Reservoir host immunology and life history shape virulence evolution in zoonotic viruses.

The management of future pandemic risk requires a better understanding of the mechanisms that determine the virulence of emerging zoonotic viruses. Meta-analyses suggest that the virulence of emerging zoonoses is correlated with but not completely predictable from reservoir host phylogeny, indicating that specific characteristics of reservoir host immunology and life history may drive the evolution of viral traits responsible for cross-species virulence. In particular, bats host viruses that cause higher case fatality rates upon spillover to humans than those derived from any other mammal, a phenomenon that cannot be explained by phylogenetic distance alone. In order to disentangle the fundamental drivers of these patterns, we develop a nested modeling framework that highlights mechanisms that underpin the evolution of viral traits in reservoir hosts that cause virulence following cross-species emergence. We apply this framework to generate virulence predictions for viral zoonoses derived from diverse mammalian reservoirs, recapturing trends in virus-induced human mortality rates reported in the literature. Notably, our work offers a mechanistic hypothesis to explain the extreme virulence of bat-borne zoonoses and, more generally, demonstrates how key differences in reservoir host longevity, viral tolerance, and constitutive immunity impact the evolution of viral traits that cause virulence following spillover to humans. Our theoretical framework offers a series of testable questions and predictions designed to stimulate future work comparing cross-species virulence evolution in zoonotic viruses derived from diverse mammalian hosts.

Bats host the most virulent-but not the most dangerous-zoonotic viruses.

SignificanceThe clear need to mitigate zoonotic risk has fueled increased viral discovery in specific reservoir host taxa. We show that a combination of viral and reservoir traits can predict zoonotic virus virulence and transmissibility in humans, supporting the hypothesis that bats harbor exceptionally virulent zoonoses. However, pandemic prevention requires thinking beyond zoonotic capacity, virulence, and transmissibility to consider collective "burden" on human health. For this, viral discovery targeting specific reservoirs may be inefficient as death burden correlates with viral, not reservoir, traits, and depends on context-specific epidemiological dynamics across and beyond the human-animal interface. These findings suggest that longitudinal studies of viral dynamics in reservoir and spillover host populations may offer the most effective strategy for mitigating zoonotic risk.

Discovery and Genomic Characterization of a Novel Henipavirus, Angavokely Virus, from Fruit Bats in Madagascar.

The genus Henipavirus (family Paramyxoviridae) currently comprises seven viruses, four of which have demonstrated prior evidence of zoonotic capacity. These include the biosafety level 4 agents Hendra (HeV) and Nipah (NiV) viruses, which circulate naturally in pteropodid fruit bats. Here, we describe and characterize Angavokely virus (AngV), a divergent henipavirus identified in urine samples from wild, Madagascar fruit bats. We report the nearly complete 16,740-nucleotide genome of AngV, which encodes the six major henipavirus structural proteins (nucleocapsid, phosphoprotein, matrix, fusion, glycoprotein, and L polymerase). Within the phosphoprotein (P) gene, we identify an alternative start codon encoding the AngV C protein and a putative mRNA editing site where the insertion of one or two guanine residues encodes, respectively, additional V and W proteins. In other paramyxovirus systems, C, V, and W are accessory proteins involved in antagonism of host immune responses during infection. Phylogenetic analysis suggests that AngV is ancestral to all four previously described bat henipaviruses-HeV, NiV, Cedar virus (CedV), and Ghanaian bat virus (GhV)-but evolved more recently than rodent- and shrew-derived henipaviruses, Mojiang (MojV), Gamak (GAKV), and Daeryong (DARV) viruses. Predictive structure-based alignments suggest that AngV is unlikely to bind ephrin receptors, which mediate cell entry for all other known bat henipaviruses. Identification of the AngV receptor is needed to clarify the virus's potential host range. The presence of V and W proteins in the AngV genome suggest that the virus could be pathogenic following zoonotic spillover. IMPORTANCE Henipaviruses include highly pathogenic emerging zoonotic viruses, derived from bat, rodent, and shrew reservoirs. Bat-borne Hendra (HeV) and Nipah (NiV) are the most well-known henipaviruses, for which no effective antivirals or vaccines for humans have been described. Here, we report the discovery and characterization of a novel henipavirus, Angavokely virus (AngV), isolated from wild fruit bats in Madagascar. Genomic characterization of AngV reveals all major features associated with pathogenicity in other henipaviruses, suggesting that AngV could be pathogenic following spillover to human hosts. Our work suggests that AngV is an ancestral bat henipavirus that likely uses viral entry pathways distinct from those previously described for HeV and NiV. In Madagascar, bats are consumed as a source of human food, presenting opportunities for cross-species transmission. Characterization of novel henipaviruses and documentation of their pathogenic and zoonotic potential are essential to predicting and preventing the emergence of future zoonoses that cause pandemics.

National dengue surveillance, Cambodia 2002-2020.

Global dengue incidence has increased dramatically over the past few decades from approximately 500 000 reported cases in 2000 to over 5 million in 2019. This trend has been attributed to population growth in endemic areas, rapid unplanned urbanization, increasing global connectivity, and climate change expanding the geographic range of the Aedes spp. mosquito, among other factors. Reporting dengue surveillance data is key to understanding the scale of the problem, identifying important changes in the landscape of disease, and developing policies for clinical management, vector control and vaccine rollout. However, surveillance practices are not standardized, and data may be difficult to interpret particularly in low- and middle-income countries with fragmented health-care systems. The latest national dengue surveillance data for Cambodia was published in 2010. Since its publication, the country experienced marked changes in health policies, population demographics, climate and urbanization. How these changes affected dengue control remains unknown. In this article, we summarize two decades of policy changes, published literature, country statistics, and dengue case data collected by the Cambodia National Dengue Control Programme to: (i) identify important changes in the disease landscape; and (ii) derive lessons to inform future surveillance and disease control strategies. We report that while dengue case morbidity and mortality rates in Cambodia fell between 2002 and 2020, dengue incidence doubled and age at infection increased. Future national surveillance, disease prevention and treatment, and vector control policies will have to account for these changes to optimize disease control.

Le taux d'incidence de la dengue dans le monde a considérablement augmenté au cours des dernières décennies, passant d'environ 500 000 cas notifiés en 2000 à plus de 5 millions en 2019. Cette tendance est attribuée à la croissance démographique dans les zones d'endémie, à l'urbanisation rapide non planifiée, au développement de la connectivité à l'échelle internationale, ainsi qu'au changement climatique, qui agrandit le territoire géographique du moustique Aedes spp., entre autres. La communication des données de surveillance de la dengue est essentielle pour comprendre l'étendue du problème, identifier les principales variations de contexte entourant la maladie et mettre au point des politiques pour la prise en charge clinique, la lutte contre les vecteurs et le déploiement des vaccins. Les pratiques en matière de surveillance ne sont toutefois pas standardisées et les données peuvent être difficiles à interpréter, surtout dans les pays à revenu faible et intermédiaire où les systèmes de soins de santé sont fragmentés. Les données de surveillance les plus récentes concernant la dengue au Cambodge ont été publiées en 2010. Depuis leur publication, le pays a subi de profondes mutations au niveau des politiques de santé, de l'évolution démographique, du climat et de l'urbanisation. L'impact de ces mutations sur la lutte contre la dengue reste à établir. Dans le présent article, nous résumons deux décennies d'amendements politiques, de documentation, de statistiques nationales et d'informations collectées sur les cas par le programme cambodgien de lutte contre la dengue afin de: (i) définir les changements importants survenus dans le contexte entourant la maladie; mais aussi (ii) tirer des leçons en vue d'élaborer, à l'avenir, des stratégies de surveillance et de lutte contre la maladie. Nous signalons qu'en dépit d'une baisse des taux de morbidité et de mortalité liés aux cas de dengue entre 2002 et 2020 au Cambodge, son incidence a doublé et l'âge des patients au moment de l'infection a augmenté. Les futures politiques nationales de surveillance, de prévention et de traitement de la dengue, mais aussi de lutte contre ses vecteurs, devront tenir compte de ces changements de façon à mieux maîtriser la maladie.

La incidencia del dengue a nivel mundial ha aumentado considerablemente en las últimas décadas, desde aproximadamente 500 000 casos notificados en el año 2000 a más de 5 millones en 2019. Esta tendencia se ha atribuido al crecimiento de la población en zonas endémicas, a una urbanización rápida y no planificada, al aumento de la conectividad a nivel mundial y al cambio climático, que está permitiendo una distribución geográfica más amplia del mosquito Aedes spp., entre otros factores. Para comprender la magnitud del problema resulta clave la notificación de datos sobre vigilancia del dengue, la identificación de cambios importantes dentro del escenario de la enfermedad, la creación de políticas enfocadas a la gestión clínica, así como el control de vectores y la implantación de la vacuna. Sin embargo, las prácticas sobre vigilancia no están estandarizadas y es posible que sea difícil interpretar los datos, especialmente en países con ingresos medios y bajos, que cuentan con sistemas fragmentados de atención sanitaria. Los datos nacionales más recientes sobre vigilancia del dengue en Camboya se publicaron en 2010. Desde su publicación, el país experimentó cambios significativos en las políticas sanitarias, la demografía de la población, el clima y la urbanización. Aún no se sabe cómo afectaron dichos cambios al control del dengue. En el presente artículo, resumimos dos décadas de cambios políticos, de bibliografía publicada, de datos estadísticos a nivel nacional y datos sobre casos de dengue recopilados por el programa nacional de control de dengue en Camboya, con el fin de: (i) identificar cambios importantes en el escenario de la enfermedad; y (ii) extraer conclusiones para orientar futuras estrategias sobre vigilancia y control de la enfermedad. Informamos de que, aunque las tasas de morbilidad y mortalidad de los casos de dengue en Camboya descendieron entre 2002 y 2020, la incidencia del dengue se duplicó y la edad de infección aumentó. Las futuras políticas nacionales sobre vigilancia, prevención y tratamiento de la enfermedad y control de vectores deberán tener en cuenta estos cambios para optimizar el control de la enfermedad.

Possibility for reverse zoonotic transmission of SARS-CoV-2 to free-ranging wildlife: A case study of bats.

The COVID-19 pandemic highlights the substantial public health, economic, and societal consequences of virus spillover from a wildlife reservoir. Widespread human transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) also presents a new set of challenges when considering viral spillover from people to naïve wildlife and other animal populations. The establishment of new wildlife reservoirs for SARS-CoV-2 would further complicate public health control measures and could lead to wildlife health and conservation impacts. Given the likely bat origin of SARS-CoV-2 and related beta-coronaviruses (ß-CoVs), free-ranging bats are a key group of concern for spillover from humans back to wildlife. Here, we review the diversity and natural host range of ß-CoVs in bats and examine the risk of humans inadvertently infecting free-ranging bats with SARS-CoV-2. Our review of the global distribution and host range of ß-CoV evolutionary lineages suggests that 40+ species of temperate-zone North American bats could be immunologically naïve and susceptible to infection by SARS-CoV-2. We highlight an urgent need to proactively connect the wellbeing of human and wildlife health during the current pandemic and to implement new tools to continue wildlife research while avoiding potentially severe health and conservation impacts of SARS-CoV-2 "spilling back" into free-ranging bat populations.

Disentangling serology to elucidate henipa- and filovirus transmission in Madagascar fruit bats.

Bats are reservoirs for emerging human pathogens, including Hendra and Nipah henipaviruses and Ebola and Marburg filoviruses. These viruses demonstrate predictable patterns in seasonality and age structure across multiple systems; previous work suggests that they may circulate in Madagascar's endemic fruit bats, which are widely consumed as human food. We aimed to (a) document the extent of henipa- and filovirus exposure among Malagasy fruit bats, (b) explore seasonality in seroprevalence and serostatus in these bat populations and (c) compare mechanistic hypotheses for possible transmission dynamics underlying these data. To this end, we amassed and analysed a unique dataset documenting longitudinal serological henipa- and filovirus dynamics in three Madagascar fruit bat species. We uncovered serological evidence of exposure to Hendra-/Nipah-related henipaviruses in Eidolon dupreanum, Pteropus rufus and Rousettus madagascariensis, to Cedar-related henipaviruses in E. dupreanum and R. madagascariensis and to Ebola-related filoviruses in P. rufus and R. madagascariensis. We demonstrated significant seasonality in population-level seroprevalence and individual serostatus for multiple viruses across these species, linked to the female reproductive calendar. An age-structured subset of the data highlighted evidence of waning maternal antibodies in neonates, increasing seroprevalence in young and decreasing seroprevalence late in life. Comparison of mechanistic epidemiological models fit to these data offered support for transmission hypotheses permitting waning antibodies but retained immunity in adult-age bats. Our findings suggest that bats may seasonally modulate mechanisms of pathogen control, with consequences for population-level transmission. Additionally, we narrow the field of candidate transmission hypotheses by which bats are presumed to host and transmit potentially zoonotic viruses globally.

Population viability and harvest sustainability for Madagascar lemurs.

Subsistence hunting presents a conservation challenge by which biodiversity preservation must be balanced with safeguarding of human livelihoods. Globally, subsistence hunting threatens primate populations, including Madagascar's endemic lemurs. We used population viability analysis to assess the sustainability of lemur hunting in Makira Natural Park, Madagascar. We identified trends in seasonal hunting of 11 Makira lemur species from household interview data, estimated local lemur densities in populations adjacent to focal villages via transect surveys, and quantified extinction vulnerability for these populations based on species-specific demographic parameters and empirically derived hunting rates. We compared stage-based Lefkovitch with periodic Leslie matrices to evaluate the impact of regional dispersal on persistence trajectories and explored the consequences of perturbations to the timing of peak hunting relative to the lemur birth pulse, under assumptions of density-dependent reproductive compensation. Lemur hunting peaked during the fruit-abundant wet season (March-June). Estimated local lemur densities were roughly inverse to body size across our study area. Life-history modeling indicated that hunting most severely threatened the species with the largest bodies (i.e., Hapalemur occidentalis, Avahi laniger, Daubentonia madagascariensis, and Indri indi), characterized by late-age reproductive onsets and long interbirth intervals. In model simulations, lemur dispersal within a regional metapopulation buffered extinction threats when a majority of local sites supported growth rates above the replacement level but drove regional extirpations when most local sites were overharvested. Hunt simulations were most detrimental when timed to overlap lemur births (a reality for D. madagascariensis and I. indri). In sum, Makira lemurs were overharvested. Regional extirpations, which may contribute to broad-scale extinctions, will be likely if current hunting rates persist. Cessation of anthropogenic lemur harvest is a conservation priority, and development programs are needed to help communities switch from wildlife consumption to domestic protein alternatives.

Population trends for two Malagasy fruit bats.

Madagascar is home to three endemic species of Old World Fruit Bat, which are important pollinators and seed dispersers. We aimed to quantitatively assess population trajectories for the two largest of these species, the IUCN-listed 'Vulnerable' Eidolon dupreanum and Pteropus rufus. To this end, we conducted a longitudinal field study, in which we live-captured E. dupreanum and P. rufus, estimated species-specific fecundity rates, and generated age-frequency data via histological analysis of cementum annuli layering in tooth samples extracted from a subset of individuals. We fit exponential models to resulting data to estimate annual survival probabilities for adult bats (s A = .794 for E. dupreanum; s A = .511 for P. rufus), then applied Lefkovitch modeling techniques to infer the minimum required juvenile survival rate needed to permit longterm population persistence. Given estimated adult survival, population persistence was only possible for E. dupreanum when field-based fecundity estimates were replaced by higher values reported in the literature for related species. For P. rufus, tooth-derived estimates of adult survival were so low that even assumptions of perfect (100%) juvenile annual survival would not permit stable population trajectories. Age-based survival analyses were further supported by longitudinal exit counts carried out from 2013-2018 at three local P. rufus roost sites, which demonstrated a statistically significant, faintly negative time trend, indicative of subtle regional population declines. These results suggest that Malagasy fruit bat species face significant threats to population viability, with P. rufus particularly imperiled. Immediate conservation interventions, including habitat restoration and cessation of legally sanctioned bat hunting, are needed to protect Madagascar's fruit bats into the future.

Applications of VirScan to broad serological profiling of bat reservoirs for emerging zoonoses.

Introduction: Bats are important providers of ecosystem services such as pollination, seed dispersal, and insect control but also act as natural reservoirs for virulent zoonotic viruses. Bats host multiple viruses that cause life-threatening pathology in other animals and humans but, themselves, experience limited pathological disease from infection. Despite bats' importance as reservoirs for several zoonotic viruses, we know little about the broader viral diversity that they host. Bat virus surveillance efforts are challenged by difficulties of field capture and the limited scope of targeted PCR- or ELISA-based molecular and serological detection. Additionally, virus shedding is often transient, thus also limiting insights gained from nucleic acid testing of field specimens. Phage ImmunoPrecipitation Sequencing (PhIP-Seq), a broad serological tool used previously to comprehensively profile viral exposure history in humans, offers an exciting prospect for viral surveillance efforts in wildlife, including bats. Methods: Here, for the first time, we apply PhIP-Seq technology to bat serum, using a viral peptide library originally designed to simultaneously assay exposures to the entire human virome. Results: Using VirScan, we identified past exposures to 57 viral genera-including betacoronaviruses, henipaviruses, lyssaviruses, and filoviruses-in semi-captive Pteropus alecto and to nine viral genera in captive Eonycteris spelaea. Consistent with results from humans, we find that both total peptide hits (the number of enriched viral peptides in our library) and the corresponding number of inferred past virus exposures in bat hosts were correlated with poor bat body condition scores and increased with age. High and low body condition scores were associated with either seropositive or seronegative status for different viruses, though in general, virus-specific age-seroprevalence curves defied assumptions of lifelong immunizing infection, suggesting that many bat viruses may circulate via complex transmission dynamics. Discussion: Overall, our work emphasizes the utility of applying biomedical tools, like PhIP-Seq, first developed for humans to viral surveillance efforts in wildlife, while highlighting opportunities for taxon-specific improvements.

Dengue in Cambodia 2002-2020: Cases, Characteristics and Capture by National Surveillance.

Objective: Data from 19 years of national dengue surveillance in Cambodia (2002-2020) were analyzed to describe trends in dengue case characteristics and incidence. Methods: Generalized additive models were fitted to dengue case incidence and characteristics (mean age, case phenotype, fatality) over time. Dengue incidence in a pediatric cohort study (2018-2020) was compared to national data during the same period to evaluate disease under-estimation by national surveillance. Findings: During 2002-2020, there were 353,270 cases of dengue (average age-adjusted incidence 1.75 cases/1,000 persons/year) recorded in Cambodia, with an estimated 2.1-fold increase in case incidence between 2002 and 2020 (slope = 0.0058, SE = 0.0021, p = 0.006). Mean age of infected individuals increased from 5.8 years in 2002 to 9.1 years in 2020 (slope = 0.18, SE = 0.088, p <0.001); case fatality rates decreased from 1.77% in 2002 to 0.10% in 2020 (slope = -0.16, SE = 0.0050, p <0.001). When compared to cohort data, national data under-estimated clinically apparent dengue case incidence by 5.0-fold (95% CI 0.2 - 26.5), and overall dengue case incidence (both apparent and inapparent cases) by 33.6-fold (range: 18.7- 53.6). Conclusion: Dengue incidence in Cambodia is increasing and disease is shifting to older pediatric populations. National surveillance continues to under-estimate case numbers. Future interventions should account for disease under-estimation and shifting demographics for scaling and to target appropriate age groups.

Detection, characterization, and phylogenetic analysis of a near-whole genome sequence of a novel astrovirus in an endemic Malagasy fruit bat, Rousettus madagascariensis.

Bats (order: Chiroptera ) are known to host a diverse range of viruses, some of which present a public health risk. Thorough viral surveillance is therefore essential to predict and potentially mitigate zoonotic spillover. Astroviruses (family: Astroviridae ) are an understudied group of viruses with a growing amount of indirect evidence for zoonotic transfer. Astroviruses have been detected in bats with significant prevalence and diversity, suggesting that bats may act as important astrovirus hosts. Most astrovirus surveillance in wild bat hosts has, to date, been restricted to single-gene PCR detection and concomitant Sanger sequencing; additionally, many bat species and many geographic regions have not yet been surveyed for astroviruses at all. Here, we use metagenomic Next Generation Sequencing (mNGS) to detect astroviruses in three species of Madagascar fruit bats, Eidolon dupreanum, Pteropus rufus, and Rousettus madagascariensis . We detect numerous partial sequences from all three species and one near-full length astrovirus sequence from Rousettus madagascariensis , which we use to characterize the evolutionary history of astroviruses both within bats and the broader mammalian clade, Mamastrovirus . Taken together, applications of mNGS implicate bats as important astrovirus hosts and demonstrate novel patterns of bat astrovirus evolutionary history, particularly in the Southwest Indian Ocean region.

Do gastrointestinal microbiomes play a role in bats' unique viral hosting capacity?

Bats are reservoirs for zoonotic viruses, which they tolerate without experiencing disease. Research focused on deciphering mechanisms of virus tolerance in bats has rarely considered the influence of their gastrointestinal tract (GIT) microbiome. In mammals, GIT microbiomes influence infections through their effect on host physiology, immunity, nutrition, and behavior. Bat GIT microbiomes more closely resemble the Proteobacteria-dominated GIT microbiomes of birds than those of other mammals. As an adaptation to flight, bats have rapid GIT transit times which may reduce the stability of their microbiome, constrain nutrient uptake, and affect pathogen exposure and evolution of tolerance mechanisms. Experimental and longitudinal studies are needed to understand the function of bats' GIT microbiomes and their role in modulating viral infection dynamics.

Reproduction, seasonal morphology, and juvenile growth in three Malagasy fruit bats.

The island nation of Madagascar is home to three endemic species of Old World fruit bat in the family Pteropodidae: Pteropus rufus, Eidolon dupreanum, and Rousettus madagascariensis, all three of which are IUCN Red Listed under some category of threat. Delineation of seasonal limits in the reproductive calendar for threatened mammals can inform conservation efforts by clarifying parameters used in population viability models, as well as elucidate understanding of the mechanisms underpinning pathogen persistence in host populations. Here, we define the seasonal limits of a staggered annual birth pulse across the three species of endemic Madagascar fruit bat, known reservoirs for viruses of high zoonotic potential. Our field studies indicate that this annual birth pulse takes place in September/October for P. rufus, November for E. dupreanum, and December for R. madagascariensis in central-eastern Madagascar where the bulk of our research was concentrated. Juvenile development periods vary across the three Malagasy pteropodids, resulting in near-synchronous weaning of pups for all species in late January-February at the height of the fruiting season for this region. We here document the size range in morphological traits for the three Malagasy fruit bat species, with P. rufus and E. dupreanum among the larger of pteropodids globally and R. madagascariensis among the smaller. All three species demonstrate subtle sexual dimorphism with males being larger than females. We explore seasonal variation in adult body condition by comparing observed body mass with body mass predicted by forearm length, demonstrating that pregnant females add weight during staggered gestation periods and males lose weight during the nutritionally deficit Malagasy winter. Finally, we quantify forearm, tibia, and ear length growth rates in juvenile bats, demonstrating both faster growth and more protracted development times for P. rufus as compared with E. dupreanum and R. madagascariensis. The longer development period for the already-threatened P. rufus further undermines the conservation status of this species as human hunting is particularly detrimental to population viability during reproductive periods. Our work highlights the importance of longitudinal field studies in collecting critical data for mammalian conservation efforts and human public health alike.

Full Genome Nobecovirus Sequences From Malagasy Fruit Bats Define a Unique Evolutionary History for This Coronavirus Clade.

Bats are natural reservoirs for both Alpha- and Betacoronaviruses and the hypothesized original hosts of five of seven known zoonotic coronaviruses. To date, the vast majority of bat coronavirus research has been concentrated in Asia, though coronaviruses are globally distributed; indeed, SARS-CoV and SARS-CoV-2-related Betacoronaviruses in the subgenus Sarbecovirus have been identified circulating in Rhinolophid bats in both Africa and Europe, despite the relative dearth of surveillance in these regions. As part of a long-term study examining the dynamics of potentially zoonotic viruses in three species of endemic Madagascar fruit bat (Pteropus rufus, Eidolon dupreanum, Rousettus madagascariensis), we carried out metagenomic Next Generation Sequencing (mNGS) on urine, throat, and fecal samples obtained from wild-caught individuals. We report detection of RNA derived from Betacoronavirus subgenus Nobecovirus in fecal samples from all three species and describe full genome sequences of novel Nobecoviruses in P. rufus and R. madagascariensis. Phylogenetic analysis indicates the existence of five distinct Nobecovirus clades, one of which is defined by the highly divergent ancestral sequence reported here from P. rufus bats. Madagascar Nobecoviruses derived from P. rufus and R. madagascariensis demonstrate, respectively, Asian and African phylogeographic origins, mirroring those of their fruit bat hosts. Bootscan recombination analysis indicates significant selection has taken place in the spike, nucleocapsid, and NS7 accessory protein regions of the genome for viruses derived from both bat hosts. Madagascar offers a unique phylogeographic nexus of bats and viruses with both Asian and African phylogeographic origins, providing opportunities for unprecedented mixing of viral groups and, potentially, recombination. As fruit bats are handled and consumed widely across Madagascar for subsistence, understanding the landscape of potentially zoonotic coronavirus circulation is essential for mitigation of future zoonotic threats.

Cross-sectional cycle threshold values reflect epidemic dynamics of COVID-19 in Madagascar.

As the national reference laboratory for febrile illness in Madagascar, we processed samples from the first epidemic wave of COVID-19, between March and September 2020. We fit generalized additive models to cycle threshold (Ct) value data from our RT-qPCR platform, demonstrating a peak in high viral load, low-Ct value infections temporally coincident with peak epidemic growth rates estimated in real time from publicly-reported incidence data and retrospectively from our own laboratory testing data across three administrative regions. We additionally demonstrate a statistically significant effect of duration of time since infection onset on Ct value, suggesting that Ct value can be used as a biomarker of the stage at which an individual is sampled in the course of an infection trajectory. As an extension, the population-level Ct distribution at a given timepoint can be used to estimate population-level epidemiological dynamics. We illustrate this concept by adopting a recently-developed, nested modeling approach, embedding a within-host viral kinetics model within a population-level Susceptible-Exposed-Infectious-Recovered (SEIR) framework, to mechanistically estimate epidemic growth rates from cross-sectional Ct distributions across three regions in Madagascar. We find that Ct-derived epidemic growth estimates slightly precede those derived from incidence data across the first epidemic wave, suggesting delays in surveillance and case reporting. Our findings indicate that public reporting of Ct values could offer an important resource for epidemiological inference in low surveillance settings, enabling forecasts of impending incidence peaks in regions with limited case reporting.

Ecology, evolution and spillover of coronaviruses from bats.

In the past two decades, three coronaviruses with ancestral origins in bats have emerged and caused widespread outbreaks in humans, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Since the first SARS epidemic in 2002-2003, the appreciation of bats as key hosts of zoonotic coronaviruses has advanced rapidly. More than 4,000 coronavirus sequences from 14 bat families have been identified, yet the true diversity of bat coronaviruses is probably much greater. Given that bats are the likely evolutionary source for several human coronaviruses, including strains that cause mild upper respiratory tract disease, their role in historic and future pandemics requires ongoing investigation. We review and integrate information on bat-coronavirus interactions at the molecular, tissue, host and population levels. We identify critical gaps in knowledge of bat coronaviruses, which relate to spillover and pandemic risk, including the pathways to zoonotic spillover, the infection dynamics within bat reservoir hosts, the role of prior adaptation in intermediate hosts for zoonotic transmission and the viral genotypes or traits that predict zoonotic capacity and pandemic potential. Filling these knowledge gaps may help prevent the next pandemic.

Optimizing COVID-19 control with asymptomatic surveillance testing in a university environment.

The high proportion of transmission events derived from asymptomatic or presymptomatic infections make SARS-CoV-2, the causative agent in COVID-19, difficult to control through the traditional non-pharmaceutical interventions (NPIs) of symptom-based isolation and contact tracing. As a consequence, many US universities developed asymptomatic surveillance testing labs, to augment NPIs and control outbreaks on campus throughout the 2020-2021 academic year (AY); several of those labs continue to support asymptomatic surveillance efforts on campus in AY2021-2022. At the height of the pandemic, we built a stochastic branching process model of COVID-19 dynamics at UC Berkeley to advise optimal control strategies in a university environment. Our model combines behavioral interventions in the form of group size limits to deter superspreading, symptom-based isolation, and contact tracing, with asymptomatic surveillance testing. We found that behavioral interventions offer a cost-effective means of epidemic control: group size limits of six or fewer greatly reduce superspreading, and rapid isolation of symptomatic infections can halt rising epidemics, depending on the frequency of asymptomatic transmission in the population. Surveillance testing can overcome uncertainty surrounding asymptomatic infections, with the most effective approaches prioritizing frequent testing with rapid turnaround time to isolation over test sensitivity. Importantly, contact tracing amplifies population-level impacts of all infection isolations, making even delayed interventions effective. Combination of behavior-based NPIs and asymptomatic surveillance also reduces variation in daily case counts to produce more predictable epidemics. Furthermore, targeted, intensive testing of a minority of high transmission risk individuals can effectively control the COVID-19 epidemic for the surrounding population. Even in some highly vaccinated university settings in AY2021-2022, asymptomatic surveillance testing offers an effective means of identifying breakthrough infections, halting onward transmission, and reducing total caseload. We offer this blueprint and easy-to-implement modeling tool to other academic or professional communities navigating optimal return-to-work strategies.

Optimizing COVID-19 control with asymptomatic surveillance testing in a university environment.

The high proportion of transmission events derived from asymptomatic or presymptomatic infections make SARS-CoV-2, the causative agent in COVID-19, difficult to control through the traditional non-pharmaceutical interventions (NPIs) of symptom-based isolation and contact tracing. As a consequence, many US universities developed asymptomatic surveillance testing labs, to augment NPIs and control outbreaks on campus throughout the 2020-2021 academic year (AY); several of those labs continue to support asymptomatic surveillance efforts on campus in AY2021-2022. At the height of the pandemic, we built a stochastic branching process model of COVID-19 dynamics at UC Berkeley to advise optimal control strategies in a university environment. Our model combines behavioral interventions in the form of group size limits to deter superspreading, symptom-based isolation, and contact tracing, with asymptomatic surveillance testing. We found that behavioral interventions offer a cost-effective means of epidemic control: group size limits of six or fewer greatly reduce superspreading, and rapid isolation of symptomatic infections can halt rising epidemics, depending on the frequency of asymptomatic transmission in the population. Surveillance testing can overcome uncertainty surrounding asymptomatic infections, with the most effective approaches prioritizing frequent testing with rapid turnaround time to isolation over test sensitivity. Importantly, contact tracing amplifies population-level impacts of all infection isolations, making even delayed interventions effective. Combination of behavior-based NPIs and asymptomatic surveillance also reduces variation in daily case counts to produce more predictable epidemics. Furthermore, targeted, intensive testing of a minority of high transmission risk individuals can effectively control the COVID-19 epidemic for the surrounding population. Even in some highly vaccinated university settings in AY2021-2022, asymptomatic surveillance testing offers an effective means of identifying breakthrough infections, halting onward transmission, and reducing total caseload. We offer this blueprint and easy-to-implement modeling tool to other academic or professional communities navigating optimal return-to-work strategies.

Cross-sectional cycle threshold values reflect epidemic dynamics of COVID-19 in Madagascar.

As the national reference laboratory for febrile illness in Madagascar, we processed samples from the first epidemic wave of COVID-19, between March and September 2020. We fit generalized additive models to cycle threshold (C t ) value data from our RT-qPCR platform, demonstrating a peak in high viral load, low-C t value infections temporally coincident with peak epidemic growth rates estimated in real time from publicly-reported incidence data and retrospectively from our own laboratory testing data across three administrative regions. We additionally demonstrate a statistically significant effect of duration of time since infection onset on C t value, suggesting that C t value can be used as a biomarker of the stage at which an individual is sampled in the course of an infection trajectory. As an extension, the population-level C t distribution at a given timepoint can be used to estimate population-level epidemiological dynamics. We illustrate this concept by adopting a recently-developed, nested modeling approach, embedding a within-host viral kinetics model within a population-level Susceptible-Exposed-Infectious-Recovered (SEIR) framework, to mechanistically estimate epidemic growth rates from cross-sectional C t distributions across three regions in Madagascar. We find that C t -derived epidemic growth estimates slightly precede those derived from incidence data across the first epidemic wave, suggesting delays in surveillance and case reporting. Our findings indicate that public reporting of C t values could offer an important resource for epidemiological inference in low surveillance settings, enabling forecasts of impending incidence peaks in regions with limited case reporting.

The science of the host-virus network.

Better methods to predict and prevent the emergence of zoonotic viruses could support future efforts to reduce the risk of epidemics. We propose a network science framework for understanding and predicting human and animal susceptibility to viral infections. Related approaches have so far helped to identify basic biological rules that govern cross-species transmission and structure the global virome. We highlight ways to make modelling both accurate and actionable, and discuss the barriers that prevent researchers from translating viral ecology into public health policies that could prevent future pandemics.