# Systems modeling to address the social and biological drivers of disparities in infection and mortality from emerging infectious diseases

> **NIH NIH R01** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2022 · $679,307

## Abstract

Project Summary/Abstract
The distribution of disease and death from the COVID-19 pandemic has been grossly unequal in every
dimension. The vaccination campaign, throughout Winter and Spring 2021, has seen these inequities repeated.
Lower-risk, wealthier, and Whiter individuals have received earlier access to vaccination than their counterparts.
To those viewing the pandemic through the theoretical lens of social epidemiology and medical sociology, the
extremity and nature of these disparities was easily anticipated. However, the predictive and dynamic systems
models that have guided the domestic and global COVID-19 response have routinely ignored the social
determinants of infection and its outcomes. The objective of this application is to outline a multi-level approach
to infectious disease transmission modeling and data analysis that places the social determinants of exposure,
severe disease and mortality on an equal footing with the biological features of transmission and disease
progression. Our overarching goal is to develop a set of tools that will extend lessons from the COVID-19
pandemic to prevent similar disparities in future outbreaks, epidemics, and pandemics. The first aim of this
project will develop and analyze transmission models that integrate the joint social and biological drivers of
infection disparities. This proposed work will identify etiologic factors driving disparities in infection risk, and
propose policy-relevant alternative approaches to measuring infection disparities. Our second aim will evaluate
the sensitivity of population-based prospective and observational study designs to socioeconomic disparities in
infection risk and outcomes. We will use simulation studies with input parameters derived from the analysis of
detailed SARS-CoV-2 case data to understand the circumstances under which these study designs obscure key
dimensions of disparity. The third aim will assess long-term effects of vaccination policies, behavior, and
interventions on population-level infection inequalities. As the COVID-19 vaccination campaign has progressed
it has become clear that vaccine hesitancy and vaccine access are dual threats to achieving substantial levels
of population immunity. We will integrate survey data on vaccine hesitancy with data on healthcare access and
SARS-CoV-2 incidence to parameterize a spatial transmission model highlighting inequity in risks and avenues
for closing these gaps for COVID-19 and other vaccine preventable diseases. Taken together, the proposed
projects will lay the foundation systems modeling tools that can be used to promote equity in future epidemic
and pandemic responses.

## Key facts

- **NIH application ID:** 10415713
- **Project number:** 1R01MD017218-01
- **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR
- **Principal Investigator:** Jonathan L Zelner
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $679,307
- **Award type:** 1
- **Project period:** 2022-07-20 → 2027-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10415713

## Citation

> US National Institutes of Health, RePORTER application 10415713, Systems modeling to address the social and biological drivers of disparities in infection and mortality from emerging infectious diseases (1R01MD017218-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10415713. Licensed CC0.

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