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1. 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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2. Fentanyl-driven acceleration of racial, gender and geographical disparities in drug overdose deaths in the United States

   https://doi.org/10.1371/journal.pgph.0000769  

   D’Orsogna, Maria R.; Böttcher, Lucas; Chou, Tom (March 2023, PLOS Global Public Health)

   Nazif-Munoz, Jose Ignacio (Ed.)

   We examine trends in drug overdose deaths by race, gender, and geography in the United States during the period 2013–2020. Race and gender specific crude rates were extracted from the final National Vital Statistics System multiple cause-of-death mortality files for several jurisdictions and used to calculate the male-to-female ratios of crude rates between 2013 and 2020. We established 2013–2019 temporal trends for four major drug types: psychostimulants with addiction potential (T43.6, such as methamphetamines); heroin (T40.1); natural and semi-synthetic opioids (T40.2, such as those contained in prescription pain-killers); synthetic opioids (T40.4, such as fentanyl and its derivatives) through a quadratic regression and determined whether changes in the pandemic year 2020 were statistically significant. We also identified which race, gender and states were most impacted by drug overdose deaths. Nationwide, the year 2020 saw statistically significant increases in overdose deaths from all drug categories except heroin, surpassing predictions based on 2013–2019 trends. Crude rates for Black individuals of both genders surpassed those for White individuals for fentanyl and psychostimulants in 2018, creating a gap that widened through 2020. In some regions, mortality among White persons decreased while overdose deaths for Black persons kept rising. The largest 2020 mortality statistic is for Black males in the District of Columbia, with a record 134 overdose deaths per 100,000 due to fentanyl, 9.4 times more than the fatality rate among White males. Male overdose crude rates in 2020 remain larger than those of females for all drug categories except in Idaho, Utah and Arkansas where crude rates of overdose deaths by natural and semisynthetic opioids for females exceeded those of males. Drug prevention, mitigation and no-harm strategies should include racial, geographical and gender-specific efforts, to better identify and serve at-risk groups. 

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3. A Spatio-temporal Cluster-aware Supervised Learning Framework for Predicting County-level Drug Overdose Deaths

   https://doi.org/10.1609/aaai.v39i27.35015  

   Feng, Zixuan; Ye, Qing; Xie, Weijun; Chen, Qiushi (April 2025, Proceedings of the AAAI Conference on Artificial Intelligence)

   The soaring drug overdose crisis in the United States has claimed more than half a million lives in the past decade and remains a major public health threat. The ability to predict drug overdose deaths at the county level can help local communities develop action plans in response to emerging changes. Applying off-the-shelf machine learning algorithms for prediction can be challenging due to the heterogeneous risk profiles of the counties and suppressed data in common publicly available data sources. To fill these gaps, we develop a cluster-aware supervised learning (CASL) framework to enhance the prediction of county-level drug overdose deaths. This CASL model simultaneously clusters counties into groups based on geographical and socioeconomic characteristics and minimizes the loss function that accounts for suppressed values and cluster-specific regularization. Our computational study uses real-world data from 2010 to 2021, focusing on the ten states most severely impacted by the drug overdose crisis. The results demonstrate that our proposed CASL framework significantly outperforms state-of-the-art methods by achieving a superior balance in prediction accuracy for both unsuppressed and suppressed observations. The proposed model also identifies different clusters of counties, capturing heterogeneous patterns of overdose mortality among counties of diverse characteristics. 

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4. The US Mortality Crisis: An Examination of Non-Hispanic White Mortality and Morbidity in Yavapai County, Arizona

   https://doi.org/10.1007/s10900-019-00648-3  

   Parsons, Michelle Anne; Barger, Steven D. (March 2019, Journal of Community Health)

   Midlife non-Hispanic white mortality in the United States is rising, particularly in small metro and rural counties. This article responds to calls for county-level studies. We examine social determinants of morbidity and mortality among adult non-Hispanic whites in Yavapai County, Arizona, as part of an integrative study. We report overall mortality trends in Yavapai County using CDC Wonder data and then examine social determinants of reported physical health and mental distress in Yavapai County data using 6 years (2011–2016) of the Arizona Behavioral Risk Factor Surveillance System (BRFSS). The BRFSS includes 1,024 non-Hispanic white respondents aged 25–64. We also present data from the recently established Yavapai County Overdose Fatality Review Board (YCOFRB). Mortality trends indicate that suicide and drug and alcoholrelated mortality have all increased since 1999. These increases affect all 5-year age groups from 25 to 64 and both men and women. BRFSS data show that low education and unemployment, but not number of children or home ownership, are significantly associated with worse reported health and frequent mental distress in multivariate analyses. The YCOFRB point to the importance of homelessness and mental health. The mortality crisis in Yavapai County is not restricted to midlife or to drug-related deaths. The unemployed and those with low levels of education are particularly at risk. There is a need for integrative approaches that use local data to elucidate social determinants of morbidity and mortality and to reveal structural determinants. 

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5. Health Promotion and Racial Disparity in COVID-19 Mortality Among African American Populations

   https://doi.org/10.29011/2690-9480.100168  

   Yedjou, CG; Webster, S; Osborne, D; Liu, J; Balagurunathan, Y; Odewuni, C; Latinwo, L; Ngnepiepa, P; Alo, R; Tchounwou, PB (September 2023, Reports on Global Health Research)

   COVID-19, known as Coronavirus Disease 2019, is a major health issue resulting from novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Its emergence has posed a significant menace to the global medical community and healthcare system across the world. Notably, on December 12, 2020, the Food and Drug Administration (FDA) approved the utilization of the Pfizer and Moderna COVID-19 vaccines. As of July 31, 2022, the United Stated has witnessed over 91.3 million cases of COVID-19 and nearly 1.03 million fatalities. An intriguing observation is the recent reduction in the mortality rate of COVID-19, attributed to an augmented focus on early detection, comprehensive screening, and widespread vaccination. Despite this positive trend in some demographics, it is noteworthy that the overall incidence rates of COVID-19 among African American and Hispanic populations have continued to escalate, even as mortality rates have decreased. Therefore, the objective of this research study is to present an overview of COVID-19, spotlighting the disparities among different racial and ethnic groups. It also delves into the management of COVID-19 within the minority populations. To reach our research objective, we used a publicly available COVID-19 dataset from kaggle: https://www.kaggle.com/datasets/paultimothymooney/covid19-casesand- deaths-by-race. In addition, we obtained COVID-19 datasets from 10 different states with the highest proportion of African American populations. Many considerable strikes have been made in COVID-19. However, success rate of treatment in the African American population remains relatively limited when compared to other ethnic groups. Hence, there arises a pressing need for novel strategies and innovative approaches to not only encourage prevention measures against COVID-19, but also to increase survival rates, diminish mortality rates, and ultimately improve the health outcomes of ethnic and racial minorities. 

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