About

Joseph W. Hogan is the Carole and Lawrence Sirovich Professor of Public Health and a Professor of Biostatistics at Brown University. His research focuses on the development of statistical methods for missing data, causal inference, and sensitivity analysis, with particular emphasis on applications related to HIV/AIDS. Hogan collaborates extensively in international health research, serving as Co-Director of the Biostatistics Program for AMPATH, an international consortium dedicated to HIV treatment and prevention in Kenya, and as Co-Director of the Biostatistics Core for the Providence-Boston Center for AIDS Research. His basic and collaborative research is funded by the NIH and NSF. Hogan has also contributed to building research capacity in biostatistics through international training programs at Moi University in Kenya. In addition to his research, he teaches both introductory and advanced courses in biostatistics and supervises PhD and master's students. He has served as Deputy Director for the Data Science Initiative at Brown University, demonstrating his leadership in the field.

Research topics

• Internal medicine
• Medicine
• Environmental health
• Computer Science
• Family medicine
• Nursing
• Immunology
• Pediatrics
• Economic growth
• Endocrinology
• Virology
• Statistics
• Data science
• Mathematics

Selected publications

• Longitudinal challenges faced by perinatally-infected young people living with HIV in Kenya during the COVID-19 pandemic

  AIDS · 2026-04-07

  article

  BACKGROUND: Understanding challenges experienced by adolescents and youth living with HIV (AYLWH) during COVID-19 can inform care during health crises. METHODS: From 2021-2023, bi-monthly in-person/phone surveys were administered to assess trends in psychological, physical, and socioeconomic challenges, and antiretroviral nonadherence, among Kenyan AYLWH, alongside COVID-19 burden (casesloads and Oxford-Stringency-Index (OSI)). Biannual viral loads (VLs) were described as virologic suppression (VL < =40copies/mL), virologic failure (VL>40copies/mL), and treatment failure (VL>1,000copies/mL). Associations among caseloads/OSI, challenges, nonadherence, and treatment failure transitions (VL < =1,000 to >1,000copies/mL and vice versa) were evaluated using regression models, accounting for repeated-measures, age, gender, clinic, and between-visit days. RESULTS: Among 441 participants (mean age 16.9 years, 49% female, mean time on ART 11.9 years), 89% reported at enrollment challenges (48% psychological, 66% physical, 61% socioeconomic). Within-subject challenges, COVID-19 caseloads, and OSI scores varied over time alongside pandemic changes. During stringent periods and surges, physical challenges worsened (OR = 1.04 per 100-cases increase/day, CI = 1.00-1.08); psychological challenges were stable (OR = 1.02, CI = 0.98-1.06); socioeconomic challenges worsened during caseloads upticks (OR = 2.08, CI = 1.14-3.81). Higher challenges burden at enrollment was associated with slower reduction in challenges over time. Nonadherence (74% at enrollment) was associated with higher prior-visit challenges (Psychological: OR = 1.37, CI = 1.24-1.51; Physical: OR = 1.43, CI = 1.22-1.69; Socioeconomic: OR = 1.27, CI = 1.11-1.46). Virologic and treatment failure occurred in 19% and 10%; suppression-to-failure transition was associated with worsening adherence (OR = 1.26, CI = 1.00-1.58). CONCLUSIONS: Kenyan AYLWH experienced substantial wellness challenges during COVID-19, possibly prompting poor adherence and viral outcomes. While stability of non-physical challenges suggests COVID-19 adaptation, targeted interventions are warranted to support this vulnerable population during public health crises.

  PublisherDOI

• Mapping social determinants of health data in sub-Saharan Africa: a scoping review protocol

  BMJ Open · 2026-02-01 · 1 citations

  articleOpen access

  INTRODUCTION: Research has increasingly underscored the impact of factors such as socioeconomic status, education, healthcare access, housing and environmental conditions in shaping population health outcomes. These factors, collectively called social determinants of health (SDOH), provide crucial context for understanding drivers of health outcomes. In sub-Saharan Africa (SSA), the study of SDOH is critical due to the region's unique sociocultural and economic conditions. Understanding how SDOH interacts with health systems and capturing SDOH in data is crucial for informing modelling efforts and policies improving population health more effectively. This scoping review aims to map the types of data used to capture SDOH in research conducted in SSA, to identify research gaps and to summarise key findings. METHODS: , providing best practices for identifying, selecting and analysing eligible studies. Key steps include (1) identifying the research question, (2) identifying relevant studies, (3) selecting eligible studies via a locally curated search, (4) extracting information, (5) collating, summarising and reporting results and (6) consultation with stakeholders. ETHICS AND DISSEMINATION: Ethical approval is not required, as this review relies solely on published literature. Findings will be disseminated across academic channels (journals, conferences) and through targeted stakeholder engagement efforts, such as policy briefs and public health workshops, to reach policymakers, healthcare practitioners and community health organisations. This dissemination strategy aims to inform health policy and drive programme development in SSA.

  PublisherDOI

• Dynamic case-control sampling for rapid estimation of vaccine effectiveness against an emerging infectious disease variant

  Biostatistics · 2026-01-01

  articleSenior author

  New SARS-CoV-2 variants arise frequently with different viral properties that can impact the effectiveness of the vaccines. Updating estimates of vaccine effectiveness (VE) in public health surveillance can be limited by the necessity of conducting a distinct study that entails analysis of prospective cohort data or using a test-negative design. We introduce a method for dynamically updating estimates of VE using data that accumulate in real time. Our method uses dynamic case-control sampling to estimate VE against a newly emerging variant relative to a previous variant. Dynamic case-control sampling is a technique that continuously updates VE estimates by comparing individuals infected with a newly emerging variant (defined as "cases") to those infected with a previously circulating variant (defined as "controls"). We use this estimate in combination with information about VE from the previous variant (these estimates are typically available from larger, traditional studies) to infer VE against the emerging variant. We demonstrate the utility of this method on the BA.1 and BA.2 sub-lineages of the Omicron variant. The method produces estimates of VE comparable to those produced using traditional methods, although with increased SE. The increase in error, however, is reasonable given a much smaller sample size than other studies, and error ranges of the estimates could be significantly improved by sequencing a larger proportion of identified cases. Our method, which assumes only a fraction of the new cases are being sequenced, can be applied by health departments using routinely collected data to produce timely, rigorous VE estimates to rapidly identify potential changes in VE.

  PublisherDOI

• SARS-CoV-2 seroprevalence in Kenyan Children and Adolescents living with HIV

  Research Square · 2025-08-22

  preprintOpen access
  PublisherOA PDFDOI

• P.046 Improving the confidence and skills of novice obstetric anaesthetists through peer delivered training in elective and emergency obstetric care.

  International Journal of Obstetric Anesthesia · 2025-05-01

  article
  PublisherDOI

• Model Calibration, Interpretability, and Decision-Making with AI-Based Risk Scores

  NEJM AI · 2025-04-24 · 1 citations

  article1st authorCorresponding
  PublisherDOI

• Improving perioperative pain management in patients undergoing major colorectal surgery through intraoperative and postoperative analgesia strategies

  BJA Open · 2025-08-21

  articleOpen access

  Background: Effective pain management is crucial for enhancing postoperative recovery in patients undergoing major colorectal surgery patients. The Princess Royal University Hospital participated in the Perioperative Quality Improvement Programme (PQIP) study to assess and improve patient outcomes. A local quality improvement project was launched to develop and implement a new guideline for intraoperative and postoperative analgesic management in patients undergoing colorectal surgery, and audit adherence to established practice.

  PublisherOA PDFDOI

• Accelerating Science with Human+AI Review

  NEJM AI · 2025-11-26 · 10 citations

  article
  PublisherDOI

• Newly Diagnosed Individuals in Molecular HIV-1 Clusters in Rhode Island Over 3 Decades

  The Journal of Infectious Diseases · 2025-06-12

  articleOpen access

  BACKGROUND: Characterizing clustering rates of people with HIV in high-risk populations can offer insights on the HIV epidemic, enhancing efforts to control its spread. METHODS: We investigated longitudinal dynamics of clustering rates among individuals newly diagnosed with HIV-1. Data were extracted from the medical records of all people with HIV in Rhode Island with available viral sequences. Partial pol sequences were grouped by HIV diagnosis year, and clusters were identified in annual phylogenies. Clustering trends were estimated within 11 sociodemographic variables with the Mann-Kendall statistic. Associations with clustering propensity and changes over time were tested via generalized linear mixed effects models. RESULTS: HIV-1 sequences from 2630 individuals representing the statewide epidemic were analyzed across 33 annual datasets (1991-2023). Over this period, a continuous increase in clustering rates among newly diagnosed individuals was observed despite decreasing diagnoses over the last decade. Significant upward trends in clustering were seen among newly diagnosed men who have sex with men, males, the 21- to 40-year age group, non-Hispanic or Latino people, White persons, those with subtype B, and US-born individuals but not among people who inject drugs, females, and incarcerated individuals. Analyses of relative associations between groups within variables corroborated these results. CONCLUSIONS: Analyses focusing on molecular HIV clusters among newly diagnosed people in a statewide epidemic over 3 decades revealed significant evolving trends among those at highest risk of HIV transmission, patterns not seen in the overall population. These findings inform the design and development of targeted public health interventions aimed at high-risk populations to curb HIV spread.

  PublisherOA PDFDOI

• OP0202 RESET-SLE: CLINICAL TRIAL EVALUATING RESE-CEL (RESECABTAGENE AUTOLEUCEL), A FULLY HUMAN, AUTOLOGOUS 4-1BB ANTI-CD19 CAR T CELL THERAPY IN NON-RENAL SLE AND LUPUS NEPHRITIS

  Annals of the Rheumatic Diseases · 2025-06-01 · 7 citations

  article
  PublisherDOI

Recent grants

• Core L - Clinical & Behavioral Sciences Core

  NIH · $21.7M · 1998–2028

• Addressing alcohol misuse in HIV prevention and care: The Brown University Alcohol Research Center on HIV (ARCH)

  NIH · $39.3M · 2010–2026

• NIH Grant R03HD035996

  NIH · $150k · 2000

• NIH Grant R01HL079457

  NIH · $770k · 2008

• Optimizing HIV Treatment Monitoring under Resource Constraints

  NIH · $3.5M · 2014–2022

Frequent coauthors

• Paula Braitstein

  Public Health Ontario

  171 shared

• Allison DeLong

  154 shared

• Rami Kantor

  John Brown University

  141 shared

• Bartolomeu Nascimento

  Fundação Getulio Vargas

  84 shared

• Philip A. Chan

  Brown University

  75 shared

• Sandro Rizoli

  Hamad Medical Corporation

  72 shared

• Lynne Moore

  Centre de Médecine Préventive

  72 shared

• David Bracco

  Muhimbili University of Health and Allied Sciences

  72 shared