The objective of this Funding Opportunity Announcement (FOA) is to support the development of new and innovative on-demand, event -driven and long-acting systemic and non-systemic multipurpose prevention technologies (MPT). It supports development of MPTs that prevent HIV infection and pregnancy (hormonal and non-hormonal methods); sexually transmitted infections (STI) and pregnancy, and (HIV/STI) and non-HIV STI MPTs in cis and trans males and females of all ages.

The goal of the Epidemiology and Laboratory Capacity for Prevention and Control of Emerging Infectious Diseases (ELC) program is to reduce illness and related deaths caused by a wide range of infectious disease threats. The ELC Program provides annual funding, strategic direction and technical assistance to domestic jurisdictions for core capacities in epidemiology, laboratory, and health information technology activities. In addition to strengthening core infectious disease capacities nationwide, this cooperative agreement also supports a myriad of specific infectious disease programs.

This Funding Opportunity Announcement (FOA) invites innovative research grant applications focused on identifying potential mechanisms and risk factors underlying HIV treatment associated neuropsychiatric symptoms and neurological toxicities experienced by some people living with HIV infection. Exploratory and high-risk research projects that may lead to identification of targets for therapeutic interventions or personalized medicine are appropriate for this FOA. Basic and preclinical research in domestic and international settings are of interest.

This Funding Opportunity Announcement (FOA) solicits applications developing computational models of immunity that advance understanding of the mechanisms required to induce and/or maintain protective immunity to infectious pathogens, other than HIV, and/or vaccines against such pathogens. The main goal of this FOA is to advance development and application of computational models of immunity that are refined through iterative immunological experimentation to validate and improve the utility and robustness of the computational models.