Dr. Michael Vuolo, Department of Sociology
Rank at time of award: Associate Professor
Abstract
This aim of this research is to examine the effect of disasters on fatal and nonfatal drug overdoses. There are compelling competing hypotheses. On one hand, disasters could hinder access to drugs, both due to disruptions to illicit markets and prescription outlets, and result in lower overdoses. On the other hand, as a “disease of despair,” drug overdoses might increase in response to the ensuing hardships following a disaster. We will construct a new county-level database of disasters using the FEMA county-level official declaration of disasters, which contains all disaster declarations back to 1964 by county. This database defines the timing, duration, and type of disasters (e.g., hurricane, fire, flood, and pandemics, including Covid-19), as well as cost figures that address the scale of the disaster. We will combine these data with CDC restricted access multiple cause of death data dating back to 1999, which identify deaths due to drug overdoses, and emergency room admission data from the CDC National Syndromic Surveillance Program (with coverage for 73% of EDs). Using fixed-effects panel modeling of counts adjusting for population, we will determine how disasters generally, as well as those of different types and magnitude, affect overdoses in the months following the event, with special attention to both possible lags and spillover effects to spatially proximate unaffected counties. The seed grant period would allow for a feasibility test in terms of creation of the disaster database and modeling approaches, which can be used as preliminary data for an R01. The eventual grant application would also produce a unique disaster database that will be publicly available, as well as potentially allow us to test for the effects of the Covid-19 pandemic as mortality data catch up. We will also test for inequalities by age, race, and education, both as measured at the county level and individual level. Ultimately, the results would inform public health policy by determining what resources need to be deployed in a time of disaster, when overdoses often become overshadowed by the event itself.