# Translating Evidence into Action: Novel modeling approaches to end the syphilis epidemic in the U.S.

> **NIH NIH R01** · JOHNS HOPKINS UNIVERSITY · 2024 · $816,272

## Abstract

PROJECT SUMMARY
Syphilis rates in the United States (US) have reached their highest levels in decades, doubling in the past five
years alone. In 2021, men who have sex with men (MSM) accounted for nearly half (46.5%) of all male primary
and secondary (P&S) cases. The rate of congenital syphilis has increased by eight-fold since 2011 – reaching
one in every 1,300 US births in 2021. The surge in syphilis cases is evident across the US, with highest
concentration in urban areas. Amidst declining public health budgets, local policymakers face the challenge of
identifying the most efficient and cost-effective ways to invest in these existing tools to alter the trajectory of the
US syphilis epidemic. Innovations in syphilis prevention and diagnoses, such as doxycycline for post-exposure
prophylaxis ("doxy-PEP") and new diagnostics like point-of-care (POC) or at-home testing, hold promise in
reducing syphilis incidence. Efforts to curb new infections require multifactorial approaches addressing
underlying transmission drivers and health disparities. To reverse syphilis trends, it is critical to identify the
most efficient use of limited public health resources, recognizing that a one-size-fits-all solution may not be
suitable for all US cities. Mathematical models of infectious disease dynamics serve as powerful tools for
forecasting the impact of infection control strategies. Despite extensive applications in studying HIV and other
sexually transmitted infections, there is a marked lack of modeling of US syphilis over the last decade. The
absence of representative models for the US syphilis epidemic hinders the effective formulation of
evidence-based policy to control further spread of infections. In this proposal, we plan to develop a novel
suite of local-level syphilis epidemiologic and economic models (LSEEM) across 40 US cities with the highest
syphilis diagnosis rates. The model will consider syphilis transmission, progression, HIV co-infection, STI care
engagement dynamics, and demographic factors such as age, racial and ethnic disparities, risk profiles, and
social determinants of health. In Aim 1, we will assess the potential impact of scaling up "existing" syphilis
control interventions, focusing on increased testing, expanded partner tracing, and faster treatment initiation.
Our objective is to provide achievable, cost-effective, and practical suggestions applicable to local jurisdictions.
Aim 2 involves evaluating the scale-up of "emerging" diagnostics and biomedical interventions under various
assumptions concerning population coverage and costs. Our goal is to determine the conditions under which
these interventions would be cost-effective when entering the market. Finally, in Aim 3, we will develop a user-
friendly online toolkit to enable decision-makers at local, state, and national levels to obtain customized
projections of the impact from diagnostic or biomedical prevention interventions. This tool will aid in translating
data into ev...

## Key facts

- **NIH application ID:** 10979631
- **Project number:** 1R01AI179776-01A1
- **Recipient organization:** JOHNS HOPKINS UNIVERSITY
- **Principal Investigator:** Parastu Kasaie
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $816,272
- **Award type:** 1
- **Project period:** 2024-07-11 → 2029-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10979631

## Citation

> US National Institutes of Health, RePORTER application 10979631, Translating Evidence into Action: Novel modeling approaches to end the syphilis epidemic in the U.S. (1R01AI179776-01A1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10979631. Licensed CC0.

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