Johns Hopkins Epidemiological and Economic Model

Evidence for
HIV Policy

JHEEM answers critical policy questions about HIV programs, interventions, and funding through calibrated mathematical modeling across US cities and states.

Demographic Precision at Scale

Detailed disease progression modeled across 32 major metros and 31 states

?

Policy Scenarios

What-if modeling of funding cuts, intervention scale-up, service disruptions

20252040

Time Horizons

Immediate impacts to long-term demographic shifts (2025-2040)

Interactive Tools

Explore Our Models

Access specialized modeling applications for HIV policy analysis across metropolitan areas and states

Recent
Research

Latest JHEEM Publications

View All Publications
2025Featured

Potential Impact of Ending the Ryan White HIV/AIDS Program on HIV Incidence in the United States: A Modeling Study

Annals of Internal MedicineForster RJ et al.

Ending the Ryan White HIV/AIDS Program could result in 75,436 additional HIV infections (95% CrI, 19,251 to 134,175) across 31 high-burden U.S. cities from 2025 to 2030—a 49% increase. Even temporary interruptions lasting 18-42 months would cause 19-38% more infections. The impact varies dramatically by city, from 9% increase in Riverside, CA to 110% in Baltimore, MD, highlighting the critical public health value of Ryan White services.

2025Featured

Impact of Proposed Cuts to the Ryan White HIV/AIDS Program on HIV Incidence: A State-Level Analysis

medRxiv (preprint)Zalesak A et al.

Proposed cuts to Ryan White Parts C/D, Minority AIDS Initiative, and Ending the HIV Epidemic programs could result in 23,883 additional HIV infections (17.6% increase) across 30 states and DC from 2025 to 2030. The impact would be largest in states with high Ryan White dependency, with rural and underserved communities experiencing disproportionate effects.

2025Featured

Potential Effect of Ending CDC Funding for HIV Testing on HIV Incidence in the United States: A Modeling Study

medRxiv (preprint)Balasubramanian R et al.

Ending CDC funding for HIV testing could result in 12,719 additional HIV infections (9.6% increase) across 18 states from 2025 to 2030. Testing reductions would delay HIV diagnoses by an average of 0.5-1.5 years, increasing onward transmission and worsening health outcomes, with disproportionate impacts in rural and underserved communities.

Research Funding
& Institutional Support

This research is supported by grants from the National Institute of Mental Health, the National Institute of Allergy and Infectious Diseases, and the National Institute on Minority Health and Health Disparities.

K08MH118094
K01AI138853
P30-AI094189
R01MD018539
JH

Johns Hopkins Bloomberg School of Public Health

Computational Epidemiology Research Group

Advancing mathematical modeling for HIV prevention and control