Seth David Judson

Background: Multiple recent yellow fever (YF) outbreaks have occurred despite a highly effective vaccine. Increasing vaccination coverage and decreasing response times have been key components of the Eliminate Yellow Fever Epidemics (EYE) strategy. However, the combined impacts of these factors on YF outbreaks, especially since implementation of the EYE strategy in 2017, remain uncertain. Methods: We developed mathematical models to simulate the effects of vaccination coverage and timing, calibrating them to recent YF outbreaks in Ghana (2021-2022) and South Sudan (2023-2024). We then projected YF morbidity and mortality under different EYE strategy thresholds for vaccination coverage and timing. Results: In Ghana, where reactive vaccination was observed at 22 days with an estimated 70% baseline coverage, modeled delays of 60 and 120 days yielded 62 (95% uncertainty interval [UI] 30-119) and 281 (95% UI 59-927) additional severe cases, respectively. Increasing baseline vaccination coverage to 80% averted an estimated 20 severe cases (95% UI 14-25). In South Sudan, where reactive vaccination occurred at 61 days with estimated 50% baseline coverage, shortening the response time to 20 days and increasing baseline coverage to 80% averted an estimated 80 (95% UI 68-91) and 95 severe cases (95% UI 80-112) independently or 103 severe cases (95% UI 85-120) if combined. Conclusion: Increasing baseline YF vaccination coverage to at least 80% can avert substantial morbidity from YF outbreaks. Decreasing vaccination response time for reactive vaccination can provide additional benefit.

Background: Yellow fever virus is transmitted by mosquitoes among humans and non-human primates (NHPs) in South America. The 2024–2025 yellow fever (YF) outbreak was notable for its spread into new areas, including the department of Tolima in Colombia's Andean region. We investigated the eco-epidemiology of human and NHP YF cases to understand the patterns and factors associated with the Tolima outbreak. Method: We collected spatiotemporal, sociodemographic, and mortality data on human YF cases in Tolima, as well as the locations of deceased NHPs with YF. We then conducted exploratory, descriptive, and spatial statistical analyses to identify risk factors and hotspots for YF. We then used inferential spatiotemporal modeling to compare ecological and sociodemographic factors. Results: From September 2024 to October 2025, 116 human and 53 non-human primate YF cases were detected in Tolima. Among the human cases, 77% were male (89/116), and the median age was 47 (interquartile range 34–63). Of these cases, 45 (39%) died, and older age was associated with increased odds of death (adjusted odds ratio, 1.43 per 10 years; 95% confidence interval, 1.18–1.78). There was significant clustering among human and NHP cases. Higher rainfall and poverty/deprivation were associated with increased YF incidence at the neighborhood level, and rainfall during the outbreak was above average due to La Niña. Conclusions: These findings demonstrate significant mortality from YF, which reemerged in Tolima after nearly a century. Rural populations with greater ecological risk and poverty/deprivation could benefit from targeted vaccination strategies for YF.

Risk maps and spatial models provide key information about the endemicity and spread of infectious diseases. Novel data streams and statistical techniques, with the aid of artificial intelligence, create the opportunity for modern risk maps. To ensure that these tools are useful for clinical decision-making, we need to understand how risk maps are used, how they are developed, and how they can be improved. This will be especially important for zoonotic, vector-borne, and environmental infectious diseases in the era of environmental change and globalization.

Containing yellow fever (YF) outbreaks rapidly through reactive vaccination campaigns (RVCs) is a key objective of the 2017–2026 Eliminate Yellow Fever Epidemics (EYE) strategy. We conducted a scoping review and quantitative analysis using grey and peer-reviewed literature on YF outbreaks in Africa (2010–2025) to compare how factors including outbreak size and timing of RVCs have changed pre- and post-EYE strategy. The overall median time between YF index case and RVC was 90.5 days (interquartile range [IQR]: 53.8-113.2), with medians of 108 days (IQR 59–111) for 2010–2016 and 79 days (IQR 51-114.5) for 2017–2025. The median (IQR) reported cases per outbreak was 91 (IQR: 16–276) in 2010–2016 and 94 (49–377) in 2017–2025, with case fatality ratios (CFRs) of 8.5% (standard error [SE]: 2.1%) and 4.9% (SE: 2.9%), respectively. High morbidity and mortality for YF persist in Africa, and more timely RVCs will be required to achieve YF control.

: West Nile virus (WNV) is transmitted by mosquitoes to humans in many regions and can cause neuroinvasive disease and death. To better understand the local burden of disease caused by WNV and risk factors for disease severity, we analyzed cases from across the Johns Hopkins Health System Corporation. We identified 86 patients who met confirmed/probable case definitions for WNV infection from 2013 to 2024. Seventy-one patients (83%) had West Nile neuroinvasive disease (WNND), and nine (10%) died. Encephalitis ( n = 47) was the most common complication and was associated with increased age, alcohol use disorder, immunocompromised status, and a higher Charlson Comorbidity Index. Of the 21 patients in the cohort who were immunocompromised, 20 (95%) developed WNND, and 4 (19%) died. The overall median hospital length of stay was 8 days (interquartile range 5–15). People diagnosed with WNV in this health care system experienced significant morbidity and mortality from WNND, notably when immunocompromised.

Background: Yellow fever virus (YFV) is transmitted by mosquitoes among humans and non-human primates (NHPs) in South America. The 2024-25 yellow fever (YF) outbreak was notable for its spread into new areas, including the department of Tolima in Colombia’s Andean region. We investigated the eco-epidemiology of human and NHP YF cases to understand the patterns and drivers of the Tolima outbreak. Methods: We collected spatiotemporal, sociodemographic, and mortality data on human YF cases in Tolima, as well as the locations of deceased NHPs with YF. We then conducted exploratory, descriptive, and spatial statistical analyses to identify risk factors and hotspots for YF. We then used inferential spatiotemporal modelling to compare ecological and sociodemographic drivers. Findings: From September 2024 to October 2025, 116 human and 53 non-human primate YF cases were detected in Tolima. Among the human cases, 77% were male (89/116), and the median age was 47 (interquartile range 34-63). Of these cases, 45 (39%) died, and older age was associated with increased odds of death (adjusted odds ratio, 1.34 per 10 years; 95% confidence interval, 1.10-1.65). There was significant clustering among human and NHP cases. Higher rainfall and poverty/deprivation were associated with increased YF incidence at the neighborhood level, and rainfall during the outbreak was above average due to La Niña. Interpretation: These findings demonstrate significant mortality from YF, which re-emerged in Tolima after nearly a century. Rural populations with greater ecological risk and poverty/deprivation could benefit from targeted vaccination strategies for YF. Funding: National Institutes of Health

Yellow fever is a mosquito-borne viral hemorrhagic fever, and recent outbreaks of yellow fever have occurred in multiple African countries, including Ghana (2021–2022). Delayed diagnosis of yellow fever may cause increased morbidity and mortality. To improve timely detection of yellow fever, we need to better understand the factors contributing to diagnostic delays. We analyzed the diagnostic testing timeline of all suspected yellow fever cases in Ghana from 2018-2022. For these patients we calculated the days from symptom onset to specimen collection and arrival at the National Public Health and Reference Laboratory for testing. We compared these times to World Health Organization (WHO) metrics. For suspected yellow fever cases, the time from symptom onset to specimen arrival had a median of 10 days (interquartile range 6–17). 5892/6345 (93%) of specimens were collected within 14 days of symptom onset, and 2653/6471 (41%) of specimens arrived within 3 days of collection (WHO metrics). Overall, we find that the timing of yellow fever testing varies among districts in Ghana. While specimens are generally collected in a timely manner, delays in specimen arrival are common. Improving specimen transport for yellow fever and/or expanded testing could lead to more timely detection of outbreaks.

Importance: West Nile virus (WNV) is the leading mosquito-borne infection in the US, causing West Nile fever or West Nile neuroinvasive disease (WNND) with substantial morbidity and mortality. Contemporary analyses are needed to identify at-risk populations and to target interventions. Objective: To assess risk factors associated with WNND and mortality among adults with WNV infection using a national cohort from federated data. Design, Setting, and Participants: This retrospective cohort study of deidentified electronic medical record data from the TriNetX research network from January 2013 to December 2024 included patients from 65 health care organizations from across the US. Data were accessed from March 28 to April 30, 2025. Exposures: Demographic characteristics (age, sex, race, and ethnicity), comorbidities (hematologic malignant neoplasms, heart disease, diabetes, HIV infection, chronic kidney disease [CKD], liver disease, hypertension, alcohol-related disorders, cerebrovascular disease [CEVD], chronic obstructive pulmonary disease, asthma, multiple sclerosis, dementia, rheumatoid arthritis, and organ transplant), and medications (immune suppressants, antineoplastics). Main Outcomes and Measures: Primary outcomes were WNND development and all-cause mortality (at 30 days, 90 days, and overall). Results: Among the initial cohort of 3064 patients with a diagnosis of WNV infection (per the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision codes), those with demographic data included 1249 (53%) who were consistent with West Nile fever (624 females [50%]; mean [SD] age, 55 [17] years) and 1127 (47%) who were consistent with WNND (691 males [61%]; mean [SD] age, 59 [17] years). Risk factors associated with WNND included age (adjusted hazard ratio [AHR], 1.10 [95% CI, 1.06-1.15] per decade), male sex (AHR, 1.29 [95% CI, 1.15-1.45]), CKD (AHR, 1.21 [95% CI, 1.00-1.45]), CEVD (AHR, 1.22 [95% CI, 1.03-1.45]), hematologic malignant neoplasms (AHR, 1.38 [95% CI, 1.09-1.76]), immune suppressant use (AHR, 1.43 [95% CI, 1.11-1.83]), hypertension (AHR, 1.18 [95% CI, 1.04-1.34]), alcohol-related disorders (AHR, 1.54 [95% CI, 1.20-1.97]), and multiple sclerosis (AHR, 2.34 [95% CI, 1.62-3.37]). Significant risk factors associated with mortality were WNND (AHR, 2.49 [95% CI, 1.37-4.52] for 30-day mortality), age (AHR, 1.32 [95% CI, 1.07-1.60] per decade), CKD (AHR, 2.08 [95% CI, 1.01-3.93]), and CEVD (AHR, 2.00 [95% CI, 1.14-3.50]). Conclusions and Relevance: In this cohort study of patients with WNV infection, multiple comorbidities were identified as risk factors associated with WNND; and patients who developed WNND had increased mortality risk. Targeted prevention strategies and countermeasures for high-risk individuals may substantially reduce morbidity and mortality.

Planetary health and One Health have become key concepts in public health, scientific, and veterinary training, yet these concepts remain incompletely integrated into clinical medical education. Recognizing this gap, we created a free online curriculum called “Medicine for a Changing Planet,” geared toward training the next generation of health professionals in clinical skills to detect and manage the impacts of global and local environmental change on their patients. Using a case conference-style format familiar to medical trainees, we created 11 clinical case studies teaching both planetary health concepts and clinical competencies, leveraging Bloom's Taxonomy. Here, we describe the creation of these clinical cases, highlighting those centered on emerging infectious diseases that teach clinical skills related to the human–animal interface, globalization, and climate change. The online cases have been visited by more than 4000 unique users from 99 countries, piloted with residency and medical school programs, and made available for CME credit.