About

William Christopher Goedel is an Associate Professor of Epidemiology at the Brown University School of Public Health and serves as the Director of the Doctoral Program in Epidemiology. He is a social epidemiologist with significant methodological expertise in geographic information systems (GIS) to guide public health practice. His research employs spatial analytical techniques to quantify the burden of pressing public health challenges across neighborhoods in the United States, aiming to identify overburdened and underserved areas. His applied work often involves collaboration with the Rhode Island Department of Health and covers conditions such as asthma, cancer, COVID-19, drug overdose, and vaccine-preventable diseases. Dr. Goedel leads research in historical epidemiology, utilizing archival records to shed light on public health issues over the past 200 years, including studies on the 1918–1920 Great Influenza Epidemic in Providence. He is the inaugural recipient of the Faculty Fellowship in University History at the John Nicholas Brown Center for Advanced Study, where he researches the origins and development of public health education at Brown University. As an educator, he teaches courses on the epidemiology of public health history, fundamentals of epidemiology, and spatial analysis in public health. He also serves as the director of the doctoral program in epidemiology and has been recognized with the Dean’s Award for Excellence in Classroom Teaching. His scholarly interests include the implementation and evaluation of graduate admissions review processes and grading systems that value both accomplishments and potential for growth regardless of background.

Research topics

• Medicine
• Demography
• Internal medicine
• Sociology
• Virology
• Environmental health
• Medical emergency
• Political Science
• Gerontology
• Emergency medicine
• Social psychology
• Psychology
• Psychiatry
• Gender studies
• Family medicine
• Immunology

Selected publications

• Association of nonfatal overdose surveillance data with concurrent and future overdose deaths in Rhode Island

  American Journal of Epidemiology · 2026-01-26

  article

  Given substantial reporting delays in overdose deaths, state health departments increasingly use nonfatal overdose data to inform geographically targeted rapid overdose response efforts. We evaluated the extent to which nonfatal overdose events were associated with concurrent and future overdose deaths in Rhode Island. We aggregated nonfatal overdose data from emergency medical services records (2019-2023) and fatal overdose data from the State Unintentional Drug Overdose Reporting System (2020-2023) in 1-, 3-, and 6-month intervals at census block group and census tract levels. Rates of fatal overdose were estimated, relative to nonfatal overdose lagged by 0-12 months, using negative binomial regression, and relative to monthly spikes in nonfatal overdose burden, using zero-inflated Poisson regression. Estimation was implemented using integrated nested Laplace approximation. Each additional nonfatal overdose event per census block group was associated with fatal overdose rates that were 48% higher (95% credible interval, 1.37-1.59) than expected in concurrent months, with smaller associations at the census tract level, in wider time intervals, and when nonfatal overdose data were lagged. Spikes in nonfatal overdose activity were associated with elevated overdose mortality in concurrent periods with fine temporal and geographic granularity, but not in longer time frames and larger geographic areas.

  PublisherDOI

• Mapping mosquito diversity in Kenya correlating species distribution with malaria prevalence across varied climatic parameters

  Figshare · 2026-01-01

  otherOpen access

  Abstract Background Malaria is a major public health problem, with over half of the world’s population, primarily in sub-Saharan Africa, at risk. Climate change is already affecting the prevalence of malaria, in part by altering the distribution and density of mosquito vectors. This study assessed the relationship between climate variables and mosquito species distribution on malaria prevalence in Kenya from January 2019 to June 2021. Methods Data from 23 Kenyan counties were analyzed using mixed-effect regression, spatial analysis, correlation analysis, and the Least Absolute Shrinkage and Selection Operator (LASSO) to select variables. Results Malaria prevalence was highest in the Lake Endemic (19%), followed by the Coastal Endemic (5%), semi-arid seasonal (2%), and low-risk (0.9%) malaria epidemiologic zones in 2020. Mosquito species distribution varied, with distinct ecological preferences observed with Anopheles gambiae dominated coastal and semi-arid areas, while Anopheles funestus was highest in the highland and lake zones. Regression analysis indicated that a combination of environmental factors and public health interventions, including insecticide-treated nets (ITN) coverage, was an important predictor of malaria prevalence. However, the relationship between these factors and malaria prevalence varied across regions and time periods. Conclusion This study provides insights into the spatial dynamics of mosquito species and their distribution in relation to malaria epidemiological zones in Kenya, thereby informing targeted control strategies.

  PublisherDOI

• Additional file 1 of Mapping mosquito diversity in Kenya correlating species distribution with malaria prevalence across varied climatic parameters

  Open MIND · 2026-01-01

  article

  Supplementary material 1.

  DOI

• Mapping mosquito diversity in Kenya correlating species distribution with malaria prevalence across varied climatic parameters

  Malaria Journal · 2026-01-05

  articleOpen access

  BACKGROUND: Malaria is a major public health problem, with over half of the world's population, primarily in sub-Saharan Africa, at risk. Climate change is already affecting the prevalence of malaria, in part by altering the distribution and density of mosquito vectors. This study assessed the relationship between climate variables and mosquito species distribution on malaria prevalence in Kenya from January 2019 to June 2021. METHODS: Data from 23 Kenyan counties were analyzed using mixed-effect regression, spatial analysis, correlation analysis, and the Least Absolute Shrinkage and Selection Operator (LASSO) to select variables. RESULTS: Malaria prevalence was highest in the Lake Endemic (19%), followed by the Coastal Endemic (5%), semi-arid seasonal (2%), and low-risk (0.9%) malaria epidemiologic zones in 2020. Mosquito species distribution varied, with distinct ecological preferences observed with Anopheles gambiae dominated coastal and semi-arid areas, while Anopheles funestus was highest in the highland and lake zones. Regression analysis indicated that a combination of environmental factors and public health interventions, including insecticide-treated nets (ITN) coverage, was an important predictor of malaria prevalence. However, the relationship between these factors and malaria prevalence varied across regions and time periods. CONCLUSION: This study provides insights into the spatial dynamics of mosquito species and their distribution in relation to malaria epidemiological zones in Kenya, thereby informing targeted control strategies.

  PublisherDOI

• Mapping mosquito diversity in Kenya correlating species distribution with malaria prevalence across varied climatic parameters

  Figshare · 2026-01-01

  otherOpen access

  Abstract Background Malaria is a major public health problem, with over half of the world’s population, primarily in sub-Saharan Africa, at risk. Climate change is already affecting the prevalence of malaria, in part by altering the distribution and density of mosquito vectors. This study assessed the relationship between climate variables and mosquito species distribution on malaria prevalence in Kenya from January 2019 to June 2021. Methods Data from 23 Kenyan counties were analyzed using mixed-effect regression, spatial analysis, correlation analysis, and the Least Absolute Shrinkage and Selection Operator (LASSO) to select variables. Results Malaria prevalence was highest in the Lake Endemic (19%), followed by the Coastal Endemic (5%), semi-arid seasonal (2%), and low-risk (0.9%) malaria epidemiologic zones in 2020. Mosquito species distribution varied, with distinct ecological preferences observed with Anopheles gambiae dominated coastal and semi-arid areas, while Anopheles funestus was highest in the highland and lake zones. Regression analysis indicated that a combination of environmental factors and public health interventions, including insecticide-treated nets (ITN) coverage, was an important predictor of malaria prevalence. However, the relationship between these factors and malaria prevalence varied across regions and time periods. Conclusion This study provides insights into the spatial dynamics of mosquito species and their distribution in relation to malaria epidemiological zones in Kenya, thereby informing targeted control strategies.

  PublisherDOI

• Evaluation of colorectal cancer screening practices in Rhode Island, 2011–2021

  Cancer Causes & Control · 2026-02-10

  article
  PublisherDOI

• Additional file 1 of Mapping mosquito diversity in Kenya correlating species distribution with malaria prevalence across varied climatic parameters

  Figshare · 2026-01-01

  articleOpen access

  Supplementary material 1.

  PublisherDOI

• Impact of Social Determinants of Health on Pre-Exposure Prophylaxis Care for HIV Prevention

  JAIDS Journal of Acquired Immune Deficiency Syndromes · 2025-01-09 · 3 citations

  article

  BACKGROUND: HIV continues to disproportionately affect men who have sex with men (MSM) in the United States. Pre-exposure prophylaxis (PrEP) is effective, but disparities persist. Limited studies have conducted systematic evaluations of social determinants of health (SDOH) and their effects on PrEP persistence among MSM. SETTING: We enrolled MSM into a prospective observational cohort to assess progression through the PrEP care continuum. We enrolled patients from 3 diverse settings in the United States from 2018 to 2022. METHODS: We explored the impact of SDOH on PrEP persistence (defined as successfully obtaining PrEP prescriptions and/or clinical documentation of retention in PrEP care) at 6 and 12 months using multilevel, mixed-effects logistic models. RESULTS: A total of N = 300 MSM were enrolled. Median age was 28 years; 40% were Black/African American, and 11% were Hispanic/Latino (H/L). PrEP persistence was 84.7% and 49.3% at 6- and 12-months, respectively. In the unadjusted analysis, Black/African American and H/L individuals were 56% and 54%, respectively, less likely to demonstrate PrEP persistence at 6-and 12-months compared with White/non-H/L individuals. Findings were no longer significant after adjusting for economic stability and educational attainment. Individuals with higher levels of internalized homophobia were less likely to persist on PrEP. Every 1-unit increase on a validated measure of internalized homophobia was independently and negatively associated with PrEP persistence (adjusted odds ratio = 0.95, 95% confidence interval: 0.93 to 0.98). CONCLUSIONS: SDOH are important predictors of racial and ethnic disparities in PrEP persistence among MSM. Addressing these factors could help mitigate racial disparities in PrEP persistence in the United States.

  PublisherDOI

• Trajectories of neighborhood-level overdose risk predictions for prioritization of harm reduction services: Results from the PROVIDENT study

  Drug and Alcohol Dependence · 2025-10-17

  articleCorresponding
  PublisherDOI

• Socioenvironmental and mental health determinants of alcohol use among Black sexually minoritized men and transgender women: Findings from the N2 cohort study

  The Journal of LGBTQ+ Mental Health · 2025-09-18

  articleOpen access

  Introduction: We aimed to identify socioenvironmental determinants of alcohol use among Black sexually minoritized men (SMM) and transgender women (TW). Method: Data were from the Neighborhoods and Networks (N2) cohort study among Black SMM and TW (01/2018-08/2020). We used stepwise negative binomial regression to identify associations with alcohol use. Result: =24±4 years), 68% reported past month alcohol use. Adverse childhood experiences (IRR=1.10;95%CI=1.03-1.18), GAD-7 (IRR=1.03;95%CI=1.00-1.07), and community violence (IRR=1.06;95%CI=1.02-1.10), were positively associated with alcohol use. Conclusion: Multilevel alcohol reduction interventions can consider reducing community violence and increasing access to mental health services.

  PublisherOA PDFDOI

Recent grants

• NIH Grant F31MH121112

  NIH · $37k · 2020

Frequent coauthors

• Brandon D. L. Marshall

  Brown University

  207 shared

• Dustin T. Duncan

  Columbia University

  99 shared

• Philip A. Chan

  Brown University

  89 shared

• Sam Bessey

  Brown University

  80 shared

• Maximilian R F King

  University of Washington

  69 shared

• Amy Nunn

  Rhode Island Department of Health

  65 shared

• Samuel R. Friedman

  New York University

  62 shared

• Ashley Buchanan

  University of Rhode Island

  55 shared

Education

• B.A., Global Public Health and Sociology

  New York University’s College of Global Public Health

  2017

• Ph.D., Epidemiology

  Brown University’s School of Public Health

  2020

Awards & honors

• Public Health Impact Award from the Rhode Island Public Heal…
• Inaugural recipient of the Faculty Fellowship in University…
• Dean’s Award for Excellence in Classroom Teaching in Public…