# COVID-19 transmission in Alaska: geographic and genomic modeling

> **NIH NIH P20** · UNIVERSITY OF ALASKA FAIRBANKS · 2022 · $126,175

## Abstract

PROJECT SUMMARY
Effective modeling of epidemic transmission depends on both a mathematical description of the most important
aspects of disease transmission and progression, and estimation of parameters from data. Collection of genetic
sequences of SARS-CoV-2 samples throughout the COVID-19 pandemic has produced an extensive new data
source to supplement more traditional public health ones. The geographical population structure in Alaska,
characterized by subpopulations with well-defined interconnections, offers a unique opportunity to use such data
to develop new models and parameter estimation methods. Moreover, in addition to geographic heterogeneity,
the progression of pandemic has involved changes in prevalence of coronavirus variants as well as mitigation
strategies, so that parameters have a temporal dependence as well.
This project leverages public health and sequencing data from the coronavirus pandemic through three main
modeling thrusts. A statistical model of variant spread, which captures both geographic structure and changing
variant proportions will be developed and applied to the Alaskan genomic data set. Estimation of transmission
rates in and between regions using phylodynamic approaches will be investigated. This includes development
of a new statistical approach for rapid estimation of parameters that change through time, as well as a focused
effort to study transmission patterns between subpopulations. Finally, a traditional compartment model of
COVID-19 in Alaska will be developed, which captures the key geographic features affecting disease dynamics
in the state. While initially fitted using public health data such as hospital incidence rates and testing results, it
will then be modified to better reflect insights and estimates emerging from the first two thrusts. A goal is to
promote and demonstrate improved predictive ability from incorporation of sequencing data into the modeling
pipeline.
Although the project focuses on modeling and data from Alaska, its methods and conclusions will be more
broadly applicable. Areas exhibiting similar population structure of an urban/suburban core and smaller, largely
rural regions with well-defined interconnections, are common in less developed countries, but they may lack
sufficient data for effective modeling. Insights into disease dynamics arising from this structure will also improve
understanding of aspects of epidemic progression in regions with more diffuse interconnections.

## Key facts

- **NIH application ID:** 10539679
- **Project number:** 3P20GM103395-21S4
- **Recipient organization:** UNIVERSITY OF ALASKA FAIRBANKS
- **Principal Investigator:** BRIAN M BARNES
- **Activity code:** P20 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $126,175
- **Award type:** 3
- **Project period:** 2001-09-24 → 2024-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10539679

## Citation

> US National Institutes of Health, RePORTER application 10539679, COVID-19 transmission in Alaska: geographic and genomic modeling (3P20GM103395-21S4). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10539679. Licensed CC0.

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