# Spatio-temporal Methods for Surveillance of the Opioid Syndemic

> **NIH NIH R01** · WAKE FOREST UNIVERSITY HEALTH SCIENCES · 2024 · $371,436

## Abstract

PROJECT SUMMARY/ABSTRACT
The United States is in the midst of a public health crisis due to the ongoing opioid syndemic. The opioid syndemic
consists of the inter-related epidemics of opioid misuse, fatal and non-fatal overdose, human immunodeficiency
virus (HIV), and hepatitis C (HCV). The consequences of opioid misuse are particularly severe in Ohio as the
state has experienced overdose rates that are double the national average as well as elevated risk for epidemic
levels of HIV and HCV. A key need for addressing the syndemic is to improve surveillance science methodology
to better measure community-levels of opioid misuse and be able to identify and target areas of emerging risk
with resources. However, no single data source currently observed by the public health surveillance system fully
characterizes opioid misuse at relevant spatial and temporal supports. Novel statistical methods are needed to
better leverage existing data and appropriately integrate multiple imperfect surveillance outcomes across different
spatial scales to comprehensively estimate levels of opioid misuse and model the syndemic over space and time.
Doing so will enable estimation and inference at small areas that are relevant to local policymakers and public
health officials while accounting for measurement error. There are several methodological challenges that will
be overcome with achievement of the following aims: 1) develop and assess a spatio-temporal factor model
that estimates a factor that can be meaningfully interpreted longitudinally, 2) develop and assess a spatial factor
model that allows for outcomes to have different spatial supports, and 3) develop and assess a multivariate spatio-
temporal model to estimate areal prevalence of latent opioid misuse. Successful development of a comprehensive
model of the opioid syndemic will advance surveillance science and will produce estimates of opioid misuse
that advance epidemiological understanding and provide valuable information to policymakers and public health
officials.

## Key facts

- **NIH application ID:** 10863902
- **Project number:** 5R01DA052214-04
- **Recipient organization:** WAKE FOREST UNIVERSITY HEALTH SCIENCES
- **Principal Investigator:** Staci Hepler
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $371,436
- **Award type:** 5
- **Project period:** 2021-09-01 → 2025-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10863902

## Citation

> US National Institutes of Health, RePORTER application 10863902, Spatio-temporal Methods for Surveillance of the Opioid Syndemic (5R01DA052214-04). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10863902. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*