Fine-scale spatial and social patterns of SARS-CoV-2 transmission from identical pathogen sequences.

Pathogen genomics can provide insights into disease transmission patterns, but new methods are needed to handle modern large-scale pathogen genome datasets. Genetically proximal viruses indicate epidemiological linkage and are informative about transmission events. Here, we leverage pairs of identical sequences using 114,298 SARS-CoV-2 genomes collected via sentinel surveillance from March 2021 to December 2022 in Washington State, USA, with linked age and residence information to characterize fine-scale transmission. The location of pairs of identical sequences is highly consistent with expectations from mobility and social contact data. Outliers in the relationship between genetic and mobility data can be explained by SARS-CoV-2 transmission between postal codes with male prisons, consistent with transmission between prison facilities. Transmission patterns between age groups vary across spatial scales. Finally, we use the timing of sequence collection to understand the age groups driving transmission. This work improves our ability to characterize transmission from large pathogen genome datasets.

Impacts of human mobility on the citywide transmission dynamics of 18 respiratory viruses in pre- and post-COVID-19 pandemic years.

Many studies have used mobile device location data to model SARS-CoV-2 dynamics, yet relationships between mobility behavior and endemic respiratory pathogens are less understood. We studied the effects of population mobility on the transmission of 17 endemic viruses and SARS-CoV-2 in Seattle over a 4-year period, 2018-2022. Before 2020, visits to schools and daycares, within-city mixing, and visitor inflow preceded or coincided with seasonal outbreaks of endemic viruses. Pathogen circulation dropped substantially after the initiation of COVID-19 stay-at-home orders in March 2020. During this period, mobility was a positive, leading indicator of transmission of all endemic viruses and lagging and negatively correlated with SARS-CoV-2 activity. Mobility was briefly predictive of SARS-CoV-2 transmission when restrictions relaxed but associations weakened in subsequent waves. The rebound of endemic viruses was heterogeneously timed but exhibited stronger, longer-lasting relationships with mobility than SARS-CoV-2. Overall, mobility is most predictive of respiratory virus transmission during periods of dramatic behavioral change and at the beginning of epidemic waves.

Local-scale phylodynamics reveal differential community impact of SARS-CoV-2 in a metropolitan US county.

SARS-CoV-2 transmission is largely driven by heterogeneous dynamics at a local scale, leaving local health departments to design interventions with limited information. We analyzed SARS-CoV-2 genomes sampled between February 2020 and March 2022 jointly with epidemiological and cell phone mobility data to investigate fine scale spatiotemporal SARS-CoV-2 transmission dynamics in King County, Washington, a diverse, metropolitan US county. We applied an approximate structured coalescent approach to model transmission within and between North King County and South King County alongside the rate of outside introductions into the county. Our phylodynamic analyses reveal that following stay-at-home orders, the epidemic trajectories of North and South King County began to diverge. We find that South King County consistently had more reported and estimated cases, COVID-19 hospitalizations, and longer persistence of local viral transmission when compared to North King County, where viral importations from outside drove a larger proportion of new cases. Using mobility and demographic data, we also find that South King County experienced a more modest and less sustained reduction in mobility following stay-at-home orders than North King County, while also bearing more socioeconomic inequities that might contribute to a disproportionate burden of SARS-CoV-2 transmission. Overall, our findings suggest a role for local-scale phylodynamics in understanding the heterogeneous transmission landscape.

Antigenic drift and subtype interference shape A(H3N2) epidemic dynamics in the United States.

Influenza viruses continually evolve new antigenic variants, through mutations in epitopes of their major surface proteins, hemagglutinin (HA) and neuraminidase (NA). Antigenic drift potentiates the reinfection of previously infected individuals, but the contribution of this process to variability in annual epidemics is not well understood. Here we link influenza A(H3N2) virus evolution to regional epidemic dynamics in the United States during 1997-2019. We integrate phenotypic measures of HA antigenic drift and sequence-based measures of HA and NA fitness to infer antigenic and genetic distances between viruses circulating in successive seasons. We estimate the magnitude, severity, timing, transmission rate, age-specific patterns, and subtype dominance of each regional outbreak and find that genetic distance based on broad sets of epitope sites is the strongest evolutionary predictor of A(H3N2) virus epidemiology. Increased HA and NA epitope distance between seasons correlates with larger, more intense epidemics, higher transmission, greater A(H3N2) subtype dominance, and a greater proportion of cases in adults relative to children, consistent with increased population susceptibility. Based on random forest models, A(H1N1) incidence impacts A(H3N2) epidemics to a greater extent than viral evolution, suggesting that subtype interference is a major driver of influenza A virus infection dynamics, presumably via heterosubtypic cross-immunity.

Trends in Risk Factors and Symptoms Associated With SARS-CoV-2 and Rhinovirus Test Positivity in King County, Washington, June 2020 to July 2022.

Importance: Few US studies have reexamined risk factors for SARS-CoV-2 positivity in the context of widespread vaccination and new variants or considered risk factors for cocirculating endemic viruses, such as rhinovirus. Objectives: To evaluate how risk factors and symptoms associated with SARS-CoV-2 test positivity changed over the course of the pandemic and to compare these with the risk factors associated with rhinovirus test positivity. Design, Setting, and Participants: This case-control study used a test-negative design with multivariable logistic regression to assess associations between SARS-CoV-2 and rhinovirus test positivity and self-reported demographic and symptom variables over a 25-month period. The study was conducted among symptomatic individuals of all ages enrolled in a cross-sectional community surveillance study in King County, Washington, from June 2020 to July 2022. Exposures: Self-reported data for 15 demographic and health behavior variables and 16 symptoms. Main Outcomes and Measures: Reverse transcription-polymerase chain reaction-confirmed SARS-CoV-2 or rhinovirus infection. Results: Analyses included data from 23 498 individuals. The median (IQR) age of participants was 34.33 (22.42-45.08) years, 13 878 (59.06%) were female, 4018 (17.10%) identified as Asian, 654 (2.78%) identified as Black, and 2193 (9.33%) identified as Hispanic. Close contact with an individual with SARS-CoV-2 (adjusted odds ratio [aOR], 3.89; 95% CI, 3.34-4.57) and loss of smell or taste (aOR, 3.49; 95% CI, 2.77-4.41) were the variables most associated with SARS-CoV-2 test positivity, but both attenuated during the Omicron period. Contact with a vaccinated individual with SARS-CoV-2 (aOR, 2.03; 95% CI, 1.56-2.79) was associated with lower odds of testing positive than contact with an unvaccinated individual with SARS-CoV-2 (aOR, 4.04; 95% CI, 2.39-7.23). Sore throat was associated with Omicron infection (aOR, 2.27; 95% CI, 1.68-3.20) but not Delta infection. Vaccine effectiveness for participants fully vaccinated with a booster dose was 93% (95% CI, 73%-100%) for Delta, but not significant for Omicron. Variables associated with rhinovirus test positivity included being younger than 12 years (aOR, 3.92; 95% CI, 3.42-4.51) and experiencing a runny or stuffy nose (aOR, 4.58; 95% CI, 4.07-5.21). Black race, residing in south King County, and households with 5 or more people were significantly associated with both SARS-CoV-2 and rhinovirus test positivity. Conclusions and Relevance: In this case-control study of 23 498 symptomatic individuals, estimated risk factors and symptoms associated with SARS-CoV-2 infection changed over time. There was a shift in reported symptoms between the Delta and Omicron variants as well as reductions in the protection provided by vaccines. Racial and sociodemographic disparities persisted in the third year of SARS-CoV-2 circulation and were also present in rhinovirus infection. Trends in testing behavior and availability may influence these results.

Local-Scale phylodynamics reveal differential community impact of SARS-CoV-2 in metropolitan US county.

SARS-CoV-2 transmission is largely driven by heterogeneous dynamics at a local scale, leaving local health departments to design interventions with limited information. We analyzed SARS-CoV-2 genomes sampled between February 2020 and March 2022 jointly with epidemiological and cell phone mobility data to investigate fine scale spatiotemporal SARS-CoV-2 transmission dynamics in King County, Washington, a diverse, metropolitan US county. We applied an approximate structured coalescent approach to model transmission within and between North King County and South King County alongside the rate of outside introductions into the county. Our phylodynamic analyses reveal that following stay-at-home orders, the epidemic trajectories of North and South King County began to diverge. We find that South King County consistently had more reported and estimated cases, COVID-19 hospitalizations, and longer persistence of local viral transmission when compared to North King County, where viral importations from outside drove a larger proportion of new cases. Using mobility and demographic data, we also find that South King County experienced a more modest and less sustained reduction in mobility following stay-at-home orders than North King County, while also bearing more socioeconomic inequities that might contribute to a disproportionate burden of SARS-CoV-2 transmission. Overall, our findings suggest a role for local-scale phylodynamics in understanding the heterogeneous transmission landscape.

Direct and Indirect Effects of the Coronavirus Disease 2019 Pandemic on Private Healthcare Utilization in South Africa, March 2020-September 2021.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic caused severe disruptions to healthcare in many areas of the world, but data remain scarce for sub-Saharan Africa. METHODS: We evaluated trends in hospital admissions and outpatient emergency department (ED) and general practitioner (GP) visits to South Africa's largest private healthcare system during 2016-2021. We fit time series models to historical data and, for March 2020-September 2021, quantified changes in encounters relative to baseline. RESULTS: The nationwide lockdown on 27 March 2020 led to sharp reductions in care-seeking behavior that persisted for 18 months after initial declines. For example, total admissions dropped 59.6% (95% confidence interval [CI], 52.4-66.8) during home confinement and were 33.2% (95% CI, 29-37.4) below baseline in September 2021. We identified 3 waves of all-cause respiratory encounters consistent with COVID-19 activity. Intestinal infections and non-COVID-19 respiratory illnesses experienced the most pronounced declines, with some diagnoses reduced 80%, even as nonpharmaceutical interventions (NPIs) relaxed. Non-respiratory hospitalizations, including injuries and acute illnesses, were 20%-60% below baseline throughout the pandemic and exhibited strong temporal associations with NPIs and mobility. ED attendances exhibited trends similar to those for hospitalizations, while GP visits were less impacted and have returned to pre-pandemic levels. CONCLUSIONS: We found substantially reduced use of health services during the pandemic for a range of conditions unrelated to COVID-19. Persistent declines in hospitalizations and ED visits indicate that high-risk patients are still delaying seeking care, which could lead to morbidity or mortality increases in the future.

Social groups constrain the spatiotemporal dynamics of wild sifaka gut microbiomes.

Primates acquire gut microbiota from conspecifics through direct social contact and shared environmental exposures. Host behaviour is a prominent force in structuring gut microbial communities, yet the extent to which group or individual-level forces shape the long-term dynamics of gut microbiota is poorly understood. We investigated the effects of three aspects of host sociality (social groupings, dyadic interactions, and individual dispersal between groups) on gut microbiome composition and plasticity in 58 wild Verreaux's sifaka (Propithecus verreauxi) from six social groups. Over the course of three dry seasons in a 5-year period, the six social groups maintained distinct gut microbial signatures, with the taxonomic composition of individual communities changing in tandem among coresiding group members. Samples collected from group members during each season were more similar than samples collected from single individuals across different years. In addition, new immigrants and individuals with less stable social ties exhibited elevated rates of microbiome turnover across seasons. Our results suggest that permanent social groupings shape the changing composition of commensal and mutualistic gut microbial communities and thus may be important drivers of health and resilience in wild primate populations.

Tracing the Source of Influenza A Virus Zoonoses in Interconnected Circuits of Swine Exhibitions.

BACKGROUND: Since 2011, influenza A viruses circulating in US swine exhibited at county fairs are associated with >460 zoonotic infections, presenting an ongoing pandemic risk. Swine "jackpot shows" that occur before county fairs each summer intermix large numbers of exhibition swine from diverse geographic locations. We investigated the role of jackpot shows in influenza zoonoses. METHODS: We collected snout wipe or nasal swab samples from 17 009 pigs attending 350 national, state, and local swine exhibitions across 8 states during 2016-2018. RESULTS: Influenza was detected in 13.9% of swine sampled at jackpot shows, and 76.3% of jackpot shows had at least 1 pig test positive. Jackpot shows had 4.3-fold higher odds of detecting at least 1 influenza-positive pig compared to county fairs. When influenza was detected at a county fair, almost half of pigs tested positive, clarifying why zoonotic infections occur primarily at county fairs. CONCLUSIONS: The earlier timing of jackpot shows and long-distance travel for repeated showing of individual pigs provide a pathway for the introduction of influenza into county fairs. Mitigation strategies aimed at curtailing influenza at jackpot shows are likely to have downstream effects on disease transmission at county fairs and zoonoses.

A Heterogeneous Swine Show Circuit Drives Zoonotic Transmission of Influenza A Viruses in the United States.

Influenza pandemics are associated with severe morbidity, mortality, and social and economic disruption. Every summer in the United States, youths attending agricultural fairs are exposed to genetically diverse influenza A viruses (IAVs) circulating in exhibition swine, resulting in over 450 lab-confirmed zoonotic infections since 2010. Exhibition swine represent a small, defined population (∼1.5% of the U.S. herd), presenting a realistic opportunity to mitigate a pandemic threat by reducing IAV transmission in the animals themselves. Through intensive surveillance and genetic sequencing of IAVs in exhibition swine in six U.S. states in 2018 (n = 212), we characterized how a heterogeneous circuit of swine shows, comprising fairs with different sizes and geographic coverage, facilitates IAV transmission among exhibition swine and into humans. Specifically, we identified the role of an early-season national show in the propagation and spatial dissemination of a specific virus (H1δ-2) that becomes dominant among exhibition swine and is associated with the majority of zoonotic infections in 2018. These findings suggest that a highly targeted mitigation strategy, such as postponing swine shows for 1 to 2 weeks following the early-season national show, could potentially reduce IAV transmission in exhibition swine and spillover into humans, and this merits further study.IMPORTANCE The varying influenza A virus (IAV) exposure and infection status of individual swine facilitates introduction, transmission, and dissemination of diverse IAVs. Since agricultural fairs bring people into intimate contact with swine, they provide a unique interface for zoonotic transmission of IAV. Understanding the dynamics of IAV transmission through exhibition swine is critical to mitigating the high incidence of variant IAV cases reported in association with agricultural fairs. We used genomic sequences from our exhibition swine surveillance to characterize the hemagglutinin and full genotypic diversity of IAV at early-season shows and the subsequent dissemination through later-season agricultural fairs. We were able to identify a critical time point with important implications for downstream IAV and zoonotic transmission. With improved understanding of evolutionary origins of zoonotic IAV, we can inform public health mitigation strategies to ultimately reduce zoonotic IAV transmission and risk of pandemic IAV emergence.

The challenges of vaccine strain selection.

New measures of influenza virus fitness could improve vaccine strain selection through more accurate forecasts of the evolution of the virus.

Beyond clinical trials: Evolutionary and epidemiological considerations for development of a universal influenza vaccine.

The prospect of universal influenza vaccines is generating much interest and research at the intersection of immunology, epidemiology, and viral evolution. While the current focus is on developing a vaccine that elicits a broadly cross-reactive immune response in clinical trials, there are important downstream questions about global deployment of a universal influenza vaccine that should be explored to minimize unintended consequences and maximize benefits. Here, we review and synthesize the questions most relevant to predicting the population benefits of universal influenza vaccines and discuss how existing information could be mined to begin to address these questions. We review three research topics where computational modeling could bring valuable evidence: immune imprinting, viral evolution, and transmission. We address the positive and negative consequences of imprinting, in which early childhood exposure to influenza shapes and limits immune responses to future infections via memory of conserved influenza antigens. However, the mechanisms at play, their effectiveness, breadth of protection, and the ability to "reprogram" already imprinted individuals, remains heavily debated. We describe instances of rapid influenza evolution that illustrate the plasticity of the influenza virus in the face of drug pressure and discuss how novel vaccines could introduce new selective pressures on the evolution of the virus. We examine the possible unintended consequences of broadly protective (but infection-permissive) vaccines on the dynamics of epidemic and pandemic influenza, compared to conventional vaccines that have been shown to provide herd immunity benefits. In conclusion, computational modeling offers a valuable tool to anticipate the benefits of ambitious universal influenza vaccine programs, while balancing the risks from endemic influenza strains and unpredictable pandemic viruses. Moving forward, it will be important to mine the vast amount of data generated in clinical studies of universal influenza vaccines to ensure that the benefits and consequences of these vaccine programs have been carefully modeled and explored.

Terrestriality and bacterial transfer: a comparative study of gut microbiomes in sympatric Malagasy mammals.

The gut microbiomes of mammals appear to mirror their hosts' phylogeny, suggesting host-driven microbial community assembly. Yet, much of this evidence stems from comparative studies of distinct wild or captive populations that lack data for disentangling the relative influences of shared phylogeny and environment. Here, we present phylogenetic and multivariate analyses of gut microbiomes from six sympatric (i.e., co-occurring) mammal species inhabiting a 1-km2 area in western Madagascar-three lemur and three non-primate species-that consider genetic, dietary, and ecological predictors of microbiome functionality and composition. Host evolutionary history, indeed, appears to shape gut microbial patterns among both closely and distantly related species. However, we also find that diet-reliance on leaves versus fruit-is the best predictor of microbiome similarity among closely related lemur species, and that host substrate use-ground versus tree-constrains horizontal transmission via incidental contact with feces, with arboreal species harboring far more distinct communities than those of their terrestrial and semi-terrestrial counterparts.

Hierarchical social networks shape gut microbial composition in wild Verreaux's sifaka.

In wild primates, social behaviour influences exposure to environmentally acquired and directly transmitted microorganisms. Prior studies indicate that gut microbiota reflect pairwise social interactions among chimpanzee and baboon hosts. Here, we demonstrate that higher-order social network structure-beyond just pairwise interactions-drives gut bacterial composition in wild lemurs, which live in smaller and more cohesive groups than previously studied anthropoid species. Using 16S rRNA gene sequencing and social network analysis of grooming contacts, we estimate the relative impacts of hierarchical (i.e. multilevel) social structure, individual demographic traits, diet, scent-marking, and habitat overlap on bacteria acquisition in a wild population of Verreaux's sifaka (Propithecus verreauxi) consisting of seven social groups. We show that social group membership is clearly reflected in the microbiomes of individual sifaka, and that social groups with denser grooming networks have more homogeneous gut microbial compositions. Within social groups, adults, more gregarious individuals, and individuals that scent-mark frequently harbour the greatest microbial diversity. Thus, the community structure of wild lemurs governs symbiotic relationships by constraining transmission between hosts and partitioning environmental exposure to microorganisms. This social cultivation of mutualistic gut flora may be an evolutionary benefit of tight-knit group living.

Characterization of the Tree Holes Used by Lepilemur ruficaudatus in the Dry, Deciduous Forest of Kirindy Mitea National Park.

Knowledge of the key resources for a species is critical for developing an effective conservation strategy. Kirindy Mitea National Park is an important refuge for the red-tailed sportive lemur (Lepilemur ruficaudatus), a nocturnal folivorous lemur endemic to the dry deciduous forest of western Madagascar. Because L. ruficaudatus sleeps in tree holes during the day, sleeping trees may be an important resource for this species. Our goal was to characterize the sleeping sites used by L. ruficaudatus at the Ankoatsifaka Research Station in Kirindy Mitea National Park. In July and August 2012, tree characteristics were recorded for 60 L. ruficaudatus sleeping sites. Intact and alive trees, particularly Strychnos madagascariensis, were preferred by L. ruficaudatus. Sleeping holes were generally located in taller trees (median hole height = 4 m) and in trees with large girths (median = 20.5 cm). Greater protection from predators and thermal shifts may be provided by intact trees and concealed tree holes. Because tree characteristics can influence the presence and abundance of forest-living primates, the availability and characteristics of particular trees as potential sleeping shelters in a habitat must be taken into account in conservation strategies for L. ruficaudatus.

Wetland cover dynamics drive hemorrhagic disease patterns in white-tailed deer in the United States.

While vector-borne diseases are known to be particularly influenced by environmental factors, the impact of land-cover change on vector-borne wildlife disease patterns is poorly understood, largely due to the paucity of data on disease occurrence at extensive spatial and temporal scales. Widespread and rapid anthropogenic land-cover change, especially urbanization, has transformed the US landscape during the last century. Epizootic hemorrhagic disease virus and blue tongue virus, vectored by Culicoides biting midges, are two RNA viruses in the Orbivirus genus that cause severe hemorrhagic disease (HD) in white-tailed deer (Odocoileus virginianus). We examine the spatial dynamics of HD affecting white-tailed deer in the contiguous United States in two periods covering 1980 to 2007 in connection with land-cover change over the same time. Using spatial statistical modeling, wetland cover emerges as a critical driver of HD morbidity, whereas the drivers of mortality patterns are more complex. Increasing wetland cover is positively associated with HD morbidity, which is consistent with the ecologic requirements of the Culicoides vector. Wetland cover is inherently dynamic due to its importance to biodiversity and water quality as well as its utility for other purposes when drained. Accordingly this analysis helps in understanding the consequences of changing wetlands on vector-borne disease patterns, to identify disease hotspots in a large landscape, and to forecast the spatial spread of HD and related diseases.