ABSTRACT STIRRUP (STI Responses and Recommendations Under PrEP) combines big data streams with mathemat- ical modeling and economic decision science to understand the optimal design of STI screening in PrEP care. Cases of gonorrhea, chlamydia, and syphilis have increased substantially over the past decade and a dispro- portionate disease burden falls on men who have sex with men (MSM). The persistently high STI rates among MSM are driven by the high proportion of asymptomatic infections and low rates of routine screening that would detect these infections. Most MSM who use PrEP are at elevated risk of acquiring STIs. PrEP care therefore provides a critical opportunity to reach and clinically engage a population who could benefit from linked HIV and STI prevention services. Screening for STIs in PrEP care following CDC recommendations can counterbalance the effects of increases in sexual risk behavior by treating asymptomatic STIs to prevent ongo- ing STI transmission chains. However, patterns of STI screening in PrEP care are far from recommended levels, with substantial variation by demographics and geography. Models informing clinical practice and public health policy must therefore incorporate data streams that span the range of healthcare settings where PrEP care is offered to these groups, and where it can be improved. Following an Extended, Multi-Disease PrEP Continuum of Care that includes steps for STI ancillary services and PrEP retention, we seek to test a leading hypothesis about the bidirectionality of these two steps: that ongoing comprehensive PrEP care is an efficient mechanism for routine STI screening and treatment, but that frequent STI ancillary services may often be a burden to retention in PrEP care. STIRRUP includes three SPECIFIC AIMS: AIM 1. We will extract, collect, analyze, and synthesize information on PrEP care, sexual behavior, mental health diagnoses, and HIV/STI screening patterns for MSM from electronic health records and epidemiological studies in three types of PrEP programs (academic, public, and private) in two geographic settings (Boston and Atlanta) distinguished by their HIV/STI burden and demographics. Analyses will guide development of an ethical framework for big data in modeling. AIM 2. With these data, we will build network-based race-stratified transmission models of four co- circulating infections (HIV, chlamydia, syphilis, and gonorrhea) among MSM at three exposure sites (urogeni- tal, rectal, and pharyngeal). These models will investigate the relationship between PrEP use and HIV/STI incidence given current bacterial STI screening/treatment (pre- and post-PrEP initiation), with a theory-driven focus on racial/ethnic disparities and mental health predictors across and within each city. AIM 3. We will eval- uate public health policies and clinical practice strategies for screening and treatment of STIs among heterogenous groups of MSM using PrEP. Economic models will estimate the cost-effectiveness of...