The global population of SARS-CoV-2 is composed of six major subtypes

A comprehensive analysis of SARS-CoV-2 missense mutations indicates that all possible amino acid replacements in the viral proteins occurred within the first two-and-a-half years of the pandemic

The surveillance of COVID-19 pandemic has led to the determination of millions of genome sequences of the SARS-CoV-2 virus, with the accumulation of a wealth of information never collected before for an infectious disease. Exploring the information retrieved from the GISAID database reporting at that time >13 million genome sequences, we classified the 141,639 unique missense mutations detected in the first two-and-a-half years (up to October 2022) of the pandemic. Notably, our analysis indicates that 98.2 % of all possible conservative amino acid replacements occurred. Even non-conservative mutations were highly represented (73.9 %). For a significant number of residues (3 %), all possible replacements with the other nineteen amino acids have been observed. These observations strongly indicate that, in this time interval, the virus explored all possible alternatives in terms of missense mutations for all sites of its polypeptide chain and that those that are not observed severely affect SARS-CoV-2 integrity. The implications of the present findings go well beyond the structural biology of SARS-CoV-2 as the huge amount of information here collected and classified may be valuable for the elucidation of the sequence-structure-function relationships in proteins.

Integrating Multi-Omics Data With EHR for Precision Medicine Using Advanced Artificial Intelligence

With the recent advancement of novel biomedical technologies such as high-throughput sequencing and wearable devices, multi-modal biomedical data ranging from multi-omics molecular data to real-time continuous bio-signals are generated at an unprecedented speed and scale every day. For the first time, these multi-modal biomedical data are able to make precision medicine close to a reality. However, due to data volume and the complexity, making good use of these multi-modal biomedical data requires major effort. Researchers and clinicians are actively developing artificial intelligence (AI) approaches for data-driven knowledge discovery and causal inference using a variety of biomedical data modalities. These AI-based approaches have demonstrated promising results in various biomedical and healthcare applications. In this review paper, we summarize the state-of-the-art AI models for integrating multi-omics data and electronic health records (EHRs) for precision medicine. We discuss the challenges and opportunities in integrating multi-omics data with EHRs and future directions. We hope this review can inspire future research and developing in integrating multi-omics data with EHRs for precision medicine.

A tool for the cheap and rapid screening of SARS-CoV-2 variants of concern (VoCs) by Sanger sequencing

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an emerging virus that, since March 2020, has been responsible for a global and ongoing pandemic. Its rapid spread over the past nearly 3 years has caused novel variants to arise. To monitor the circulation and emergence of SARS-CoV-2 variants, surveillance systems based on nucleotide mutations are required. In this regard, we searched in the spike, ORF8, and nucleocapsid genes to detect variable sites among SARS-CoV-2 variants. We describe polymorphic genetic regions that enable us to differentiate between the Alpha, Beta, Gamma, Delta, and Omicron variants of concern (VoCs). We found 21 relevant mutations, 13 of which are unique for Omicron lineages BA.1/BA.1.1, BA.2, BA.3, BA.4, and BA.5. This genetic profile enables the discrimination between VoCs using only four reverse transcription PCR fragments and Sanger sequencing, offering a cheaper and faster alternative to whole-genome sequencing for SARS-CoV-2 surveillance. IMPORTANCE Our work describes a new (Sanger sequencing-based) screening methodology for SARS-CoV-2, performing PCR amplifications of a few target regions to detect diagnostic mutations between virus variants. Using the methodology developed in this work, we were able to discriminate between the following VoCs: Alpha, Beta, Gamma, Delta, and Omicron (BA.1/BA.1.1, BA.2, BA.3, BA.4, and BA.5). This becomes important, especially in low-income countries where current methodologies like next-generation sequencing have prohibitive costs. Furthermore, rapid detection would allow sanitary authorities to take rapid measures to limit the spread of the virus and therefore reduce the probability of new virus dispersion. With this methodological approach, 13 previously unreported diagnostic mutations among several Omicron lineages were found.

Porcine Reproductive and Respiratory Syndrome (PRRSV2) Viral Diversity within a Farrow-to-Wean Farm Cohort Study

Describing PRRSV whole-genome viral diversity data over time within the host and within-farm is crucial for a better understanding of viral evolution and its implications. A cohort study was conducted at one naïve farrow-to-wean farm reporting a PRRSV outbreak. All piglets 3-5 days of age (DOA) born to mass-exposed sows through live virus inoculation with the recently introduced wild-type virus two weeks prior were sampled and followed up at 17-19 DOA. Samples from 127 piglets were individually tested for PRRSV by RT-PCR and 100 sequences were generated using Oxford Nanopore Technologies chemistry. Female piglets had significantly higher median Ct values than males (15.5 vs. 13.7, Kruskal-Wallis p < 0.001) at 3-5 DOA. A 52.8% mortality between sampling points was found, and the odds of dying by 17-19 DOA decreased with every one unit increase in Ct values at 3-5 DOA (OR = 0.76, 95% CI 0.61-0.94, p = 0.01). Although the within-pig percent nucleotide identity was overall high (99.7%) between 3-5 DOA and 17-19 DOA samples, ORFs 4 and 5a showed much lower identities (97.26% and 98.53%, respectively). When looking solely at ORF5, 62% of the sequences were identical to the 3-5 DOA consensus. Ten and eight regions showed increased nucleotide and amino acid genetic diversity, respectively, all found throughout ORFs 2a/2b, 4, 5a/5, 6, and 7.

Tracking of Mutational Signature of SARS-CoV-2 Omicron on Distinct Continents and Little Difference was Found

The Omicron variant is currently ravaging the world, raising serious concern globally. Monitoring genomic variations and determining their influence on biological features are critical for tracing its ongoing transmission and facilitating effective measures. Based on large-scale sequences from different continents, this study found that: (i) The genetic diversity of Omicron is much lower than that of the Delta variant. Still, eight deletions (Del 1-8) and 1 insertion, as well as 130 SNPs, were detected on the Omicron genomes, with two deletions (Del 3 and 4) and 38 SNPs commonly detected on all continents and exhibiting high-occurring frequencies. (ii) Four groups of tightly linked SNPs (linkage I-IV) were detected, among which linkage I, containing 38 SNPs, with 6 located in the RBD, increased its occurring frequency remarkably over time. (iii) The third codons of the Omicron shouldered the most mutation pressures, while the second codons presented the least flexibility. (iv) Four major mutants with amino acid substitutions in the RBD were detected, and further structural analysis suggested that the substitutions did not alter the viral receptor binding ability greatly. It was inferred that though the Omicron genome harbored great changes in antigenicity and remarkable ability to evade immunity, it was immune-pressure selected. This study tracked mutational signatures of Omicron variant and the potential biological significance of the SNPs, and the linkages await further functional verification.

Clinical and temporal characterization of COVID-19 subgroups using patient vector embeddings of electronic health records

OBJECTIVE

To identify and characterize clinical subgroups of hospitalized Coronavirus Disease 2019 (COVID-19) patients.

MATERIALS AND METHODS

Electronic health records of hospitalized COVID-19 patients at NewYork-Presbyterian/Columbia University Irving Medical Center were temporally sequenced and transformed into patient vector representations using Paragraph Vector models. K-means clustering was performed to identify subgroups.

RESULTS

A diverse cohort of 11 313 patients with COVID-19 and hospitalizations between March 2, 2020 and December 1, 2021 were identified; median [IQR] age: 61.2 [40.3-74.3]; 51.5% female. Twenty subgroups of hospitalized COVID-19 patients, labeled by increasing severity, were characterized by their demographics, conditions, outcomes, and severity (mild-moderate/severe/critical). Subgroup temporal patterns were characterized by the durations in each subgroup, transitions between subgroups, and the complete paths throughout the course of hospitalization.

DISCUSSION

Several subgroups had mild-moderate severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections but were hospitalized for underlying conditions (pregnancy, cardiovascular disease [CVD], etc.). Subgroup 7 included solid organ transplant recipients who mostly developed mild-moderate or severe disease. Subgroup 9 had a history of type-2 diabetes, kidney and CVD, and suffered the highest rates of heart failure (45.2%) and end-stage renal disease (80.6%). Subgroup 13 was the oldest (median: 82.7 years) and had mixed severity but high mortality (33.3%). Subgroup 17 had critical disease and the highest mortality (64.6%), with age (median: 68.1 years) being the only notable risk factor. Subgroups 18-20 had critical disease with high complication rates and long hospitalizations (median: 40+ days). All subgroups are detailed in the full text. A chord diagram depicts the most common transitions, and paths with the highest prevalence, longest hospitalizations, lowest and highest mortalities are presented. Understanding these subgroups and their pathways may aid clinicians in their decisions for better management and earlier intervention for patients.

Unsupervised clustering of SARS-CoV-2 using deep convolutional autoencoder

SARS-CoV-2’s population structure might have a substantial impact on public health management and diagnostics if it can be identified. It is critical to rapidly monitor and characterize their lineages circulating globally for a more accurate diagnosis, improved care, and faster treatment. For a clearer picture of the SARS-CoV-2 population structure, clustering the sequencing data is essential. Here, deep clustering techniques were used to automatically group 29,017 different strains of SARS-CoV-2 into clusters. We aim to identify the main clusters of SARS-CoV-2 population structure based on convolutional autoencoder (CAE) trained with numerical feature vectors mapped from coronavirus Spike peptide sequences. Our clustering findings revealed that there are six large SARS-CoV-2 population clusters (C1, C2, C3, C4, C5, C6). These clusters contained 43 unique lineages in which the 29,017 publicly accessible strains were dispersed. In all the resulting six clusters, the genetic distances within the same cluster (intra-cluster distances) are less than the distances between inter-clusters (P-value 0.0019, Wilcoxon rank-sum test). This indicates substantial evidence of a connection between the cluster’s lineages. Furthermore, comparisons of the K-means and hierarchical clustering methods have been examined against the proposed deep learning clustering method. The intra-cluster genetic distances of the proposed method were smaller than those of K-means alone and hierarchical clustering methods. We used T-distributed stochastic-neighbor embedding (t-SNE) to show the outcomes of the deep learning clustering. The strains were isolated correctly between clusters in the t-SNE plot. Our results showed that the (C5) cluster exclusively includes Gamma lineage (P.1) only, suggesting that strains of P.1 in C5 are more diversified than those in the other clusters. Our study indicates that the genetic similarity between strains in the same cluster enables a better understanding of the major features of the unknown population lineages when compared to some of the more prevalent viral isolates. This information helps researchers figure out how the virus changed over time and spread to people all over the world.

A survey on the correlation between PM2.5 concentration and the incidence of suspected and positive cases of COVID-19 referred to medical centers: A case study of Tehran

COVID-19, one of the greatest health challenges of the present century, has infected millions of people and caused more than 6 million deaths worldwide. The causative agent of this disease is the new virus SARS-CoV-2; which continues to spread globally and sometimes with new and more complex aspects than before. The present study is an observational study aimed to investigate the role of AQI; PM_2.5 and its relationship with the incidence of suspected cases (SC) and positive cases (PC) of COVID-19 at different levels of the air quality index (AQI) in Tehran, the capital of Iran in the period from Feb 20th, 2020 to Feb 22nd, 2021. Data on AQI were collected online from the air monitoring website of Air Quality Control Company under the supervision of Tehran Municipality. The data on suspected and positive cases were obtained from the Iranian Ministry of Health. The results and statistical analysis (Pearson correlation test) showed that with the increase of AQI level, the number of suspected cases (SC) and positive cases (PC), also increased (P-value<0.01). The average daily number of suspected and positive COVID-19 cases referred to medical centers, at different levels of the AQI was as follows: level II: yellow, moderate (SC: N_ave = 466; PC: N_ave = 223), level III: orange, unhealthy for sensitive groups (SC: N_ave = 564; PC: N_ave = 275), and Level IV: red, unhealthy (SC: N_ave = 558; PC: N_ave = 294). The results of the GEE for seasonal comparison (winter as reference season), showed that there is an epidemiological pattern in autumn with colder weather compared to other seasons in both suspected (Cl: %95, B = 408.94) and positive (Cl: %95, B = 83.42) cases of COVID-19. The results of this study will serve policymakers as an informative tool for guidance on the importance of the role of air pollution in viral epidemics.

Contrasting Epidemiology and Population Genetics of COVID-19 Infections Defined by Multilocus Genotypes in SARS-CoV-2 Genomes Sampled Globally

Since its emergence in 2019, SARS-CoV-2 has spread and evolved globally, with newly emerged variants of concern (VOCs) accounting for more than 500 million COVID-19 cases and 6 million deaths. Continuous surveillance utilizing simple genetic tools is needed to measure the viral epidemiological diversity, risk of infection, and distribution among different demographics in different geographical regions. To help address this need, we developed a proof-of-concept multilocus genotyping tool and demonstrated its utility to monitor viral populations sampled in 2020 and 2021 across six continents. We sampled globally 22,164 SARS-CoV-2 genomes from GISAID (inclusion criteria: available clinical and demographic data). They comprised two study populations, “2020 genomes” (N = 5959) sampled from December 2019 to September 2020 and “2021 genomes” (N = 16,205) sampled from 15 January to 15 March 2021. All genomes were aligned to the SARS-CoV-2 reference genome and amino acid polymorphisms were called with quality filtering. Thereafter, 74 codons (loci) in 14 genes including orf1ab polygene (N = 9), orf3a, orf8, nucleocapsid (N), matrix (M), and spike (S) met the 0.01 minimum allele frequency criteria and were selected to construct multilocus genotypes (MLGs) for the genomes. At these loci, 137 mutant/variant amino acids (alleles) were detected with eight VOC-defining variant alleles, including N KR203&204, orf1ab (I265, F3606, and L4715), orf3a H57, orf8 S84, and S G614, being predominant globally with > 35% prevalence. Their persistence and selection were associated with peaks in the viral transmission and COVID-19 incidence between 2020 and 2021. Epidemiologically, older patients (≥20 years) compared to younger patients (<20 years) had a higher risk of being infected with these variants, but this association was dependent on the continent of origin. In the global population, the discriminant analysis of principal components (DAPC) showed contrasting patterns of genetic clustering with three (Africa, Asia, and North America) and two (North and South America) continental clusters being observed for the 2020 and 2021 global populations, respectively. Within each continent, the MLG repertoires (range 40−199) sampled in 2020 and 2021 were genetically differentiated, with ≤4 MLGs per repertoire accounting for the majority of genomes sampled. These data suggested that the majority of SARS-CoV-2 infections in 2020 and 2021 were caused by genetically distinct variants that likely adapted to local populations. Indeed, four GISAID clade-defined VOCs - GRY (Alpha), GH (Beta), GR (Gamma), and G/GK (Delta variant) were differentiated by their MLG signatures, demonstrating the versatility of the MLG tool for variant identification. Results from this proof-of-concept multilocus genotyping demonstrates its utility for SARS-CoV-2 genomic surveillance and for monitoring its spatiotemporal epidemiology and evolution, particularly in response to control interventions including COVID-19 vaccines and chemotherapies.

In-Silico targeting of SARS-CoV-2 NSP6 for drug and natural products repurposing

Non-Structural Protein 6 (NSP6) has a protecting role for SARS-CoV-2 replication by inhibiting the expansion of autophagosomes inside the cell. NSP6 is involved in the endoplasmic reticulum stress response by binding to Sigma receptor 1 (SR1). Nevertheless, NSP6 crystal structure is not solved yet. Therefore, NSP6 is considered a challenging target in Structure-Based Drug Discovery. Herein, we utilized the high quality NSP6 model built by AlphaFold in our study. Targeting a putative NSP6 binding site is believed to inhibit the SR1-NSP6 protein-protein interactions. Three databases were virtually screened, namely FDA-approved drugs (DrugBank), Northern African Natural Products Database (NANPDB) and South African Natural Compounds Database (SANCDB) with a total of 8158 compounds. Further validation for 9 candidates via molecular dynamics simulations for 100 ns recommended potential binders to the NSP6 binding site. The proposed candidates are recommended for biological testing to cease the rapidly growing pandemic.

Genomic surveillance of SARS-CoV-2 in a university community: insights into tracking variants, transmission, and spread of Gamma (P.1) variant

Background

Using a combination of data from routine surveillance, genomic sequencing, and phylogeographic analysis we tracked the spread and introduction events of SARS-CoV-2 variants focusing on a large university community.

Methods

Here, we sequenced and analyzed 677 high-quality SARS-CoV-2 genomes from positive RNA samples collected from Purdue University students, faculty, and staff who tested positive for the virus between January 2021 and May 2021, comprising an average of 32% of weekly cases across the time frame.

Results

Our analysis of circulating SARS-CoV-2 variants over time revealed periods when Variant of Concern (VOC) Alpha (B.1.1.7) and Iota (B.1.526) reached rapid dominance and documented that VOC Gamma (P.1) was increasing in frequency as campus surveillance was ending. Phylodynamic analysis of Gamma genomes from campus alongside a subsampling of &gt;20,000 previously published P.1 genomes revealed ten independent introductions of this variant into the Purdue community, predominantly from elsewhere in the United States, with introductions from within the state of Indiana and from Illinois, and possibly Washington and New York, suggesting a degree of domestic spread.

Conclusions

We conclude that a robust and sustained active and passive surveillance program coupled with genomic sequencing during a pandemic offers important insights into the dynamics of pathogen arrival and spread in a campus community and can help guide mitigation measures.

An Update on Severe Acute Respiratory Syndrome Coronavirus 2 Diversity in the US National Capital Region: Evolution of Novel and Variants of Concern

BACKGROUND

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants concerning for enhanced transmission, evasion of immune responses, or associated with severe disease have motivated the global increase in genomic surveillance. In the current study, large-scale whole-genome sequencing was performed between November 2020 and the end of March 2021 to provide a phylodynamic analysis of circulating variants over time. In addition, we compared the viral genomic features of March 2020 and March 2021.

METHODS

A total of 1600 complete SARS-CoV-2 genomes were analyzed. Genomic analysis was associated with laboratory diagnostic volumes and positivity rates, in addition to an analysis of the association of selected variants of concern/variants of interest with disease severity and outcomes. Our real-time surveillance features a cohort of specimens from patients who tested positive for SARS-CoV-2 after completion of vaccination.

RESULTS

Our data showed genomic diversity over time that was not limited to the spike sequence. A significant increase in the B.1.1.7 lineage (alpha variant) in March 2021 as well as a transient circulation of regional variants that carried both the concerning S: E484K and S: P681H substitutions were noted. Lineage B.1.243 was significantly associated with intensive care unit admission and mortality. Genomes recovered from fully vaccinated individuals represented the predominant lineages circulating at specimen collection time, and people with those infections recovered with no hospitalizations.

CONCLUSIONS

Our results emphasize the importance of genomic surveillance coupled with laboratory, clinical, and metadata analysis for a better understanding of the dynamics of viral spread and evolution.

The human ACE-2 receptor binding domain of SARS-CoV-2 express on the viral surface of the Newcastle disease virus as a non-replicating viral vector vaccine candidate

Since the SARS-CoV-2 infection was identified in December 2019, SARS-CoV-2 infection has rapidly spread worldwide and has become a significant pandemic disease. In addition, human death and serious health problem caused by SARS-CoV-2 infection, the socio-economic impact has been very serious. Here, we describe the development of the viral vector vaccine, which is the receptor-binding domain (RBD) of SARS-CoV-2 expressed on the surface of Newcastle disease virus (LVP-K1-RBD19). The RBD protein concentrations on the viral surface were measured by the sandwich ELISA method. 106.7 TCID50/ml of LVP-K1-RBD19 has a 0.17 μg of RBD protein. Optical density (OD) values of mouse sera inoculated with 10 μg of RBD protein expressed on the surface of LVP-K1-RBD19 generated 1.78-fold higher RBD-specific antibody titers than mice inoculated with 10 μg RBD protein with alum at 28 dpi. Moreover, mice inoculated with 10 μg of RBD protein expressed on the surface of LVP-K1-RBD19 virus showed more than 80% neutralization at 1:256 against the SARS-CoV-2 pseudovirus. These results demonstrated that inactivated LVP-K1-RBD19 virus produces neutralizing antibodies against SARS-CoV-2 in a short period and could be elect protective immunity in humans and LVP-K1-RBD19 will be a good candidate for the COVID-19 vaccine.

Growth, Antigenicity, and Immunogenicity of SARS-CoV-2 Spike Variants Revealed by a Live rVSV-SARS-CoV-2 Virus

SARS-CoV-2 is an emerging coronavirus threatening human health and the economy worldwide. As an RNA virus, variants emerge during the pandemic and potentially influence the efficacy of the anti-viral drugs and vaccines. Eight spike variants harboring highly recurrent mutations were selected and introduced into a replication-competent recombinant VSV in place of the original G protein (rVSV-SARS-CoV-2). The resulting mutant viruses displayed similar growth curves in vitro as the wild-type virus and could be neutralized by sera from convalescent COVID-19 patients. Several variants, especially Beta strain, showed resistance to human neutralizing monoclonal antibodies targeting the receptor-binding domain (RBD). A single dose of rVSV-SARS-CoV-2 Beta variant could elicit enhanced and broad-spectrum neutralizing antibody responses in human ACE2 knock-in mice and golden Syrian hamsters, while other mutants generated antibody levels comparable to the wild-type. Therefore, our results will be of value to the development of next-generation vaccines and therapeutic antibodies.

Identification of genotypic variants and its proteomic mutations of Brazilian SARS-CoV-2 isolates

The second wave of COVID-19 caused by severe acute respiratory syndrome virus (SARS-CoV-2) is rapidly spreading over the world. Mechanisms behind the flee from current antivirals are still unclear due to the continuous occurrence of SARS-CoV-2 genetic variants. Brazil is the world's second-most COVID-19 affected country. In the present study, we identified the genomic and proteomic variants of Brazilian SARS-CoV-2 isolates. We identified 16 different genotypic variants were found among the 27 isolates. The genotypes of three isolates such as Bra/1236/2021 (G15), Bra/MASP2C844R2/2020 (G11), and Bra/RJ-DCVN5/2020 (G9) have a unique mutant in NSP4 (S184N), 2′O-Mutase (R216N), membrane protein (A2V) and Envelope protein (V5A). A mutation in RdRp of SARS-CoV-2, particularly the change of Pro-to Leu-at 323 resulted in the stabilization of the structure in BRA/CD1739-P4/2020. NSP4, NSP5 protein mutants are more virulent in genotype 15 and 16. A fast protein folding rate changes the structural stability and leads to escape for current antivirals. Thus, our findings help researchers to develop the best potent antivirals based on the new mutant of Brazilian isolates.

Insight into COVID-19's epidemiology, pathology, and treatment

The newly emerged 2019 coronavirus disease (COVID-19) has urged scientific and medical communities to focus on epidemiology, pathophysiology, and treatment of SARS-CoV-2. Indeed, little is known about the virus causing this severe acute respiratory syndrome pandemic, coronavirus (SARS-CoV-2). Data already collected on viruses belonging to the coronaviridae family are of interest to improve our knowledge rapidly on this pandemic. The current review aims at delivering insight into the fundamental advances inSARS-CoV-2 epidemiology, pathophysiology, life cycle, and treatment.

Biology of the SARS-CoV-2 Coronavirus

New coronavirus infection causing COVID-19, which was first reported in late 2019 in China, initiated severe social and economic crisis that affected the whole world. High frequency of the errors in replication of RNA viruses, zoonotic nature of transmission, and high transmissibility allowed betacoronaviruses to cause the third pandemic in the world since the beginning of 2003: SARS-CoV in 2003, MERS-CoV in 2012, and SARS-CoV-2 in 2019. The latest pandemic united scientific community and served as a powerful impetus in the study of biology of coronaviruses: new routes of virus penetration into the human cells were identified, features of the replication cycle were studied, and new functions of coronavirus proteins were elucidated. It should be recognized that the pandemic was accompanied by the need to obtain and publish results within a short time, which led to the emergence of an array of conflicting data and low reproducibility of research results. We systematized and analyzed scientific literature, filtered the results according to reliability of the methods of analysis used, and prepared a review describing molecular mechanisms of functioning of the SARS-CoV-2 coronavirus. This review considers organization of the genome of the SARS-CoV-2 virus, mechanisms of its gene expression and entry of the virus into the cell, provides information on key mutations that characterize different variants of the virus, and their contribution to pathogenesis of the disease.

A global analysis of conservative and non-conservative mutations in SARS-CoV-2 detected in the first year of the COVID-19 world-wide diffusion

The ability of SARS-CoV-2 to rapidly mutate represents a remarkable complicancy. Quantitative evaluations of the effects that these mutations have on the virus structure/function is of great relevance and the availability of a large number of SARS-CoV-2 sequences since the early phases of the pandemic represents a unique opportunity to follow the adaptation of the virus to humans. Here, we evaluated the SARS-CoV-2 amino acid mutations and their progression by analyzing publicly available viral genomes at three stages of the pandemic (2020 March 15th and October 7th, 2021 February 7th). Mutations were classified in conservative and non-conservative based on the probability to be accepted during the evolution according to the Point Accepted Mutation substitution matrices and on the similarity of the encoding codons. We found that the most frequent substitutions are T > I, L > F, and A > V and we observe accumulation of hydrophobic residues. These findings are consistent among the three stages analyzed. We also found that non-conservative mutations are less frequent than conservative ones. This finding may be ascribed to a progressive adaptation of the virus to the host. In conclusion, the present study provides indications of the early evolution of the virus and tools for the global and genome-specific evaluation of the possible impact of mutations on the structure/function of SARS-CoV-2 variants.

Unsupervised clustering analysis of SARS-Cov-2 population structure reveals six major subtypes at early stage across the world

Identifying the population structure of the newly emerged coronavirus SARS-CoV-2 has significant potential to inform public health management and diagnosis. As SARS-CoV-2 sequencing data accrued, grouping them into clusters is important for organizing the landscape of the population structure of the virus. Due to the limited prior information on the newly emerged coronavirus, we utilized four different clustering algorithms to group 16,873 SARS-CoV-2 strains, which automatically enables the identification of spatial structure for SARS-CoV-2. A total of six distinct genomic clusters were identified using mutation profiles as input features. Comparison of the clustering results reveals that the four algorithms produced highly consistent results, but the state-of-the-art unsupervised deep learning clustering algorithm performed best and produced the smallest intra-cluster pairwise genetic distances. The varied proportions of the six clusters within different continents revealed specific geographical distributions. In particular, our analysis found that Oceania was the only continent on which the strains were dispersively distributed into six clusters. In summary, this study provides a concrete framework for the use of clustering methods to study the global population structure of SARS-CoV-2. In addition, clustering methods can be used for future studies of variant population structures in specific regions of these fast-growing viruses.

Surfaces and Air contamination by SARS-CoV-2 using High-flow Nasal Oxygenation or Assisted Mechanical Ventilation System in ICU rooms of COVID-19 Patients

BACKGROUND

Understanding patterns of environmental contamination by SARS-CoV-2 is essential for infection prevention policies.

METHODS

We screened surfaces and air samples from single bed ICU rooms of COVID-19 adult patients for SARS-CoV-2 RNA and viable viruses.

RESULTS AND DISCUSSION

We evidenced viral RNA environmental contamination in 76% of 100 surfaces samples and in 30% of 40 air samples without any viable virus detection by cell culture assays. No significant differences of viral RNA levels on surfaces and in ambient air were observed between rooms of patients with assisted mechanical ventilation and those of patients with high-flow nasal cannula system. Using an original experimental SARS-CoV-2 infection model of surfaces, we assessed that infectious viruses might have been present on benches within 15 hours before the time of sampling in patient rooms.

CONCLUSIONS

We observed that SARS-CoV-2 environmental contamination around COVID-19 patients hospitalized in single ICU rooms was extensive and that a high-flow nasal cannula system did not generate more viral aerosolization than a mechanical ventilation system in COVID-19 patients. Despite an absence of SARS-CoV-2 viable particles in study samples, our experimental model confirmed the need to apply strict environmental disinfection procedures and classical standard and droplet precautions in ICU wards.

Analysis of SARS-COV2 spike protein variants among Iraqi isolates

The ongoing pandemic of COVID-19 caused by the SARS-COV2 virus has triggered millions of deaths around the globe. Emerging several variants of the virus with increased transmissibility, the severity of disease, and the ability of the virus to escape from the immune system has a cause for concerns. Here, we compared the spike protein sequence of 91 human SARS CoV2 strains of Iraq to the first reported sequence of SARS-CoV2 isolate from Wuhan Hu-1/China. The strains were isolated between June 2020 and March 2021. Twenty-two distinct mutations were identified within the spike protein regions which were: L5F, L18F, T19R, S151T, G181A, A222V, A348S, L452 (Q or M), T478K, N501Y, A520S, A522V, A570D, S605A, D614G, Q675H, N679K, P681H, T716I, S982A, A1020S, D1118H. The most frequently mutations occurred at the D614G (87/91), followed by S982A (50/91), and A570D (48/91), respectively. In addition, a distinct shift was observed in the type of SARS-COV2 variants present in 2020 compared to 2021 isolates. In 2020, B.1.428.1 lineage was appeared to be a dominant variant (85%). However, the diversity of the variants increased in 2021, and the majority (73%) of the isolated were appeared to belong to B.1.1.7 lineage (VOC/alpha variants). To our knowledge, this is the first major genome analysis of SARS-CoV2 in Iraq. The data from this research could provide insights into SARS-CoV2 evolution, and can be potentially used to recognize the effective vaccine against the disease.

Phylogenomics and population genomics of SARS-CoV-2 in Mexico during the pre-vaccination stage reveals variants of interest B.1.1.28.4 and B.1.1.222 or B.1.1.519 and the nucleocapsid mutation S194L associated with symptoms

Understanding the evolution of the SARS-CoV-2 virus in various regions of the world during the Covid-19 pandemic is essential to help mitigate the effects of this devastating disease. We describe the phylogenomic and population genetic patterns of the virus in Mexico during the pre-vaccination stage, including asymptomatic carriers. A real-time quantitative PCR screening and phylogenomic reconstructions directed at sequence/structure analysis of the spike glycoprotein revealed mutation of concern E484K in genomes from central Mexico, in addition to the nationwide prevalence of the imported variant 20C/S:452R (B.1.427/9). Overall, the detected variants in Mexico show spike protein mutations in the N-terminal domain (i.e. R190M), in the receptor-binding motif (i.e. T478K, E484K), within the S1-S2 subdomains (i.e. P681R/H, T732A), and at the basis of the protein, V1176F, raising concerns about the lack of phenotypic and clinical data available for the variants of interest we postulate: 20B/478K.V1 (B.1.1.222 or B.1.1.519) and 20B/P.4 (B.1.1.28.4). Moreover, the population patterns of single nucleotide variants from symptomatic and asymptomatic carriers obtained with a self-sampling scheme confirmed the presence of several fixed variants, and differences in allelic frequencies among localities. We identified the mutation N:S194L of the nucleocapsid protein associated with symptomatic patients. Phylogenetically, this mutation is frequent in Mexican sub-clades. Our results highlight the dual and complementary role of spike and nucleocapsid proteins in adaptive evolution of SARS-CoV-2 to their hosts and provide a baseline for specific follow-up of mutations of concern during the vaccination stage.

Large-scale analysis of SARS-CoV-2 spike-glycoprotein mutants demonstrates the need for continuous screening of virus isolates

Due to the widespread of the COVID-19 pandemic, the SARS-CoV-2 genome is evolving in diverse human populations. Several studies already reported different strains and an increase in the mutation rate. Particularly, mutations in SARS-CoV-2 spike-glycoprotein are of great interest as it mediates infection in human and recently approved mRNA vaccines are designed to induce immune responses against it. We analyzed 1,036,030 SARS-CoV-2 genome assemblies and 30,806 NGS datasets from GISAID and European Nucleotide Archive (ENA) focusing on non-synonymous mutations in the spike protein. Only around 2.5% of the samples contained the wild-type spike protein with no variation from the reference. Among the spike protein mutants, we confirmed a low mutation rate exhibiting less than 10 non-synonymous mutations in 99.6% of the analyzed sequences, but the mean and median number of spike protein mutations per sample increased over time. 5,472 distinct variants were found in total. The majority of the observed variants were recurrent, but only 21 and 14 recurrent variants were found in at least 1% of the mutant genome assemblies and NGS samples, respectively. Further, we found high-confidence subclonal variants in about 2.6% of the NGS data sets with mutant spike protein, which might indicate co-infection with various SARS-CoV-2 strains and/or intra-host evolution. Lastly, some variants might have an effect on antibody binding or T-cell recognition. These findings demonstrate the continuous importance of monitoring SARS-CoV-2 sequences for an early detection of variants that require adaptations in preventive and therapeutic strategies.

Clinical Symptoms and Types of Samples Are Critical Factors for the Molecular Diagnosis of Symptomatic COVID-19 Patients: A Systematic Literature Review

BACKGROUND

Currently, a novel coronavirus found in 2019 known as SARS-CoV-2 is the etiological agent of the COVID-19 pandemic. Various parameters including clinical manifestations and molecular evaluation can affect the accuracy of diagnosis. This review aims to discuss the various clinical symptoms and molecular evaluation results in COVID-19 patients, to point out the importance of onset symptoms, type, and timing of the sampling, besides the methods that are used for detection of SARS-CoV-2.

METHODS

A systematic literature review of current articles in the Web of Science, PubMed, Scopus, and EMBASE was conducted according to the PRISMA guideline.

RESULTS

Of the 12946 patients evaluated in this investigation, 7643 were confirmed to be COVID-19 positive by molecular techniques, particularly the RT-PCR/qPCR combined technique (qRT-PCR). In most of the studies, all of the enrolled cases had 100% positive results for molecular evaluation. Among the COVID-19 patients who were identified as such by positive PCR results, most of them showed fever or cough as the primary clinical signs. Less common symptoms observed in clinically confirmed cases were hemoptysis, bloody sputum, mental disorders, and nasal congestion. The most common clinical samples for PCR-confirmed COVID-19 patients were obtained from throat, oropharyngeal, and nasopharyngeal swabs, while tears and conjunctival secretions seem to be the least common clinical samples for COVID-19 diagnosis among studies. Also, different conserved SARS-CoV-2 gene sequences could be targeted for qRT-PCR detection. The suggested molecular assay being used by most laboratories for the detection of SARS-CoV-2 is qRT-PCR.

CONCLUSION

There is a worldwide concern on the COVID-19 pandemic and a lack of well-managed global control. Hence, it is crucial to update the molecular diagnostics protocols for handling the situation. This is possible by understanding the available advances in assays for the detection of the SARS-CoV-2 infection. Good sampling procedure and using samples with enough viral loads, also considering the onset symptoms, may reduce the qRT-PCR false-negative results in symptomatic COVID-19 patients. Selection of the most efficient primer-probe for target genes and samples containing enough viral loads to search for the existence of SARS-CoV-2 helps detecting the virus on time using qRT-PCR.

Mutational Landscape and Interaction of SARS-CoV-2 with Host Cellular Components

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its rapid evolution has led to a global health crisis. Increasing mutations across the SARS-CoV-2 genome have severely impacted the development of effective therapeutics and vaccines to combat the virus. However, the new SARS-CoV-2 variants and their evolutionary characteristics are not fully understood. Host cellular components such as the ACE2 receptor, RNA-binding proteins (RBPs), microRNAs, small nuclear RNA (snRNA), 18s rRNA, and the 7SL RNA component of the signal recognition particle (SRP) interact with various structural and non-structural proteins of the SARS-CoV-2. Several of these viral proteins are currently being examined for designing antiviral therapeutics. In this review, we discuss current advances in our understanding of various host cellular components targeted by the virus during SARS-CoV-2 infection. We also summarize the mutations across the SARS-CoV-2 genome that directs the evolution of new viral strains. Considering coronaviruses are rapidly evolving in humans, this enables them to escape therapeutic therapies and vaccine-induced immunity. In order to understand the virus's evolution, it is essential to study its mutational patterns and their impact on host cellular machinery. Finally, we present a comprehensive survey of currently available databases and tools to study viral-host interactions that stand as crucial resources for developing novel therapeutic strategies for combating SARS-CoV-2 infection.

Genetic Diversity and Evolution of the Biological Features of the Pandemic SARS-CoV-2

The new coronavirus infection (COVID-19) represents a challenge for global health. Since the outbreak began, the number of confirmed cases has exceeded 117 million, with more than 2.6 million deaths worldwide. With public health measures aimed at containing the spread of the disease, several countries have faced a crisis in the availability of intensive care units. Currently, a large-scale effort is underway to identify the nucleotide sequences of the SARS-CoV-2 coronavirus that is an etiological agent of COVID-19. Global sequencing of thousands of viral genomes has revealed many common genetic variants, which enables the monitoring of the evolution of SARS-CoV-2 and the tracking of its spread over time. Understanding the current evolution of SARS-CoV-2 is necessary not only for a retrospective analysis of the new coronavirus infection spread, but also for the development of approaches to the therapy and prophylaxis of COVID-19. In this review, we have focused on the general characteristics of SARS-CoV-2 and COVID-19. Also, we have analyzed available publications on the genetic diversity of the virus and the relationship between the diversity and the biological properties of SARS-CoV-2, such as virulence and contagiousness.

Evolution and spread of SARS-CoV-2 likely to be affected by climate

COVID-19 pandemic has been a subject of extensive study. However, it is still unclear why it was restricted to higher latitudes during the initial days and later cascaded in the tropics. Here, we analyzed 176 SARS-CoV-2 genomes across different climate zones and Köppen's climate that provided insights about within-species virus evolution and its relation to abiotic factors. Two genetically variant groups, named G1 and G2, were identified, well defined by four mutations. The G1 group (ancestor) is mainly restricted to warm and moist, temperate climate (Köppen's C climate) while its descendent G2 group surpasses the climatic restrictions of G1, initially cascading into neighboring cold climate (D) of higher latitudes and later into the hot climate of the tropics (A). It appears that the gradation of temperate climate (Cfa-Cfb) to cold climate (Dfa-Dfb) drives the evolution of G1 into the G2 variant group, which later adapted to tropical climate (A) as well. It seems this virus followed an inverse latitudinal gradient in the beginning due to its preference towards temperate (C) and cold climate (D). Our work elucidates virus evolutionary studies combined with climatic studies can provide crucial information about the pathogenesis and natural spreading pathways in such outbreaks, which is hard to achieve through individual studies. Mutational insights gained may help design an efficacious vaccine.

SARS-CoV-2 Gastrointestinal Infection Prolongs the Time to Recover From COVID-19

Objectives: We previously reported that SARS-CoV-2 infects the gastrointestinal (GI) epithelium. In this study, we aimed to explore the impact of SARS-CoV-2 GI infection on clinical outcomes of COVID-19.

Materials and Methods: For this retrospective cohort study, 104 patients with COVID-19 were classified into a SARS-CoV-2 GI infection group and a non-infection group. The primary endpoint was the time of negative conversion of SARS-CoV-2 RNA in respiratory tract samples. The secondary outcome was the time of hospitalization for COVID-19.

Results: Patients with SARS-CoV-2 GI infection had a longer duration of positive SARS-CoV-2 RNA in respiratory tract samples (median 12.0 days [95% CI: 10.0–13.2] vs. 9.0 days [95% CI: 7.5–10.5]; HR 0.575 [95% CI: 0.386–0.857]; P = 0.003) and hospitalization (median 28.0 days [95% CI: 23.2–32.8] vs. 15.0 days [95% CI: 13.6–16.4]; HR 0.149 [95% CI: 0.087–0.252]; P < 0.001) than patients without SARS-CoV-2 GI infection. Subgroup analyses for sex, age, epidemiological history, clinical classification and antiviral treatment showed consistent results.

Conclusion: Our study indicates that SARS-CoV-2 GI infection prolongs the duration of SARS-CoV-2 shedding and hospitalization in the patients with COVID-19. More attention should be paid to SARS-CoV-2 GI infection of COVID-19 and fecal SARS-CoV-2 RNA test should be completed in time.

Mutations and Epidemiology of SARS-CoV-2 Compared to Selected Corona Viruses during the First Six Months of the COVID-19 Pandemic: A Review

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus (CoV) disease 2019 (COVID-19). This study compared the genome, mutations, and infectivity/transmissibility of SARS-CoV-2 with selected betacoronaviruses (beta-CoVs). This study further examined the origin, risk factors, and outbreaks caused by beta-CoVs. We searched the following databases for relevant studies: PubMed, Google Scholar, and the World Health Organization COVID-19 database. A close relationship between SARS-CoV-2 and SARS bat-like CoV RaTG13 (98.9%) was found at the amino acid level, followed by pangolin CoVs. Non-synonymous mutations occur at high frequencies in the open reading frame (ORF) 1ab, spike (S) protein, and nucleocapsid. Mutations P323L and D614G in the RNA-dependent RNA polymerase (RdRp) and S protein, respectively, occur at a high frequency globally. Mutations at position 3037 in the nonstructural protein (Nsp) 3, 14408 (RdRp), and 23403 (S) confer transmissibility to SARS-CoV-2. SARS-CoV-2 has higher infectivity and transmissibility than SARS-CoV, which shares the same receptor. Although bats are confirmed reservoirs, intermediate hosts are currently unknown. Smoking, old age, diabetes, cardiovascular diseases, and hypertension have all been associated with COVID-19. Within six months of its outbreak, COVID-19 was reported in all countries worldwide, whereas SARS was reported in 28 countries and Middle East respiratory syndrome (MERS) in 5 countries. However, the fatality rate of MERS (65%) was higher than that of COVID-19 (4.9%) and SARS (6.6%). Identifying the SARS-CoV-2 intermediate hosts will help prevent future outbreaks. Attention should be given to the pangolin CoVs. Variations in the S gene may confer transmissibility and infectivity.

The Genetic Variant of SARS-CoV-2: would It Matter for Controlling the Devastating Pandemic?

The pandemic of COVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is far from being controlled despite the great effort that have been taken throughout the world. Herd immunity through vaccination is our major expectation to rein the virus. However, the emergence of widespread genetic variants could potentially undermine the vaccines. The evidence that some variants could evade immune responses elicited by vaccines and previous infection is growing. In this review, we summarized the current understanding on five notable genetic variants, i.e., D614G, Cluster 5, VOC 202012/01, 501Y.V2 and P.1, and discussed the potential impact of these variants on the virus transmission, pathogenesis and vaccine efficacy. We also highlight that mutations in the N-terminal domain of spike protein should be considered when evaluating the antibody neutralization abilities. Among these genetic variants, a concern of genetic variant 501Y.V2 to escape the protection by vaccines was raised. We therefore call for new vaccines targeting this variant to be developed.

A Study of 3CLpros as Promising Targets against SARS-CoV and SARS-CoV-2

The outbreak of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), results in serious chaos all over the world. In addition to the available vaccines, the development of treatments to cure COVID-19 should be done quickly. One of the fastest strategies is to use a drug-repurposing approach. To provide COVID-19 patients with useful information about medicines currently being used in clinical trials, twenty-four compounds, including antiviral agents, were selected and assayed. These compounds were applied to verify the inhibitory activity for the protein function of 3CLpros (main proteases) of SARS-CoV and SARS-CoV-2. Among them, viral reverse-transcriptase inhibitors abacavir and tenofovir revealed a good inhibitory effect on both 3CLpros. Intriguingly, sildenafil, a cGMP-specific phosphodiesterase type 5 inhibitor also showed significant inhibitory function against them. The in silico docking study suggests that the active-site residues located in the S1 and S2 sites play key roles in the interactions with the inhibitors. The result indicates that 3CLpros are promising targets to cope with SAR-CoV-2 and its variants. The information can be helpful to design treatments to cure patients with COVID-19.

Structural insights into SARS-CoV-2 infection and therapeutics development

The current COVID-19 pandemic is caused by the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2). By late October 2020, more than 43 million cases of infections, including over 1.15 million deaths, have been confirmed worldwide. This review focuses on our current understanding of SARS-CoV-2 from the perspective of the three-dimensional (3D) structures of SARS-CoV-2 viral proteins and their implications on therapeutics development against COVID-19.

SARS-CoV-2, the pandemic coronavirus: Molecular and structural insights

The outbreak of a novel coronavirus associated with acute respiratory disease, called COVID-19, marked the introduction of the third spillover of an animal coronavirus (CoV) to humans in the last two decades. The genome analysis with various bioinformatics tools revealed that the causative pathogen (SARS-CoV-2) belongs to the subgenus Sarbecovirus of the genus Betacoronavirus, with highly similar genome as bat coronavirus and receptor-binding domain (RBD) of spike glycoprotein as Malayan pangolin coronavirus. Based on its genetic proximity, SARS-CoV-2 is likely to have originated from bat-derived CoV and transmitted to humans via an unknown intermediate mammalian host, probably Malayan pangolin. Further, spike protein S1/S2 cleavage site of SARS-CoV-2 has acquired polybasic furin cleavage site which is absent in bat and pangolin suggesting natural selection either in an animal host before zoonotic transfer or in humans following zoonotic transfer. In the current review, we recapitulate a preliminary opinion about the disease, origin and life cycle of SARS-CoV-2, roles of virus proteins in pathogenesis, commonalities, and differences between different corona viruses. Moreover, the crystal structures of SARS-CoV-2 proteins with unique characteristics differentiating it from other CoVs are discussed. Our review also provides comprehensive information on the molecular aspects of SARS-CoV-2 including secondary structures in the genome and protein-protein interactions which can be useful to understand the aggressive spread of the SARS-CoV-2. The mutations and the haplotypes reported in the SARS-CoV-2 genome are summarized to understand the virus evolution.

Reactivation of SARS-CoV-2 infection following recovery from COVID-19

Introduction

Many individuals test positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA after recovering from the coronavirus disease (COVID-19), but the incidence of reactivation is unknown. We, therefore, estimated the incidence of reactivation among individuals who had recovered from COVID-19 and determined its predictors.

Methods

In this retrospective cohort study, patients with COVID-19 were followed up for at least 14 days after two consecutive negative SARS-CoV-2 polymerase chain reaction test results obtained ≥24 h apart, and the frequency of SARS-CoV-2 reactivation was assessed.

Results

Of the 109 patients, 29 (27%) experienced reactivation, and seven (24%) of these were symptomatic. The mean period for the real-time PCR tests for SARS-CoV-2 from negative to positive results was 17 days. Compared with patients without reactivation, those with reactivation were significantly younger and more likely to have a lymphocyte count of <1500/μL (odds ratio [OR]: 0.34, 95% confidence interval [CI]: 0.12–0.94) and two or fewer symptoms (OR: 0.20, 95% CI: 0.07–0.55) during the initial episode.

Conclusion

Risk-stratified surveillance should be conducted among patients who have recovered from COVID-19.

Genetic diversity and genomic epidemiology of SARS-CoV-2 in Morocco

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), declared as a pandemic due to its rapid spread worldwide. In this study, we investigate the genetic diversity and genomic epidemiology of SARS-CoV-2, using 22 virus genome sequences reported by three different laboratories in Morocco till June 7,2020, as well as 40,366 virus genomes from all around the world. The SARS-CoV-2 genomes from Moroccan patients revealed 62 mutations, of which 30 were mis-sense mutations. The mutations Spike_D614G and NSP12_P323L were present in all the 22 analyzed sequences, followed by N_G204R and N_R203K, which occurred in 9 among the 22 sequences. The mutations NSP10_R134S, NSP15_D335N, NSP16_I169L, NSP3_L431H, NSP3_P1292L and Spike_V6F occurred once in Moroccan sequences, with no record in other sequences worldwide. Phylogenetic analyses revealed that Moroccan SARS-CoV-2 genomes included 9 viruses belonging to Clade 20A, 9 to Clade 20B and 2 to Clade 20C, suggesting that the epidemic spread in Morocco did not display a predominant SARS-CoV-2 route. Therefore, multiple and unrelated introductions of SARS-CoV-2 into Morocco through different routes have occurred, giving rise to the diversity of virus genomes in the country. Further, in all probability, the SARS-CoV-2 circulated in a cryptic way in Morocco, starting from January 15, 2020 before the first case was officially discovered on March 2, 2020.

Air transportation, population density and temperature predict the spread of COVID-19 in Brazil

There is evidence that COVID-19, the disease caused by the betacoronavirus SARS-CoV-2, is sensitive to environmental conditions. However, such conditions often correlate with demographic and socioeconomic factors at larger spatial extents, which could confound this inference. We evaluated the effect of meteorological conditions (temperature, solar radiation, air humidity and precipitation) on 292 daily records of cumulative number of confirmed COVID-19 cases across the 27 Brazilian capital cities during the 1st month of the outbreak, while controlling for an indicator of the number of tests, the number of arriving flights, population density, proportion of elderly people and average income. Apart from increasing with time, the number of confirmed cases was mainly related to the number of arriving flights and population density, increasing with both factors. However, after accounting for these effects, the disease was shown to be temperature sensitive: there were more cases in colder cities and days, and cases accumulated faster at lower temperatures. Our best estimate indicates that a 1 °C increase in temperature has been associated with a decrease in confirmed cases of 8%. The quality of the data and unknowns limit the analysis, but the study reveals an urgent need to understand more about the environmental sensitivity of the disease to predict demands on health services in different regions and seasons.