# Modeling Excess Deaths After a Natural Disaster with Application to Hurricane Maria

## TL;DR

This paper develops two statistical models to estimate excess deaths caused by natural disasters, exemplified by Hurricane Maria, addressing challenges in indirect death attribution and data limitations.

## Contribution

It introduces a simple profile likelihood model and a flexible, covariate-inclusive model for more accurate excess death estimation during emergencies.

## Key findings

- Models provide confidence intervals for Hurricane Maria's death toll.
- Flexible model captures temporal variation and population displacement effects.
- Simple model allows estimation with minimal data.

## Abstract

Estimation of excess deaths due to a natural disaster is an important public health problem. The CDC provides guidelines to fill death certificates to help determine the death toll of such events. But, even when followed by medical examiners, the guidelines can not guarantee a precise calculation of excess deaths.%particularly due to the ambiguity of indirect deaths. We propose two models to estimate excess deaths due to an emergency. The first model is simple, permitting excess death estimation with little data through a profile likelihood method. The second model is more flexible, incorporating: temporal variation, covariates, and possible population displacement; while allowing inference on how the emergency's effect changes with time. The models are implemented to build confidence intervals estimating Hurricane Maria's death toll.