The discovery of viruses similar to SARS-CoV-2 in horseshoe bats has emphasized the importance of identifying sources of zoonotic pathogens in wildlife. Identifying which animals are hosts for these pathogens is essential to predicting when and where disease spillover from these animals into human populations will most likely occur.
It is well-established that most infectious diseases, specifically viruses, originated in wildlife populations. However, a lack of knowledge about the number of viruses that exist globally remains. Improvements in epidemiological modeling and a growing pool of host-virus association data have enhanced the ability of scientists to predict which animals are most likely to host viruses and prioritize field sampling.
In order to improve the predictive methodology of wildlife pathogens, a better understanding of infection dynamics and epidemiological patterns is necessary. An important component of predicting spillover is understanding the immunology of potential animal hosts, since immune response to a pathogen impacts susceptibility to infection, the ability to tolerate the infection (the severity of the impact of the health of the host), and the likelihood of spreading the pathogen.
CEID’s Daniel Becker worked with a team to examine ways to improve predictive spillover methods. The team proposed integration between wildlife field studies and molecular analysis of pathogens and immunology to achieve these predictive goals. Combining these approaches would be especially beneficial for species such as bats, which are hosts for a variety of diseases, since bats typically have high rates of infection tolerance, a low probability of mortality from disease, and are likely to have chronic infections. These host traits allow bats to carry viruses that would be lethal for other mammal species.
The team proposes that improved integration between molecular and field studies will provide insight into the relationship between zoonotic pathogens and reservoir hosts. Field studies can highlight which host species should be prioritized for further study and molecular analysis. A collaborative initiative between these two investigative methods will enhance the ability to predict spillover risk across a variety of systems, including bat viruses, by providing information on the population dynamics and unique traits that drive initial infection in host species.
Moreover, field studies can identify intrinsic or extrinsic stressors that increase susceptibility of infection, pathogen replication, and shedding (sharing of viral material). Once hypotheses are derived from field data regarding pathogen circulation in hosts, molecular investigations can experimentally assess these hypotheses. For example, stressors of varying intensity could be mimicked in cellular experiments to measure changes in immunity and immune response. These results can be measured against immune expression and patterns from field data. Molecular mechanisms of transmission and immunity can also be incorporated into predictive models to simulate interventions, examine different transmission circumstances, and forecast infection prevalence in reservoir hosts. For this reason, the research team encourages interdisciplinary collaboration between evolutionary biologists, immunologists, virologists, microbiologists, and ecologists to establish integration between wildlife field studies and molecular analysis.
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By: Brenna Daly