Forecasting drug overdose mortality by age in the United States at the national and county levels

TL;DR

This paper presents a novel forecasting method that combines observational data with an age-structured model to predict drug overdose mortality patterns at national and local levels in the US.

Contribution

It introduces a new approach for forecasting age-specific overdose mortality by integrating data with an age-structured epidemiological model.

Findings

Accurately forecasts overdose mortality trends at national and local levels.

Provides estimates of age-specific addiction and mortality rates.

Demonstrates applicability to multiple geographic areas.

Abstract

The drug overdose crisis in the United States continues to intensify. Fatalities have increased five-fold since 1999 reaching a record high of 108,000 deaths in 2021. The epidemic has unfolded through distinct waves of different drug types, uniquely impacting various age, gender, race and ethnic groups in specific geographical areas. One major challenge in designing effective interventions is the forecasting of age-specific overdose patterns at the local level so that prevention and preparedness can be effectively delivered. We develop a forecasting method that assimilates observational data obtained from the CDC WONDER database with an age-structured model of addiction and overdose mortality. We apply our method nationwide and to three select areas: Los Angeles County, Cook County and the five boroughs of New York City, providing forecasts of drug-overdose mortality and estimates of relevant epidemiological quantities, such as mortality and age-specific addiction rates.