Background and Objectives: HIV/aids incidence rose 40% during the COVID-19 pandemic in Guatemala. Previous scholarly work shows that targeting social and economic vulnerabilities reduces HIV incidence rates. Thus, this study aimed to analyze the relationship between conditional cash transfer programs (CTP) and HIV/aids incidence in Guatemala. Methods: This work is part of a larger study titled: “conditional cash transfer programs (CTP) and HIV/aids incidence in Guatemala: 2013-2021”. We conducted a cross-sectional exploratory analysis for 2018. HIV/aids incidence rates, coverage of the CTP, amount of cash received, and health assistance rates were calculated for the 340 municipalities. Data was collected from Guatemala’s Ministry of Health, and Ministry of Social Development. We used direct standardization method for rates comparability. We categorized incidence rates and CTP coverage for risk estimation. Finally, we investigated association through bivariate analysis. Results: Highest coverage of the CTP was 5.2%. Municipalities in the Northeast had the higher coverages of both CPT and health assistance, and those in the metropolitan area had the lowest. Medium-sized cities in the Northern and Central regions had the highest standardized rates of HIV/aids and had no coverage of CTP. We found that HIV incidence rates were negatively correlated to CTP coverage (ρ: -0.113 p<0.05) and the amount of cash received (ρ: -0.123 p<0.05); and positively correlated with health assistance rates (ρ: 0.144 p<0.01). Lastly, municipalities with CTP coverage <1% had greater odds for having high HIV incidence rates (OR: 1.76 IC95%: 1.1 – 2.8). Conclusions: Conditional cash transfer programs are associated with the reduction of HIV/aids incidence rates. This evidence remarks the urge to include public policies targeting programmatic vulnerabilities in the HIV/aids prevention programs, in order to achieve the global agenda goals for reducing HIV transmission rates. The study’s second phase will include longitudinal and multivariate analysis to better describe this association.