# Reducing Drug-Related Mortality Using Predictive Analytics: A Randomized, Statewide, Community Intervention Trial

> **NIH NIH R01** · BROWN UNIVERSITY · 2020 · $168,548

## Abstract

The COVID-19 pandemic is colliding with the ongoing drug overdose epidemic, a public health crisis that has
taken over 750,000 lives in the United States over the past two decades. The pandemic and associated
policy responses will have lasting impacts of the lives of people at risk for overdose. Moreover, the immediate
effects of the pandemic on access to overdose prevention and treatment resources, as well as fatal and
nonfatal overdose rates, are in need of urgent study. This research will determine how policies enacted as a
result of the COVID-19 pandemic response have affected both access to overdose prevention and treatment
resources, as well as rates of fatal and non-fatal overdoses in the community. The effect of acute changes on
COVID-19 related diagnoses, hospitalizations, and deaths on subsequent spikes in fatal and nonfatal
overdose, particularly in racial/ethnic and economically distressed communities, will also be examined.
Documenting these impacts will provide important insights into the types of health service measures that
need to be put in place during future disasters to avoid escalation of drug overdose risk. The study will take
place in Rhode Island, a state with the 4th highest COVID-10 diagnosis rate and the 7th highest COVIDassociated
mortality rates in the nation (as of May 18th, 2020). In Aim 1, we will determine how policies
enacted as part of the state’s COVID-19 pandemic response have influenced both access to and utilization of
harm reduction resources (e.g., naloxone) and engagement in substance use treatment, as well as rates of
fatal and non-fatal overdoses. In Aim 2, we hypothesize that various measures of COVID-19 disease burden
(e.g., diagnosis rates, hospitalizations) will predict subsequent spikes in fatal and non-fatal overdose, and that
these spikes will be particularly pronounced in economically distressed and racial/ethnic minority
communities. This work will help build an urgently needed evidence base to determine how best to effectively
manage the adverse effects of COVID-19 on the overdose epidemic, and to support addiction-related health
and social service systems during unanticipated public health crises in the future.

## Key facts

- **NIH application ID:** 10173211
- **Project number:** 3R01DA046620-02S1
- **Recipient organization:** BROWN UNIVERSITY
- **Principal Investigator:** Magdalena Cerda
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $168,548
- **Award type:** 3
- **Project period:** 2019-09-30 → 2024-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10173211

## Citation

> US National Institutes of Health, RePORTER application 10173211, Reducing Drug-Related Mortality Using Predictive Analytics: A Randomized, Statewide, Community Intervention Trial (3R01DA046620-02S1). Retrieved via AI Analytics 2026-06-01 from https://api.ai-analytics.org/grant/nih/10173211. Licensed CC0.

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