Phylogenetic modeling of viral transmission dynamics at the human-wildlife interface in Uganda
- Funded by National Institutes of Health (NIH)
- Total publications:0 publications
Grant number: 5R01TW012704-02
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Key facts
Disease
COVID-19, Disease XStart & end year
20232028Known Financial Commitments (USD)
$667,311Funder
National Institutes of Health (NIH)Principal Investigator
ASSISTANT PROFESSOR Krista MilichResearch Location
United States of AmericaLead Research Institution
WASHINGTON UNIVERSITYResearch Priority Alignment
N/A
Research Category
Pathogen: natural history, transmission and diagnostics
Research Subcategory
Pathogen genomics, mutations and adaptations
Special Interest Tags
N/A
Study Type
Non-Clinical
Clinical Trial Details
N/A
Broad Policy Alignment
Pending
Age Group
Not Applicable
Vulnerable Population
Not applicable
Occupations of Interest
Not applicable
Abstract
Many infectious diseases that threaten humans originated among wildlife, yet we know relatively little about the real-world ecological conditions that enable spillover events. Despite its importance, identifying novel viral pathogens and characterizing their transmission dynamics remains difficult because it requires advanced genetic sequencing technologies, sampling wildlife likely to harbor pathogens of concern to humans, and sophisticated modeling techniques. We will study red colobus monkeys in Kibale National Park, Uganda, other nonhuman primates, and people who neighbor these wildlife populations to quantify transmission dynamics within and between species. Our team will collect behavioral ecology data on red colobus monkeys living in areas of the forest with different degrees of anthropogenic disturbance and conduct interviews with people living along the boundary of the park with varying exposure risks for zoonotic diseases. We will conduct repeat sampling of people and individually identifiable red colobus monkeys to analyze the gut virome, assess infection with gastrointestinal parasites known to infect both red colobus and people, discover previously undocumented viral diversity, detect the presence of novel pathogens of concern to humans, red colobus monkeys, and other primates (e.g. SARS-CoV-2), and track the evolutionary spread of detected pathogens. To model how red colobus-associated viruses spread, we will develop new phylodynamic models that allow longitudinal ecological and biogeographical data to structure time-heterogenous epidemiological event rates. We will also create, test, and distribute new software for simulation, Bayesian inference, and deep learning-based inference to model how infectious diseases spread in a wide variety of ecosystem-level transmission scenarios. Our proposed project will benefit public health and wildlife conservation and expand STEM training in the USA and Uganda. Working with Ugandan communities, we will co-create solutions to address risks for zoonotic disease transmission and test mitigation strategies to reduce transmission pathways.