# Optimizing Efforts to Restore Psychiatric and Social Function After a Major Hurricane

> **NIH NIH R01** · BOSTON UNIVERSITY MEDICAL CAMPUS · 2022 · $576,987

## Abstract

PROJECT SUMMARY/ABSTRACT
The 2017 fall Atlantic hurricane season, including Hurricane Harvey, was the most extreme in recorded history,
and, in light of global climate change, a possible harbinger of future seasons to come. It is increasingly critical
to understand how potentially modifiable pre-, peri-, and post-hurricane factors shape the long-term mental
health of affected populations, so that we may optimize interventions to limit the ultimate impact of such
storms. Individual-level experiences during and after hurricanes – such as displacement and job loss – shape
post-hurricane mental health, but a better understanding of how these individual-level events interact with
community-level factors to produce outcomes could help us to further tailor treatment approaches for
individuals and communities in disaster settings. Critically, very little is known about the effects of hurricane
relief efforts – including housing and income assistance – on longer-term outcomes. We will address these
gaps using a pre-, peri-, and post-hurricane framework to organize the influences of exposure characteristics
and sequencing on mental health outcomes. In our first aim, we will characterize how interactions among pre-
hurricane capacities (e.g., social capital) and vulnerabilities (e.g., poor housing quality) as well as peri-
hurricane stressors (e.g., power outages) and protectors (e.g., efficient government responses) – at both
individual and community levels – shape post-hurricane depression and posttraumatic stress disorder. In our
second aim, we will identify and test the effects of hypothetical interventions on post-hurricane mental health
through discrete stochastic simulations, under varying profiles of pre-, peri-, and post-hurricane capacities,
vulnerabilities, stressors, and protectors derived from aim 1. The primary goal of this proposed project is to
build on and validate prior simulation analyses to create a set of first-in-class simulation models to identify
optimal approaches to mental health services following natural disasters, and to project their public health
impact. To achieve these aims, we will geographically sample and survey individuals who lived in Hurricane
Harvey-affected areas of Texas about their experiences, incorporating a recall validation subsample with
previously collected pre-hurricane data. We will also capitalize on archival data by collecting variables at the
community level such as income inequality measures, quality of built environment, and hurricane exposure
indicators, to perform multilevel analyses across varying geographic levels. Finally, we will leverage data from
our de-novo survey to create synthetic populations with varying combinations of pre-, peri-, and post-event
factors, and use data from an ongoing post-hurricane randomized control trial to calibrate and validate
simulation models. Such in-silico experiments will shed light on the effectiveness of candidate interventions
and help us to understand their ...

## Key facts

- **NIH application ID:** 10364641
- **Project number:** 5R01MH119193-03
- **Recipient organization:** BOSTON UNIVERSITY MEDICAL CAMPUS
- **Principal Investigator:** SANDRO GALEA
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $576,987
- **Award type:** 5
- **Project period:** 2020-04-10 → 2024-02-29

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10364641

## Citation

> US National Institutes of Health, RePORTER application 10364641, Optimizing Efforts to Restore Psychiatric and Social Function After a Major Hurricane (5R01MH119193-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10364641. Licensed CC0.

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