Comparative evolution of influenza A virus H1 and H3 head and stalk domains across host species.

IMPORTANCE: For decades, researchers have studied the rapid evolution of influenza A viruses for vaccine design and as a useful model system for the study of host/parasite evolution. By performing an exhaustive analysis of hemagglutinin protein (HA) sequences from 49 lineages independently evolving in birds, swine, canines, equines, and humans over the last century, our work uncovers surprising features of HA evolution. In particular, the canine H3 stalk, unlike human H3 and H1 stalk domains, is not evolving slowly, suggesting that evolution in the stalk domain is not universally constrained across all host species. Therefore, a broader multi-host perspective on HA evolution may be useful during the evaluation and design of stalk-targeted vaccine candidates.

A comprehensive SARS-CoV-2 and COVID-19 review, Part 2: host extracellular to systemic effects of SARS-CoV-2 infection.

COVID-19, the disease caused by SARS-CoV-2, has caused significant morbidity and mortality worldwide. The betacoronavirus continues to evolve with global health implications as we race to learn more to curb its transmission, evolution, and sequelae. The focus of this review, the second of a three-part series, is on the biological effects of the SARS-CoV-2 virus on post-acute disease in the context of tissue and organ adaptations and damage. We highlight the current knowledge and describe how virological, animal, and clinical studies have shed light on the mechanisms driving the varied clinical diagnoses and observations of COVID-19 patients. Moreover, we describe how investigations into SARS-CoV-2 effects have informed the understanding of viral pathogenesis and provide innovative pathways for future research on the mechanisms of viral diseases.

Optimizing ancestral trait reconstruction of large HIV Subtype C datasets through multiple-trait subsampling.

Large datasets along with sampling bias represent a challenge for phylodynamic reconstructions, particularly when the study data are obtained from various heterogeneous sources and/or through convenience sampling. In this study, we evaluate the presence of unbalanced sampled distribution by collection date, location, and risk group of human immunodeficiency virus Type 1 Subtype C using a comprehensive subsampling strategy and assess their impact on the reconstruction of the viral spatial and risk group dynamics using phylogenetic comparative methods. Our study shows that a most suitable dataset for ancestral trait reconstruction can be obtained through subsampling by all available traits, particularly using multigene datasets. We also demonstrate that sampling bias is inflated when considerable information for a given trait is unavailable or of poor quality, as we observed for the trait risk group. In conclusion, we suggest that, even if traits are not well recorded, including them deliberately optimizes the representativeness of the original dataset rather than completely excluding them. Therefore, we advise the inclusion of as many traits as possible with the aid of subsampling approaches in order to optimize the dataset for phylodynamic analysis while reducing the computational burden. This will benefit research communities investigating the evolutionary and spatio-temporal patterns of infectious diseases.

SARS-CoV-2 Orphan Gene ORF10 Contributes to More Severe COVID-19 Disease.

The orphan gene of SARS-CoV-2, ORF10, is the least studied gene in the virus responsible for the COVID-19 pandemic. Recent experimentation indicated ORF10 expression moderates innate immunity in vitro. However, whether ORF10 affects COVID-19 in humans remained unknown. We determine that the ORF10 sequence is identical to the Wuhan-Hu-1 ancestral haplotype in 95% of genomes across five variants of concern (VOC). Four ORF10 variants are associated with less virulent clinical outcomes in the human host: three of these affect ORF10 protein structure, one affects ORF10 RNA structural dynamics. RNA-Seq data from 2070 samples from diverse human cells and tissues reveals ORF10 accumulation is conditionally discordant from that of other SARS-CoV-2 transcripts. Expression of ORF10 in A549 and HEK293 cells perturbs immune-related gene expression networks, alters expression of the majority of mitochondrially-encoded genes of oxidative respiration, and leads to large shifts in levels of 14 newly-identified transcripts. We conclude ORF10 contributes to more severe COVID-19 clinical outcomes in the human host.

Evolutionary and spatiotemporal analyses reveal multiple introductions and cryptic transmission of SARS-CoV-2 VOC/VOI in Malta.

IMPORTANCE: Our study provides insights into the evolution of the coronavirus disease 2019 (COVID-19) pandemic in Malta, a highly connected and understudied country. We combined epidemiological and phylodynamic analyses to analyze trends in the number of new cases, deaths, tests, positivity rates, and evolutionary and dispersal patterns from August 2020 to January 2022. Our reconstructions inferred 173 independent severe acute respiratory syndrome coronavirus 2 introductions into Malta from various global regions. Our study demonstrates that characterizing epidemiological trends coupled with phylodynamic modeling can inform the implementation of public health interventions to help control COVID-19 transmission in the community.

Sequential viral introductions and spread of BA.1 across Pakistan provinces during the Omicron wave.

BACKGROUND: COVID-19 waves caused by specific SARS-CoV-2 variants have occurred globally at different times. We focused on Omicron variants to understand the genomic diversity and phylogenetic relatedness of SARS-CoV-2 strains in various regions of Pakistan. METHODS: We studied 276,525 COVID-19 cases and 1,031 genomes sequenced from December 2021 to August 2022. Sequences were analyzed and visualized using phylogenetic trees. RESULTS: The highest case numbers and deaths were recorded in Sindh and Punjab, the most populous provinces in Pakistan. Omicron variants comprised 93% of all genomes, with BA.2 (32.6%) and BA.5 (38.4%) predominating. The first Omicron wave was associated with the sequential identification of BA.1 in Sindh, then Islamabad Capital Territory, Punjab, Khyber Pakhtunkhwa (KP), Azad Jammu Kashmir (AJK), Gilgit-Baltistan (GB) and Balochistan. Phylogenetic analysis revealed Sindh to be the source of BA.1 and BA.2 introductions into Punjab and Balochistan during early 2022. BA.4 was first introduced in AJK and BA.5 in Punjab. Most recent common ancestor (MRCA) analysis revealed relatedness between the earliest BA.1 genome from Sindh with Balochistan, AJK, Punjab and ICT, and that of first BA.1 from Punjab with strains from KPK and GB. CONCLUSIONS: Phylogenetic analysis provides insights into the introduction and transmission dynamics of the Omicron variant in Pakistan, identifying Sindh as a hotspot for viral dissemination. Such data linked with public health efforts can help limit surges of new infections.

Accelerating Bayesian inference of dependency between mixed-type biological traits.

Inferring dependencies between mixed-type biological traits while accounting for evolutionary relationships between specimens is of great scientific interest yet remains infeasible when trait and specimen counts grow large. The state-of-the-art approach uses a phylogenetic multivariate probit model to accommodate binary and continuous traits via a latent variable framework, and utilizes an efficient bouncy particle sampler (BPS) to tackle the computational bottleneck-integrating many latent variables from a high-dimensional truncated normal distribution. This approach breaks down as the number of specimens grows and fails to reliably characterize conditional dependencies between traits. Here, we propose an inference pipeline for phylogenetic probit models that greatly outperforms BPS. The novelty lies in 1) a combination of the recent Zigzag Hamiltonian Monte Carlo (Zigzag-HMC) with linear-time gradient evaluations and 2) a joint sampling scheme for highly correlated latent variables and correlation matrix elements. In an application exploring HIV-1 evolution from 535 viruses, the inference requires joint sampling from an 11,235-dimensional truncated normal and a 24-dimensional covariance matrix. Our method yields a 5-fold speedup compared to BPS and makes it possible to learn partial correlations between candidate viral mutations and virulence. Computational speedup now enables us to tackle even larger problems: we study the evolution of influenza H1N1 glycosylations on around 900 viruses. For broader applicability, we extend the phylogenetic probit model to incorporate categorical traits, and demonstrate its use to study Aquilegia flower and pollinator co-evolution.

Core mitochondrial genes are down-regulated during SARS-CoV-2 infection of rodent and human hosts.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral proteins bind to host mitochondrial proteins, likely inhibiting oxidative phosphorylation (OXPHOS) and stimulating glycolysis. We analyzed mitochondrial gene expression in nasopharyngeal and autopsy tissues from patients with coronavirus disease 2019 (COVID-19). In nasopharyngeal samples with declining viral titers, the virus blocked the transcription of a subset of nuclear DNA (nDNA)-encoded mitochondrial OXPHOS genes, induced the expression of microRNA 2392, activated HIF-1α to induce glycolysis, and activated host immune defenses including the integrated stress response. In autopsy tissues from patients with COVID-19, SARS-CoV-2 was no longer present, and mitochondrial gene transcription had recovered in the lungs. However, nDNA mitochondrial gene expression remained suppressed in autopsy tissue from the heart and, to a lesser extent, kidney, and liver, whereas mitochondrial DNA transcription was induced and host-immune defense pathways were activated. During early SARS-CoV-2 infection of hamsters with peak lung viral load, mitochondrial gene expression in the lung was minimally perturbed but was down-regulated in the cerebellum and up-regulated in the striatum even though no SARS-CoV-2 was detected in the brain. During the mid-phase SARS-CoV-2 infection of mice, mitochondrial gene expression was starting to recover in mouse lungs. These data suggest that when the viral titer first peaks, there is a systemic host response followed by viral suppression of mitochondrial gene transcription and induction of glycolysis leading to the deployment of antiviral immune defenses. Even when the virus was cleared and lung mitochondrial function had recovered, mitochondrial function in the heart, kidney, liver, and lymph nodes remained impaired, potentially leading to severe COVID-19 pathology.

Global dissemination of influenza A virus is driven by wild bird migration through arctic and subarctic zones.

Influenza A viruses (IAV) circulate endemically among many wild aquatic bird populations that seasonally migrate between wintering grounds in southern latitudes to breeding ranges along the perimeter of the circumpolar arctic. Arctic and subarctic zones are hypothesized to serve as ecologic drivers of the intercontinental movement and reassortment of IAVs due to high densities of disparate populations of long distance migratory and native bird species present during breeding seasons. Iceland is a staging ground that connects the East Atlantic and North Atlantic American flyways, providing a unique study system for characterizing viral flow between eastern and western hemispheres. Using Bayesian phylodynamic analyses, we sought to evaluate the viral connectivity of Iceland to proximal regions and how inter-species transmission and reassortment dynamics in this region influence the geographic spread of low and highly pathogenic IAVs. Findings demonstrate that IAV movement in the arctic and subarctic reflects wild bird migration around the perimeter of the circumpolar north, favouring short-distance flights between proximal regions rather than long distance flights over the polar interior. Iceland connects virus movement between mainland Europe and North America, consistent with the westward migration of wild birds from mainland Europe to Northeastern Canada and Greenland. Though virus diffusion rates were similar among avian taxonomic groups in Iceland, gulls play an outsized role as sinks of IAVs from other avian hosts prior to onward migration. These data identify patterns of virus movement in northern latitudes and inform future surveillance strategies related to seasonal and emergent IAVs with potential public health concern.

COVID-19 Exposure Assessment Tool (CEAT): Exposure quantification based on ventilation, infection prevalence, group characteristics, and behavior.

The coronavirus disease 2019 (COVID-19) Exposure Assessment Tool (CEAT) allows users to compare respiratory relative risk to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) for various scenarios, providing understanding of how combinations of protective measures affect risk. CEAT incorporates mechanistic, stochastic, and epidemiological factors including the (i) emission rate of virus, (ii) viral aerosol degradation and removal, (iii) duration of activity/exposure, (iv) inhalation rates, (v) ventilation rates (indoors/outdoors), (vi) volume of indoor space, (vii) filtration, (viii) mask use and effectiveness, (ix) distance between people (taking into account both near-field and far-field effects of proximity), (x) group size, (xi) current infection rates by variant, (xii) prevalence of infection and immunity in the community, (xiii) vaccination rates, and (xiv) implementation of COVID-19 testing procedures. CEAT applied to published studies of COVID-19 transmission events demonstrates the model's accuracy. We also show how health and safety professionals at NASA Ames Research Center used CEAT to manage potential risks posed by SARS-CoV-2 exposures.

Origins and Evolution of Seasonal Human Coronaviruses.

Four seasonal human coronaviruses (sHCoVs) are endemic globally (229E, NL63, OC43, and HKU1), accounting for 5-30% of human respiratory infections. However, the epidemiology and evolution of these CoVs remain understudied due to their association with mild symptomatology. Using a multigene and complete genome analysis approach, we find the evolutionary histories of sHCoVs to be highly complex, owing to frequent recombination of CoVs including within and between sHCoVs, and uncertain, due to the under sampling of non-human viruses. The recombination rate was highest for 229E and OC43 whereas substitutions per recombination event were highest in NL63 and HKU1. Depending on the gene studied, OC43 may have ungulate, canine, or rabbit CoV ancestors. 229E may have origins in a bat, camel, or an unsampled intermediate host. HKU1 had the earliest common ancestor (1809-1899) but fell into two distinct clades (genotypes A and B), possibly representing two independent transmission events from murine-origin CoVs that appear to be a single introduction due to large gaps in the sampling of CoVs in animals. In fact, genotype B was genetically more diverse than all the other sHCoVs. Finally, we found shared amino acid substitutions in multiple proteins along the non-human to sHCoV host-jump branches. The complex evolution of CoVs and their frequent host switches could benefit from continued surveillance of CoVs across non-human hosts.

A comprehensive SARS-CoV-2 and COVID-19 review, Part 1: Intracellular overdrive for SARS-CoV-2 infection.

COVID-19, the disease caused by SARS-CoV-2, has claimed approximately 5 million lives and 257 million cases reported globally. This virus and disease have significantly affected people worldwide, whether directly and/or indirectly, with a virulent pathogen that continues to evolve as we race to learn how to prevent, control, or cure COVID-19. The focus of this review is on the SARS-CoV-2 virus' mechanism of infection and its proclivity at adapting and restructuring the intracellular environment to support viral replication. We highlight current knowledge and how scientific communities with expertize in viral, cellular, and clinical biology have contributed to increase our understanding of SARS-CoV-2, and how these findings may help explain the widely varied clinical observations of COVID-19 patients.

Ecological divergence of wild birds drives avian influenza spillover and global spread.

The diversity of influenza A viruses (IAV) is primarily hosted by two highly divergent avian orders: Anseriformes (ducks, swans and geese) and Charadriiformes (gulls, terns and shorebirds). Studies of IAV have historically focused on Anseriformes, specifically dabbling ducks, overlooking the diversity of hosts in nature, including gull and goose species that have successfully adapted to human habitats. This study sought to address this imbalance by characterizing spillover dynamics and global transmission patterns of IAV over 10 years at greater taxonomic resolution than previously considered. Furthermore, the circulation of viral subtypes in birds that are either host-adapted (low pathogenic H13, H16) or host-generalist (highly pathogenic avian influenza-HPAI H5) provided a unique opportunity to test and extend models of viral evolution. Using Bayesian phylodynamic modelling we uncovered a complex transmission network that relied on ecologically divergent bird hosts. The generalist subtype, HPAI H5 was driven largely by wild geese and swans that acted as a source for wild ducks, gulls, land birds, and domestic geese. Gulls were responsible for moving HPAI H5 more rapidly than any other host, a finding that may reflect their long-distance, pelagic movements and their immuno-naïve status against this subtype. Wild ducks, long viewed as primary hosts for spillover, occupied an optimal space for viral transmission, contributing to geographic expansion and rapid dispersal of HPAI H5. Evidence of inter-hemispheric dispersal via both the Pacific and Atlantic Rims was detected, supporting surveillance at high latitudes along continental margins to achieve early detection. Both neutral (geographic expansion) and non-neutral (antigenic selection) evolutionary processes were found to shape subtype evolution which manifested as unique geographic hotspots for each subtype at the global scale. This study reveals how a diversity of avian hosts contribute to viral spread and spillover with the potential to improve surveillance in an era of rapid global change.

Evolutionary history and introduction of SARS-CoV-2 Alpha VOC/B.1.1.7 in Pakistan through international travelers.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants continue to emerge, and their identification is important for the public health response to coronavirus disease 2019 (COVID-19). Genomic sequencing provides robust information but may not always be accessible, and therefore, mutation-based polymerase chain reaction (PCR) approaches can be used for rapid identification of known variants. International travelers arriving in Karachi between December 2020 and February 2021 were tested for SARS-CoV-2 by PCR. A subset of positive samples was tested for S-gene target failure (SGTF) on TaqPathTM COVID-19 (Thermo Fisher Scientific) and for mutations using the GSD NovaType SARS-CoV-2 (Eurofins Technologies) assays. Sequencing was conducted on the MinION platform (Oxford Nanopore Technologies). Bayesian phylogeographic inference was performed integrating the patients' travel history information. Of the thirty-five COVID-19 cases screened, thirteen had isolates with SGTF. The travelers transmitted infection to sixty-eight contact cases. The B.1.1.7 lineage was confirmed through sequencing and PCR. The phylogenetic analysis of sequence data available for six cases included four B.1.1.7 strains and one B.1.36 and B.1.1.212 lineage isolate. Phylogeographic modeling estimated at least three independent B.1.1.7 introductions into Karachi, Pakistan, originating from the UK. B.1.1.212 and B.1.36 were inferred to be introduced either from the UK or the travelers' layover location. We report the introduction of SARS-CoV-2 B.1.1.7 and other lineages in Pakistan by international travelers arriving via different flight routes. This highlights SARS-CoV-2 transmission through travel, importance of testing, and quarantine post-travel to prevent transmission of new strains, as well as recording detailed patients' metadata. Such results help inform policies on restricting travel from destinations where new highly transmissible variants have emerged.

The emergence and transmission dynamics of HIV-1 CRF07_BC in Mainland China.

A total of 1155 partial pol gene sequences of human immunodeficiency virus (HIV)-1 CRF07_BC were sampled between 1997 and 2015, spanning 13 provinces in Mainland China and risk groups [heterosexual, injecting drug users (IDU), and men who have sex with men (MSM)] to investigate the evolution, adaptation, spatiotemporal and risk group dynamics, migration patterns, and protein structure of HIV-1 CRF07_BC. Due to the unequal distribution of sequences across time, location, and risk group in the complete dataset ('full1155'), subsampling methods were used. Maximum-likelihood and Bayesian phylogenetic analysis as well as discrete trait analysis of geographical location and risk group were carried out. To study mutations of a cluster of HIV-1 CRF07_BC (CRF07-1), we performed a comparative analysis of this cluster to the other CRF07_BC sequences ('backbone_295') and mapped the mutations observed in the respective protein structure. Our findings showed that HIV-1 CRF07_BC most likely originated among IDU in Yunnan Province between October 1992 to July 1993 [95 per cent hightest posterior density (HPD): May 1989-August 1995] and that IDU in Yunnan Province and MSM in Guangdong Province likely served as the viral sources during the early and more recent spread in Mainland China. We also revealed that HIV-1 CRF07-1 has been spreading for roughly 20 years and continues to cause local transmission in Mainland China and worldwide. Overall, our study sheds light on the dynamics of HIV-1 CRF07_BC distribution patterns in Mainland China. Our research may also be useful in formulating public health policies aimed at controlling acquired immune deficiency syndrome in Mainland China and globally.

Readdressing the genetic diversity and taxonomy of the Mesoniviridae family, as well as its relationships with other nidoviruses and putative mesonivirus-like viral sequences.

Research on the recently established Mesoniviridae family (Order Nidovirales), RNA genome insect-specific viruses, has been steadily growing in the last decade. However, after the last detailed phylogenetic characterization of mesoniviruses in 2014, numerous new sequences, even in organisms other than mosquitos, have been identified and characterized. In this study, we analyzed nucleotide and protein sequences of mesoniviruses with a wide range of molecular tools including genetic distance, Shannon entropy, selective pressure analysis, polymorphism identification, principal coordinate analysis, likelihood mapping and phylodynamic reconstruction. We also sought to revaluate new mesoniviruses sequence positions within the family, proposing a taxonomic revision. The different sub-lineages of mosquito mesoniviruses sequences presented low sequence diversity and entropy, with incongruences to the existing taxonomy being found after an extensive phylogenetic characterization. High sequence discrepancy and differences in genome organization were found between mosquito mesoniviruses and other mesoniviruses, so their future classification, as other meso-like viruses that are found in other organisms, should be approached with caution. No evidence of frequent recombination was found, and mesonivirus genomes seem to evolve under strong purifying selection. Insufficient data by root-to-tip analysis did not yet allow for an adequate phylogeographic reconstruction.

Insect-specific viruses in the Parvoviridae family: Genetic lineage characterization and spatiotemporal dynamics of the recently established Brevihamaparvovirus genus.

The analysis of the viruses allocated to the recently established Brevihamaparvovirus genus (Parvoviridae family), which includes all previously known brevidensoviruses, has not yet been carried out on an extensive basis. As a result, no detailed genetic lineage characterization has ever been performed for this group of insect-specific viruses. Using a wide range of molecular tools, we have explored this taxon by calculating Shannon entropy values, intra- and inter-taxon genetic distances, analysed sequence polymorphisms, and evaluated selective pressures acting on the viral genome. While the calculated Brevihamaparvovirus mutation rates were within the range of those of other parvoviruses, their genomes look to be under strong purifying selection, and are also characterized by low diversity and entropy. Furthermore, even though recombination events are quite common among parvoviruses, no evidence of recombination (either intra or intergenic) was found in the Brevihamaparvoviruses sequences analyzed. An extended taxonomic analysis and reevaluation of existing Brevihamaparvoviruses sequences, many still unclassified, was performed using cut-off values defining NS1 identity between viral sequences from the Parvovirus family. Two existing genetic lineages, Dipteran Brevihamaparvovirus 1 and Dipteran Brevihamaparvovirus 2, were rearranged and the creation of a new one, Dipteran Brevihamaparvovirus 3, was suggested. Finally, despite the uncertainties associated with both the time estimates of the most recent common ancestors, which could span from twenty thousand years before the current era to way earlier (in the last century), and the dispersal routes proposed for Brevihamaparvoviruses sequences by phylodynamic reconstruction, the analyses here presented could help define how future studies should be conducted as more isolates continue to be identified in the future, and contribute to eliminating possible analytical biases.

Covid-19 Exposure Assessment Tool (CEAT): Easy-to-use tool to quantify exposure based on airflow, group behavior, and infection prevalence in the community.

The COVID-19 Exposure Assessment Tool (CEAT) allows users to compare respiratory relative risk to SARS-CoV-2 for various scenarios, providing understanding of how combinations of protective measures affect exposure, dose, and risk. CEAT incorporates mechanistic, stochastic and epidemiological factors including the: 1) emission rate of virus, 2) viral aerosol degradation and removal, 3) duration of activity/exposure, 4) inhalation rates, 5) ventilation rates (indoors/outdoors), 6) volume of indoor space, 7) filtration, 8) mask use and effectiveness, 9) distance between people, 10) group size, 11) current infection rates by variant, 12) prevalence of infection and immunity in the community, 13) vaccination rates of the community, and 14) implementation of COVID-19 testing procedures. Demonstration of CEAT, from published studies of COVID-19 transmission events, shows the model accurately predicts transmission. We also show how health and safety professionals at NASA Ames Research Center used CEAT to manage potential risks posed by SARS-CoV-2 exposures. Given its accuracy and flexibility, the wide use of CEAT will have a long lasting beneficial impact in managing both the current COVID-19 pandemic as well as a variety of other scenarios.

Epidemiology and genetic diversity of SARS-CoV-2 lineages circulating in Africa.

There is a dearth of information on COVID-19 disease dynamics in Africa. To fill this gap, we investigated the epidemiology and genetic diversity of SARS-CoV-2 lineages circulating in the continent. We retrieved 5229 complete genomes collected in 33 African countries from the GISAID database. We investigated the circulating diversity, reconstructed the viral evolutionary divergence and history, and studied the case and death trends in the continent. Almost a fifth (144/782, 18.4%) of Pango lineages found worldwide circulated in Africa, with five different lineages dominating over time. Phylogenetic analysis revealed that African viruses cluster more closely with those from Europe. We also identified two motifs that could function as integrin-binding sites and N-glycosylation domains. These results shed light on the epidemiological and evolutionary dynamics of the circulating viral diversity in Africa. They also emphasize the need to expand surveillance efforts in Africa to help inform and implement better public health measures.

SARS-CoV-2 antibody prevalence in a pediatric cohort of unvaccinated children in Mérida, Yucatán, México.

The prevalence of SARS-CoV-2 exposure in children during the global COVID-19 pandemic has been underestimated due to lack of testing and the relatively mild symptoms in adolescents. Understanding the exposure rates in the pediatric population is essential as children are the last to receive vaccines and can act as a source for SARS-CoV-2 mutants that may threaten vaccine escape. This cross-sectional study aims to quantify the prevalence of anti-SARS-CoV-2 serum antibodies in children in a major city in México in the Spring of 2021 and determine if there are any demographic or socioeconomic correlating factors. We obtained socioeconomic information and blood samples from 1,005 children from 50 neighborhood clusters in Mérida, Yucatán, México. We then tested the sera of these participants for anti-SARS-CoV-2 IgG and IgM antibodies using lateral flow immunochromatography. We found that 25.5% of children in our cohort were positive for anti-SARS-CoV-2 antibodies and there was no correlation between age and antibody prevalence. Children that lived with large families were statistically more likely to have antibodies against SARS-CoV-2. Spatial analyses identified two hotspots of high SARS-CoV-2 seroprevalence in the west of the city. These results indicate that a large urban population of unvaccinated children has been exposed to SARS-CoV-2 and that a major correlating factor was the number of people within the child's household with a minor correlation with particular geographical hotspots. There is also a larger population of children that may be susceptible to future infection upon easing of social distancing measures. These findings suggest that in future pandemic scenarios, limited public health resources can be best utilized on children living in large households in urban areas.