Who acquires infection from whom? Estimating herpesvirus transmission rates between wild rodent host groups

Influence of Host and Landscape-Associated Factors in the Infection and Transmission of Pathogens: The Case of Directly Transmitted Virus in Mammals

BACKGROUND

Among pathogens associated with mammals, numerous viruses with a direct transmission route impact human, domestic and wild species health. Host and landscape factors affect viral infection and transmission dynamics of these viruses, along with barriers to host dispersal and gene exchange. However, studies show biases toward certain locations, hosts and detected pathogens, with regional variations in similar host-virus associations.

METHODS

Using a systematic review, in two electronic repositories for articles published until December 2022, we analysed the available information on host- and landscape-associated factors influencing the infection and transmission of directly transmitted viruses in mammals.

RESULTS

In the analysis, about 50% of papers examined either host traits, landscape composition or configuration measures, while approximately 24% combined host and landscape-associated factors. Additionally, approximately 17% of the articles included climatic data and 30% integrated factors related to anthropogenic impact, as these variables have a role in host density, distribution and virus persistence. The most significant and frequent host traits used as predictor variables were sex, age, body weight, host density and species identity. Land cover was the most evaluated landscape attribute, while some explored configuration variables like edge density and fragmentation indexes. Finally, temperature, precipitation and features such as human population density and human footprint index were also typically measured and found impactful.

CONCLUSION

Given the many contributions host- and landscape-related factors have in pathogen dynamics, this systematic study contributes to a better knowledge of host-virus dynamics and the identification of variables and gaps that can be used for disease prevention.

Inferring the disruption of rabies circulation in vampire bat populations using a betaherpesvirus-vectored transmissible vaccine

Transmissible vaccines are an emerging biotechnology that hold prospects to eliminate pathogens from wildlife populations. Such vaccines would genetically modify naturally occurring, nonpathogenic viruses ("viral vectors") to express pathogen antigens while retaining their capacity to transmit. The epidemiology of candidate viral vectors within the target wildlife population has been notoriously challenging to resolve but underpins the selection of effective vectors prior to major investments in vaccine development. Here, we used spatiotemporally replicated deep sequencing to parameterize competing epidemiological mechanistic models of Desmodus rotundus betaherpesvirus (DrBHV), a proposed vector for a transmissible vaccine targeting vampire bat-transmitted rabies. Using 36 strain- and location-specific time series of prevalence collected over 6 y, we found that lifelong infections with cycles of latency and reactivation, combined with a high R0 (6.9; CI: 4.39 to 7.85), are necessary to explain patterns of DrBHV infection observed in wild bats. These epidemiological properties suggest that DrBHV may be suited to vector a lifelong, self-boosting, and transmissible vaccine. Simulations showed that inoculating a single bat with a DrBHV-vectored rabies vaccine could immunize >80% of a bat population, reducing the size, frequency, and duration of rabies outbreaks by 50 to 95%. Gradual loss of infectious vaccine from vaccinated individuals is expected but can be countered by inoculating larger but practically achievable proportions of bat populations. Parameterizing epidemiological models using accessible genomic data brings transmissible vaccines one step closer to implementation.

A novel method to jointly estimate transmission rate and decay rate parameters in environmental transmission models

In environmental transmission, pathogens transfer from one individual to another via the environment. It is a common transmission mechanism in a wide range of host-pathogen systems. Incorporating environmental transmission in dynamic transmission models is crucial for gauging the effect of interventions, as extrapolating model results to new situations is only valid when the mechanisms are modelled correctly. The challenge in environmental transmission models lies in not jointly identifiable parameters for pathogen shedding, decay, and transmission dynamics. To solve this unidentifiability issue, we present a stochastic environmental transmission model with a novel scaling method for shedding rate parameter and a novel estimation method that distinguishes transmission rate and decay rate parameters. The core of our scaling and estimation method is calculating exposure and relating exposure to infection risks. By scaling shedding rate parameter, we standardize exposure to pathogens contributed by one infectious individual present during one time interval to one. The standardized exposure leads to a standard definition of transmission rate parameter applicable to scenarios with different decay rate parameters. Hence, we unify direct transmission (large decay rate) and environmental transmission in a continuous manner. More importantly, our exposure-based estimation method can correctly estimate back the transmission rate and the decay rate parameters, while the commonly used trajectory-based method failed. The reason is that exposure-based method gives the correct weight to infection data from previous observation periods. The correct estimation from exposure-based method will lead to more reliable predictions of intervention impact. Using the effect of disinfection as an example, we show how incorrectly estimated parameters may lead to incorrect conclusions about the effectiveness of interventions. This illustrates the importance of correct estimation of transmission rate and decay rate parameters for extrapolating environmental transmission models and predicting intervention effects.

The predicted impact of resource provisioning on the epidemiological responses of different parasites

Anthropogenic activities and natural events such as periodic tree masting can alter resource provisioning in the environment, directly affecting animals, and potentially impacting the spread of infectious diseases in wildlife. The impact of these additional resources on infectious diseases can manifest through different pathways, affecting host susceptibility, contact rate and host demography. To date however, empirical research has tended to examine these different pathways in isolation, for example by quantifying the effects of provisioning on host behaviour in the wild or changes in immune responses in controlled laboratory studies. Furthermore, while theory has investigated the interactions between these pathways, this work has focussed on a narrow subset of pathogen types, typically directly transmitted microparasites. Given the diverse ways that provisioning can affect host susceptibility, contact patterns or host demography, we may expect the epidemiological consequences of provisioning to vary among different parasite types, dependent on key aspects of parasite life history, such as the duration of infection and transmission mode. Focusing on an exemplar empirical system, the wood mouse Apodemus sylvaticus, and its diverse parasite community, we developed a suite of epidemiological models to compare how resource provisioning alters responses for a range of these parasites that vary in their biology (microparasite and macroparasite), transmission mode (direct, environmental and vector transmitted) and duration of infection (acute, latent and chronic) within the same host population. We show there are common epidemiological responses to host resource provisioning across all parasite types examined. In particular, the epidemiological impact of provisioning could be driven in opposite directions, depending on which host pathways (contact rate, susceptibility or host demography) are most altered by the addition of resources to the environment. Broadly, these responses were qualitatively consistent across all parasite types, emphasising the importance of identifying general trade-offs between provisioning-altered parameters. Despite the qualitative consistency in responses to provisioning across parasite types, we predicted notable quantitative differences between parasites, with directly transmitted parasites (those conforming to SIR and SIS frameworks) predicted to show the strongest responses to provisioning among those examined, whereas the vector-borne parasites showed negligible responses to provisioning. As such, these analyses suggest that different parasites may show different scales of response to the same provisioning scenario, even within the same host population. This highlights the importance of knowing key aspects of host-parasite biology, to understand and predict epidemiological responses to provisioning for any specific host-parasite system.

Longitudinal deep sequencing informs vector selection and future deployment strategies for transmissible vaccines

Vaccination is a powerful tool in combating infectious diseases of humans and companion animals. In most wildlife, including reservoirs of emerging human diseases, achieving sufficient vaccine coverage to mitigate disease burdens remains logistically unattainable. Virally vectored "transmissible" vaccines that deliberately spread among hosts are a potentially transformative, but still theoretical, solution to the challenge of immunising inaccessible wildlife. Progress towards real-world application is frustrated by the absence of frameworks to guide vector selection and vaccine deployment prior to major in vitro and in vivo investments in vaccine engineering and testing. Here, we performed deep sequencing on field-collected samples of Desmodus rotundus betaherpesvirus (DrBHV), a candidate vector for a transmissible vaccine targeting vampire bat-transmitted rabies. We discovered 11 strains of DrBHV that varied in prevalence and geographic distribution across Peru. The phylogeographic structure of DrBHV strains was predictable from both host genetics and landscape topology, informing long-term DrBHV-vectored vaccine deployment strategies and identifying geographic areas for field trials where vaccine spread would be naturally contained. Multistrain infections were observed in 79% of infected bats. Resampling of marked individuals over 4 years showed within-host persistence kinetics characteristic of latency and reactivation, properties that might boost individual immunity and lead to sporadic vaccine transmission over the lifetime of the host. Further, strain acquisitions by already infected individuals implied that preexisting immunity and strain competition are unlikely to inhibit vaccine spread. Our results support the development of a transmissible vaccine targeting a major source of human and animal rabies in Latin America and show how genomics can enlighten vector selection and deployment strategies for transmissible vaccines.

Public Health Policy Pillars for the Sustainable Elimination of Zoonotic Schistosomiasis

Schistosomiasis is a parasitic disease acquired through contact with contaminated freshwater. The definitive hosts are terrestrial mammals, including humans, with some Schistosoma species crossing the animal-human boundary through zoonotic transmission. An estimated 12 million people live at risk of zoonotic schistosomiasis caused by Schistosoma japonicum and Schistosoma mekongi, largely in the World Health Organization’s Western Pacific Region and in Indonesia. Mathematical models have played a vital role in our understanding of the biology, transmission, and impact of intervention strategies, however, these have mostly focused on non-zoonotic Schistosoma species. Whilst these non-zoonotic-based models capture some aspects of zoonotic schistosomiasis transmission dynamics, the commonly-used frameworks are yet to adequately capture the complex epi-ecology of multi-host zoonotic transmission. However, overcoming these knowledge gaps goes beyond transmission dynamics modelling. To improve model utility and enhance zoonotic schistosomiasis control programmes, we highlight three pillars that we believe are vital to sustainable interventions at the implementation (community) and policy-level, and discuss the pillars in the context of a One-Health approach, recognising the interconnection between humans, animals and their shared environment. These pillars are: (1) human and animal epi-ecological understanding; (2) economic considerations (such as treatment costs and animal losses); and (3) sociological understanding, including inter- and intra-human and animal interactions. These pillars must be built on a strong foundation of trust, support and commitment of stakeholders and involved institutions.

Social networks strongly predict the gut microbiota of wild mice

The mammalian gut teems with microbes, yet how hosts acquire these symbionts remains poorly understood. Research in primates suggests that microbes can be picked up via social contact, but the role of social interactions in non-group-living species remains underexplored. Here, we use a passive tracking system to collect high resolution spatiotemporal activity data from wild mice (Apodemus sylvaticus). Social network analysis revealed social association strength to be the strongest predictor of microbiota similarity among individuals, controlling for factors including spatial proximity and kinship, which had far smaller or nonsignificant effects. This social effect was limited to interactions involving males (male-male and male-female), implicating sex-dependent behaviours as driving processes. Social network position also predicted microbiota richness, with well-connected individuals having the most diverse microbiotas. Overall, these findings suggest social contact provides a key transmission pathway for gut symbionts even in relatively asocial mammals, that strongly shapes the adult gut microbiota. This work underlines the potential for individuals to pick up beneficial symbionts as well as pathogens from social interactions.