Using virus genomes and patient data to map how outbreaks spread

Statistical Innovation to Integrate Sequences and Phenotypes for Scalable Phylodynamic Inference

NIH-funded research University of California Los Angeles · NIH-11291614

This project creates new computer methods that link virus genetic sequences with health and location information to better track how fast-changing viruses spread and help public health teams respond.

Quick facts

Grant typeR01 grant
Study typeNIH-funded research
Funding institutionUniversity of California Los Angeles NIH-funded
Lab location1 site (Los Angeles, United States)
Project IDNIH-11291614 on NIH RePORTER

What this research studies

This project builds statistical methods and software that connect virus genome sequences with clinical, geographic, and other measurements to map how infections start and move. The team will use Bayesian models and scalable algorithms to handle tens of thousands of genomes and patient or environmental data from outbreaks like COVID-19, influenza, dengue, Ebola, mpox, and yellow fever. For patients, that means researchers can more clearly identify transmission chains, where infections are spreading, and which factors change risk. The tools and software will be shared with public-health labs so findings can help speed up and target epidemic responses.

Who could benefit from this research

Good fit: People recently infected with viruses such as SARS-CoV-2, influenza, dengue, mpox, HIV, hepatitis B, or yellow fever who can provide diagnostic samples and basic clinical or location information could be included in the data used by this project.

Not a fit: People without infectious diseases or those not participating in surveillance or sample-sharing networks are unlikely to receive direct benefit from this work.

Why it matters

Potential benefit: If successful, these tools could enable faster, more targeted public-health actions that reduce infections and improve patient outcomes.

How similar studies have performed: Genomic surveillance and phylodynamic tools have already helped guide outbreak responses (notably during SARS-CoV-2), but this project aims to scale and improve those approaches.

Where this research is happening

Los Angeles, United States

Researchers

About this research

  1. This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
  2. Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
  3. For full project details, budget, and progress reports, visit the official NIH RePORTER page below.
Last reviewed 2026-06-15 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.