidity were both negatively related to daily new cases and deaths. A 1 °C increase in temperature was associated with a 3.08% (95% CI: 1.53%, 4.63%) reduction in daily new cases and a 1.19% (95% CI: 0.44%, 1.95%) reduction in daily new deaths, whereas a 1% increase in relative humidity was associated with a 0.85% (95% CI: 0.51%, 1.19%) reduction in daily new cases and a 0.51% (95% CI: 0.34%, 0.67%) reduction in daily new deaths. The results remained robust when different lag structures and the sensitivity analysis were used. These findings provide preliminary evidence that the COVID-19 pandemic may be partially suppressed with temperature and humidity increases. However, active measures must be taken to control the source of infection, block transmission and prevent further spread of COVID-19. | axn5dgkh |
coronavirus response to weather changes | 2 | A mechanism-based parameterisation scheme to investigate the association between transmission rate of COVID-19 and meteorological factors on plains in China | The novel coronavirus disease 2019 (COVID-19), which first emerged in Hubei province, China, has become a pandemic. However, data regarding the effects of meteorological factors on its transmission are limited and inconsistent. A mechanism-based parameterisation scheme was developed to investigate the association between the scaled transmission rate (STR) of COVID-19 and the meteorological parameters in 20 provinces/municipalities located on the plains in China. We obtained information on the scale of population migrated from Wuhan, the world epicentre of the COVID-19 outbreak, into the study provinces/municipalities using mobile-phone positioning system and big data techniques. The highest STRs were found in densely populated metropolitan areas and in cold provinces located in north-eastern China. Population density had a non-linear relationship with disease spread (linearity index, 0.9). Among various meteorological factors, only temperature was significantly associated with the STR after controlling for the effect of population density. A negative and exponential relationship was identified between the transmission rate and the temperature (correlation coefficient, -0.56; 99% confidence level). The STR increased substantially as the temperature in north-eastern China decreased below 0 °C (the STR ranged from 3.5 to 12.3 when the temperature was between -9.41 °C and -13.87 °C), whilst the STR showed less temperature dependence in the study areas with temperate weather conditions (the STR was 1.21 ± 0.57 when the temperature was above 0 °C). Therefore, a higher population density was linearly whereas a lower temperature (<0 °C) was exponentially associated with an increased transmission rate of COVID-19. These findings suggest that the mitigation of COVID-19 spread in densely populated and/or cold regions will be a great challenge. | o2lr936b |
coronavirus response to weather changes | 2 | Effect of weather on COVID-19 spread in the US: A prediction model for India in 2020 | The effect of weather on COVID-19 spread is poorly understood. Recently, few studies have claimed that warm weather can possibly slowdown the global pandemic, which has already affected over 1.6 million people worldwide. Clarification of such relationships in the worst affected country, the US, can be immensely beneficial to understand the role of weather in transmission of the disease in the highly populated countries, such as India. We collected the daily data of new cases in 50 US states between Jan 1-Apr 9, 2020 and also the corresponding weather information (i.e., temperature (T) and absolute humidity (AH)). Distribution modeling of new cases across AH and T, helped identify the narrow and vulnerable AH range. We validated the results for 10-day intervals against monthly observations, and also worldwide trends. The results were used to predict Indian regions which would be vulnerable to weather based spread in upcoming months of 2020. COVID-19 spread in the US is significant for states with 4 < AH < 6 g/m3 and number of new cases > 10,000, irrespective of the chosen time intervals for study parameters. These trends are consistent with worldwide observations, but do not correlate well with India so far possibly due the total cases reported per interval < 10,000. The results clarify the relationship between weather parameters and COVID-19 spread. The vulnerable weather parameters will help classify the risky geographic areas in different countries. Specifically, with further reporting of new cases in India, prediction of states with high risk of weather based spread will be apparent. | q2mn9y70 |
coronavirus response to weather changes | 2 | Short-term effects of specific humidity and temperature on COVID-19 morbidity in select US cities | Little is known about the environmental conditions that drive the spatiotemporal patterns of SARS-CoV-2. Preliminary research suggests an association with meteorological parameters. However, the relationship with temperature and humidity is not yet apparent for COVID-19 cases in US cities first impacted. The objective of this study is to evaluate the association between COVID-19 cases and meteorological parameters in select US cities. A case-crossover design with a distributed lag nonlinear model was used to evaluate the contribution of ambient temperature and specific humidity on COVID-19 cases in select US cities. The case-crossover examines each COVID case as its own control at different time periods (before and after transmission occurred). We modeled the effect of temperature and humidity on COVID-19 transmission using a lag period of 7 days. A subset of 8 cities were evaluated for the relationship with meteorological parameters and 5 cities were evaluated in detail. Short-term exposure to humidity was positively associated with COVID-19 transmission in 4 cities. The associations were small with 3 out of 4 cities exhibiting higher COVID19 transmission with specific humidity that ranged from 6 to 9 g/kg. Our results suggest that weather should be considered in infectious disease modeling efforts. Future work is needed over a longer time period and across different locations to clearly establish the weather-COVID19 relationship. | qnkntgnv |
coronavirus response to weather changes | 2 | Impact of meteorological factors on the COVID-19 transmission: A multi-city study in China | The purpose of the present study is to explore the associations between novel coronavirus disease 2019 (COVID-19) case counts and meteorological factors in 30 provincial capital cities of China. We compiled a daily dataset including confirmed case counts, ambient temperature (AT), diurnal temperature range (DTR), absolute humidity (AH) and migration scale index (MSI) for each city during the period of January 20th to March 2nd, 2020. First, we explored the associations between COVID-19 confirmed case counts, meteorological factors, and MSI using non-linear regression. Then, we conducted a two-stage analysis for 17 cities with more than 50 confirmed cases. In the first stage, generalized linear models with negative binomial distribution were fitted to estimate city-specific effects of meteorological factors on confirmed case counts. In the second stage, the meta-analysis was conducted to estimate the pooled effects. Our results showed that among 13 cities that have less than 50 confirmed cases, 9 cities locate in the Northern China with average AT below 0 °C, 12 cities had average AH below 4 g/m3, and one city (Haikou) had the highest AH (14.05 g/m3). Those 17 cities with 50 and more cases accounted for 90.6% of all cases in our study. Each 1 °C increase in AT and DTR was related to the decline of daily confirmed case counts, and the corresponding pooled RRs were 0.80 (95% CI: 0.75, 0.85) and 0.90 (95% CI: 0.86, 0.95), respectively. For AH, the association with COVID-19 case counts were statistically significant in lag 07 and lag 014. In addition, we found the all these associations increased with accumulated time duration up to 14 days. In conclusions, meteorological factors play an independent role in the COVID-19 transmission after controlling population migration. Local weather condition with low temperature, mild diurnal temperature range and low humidity likely favor the transmission. | c32lvwcc |
coronavirus response to weather changes | 2 | Temperature significantly changes COVID-19 transmission in (sub)tropical cities of Brazil | The coronavirus disease 2019 (COVID-19) outbreak has become a severe public health issue. The novelty of the virus prompts a search for understanding of how ecological factors affect the transmission and survival of the virus. Several studies have robustly identified a relationship between temperature and the number of cases. However, there is no specific study for a tropical climate such as Brazil. This work aims to determine the relationship of temperature to COVID-19 infection for the state capital cities of Brazil. Cumulative data with the daily number of confirmed cases was collected from February 27 to April 1, 2020, for all 27 state capital cities of Brazil affected by COVID-19. A generalized additive model (GAM) was applied to explore the linear and nonlinear relationship between annual average temperature compensation and confirmed cases. Also, a polynomial linear regression model was proposed to represent the behavior of the growth curve of COVID-19 in the capital cities of Brazil. The GAM dose-response curve suggested a negative linear relationship between temperatures and daily cumulative confirmed cases of COVID-19 in the range from 16.8 °C to 27.4 °C. Each 1 °C rise of temperature was associated with a -4.8951% (t = -2.29, p = 0.0226) decrease in the number of daily cumulative confirmed cases of COVID-19. A sensitivity analysis assessed the robustness of the results of the model. The predicted R-squared of the polynomial linear regression model was 0.81053. In this study, which features the tropical temperatures of Brazil, the variation in annual average temperatures ranged from 16.8 °C to 27.4 °C. Results indicated that temperatures had a negative linear relationship with the number of confirmed cases. The curve flattened at a threshold of 25.8 °C. There is no evidence supporting that the curve declined for temperatures above 25.8 °C. The study had the goal of supporting governance for healthcare policymakers. | dekdf7vu |
coronavirus response to weather changes | 2 | Projections for COVID-19 pandemic in India and effect of temperature and humidity | BACKGROUND AND AIMS: As, the COVID-19 has been deemed a pandemic by World Health Organization (WHO), and since it spreads everywhere throughout the world, investigation in relation to this disease is very much essential. Investigation of pattern in the occurrence of COVID-19, to check the influence of different meteorological factors on the incidence of COVID-19 and prediction of incidence of COVID-19 are the objectives of this paper. METHODS: For trend analysis, Sen's Slope and Man-Kendall test have been used, Generalized Additive Model (GAM) of regression has been used to check the influence of different meteorological factors on the incidence and to predict the frequency of COVID-19, and Verhulst (Logistic) Population Model has been used. RESULTS: Statistically significant linear trend found for the daily-confirmed cases of COVID-19. The regression analysis indicates that there is some influence of the interaction of average temperature (AT) and average relative humidity (ARH) on the incidence of COVID-19. However, this result is not consistent throughout the study area. The projections have been made up to 21st May, 2020. CONCLUSIONS: Trend and regression analysis give an idea of the incidence of COVID-19 in India while projection made by Verhulst (Logistic) Population Model for the confirmed cases of the study area are encouraging as the sample prediction is as same as the actual number of confirmed COVID-19 cases. | ipxvnlu2 |
coronavirus response to weather changes | 2 | Development of an Assessment Method for Investigating the Impact of Climate and Urban Parameters in Confirmed Cases of COVID-19: A New Challenge in Sustainable Development | Sustainable development has been a controversial global topic, and as a complex concept in recent years, it plays a key role in creating a favorable future for societies. Meanwhile, there are several problems in the process of implementing this approach, like epidemic diseases. Hence, in this study, the impact of climate and urban factors on confirmed cases of COVID-19 (a new type of coronavirus) with the trend and multivariate linear regression (MLR) has been investigated to propose a more accurate prediction model. For this propose, some important climate parameters, including daily average temperature, relative humidity, and wind speed, in addition to urban parameters such as population density, were considered, and their impacts on confirmed cases of COVID-19 were analyzed. The analysis was performed for three case studies in Italy, and the application of the proposed method has been investigated. The impacts of parameters have been considered with a delay time from one to nine days to find out the most suitable combination. The result of the analysis demonstrates the effectiveness of the proposed model and the impact of climate parameters on the trend of confirmed cases. The research hypothesis approved by the MLR model and the present assessment method could be applied by considering several variables that exhibit the exact delay of them to new confirmed cases of COVID-19. | qmrgkkpr |
coronavirus response to weather changes | 2 | Factors determining the diffusion of COVID-19 and suggested strategy to prevent future accelerated viral infectivity similar to COVID | This study has two goals. The first is to explain the geo-environmental determinants of the accelerated diffusion of COVID-19 that is generating a high level of deaths. The second is to suggest a strategy to cope with future epidemic threats similar to COVID-19 having an accelerated viral infectivity in society. Using data on sample of N = 55 Italian province capitals, and data of infected individuals at as of April 7th, 2020, results reveal that the accelerate and vast diffusion of COVID-19 in North Italy has a high association with air pollution of cities measured with days exceeding the limits set for PM10 (particulate matter 10 µm or less in diameter) or ozone. In particular, hinterland cities with average high number of days exceeding the limits set for PM10 (and also having a low wind speed) have a very high number of infected people on 7th April 2020 (arithmetic mean is about 2200 infected individuals, with average polluted days greater than 80 days per year), whereas coastal cities also having days exceeding the limits set for PM10 or ozone but with high wind speed have about 944.70 average infected individuals, with about 60 average polluted days per year; moreover, cities having more than 100 days of air pollution (exceeding the limits set for PM10), they have a very high average number of infected people (about 3350 infected individuals, 7th April 2020), whereas cities having less than 100 days of air pollution per year, they have a lower average number of infected people (about 1014 individuals). The findings here also suggest that to minimize the impact of future epidemics similar to COVID-19, the max number of days per year that Italian provincial capitals or similar industrialized cities can exceed the limits set for PM10 or for ozone, considering their meteorological conditions, is about 48 days. Moreover, results here reveal that the explanatory variable of air pollution in cities seems to be a more important predictor in the initial phase of diffusion of viral infectivity (on 17th March 2020, b1 = 1.27, p < 0.001) than interpersonal contacts (b2 = 0.31, p < 0.05). In the second phase of maturity of the transmission dynamics of COVID-19, air pollution reduces intensity (on 7th April 2020 with b'1 = 0.81, p < 0.001) also because of the indirect effect of lockdown, whereas regression coefficient of transmission based on interpersonal contacts has a stable level (b'2 = 0.31, p < 0.01). This result reveals that accelerated transmission dynamics of COVID-19 is due to mainly to the mechanism of "air pollution-to-human transmission" (airborne viral infectivity) rather than "human-to-human transmission". Overall, then, transmission dynamics of viral infectivity, such as COVID-19, is due to systemic causes: general factors that are the same for all regions (e.g., biological characteristics of virus, incubation period, etc.) and specific factors which are different for each region and/or city (e.g., complex interaction between air pollution, meteorological conditions and biological characteristics of viral infectivity) and health level of individuals (habits, immune system, age, sex, etc.). Lessons learned for COVID-19 in the case study here suggest that a proactive strategy to cope with future epidemics is also to apply especially an environmental and sustainable policy based on reduction of levels of air pollution mainly in hinterland and polluting cities- (having low wind speed, high percentage of moisture and number of fog days) -that seem to have an environment that foster a fast transmission dynamics of viral infectivity in society. Hence, in the presence of polluting industrialization in regions that can trigger the mechanism of air pollution-to-human transmission dynamics of viral infectivity, this study must conclude that a comprehensive strategy to prevent future epidemics similar to COVID-19 has to be also designed in environmental and socioeconomic terms, that is also based on sustainability science and environmental science, and not only in terms of biology, medicine, healthcare and health sector. | kysm5eq2 |
coronavirus response to weather changes | 2 | Impact of temperature on the dynamics of the COVID-19 outbreak in China | A COVID-19 outbreak emerged in Wuhan, China at the end of 2019 and developed into a global pandemic during March 2020. The effects of temperature on the dynamics of the COVID-19 epidemic in China are unknown. Data on COVID-19 daily confirmed cases and daily mean temperatures were collected from 31 provincial-level regions in mainland China between Jan. 20 and Feb. 29, 2020. Locally weighted regression and smoothing scatterplot (LOESS), distributed lag nonlinear models (DLNMs), and random-effects meta-analysis were used to examine the relationship between daily confirmed cases rate of COVID-19 and temperature conditions. The daily number of new cases peaked on Feb. 12, and then decreased. The daily confirmed cases rate of COVID-19 had a biphasic relationship with temperature (with a peak at 10 °C), and the daily incidence of COVID-19 decreased at values below and above these values. The overall epidemic intensity of COVID-19 reduced slightly following days with higher temperatures with a relative risk (RR) was 0.96 (95% CI: 0.93, 0.99). A random-effect meta-analysis including 28 provinces in mainland China, we confirmed the statistically significant association between temperature and RR during the study period (Coefficient = -0.0100, 95% CI: -0.0125, -0.0074). The DLNMs in Hubei Province (outside of Wuhan) and Wuhan showed similar patterns of temperature. Additionally, a modified susceptible-exposed-infectious-recovered (M-SEIR) model, with adjustment for climatic factors, was used to provide a complete characterization of the impact of climate on the dynamics of the COVID-19 epidemic. | u1mrvjjf |
coronavirus response to weather changes | 2 | Arctic Oscillation: possible trigger of COVID-19 outbreak | The current COVID-19 pandemic is having detrimental consequences worldwide. The pandemic started to develop strongly by the end of January and beginning of February 2020, first in China with subsequent rapid spread to other countries with new epicenters of the outbreaks concentrated mainly within the 30-50 degrees North latitudinal band (e.g., South Korea, Japan, Iran, Italy, Spain). Simultaneously, an unusual persistent anticyclonic situation prevailing at latitudes around 40 degrees North was observed on global scale, in line with an anomalously strong positive phase of the Arctic Oscillation. This atypical situation could have resulted in favorable meteorological conditions for a quicker spread of the virus over the latitude band detailed above. This possible connection needs further attention in order to understand the meteorological and climatological factors related to the COVID-19 outbreak, and for anticipating the spatio-temporal distribution of possible future pandemics. | n0c0928t |
coronavirus response to weather changes | 2 | Assessing the relationship between ground levels of ozone (O3) and nitrogen dioxide (NO2) with coronavirus (COVID-19) in Milan, Italy | This paper investigates the correlation between the high level of coronavirus SARS-CoV-2 infection accelerated transmission and lethality, and surface air pollution in Milan metropolitan area, Lombardy region in Italy. For January-April 2020 period, time series of daily average inhalable gaseous pollutants ozone (O3) and nitrogen dioxide (NO2), together climate variables (air temperature, relative humidity, wind speed, precipitation rate, atmospheric pressure field and Planetary Boundary Layer) were analyzed. In spite of being considered primarily transmitted by indoor bioaerosols droplets and infected surfaces or direct human-to-human personal contacts, it seems that high levels of urban air pollution, and climate conditions have a significant impact on SARS-CoV-2 diffusion. Exhibited positive correlations of ambient ozone levels and negative correlations of NO2 with the increased rates of COVID-19 infections (Total number, Daily New positive and Total Deaths cases), can be attributed to airborne bioaerosols distribution. The results show positive correlation of daily averaged O3 with air temperature and inversely correlations with relative humidity and precipitation rates. Viral genome contains distinctive features, including a unique N-terminal fragment within the spike protein, which allows coronavirus attachment on ambient air pollutants. At this moment it is not clear if through airborne diffusion, in the presence of outdoor and indoor aerosols, this protein "spike" of the new COVID-19 is involved in the infectious agent transmission from a reservoir to a susceptible host during the highest nosocomial outbreak in some agglomerated industrialized urban areas like Milan is. Also, in spite of collected data for cold season (winter-early spring) period, when usually ozone levels have lower values than in summer, the findings of this study support possibility as O3 can acts as a COVID-19 virus incubator. Being a novel pandemic coronavirus version, it might be ongoing during summer conditions associated with higher air temperatures, low relative humidity and precipitation levels. | ksu2gjyb |
coronavirus response to weather changes | 2 | Prioritizing and Analyzing the Role of Climate and Urban Parameters in the Confirmed Cases of COVID-19 Based on Artificial Intelligence Applications | Nowadays, an infectious disease outbreak is considered one of the most destructive effects in the sustainable development process. The outbreak of new coronavirus (COVID-19) as an infectious disease showed that it has undesirable social, environmental, and economic impacts, and leads to serious challenges and threats. Additionally, investigating the prioritization parameters is of vital importance to reducing the negative impacts of this global crisis. Hence, the main aim of this study is to prioritize and analyze the role of certain environmental parameters. For this purpose, four cities in Italy were selected as a case study and some notable climate parameters-such as daily average temperature, relative humidity, wind speed-and an urban parameter, population density, were considered as input data set, with confirmed cases of COVID-19 being the output dataset. In this paper, two artificial intelligence techniques, including an artificial neural network (ANN) based on particle swarm optimization (PSO) algorithm and differential evolution (DE) algorithm, were used for prioritizing climate and urban parameters. The analysis is based on the feature selection process and then the obtained results from the proposed models compared to select the best one. Finally, the difference in cost function was about 0.0001 between the performances of the two models, hence, the two methods were not different in cost function, however, ANN-PSO was found to be better, because it reached to the desired precision level in lesser iterations than ANN-DE. In addition, the priority of two variables, urban parameter, and relative humidity, were the highest to predict the confirmed cases of COVID-19. | nz5fqi0e |
coronavirus response to weather changes | 2 | Susceptible supply limits the role of climate in the early SARS-CoV-2 pandemic | Preliminary evidence suggests that climate may modulate the transmission of SARS-CoV-2. Yet it remains unclear whether seasonal and geographic variations in climate can substantially alter the pandemic trajectory, given high susceptibility is a core driver. Here, we use a climate-dependent epidemic model to simulate the SARS-CoV-2 pandemic probing different scenarios based on known coronavirus biology. We find that while variations in weather may be important for endemic infections, during the pandemic stage of an emerging pathogen the climate drives only modest changes to pandemic size. A preliminary analysis of non-pharmaceutical control measures indicates that they may moderate the pandemic-climate interaction via susceptible depletion. Our findings suggest, without effective control measures, strong outbreaks are likely in more humid climates and summer weather will not substantially limit pandemic growth. | aiwxlxzt |
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CLUSTREC-COVID: A Topical Clustering Benchmark for COVID-19 Scientific Research
Dataset Summary
CLUSTREC-COVID is a modified version of the TREC-COVID dataset, transformed into a topical clustering benchmark. The dataset consists of titles and abstracts from scientific papers about COVID-19 research, covering a diverse range of research topics. Each document in the dataset is assigned to a specific subtopic, making it ideal for use in document clustering and topic modeling tasks.
The dataset is useful for researchers aiming to evaluate clustering algorithms and techniques for automatic organization of scientific literature. It can also be used for exploring information retrieval systems that aim to group documents by subtopic or related research areas.
The source of this dataset is the TREC-COVID retrieval dataset, which has been adapted for clustering and organization tasks.
Dataset Structure
Each document in the dataset includes the following fields:
- topic_name (string): The specific subtopic to which the document has been assigned. (e.g., "coronavirus response to weather changes").
- topic_id (string): A unique identifier for the topic. (cluster identifier)
- title (string): The title of the scientific paper.
- abstract (string): The abstract or summary of the paper.
- doc_id (string): A unique document identifier.
Example Entry
{
"topic_name": "coronavirus response to weather changes",
"topic_id": "2",
"title": "Weather variables impact on COVID-19 incidence",
"abstract": "We test the hypothesis of COVID-19 contagion being influenced by meteorological parameters such as temperature or humidity.\
We analysed data at high spatial resolution (regions in Italy and counties in the USA) and found that while at low resolution this might seem the case,\
at higher resolution no correlation is found. Our results are consistent with a poor outdoors transmission of the disease. However,\
a possible indirect correlation between good weather and a decrease in disease spread may occur,\
as people spend longer time outdoors.",
"doc_id": "hadnxjeo",
}
Citation Information
Cite as:
@article{katz2024knowledge,
title={Knowledge Navigator: LLM-guided Browsing Framework for Exploratory Search in Scientific Literature},
author={Katz, Uri and Levy, Mosh and Goldberg, Yoav},
journal={arXiv preprint arXiv:2408.15836},
year={2024}
}
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