Sep 2023

  • We’re pleased to announce that our project is being funded for 5 years by the NSF/NIH Ecology and Evolution of Infectious Diseases (EEID) program! More news to come.

Jul 2023

  • Ammon and Michael presented their work on deep learning for viral phylogeography for Phyloseminar [link].

Jun 2023

  • We have our first batch of samples! Giovanna is back from Uganda and working with the Milich team to process GPS and behavioral data.
  • Ammon Thompson and Michael from the Landis Lab presented research on deep learning approaches for viral phylogeography at the Evolution conference in Albuquerque.

Mar 2023

  • Dr. Giovanna Bonadonna from the Milich Lab is now on site in Kibale to establish connections with the community and to begin fecal virome sampling.

Feb 2023

  • New preprint [link] from the Landis Lab showing that likelihood-free deep learning methods estimate phylogenetic rates of viral spread as well classical likelihood-based methods, but in milliseconds instead of hours.

Nov 2022

Oct 2022


The spread of new infectious diseases, climate change, and biodiversity loss are three of the most urgent problems facing society today and they are intricately connected. Exploiting the environment for resources contributes to climate change and biodiversity loss, which both fuel increases in emerging infectious diseases. Many infectious diseases that now threaten humans originated among wildlife, yet we know relatively little about wildlife transmission dynamics and ways to prevent spillover events. Viruses constitute a significant portion of such infectious diseases of global concern, including SARS-CoV-2, Ebola, monkeypox, and Zika. Identifying novel viral pathogens and understanding their transmission dynamics requires advanced genetic sequencing technologies, access to samples from species likely to harbor pathogens of concern to humans, and sophisticated modeling techniques.

Schematic of project framework, activities, and objectives.

Our project focuses on the human-wildlife interface at one site in Uganda, though our innovative framework will inform similar projects wherever humans and wildlife are in close contact. We will apply community-driven methods that meaningfully involve local residents in the research and implementation of strategies to reduce zoonotic disease transmission. We will generate data on known and novel pathogens to reconstruct viral transmission dynamics in wild nonhuman primates and neighboring human communities. Our project will also design and deploy new statistical tools to identify ecosystem-level scenarios that are likely to promote the spread of infectious diseases within and between species. Based on our results, we will use a data-driven and community-centered approach to implement strategies to reduce the opportunities for spillover events, ultimately striving to predict and prevent future pandemics.


Our team is supported by seed funds awarded by the Incubator for Transdisciplinary Futures, a program created through the Arts & Sciences Strategic Plan to stimulate new cross-departmental collaborations throughout Washington University.

Krista Milich
Assistant professor of Anthropology
Washington University
Innocent Rwego
Senior lecturer of Veterinary Medicine
Makerere University
Michael Landis
Assistant professor of Biology
Washington University
Dave Wang
Professor of Pathology & Immunology
Washington University