Johns Hopkins Bloomberg School of Public Health

The Johns Hopkins Epidemiological and Economic Model

JHEEM provides evidence for HIV policy decisions through calibrated mathematical modeling across US metropolitan areas and states.

Population dynamics

Disease progression modeled across 32 metros and 31 states

Scenario analysis

What-if modeling of funding changes and interventions

Time horizons

Projections from immediate impacts to 2040

Recent Finding

Our models project 12,700 additional HIV infections if CDC-funded testing programs end permanently across 18 states.

Recent Publications

Peer-reviewed research using JHEEM

View all publications →
2025

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

Forster RJ, Kasaie P, Schnure MC et al.

Annals of Internal Medicine

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.

2025

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

Zalesak A, Kasaie P, Schnure MC et al.

medRxiv (preprint)

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.

2025

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

Balasubramanian R, Kasaie P, Schnure MC et al.

medRxiv (preprint)

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