# Health Decision-Making in the Aftermath of Disaster

> **NIH NIH R01** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2021 · $661,298

## Abstract

Abstract
How do disasters affect health decision-making? Do disaster impacts operate, at least in part, through changes
in economic preferences and psychological factors? Can public health programs help shield communities from
the impacts of disasters? We pursue these questions by studying a major disaster that struck in the midst of a
randomized evaluation we are conducting of a community-level public health program in Mozambique. Prior to
the disaster, in 2017-2018, this study team had administered a baseline survey of approximately 4,500
households, and had facilitated random assignment of the program, Força à Comunidade e Crianças (FCC,
“Strengthening Communities and Children”). Out of 76 communities, half were assigned to the treatment
group, receiving the FCC program; the remainder serve as the control group. In March 2019, Cyclone Idai, the
most destructive cyclone ever recorded in Africa, struck our study areas. The FCC program implements an
interrelated set of health, educational, and economic interventions. Households are connected to community
support networks, encouraged to visit and use local public health clinics, provided with information to improve
health decision-making, and participate in microfinance programs. We first estimate human and economic
losses, as well as impacts on risky sexual behaviors (including transactional sex), sexually transmitted infection
(STI) testing, STI incidence, and COVID-19-related outcomes. We estimate impacts in a survey sample
determined prior to the disaster, and are thus able to deal with selection biases (e.g., differential sample
inclusion based on disaster exposure) that otherwise compromise treatment effect estimates. Impact estimates
will exploit heterogeneity in hurricane exposure across study communities. Then, we will study impacts on
individual preferences and psychological factors that may mediate the effects of disasters on health decision-
making. Examining motivated belief biases (in this context, over-optimism maintained by health risk denial) is
particularly novel; it is a new behavioral economics frontier but has not been empirically evaluated in health-
related contexts. Our measurement tools are piloted, refined, and ready for large-scale implementation. Finally,
we will assess whether the FCC program helps shield communities from the negative impacts of disaster
exposure on risky sexual behaviors; STI testing, prevalence, and treatment; and on COVID-19-related
outcomes. Causal inference will rely on the pre-disaster random assignment of the FCC program. We will also
examine mechanisms through which the program achieves its protective effects. This project's findings can
help guide the design of public health programs in the future. Insights into the economics and psychology of
post-disaster decision-making can suggest novel interventions to mitigate disaster-induced deterioration of
health decisions. Evidence on whether and how public health programs shield people from disaste...

## Key facts

- **NIH application ID:** 10206810
- **Project number:** 1R01HD102382-01A1
- **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR
- **Principal Investigator:** Dean Yang
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $661,298
- **Award type:** 1
- **Project period:** 2021-05-20 → 2026-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10206810

## Citation

> US National Institutes of Health, RePORTER application 10206810, Health Decision-Making in the Aftermath of Disaster (1R01HD102382-01A1). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10206810. Licensed CC0.

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