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Principal Investigator: Krista Milich
Organization: WASHINGTON UNIVERSITY
Fiscal Year: 2024
Award: $667,311
Funding agency: John E. Fogarty International Center for Advanced Study in the Health Sciences
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.
Terms: <2019 novel corona virus><2019 novel coronavirus><2019-nCoV><Address><Area><Associated Viruses><Bayesian Analysis><Bayesian computation><Bayesian inference><Bayesian network analysis><Bayesian spatial analysis><Bayesian statistical analysis><Bayesian statistical inference><Bayesian statistics><Behavioral><Bionomics><COVID-19 virus><COVID19 virus><CoV-2><CoV2><Colobus><Colobus Genus><Colobus Monkey><Communicable Diseases><Communities><Data><Disease><Disorder><Ecologic Systems><Ecological Systems><Ecology><Ecosystem><Epidemiology><Event><Genetic><Human><Individual><Infection><Infectious Disease Pathway><Infectious Diseases><Infectious Disorder><Interview><Methods><Modeling><Modern Man><Parasites><Pathogen detection><Pathway interactions><Persons><Phylogenetic Analysis><Phylogenetics><Population><Primates><Primates Mammals><Public Health><Research><Risk><SARS corona virus 2><SARS-CO-V2><SARS-COVID-2><SARS-CoV-2><SARS-CoV2><SARS-associated corona virus 2><SARS-associated coronavirus 2><SARS-coronavirus-2><SARS-related corona virus 2><SARS-related coronavirus 2><SARSCoV2><Sampling><Satellite Viruses><Severe Acute Respiratory Coronavirus 2><Severe Acute Respiratory Distress Syndrome CoV 2><Severe Acute Respiratory Distress Syndrome Corona Virus 2><Severe Acute Respiratory Distress Syndrome Coronavirus 2><Severe Acute Respiratory Syndrome CoV 2><Severe Acute Respiratory Syndrome-associated coronavirus 2><Severe Acute Respiratory Syndrome-related coronavirus 2><Severe acute respiratory syndrome associated corona virus 2><Severe acute respiratory syndrome coronavirus 2><Severe acute respiratory syndrome related corona virus 2><Statistical Data Analyses><Statistical Data Analysis><Statistical Data Interpretation><Structure><Techniques><Technology><Testing><Time><Training><Transmission><Uganda><Viral><Viral Genome><Virus><Wuhan coronavirus><Zoonoses><Zoonotic><Zoonotic Infection><anthropogenesis><anthropogenic><communicable disease transmission><coronavirus disease 2019 virus><coronavirus disease-19 virus><deep learning><deep learning method><deep learning strategy><disease transmission><emerging pathogen><epidemiologic><epidemiological><forest><gastrointestinal><hCoV19><infectious disease model><infectious disease transmission><nCoV2><new pathogen><non-human primate><nonhuman primate><novel><novel pathogen><pathogen><pathogenic virus><pathway><simulation software><spillover event><statistical analysis><transmission process><viral microbiome><viral pathogen><viral transmission><virome><virus genome><virus pathogen><virus transmission>