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1. Modeling and forecasting age-specific drug overdose mortality in the United States

   https://doi.org/10.1140/epjs/s11734-023-00801-z  

   Böttcher, Lucas; Chou, Tom; D’Orsogna, Maria R. (April 2023, The European Physical Journal Special Topics)

   Abstract Drug overdose deaths continue to increase in the United States for all major drug categories. Over the past two decades the total number of overdose fatalities has increased more than fivefold; since 2013 the surge in overdose rates is primarily driven by fentanyl and methamphetamines. Different drug categories and factors such as age, gender, and ethnicity are associated with different overdose mortality characteristics that may also change in time. For example, the average age at death from a drug overdose has decreased from 1940 to 1990 while the overall mortality rate has steadily increased. To provide insight into the population-level dynamics of drug overdose mortality, we develop an age-structured model for drug addiction. Using an augmented ensemble Kalman filter (EnKF), we show through a simple example how our model can be combined with synthetic observation data to estimate mortality rate and an age-distribution parameter. Finally, we use an EnKF to combine our model with observation data on overdose fatalities in the United States from 1999 to 2020 to forecast the evolution of overdose trends and estimate model parameters. 

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2. Child Overdoses Amid the Deaths-of-Despair Epidemic: Racial and Ethnic Differences in Intergenerational and Network Diffusion

   Corina Graif, Christopher Seto (April 2022, Annual Meeting of the Population Association of America)

   Since the early 2000s, contributors to the deaths-of-despair epidemic such as alcohol and drug related deaths have more than doubled. Evidence of the role of patient networks in the diffusion of prescription behaviors among physicians and of intra-household diffusion of opioids use contribute to important new questions about the population level effects of workplace- and intergenerational networks. This study responds to this need by expanding the focus from households and opioids overdose risk to examine the role of intergenerational and commuting networks in the diffusion of overdose risk from alcohol and drugs more generally among children. Analyses using negative binomial regression combined with computational statistics approaches such as cross-validation and permutation indicated that exposures to extra-local network overdose risks were associated with local adult- and child overdose deaths. These associations remained significant after controlling for multiple socioeconomic and demographic factors. The results showed that the link between network overdose risk and local child overdose deaths was accounted for in large part by intergenerational effects. Above and beyond intergenerational and spatial diffusion, network effects remained significant for Black children. High concentrations of other white residents protected white children against overdose risk but none of the minority groups. In turn, higher concentration of minority residents protected Black and Hispanic children. Higher population density increased the risk of overdose deaths among adults of all racial and ethnic groups, consistent with expectations of social and economic strain. However, it decreased the risk among children, consistent with social control expectations. Implications for future research and policy are discussed. 

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

   https://doi.org/10.1093/pnasnexus/pgae050  

   Böttcher, Lucas; Chou, Tom; D’Orsogna, Maria R (February 2024, PNAS Nexus)

   Galea, Sandro (Ed.)

   Abstract The drug-overdose crisis in the United States continues to intensify. Fatalities have increased 5-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 interventions and efficiently delivering treatment is forecasting age-specific overdose patterns at the local level. To address this need, 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. 

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4. Mortality From Forces of Nature Among Older Adults by Race/Ethnicity and Gender

   https://doi.org/10.1177/0733464820954676  

   Adams, Rachel M.; Evans, Candace M.; Mathews, Mason Clay; Wolkin, Amy; Peek, Lori (January 2020, Journal of Applied Gerontology)

   null (Ed.)

   Older adults are especially vulnerable to disasters due to high rates of chronic illness, disability, and social isolation. Limited research examines how gender, race/ethnicity, and forces of nature—defined here as different types of natural hazards, such as storms and earthquakes—intersect to shape older adults’ disaster-related mortality risk. We compare mortality rates among older adults (60+ years) in the United States across gender, race/ethnicity, and hazard type using the Centers for Disease Control and Prevention’s Wonder database. Our results demonstrate that older adult males have higher mortality rates than females. American Indian/Alaska Native (AI/AN) males have the highest mortality and are particularly impacted by excessive cold. Mortality is also high among Black males, especially due to cataclysmic storms. To address disparities, messaging and programs targeting the dangers of excessive cold should be emphasized for AI/AN older adult males, whereas efforts to reduce harm from cataclysmic storms should target Black older adult males. 

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5. Spatiotemporal Analysis of Fentanyl-Associated Overdose Deaths in Chicago, IL, USA

   https://doi.org/10.1007/s11524-025-00986-9  

   Kang, Hyojung; Janakos, Kaylee; Varga, Csaba (June 2025, Journal of Urban Health)

   Abstract Overdose deaths involving fentanyl represent a major public health crisis in the USA. This study investigates the spatiotemporal dynamics of fentanyl-involved deaths before, during, and after the COVID-19 pandemic and examines how sociodemographic factors influence these deaths across geographic regions. Using a retrospective ecological approach, we analyzed data on ZIP code-level fentanyl-related deaths in Cook County, IL, between 2018 and 2023, obtained from the Medical Examiner’s Office and linked with sociodemographic data from the American Community Survey. We first mapped area-level death rates to assess their distribution and then conducted global and local clustering analyses to identify spatial autocorrelations and the locations of high- or low-death-rate areas. A geographically weighted Poisson regression (GWPR) model evaluated the associations between area-level fentanyl-related death rates and the area-level proportion of young adults, males, and individuals with at least a college degree, disability rate, and poverty rate. Spatial analyses found stronger spatial autocorrelations during (2020–2021) and after (2022–2023) the pandemic. Initially, high death rates were concentrated in the downtown area of Chicago, and they expanded to the surrounding areas during and after the pandemic. The GWPR model revealed that an increase in the area-level proportions of poverty, disability, and young adult residents increased the fentanyl-related death rates in most of the areas. Our findings highlight the urgent need to address the evolving dynamics of fentanyl-related overdoses through tailored public health interventions that account for the unique socioeconomic determinants of different regions. Importantly, a comprehensive approach to addressing differences in overdose death rates and their risk factors will be crucial to mitigating this public health crisis. 

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