Despite evidence that eHealth approaches can be effective in reducing HIV risk, their implementation requirements do not fit within established strategies for public health scale up?leaving it an open question as to how to bring these programs into practice. The overarching goal of this proposal is to address this need by developing and evaluating novel strategies for implementing eHealth HIV prevention programs. Keep It Up! (KIU!) is an online program proven to reduce HIV risk among young men who have sex with men (YMSM), including YMSM at elevated HIV risk due to behaviors (i.e., condomless sex, substance use) and demographics (i.e., racial/ethnic minorities). Strong evidence of effectiveness on behavioral and biomedical outcomes makes KIU! an ideal eHealth intervention for implementation science. Lessons learned will set the pathway for implementation of the many HIV eHealth programs currently undergoing efficacy testing. Through formative research with community-based organizations (CBOs), health departments, the CDC, and researchers we have identified two pragmatic implementation strategies that we will evaluate and compare: Strategy 1: CBOs apply for, and are selected for, funding to deliver KIU! through their current HIV testing programs. Strategy 2 is a ?direct-to-consumer? (DTC) model where centralized staff recruit participants nationally through online advertising campaigns and manage engagement. HIV/STI testing kits are shipped directly to YMSM and, upon documentation of an HIV negative test result, participants are delivered KIU! Aim 1: Compare two implementation strategies using a cluster randomized trial. 75 counties with large YMSM populations will be randomized 2:1 to strategy 1 (CBO) or strategy 2 (DTC). KIU! will be delivered in each county for two years. In this cluster randomized trial, the unit of randomization is the county, with implementation and effectiveness outcome data collected from YMSM participants, CBOs, and the technology vendor. Our primary outcomes are public health impact (defined as reach X effectiveness) and cost per infection averted. We will also collect and report as secondary outcomes multiple metrics of reach, effectiveness, and implementation. Aim 2: Examine adoption characteristics that explain variability in implementation outcomes. We will conduct mixed-methods research on the domains from the consolidated framework for implementation research (CFIR) to explain variability in implementation success. Data on CFIR characteristics will be collected through administrative data, and surveys and telephone interviews with key stakeholders. We will also explore maintenance/sustainment of KIU! at the completion of the study. CBOs will be provided with materials to facilitate applying for external funding to continue to provide KIU! after study completion, including an Impact Tool to estimate local impact and costs. Through expert consultation we will examine models for ongoing sustainment of the DTC model.