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Background Risk of heterosexual HIV-1 transmission is elevated in the presence of sexually transmitted infections (STIs) such as chlamydia (CT) and gonorrhea (NG). Syndromic management is a common, low-resource, approach to detecting STIs. However, CT and/or NG infections in women are often asymptomatic and therefore missed by syndromic management. Molecular testing for STIs is highly sensitive, but time and cost restraints preclude implementation of these technologies in resource-limited settings. Pooling samples for testing together in GeneXpert cartridges is one strategy for reducing the cost per individual tested. Methods This project describes the development of a pooling strategy based on social and demographic factors associated with CT/NG prevalence rates in a cohort of high-risk women in Zambia. Logistic regression modeling was used to predict the probability of a positive CT/NG test result in the presence of various factors. Data from a 2016 cross-sectional sub-study on intra-vaginal practices in 509 women was examined and an easy-to-use diagnostic screening checklist was created to categorize women by probability of testing positive on the GeneXpert. An algorithm considering cost of each test and prevalence of disease in each group determined the optimal pool size for each risk category. Results Logistic regression identified CT/NG to be associated with: city, age, education, long-acting reversible contraception usage, and laboratory results for bacterial vaginosis, Trichomonas vaginalis , and incident syphilis on the day of CT/NG testing. Signs and symptoms were not found to be associated. The overall prevalence of either CT and/or NG infection in this population was 17%. Low, middle, and high-risk groups could be separated based on checklist score with 7.52%, 18.30%, and 46.51% CT/NG prevalence, respectively. Conclusion Pooling women with similar CT/NG predictive factors together, or testing those at highest risk individually, reduces the cost per test. Further implementation of this tool to guide presumptive treatment, in lieu of molecular testing, increases the cost-saving potential. The strategies described in this study are applicable to other low-resource clinical settings seeking to provide the accuracy of molecular testing with a reduced financial burden. Disclosures All authors: No reported disclosures. [ABSTRACT FROM AUTHOR]