Leveraging Integrated liNked data to assess and optimize Child outcomes (LINC)

PROJECT SUMMARY Children who are perinatally HIV exposed and uninfected (CHEU) have worse birth, mortality, infectious disease and neurodevelopmental outcomes than children perinatally HIV unexposed (CHU). Given the scale of perinatal HIV exposure in high prevalence countries, even small CHEU/CHU health disparities may have important public health and societal impacts e.g., on overall child mortality, hospitalization, education, adult health and productivity. While many CHEU may have expected health outcomes, a subset may be at risk of sub-optimal outcomes potentially mitigated by targeted interventions. A paradigm shift is thus needed for vertical HIV transmission prevention (VTP) programs that currently measure success as a child who is HIV free, to a public health approach ensuring all children are HIV free with equivalent health outcomes. Integrated surveillance with linked mother-child data is critical for a public health approach to 1) quantify and understand IHEU outcomes and the impact of ever-evolving interventions to improve the health of pregnant people with HIV or at risk of acquiring HIV and their children, and 2) identify those at high risk of sub-optimal outcomes to ensure optimal patient-centered intervention delivery. Leveraging the strength of the NICHD- funded (R61) CHERISH Provincial Health Data Centre (PHDC) in the Western Cape (WC), South Africa (SA), the first comprehensive linked health information exchange in Africa, and considerable investments in using routinely collected health service data to optimize health outcomes in Botswana and Kenya, we will establish and enhance integrated platforms for CHEU/CHU surveillance with the following Specific Aims: Aim 1: To use WC PHDC linked mother-child data (~1.3 million pregnancies; ~1 million live-born children from 2018-2029) to compare a) pregnancy and birth outcomes, b) infant/child outcomes up to age 5 years (mortality, tuberculosis, infectious disease hospitalization), c) longer term (≥age 15 years) outcomes (e.g., reproductive health) by maternal HIV and antiretroviral (ARV) exposure status, including long-acting ARVs. We will enhance PHDC data by a) using artificial intelligence to improve exposure and outcome inference algorithms and b) linking to detailed socio-economic data from an existing ongoing demographic and health surveillance study Aim 2: To assess the utility of PHDC programmatic linked mother-child data to identify CHEU/CHU at high risk of sub-optimal neurodevelopment, infectious disease and tuberculosis for delivery of targeted interventions. Aim 3: To engage Botswana and Kenya Ministries of Health, leveraging existing interest in enhancing routinely collected health data to co-create and pilot a toolkit/blueprint for linkage of programmatic mother-child data. Developing CHEU/CHU population surveillance using mother-child linked data integrated with routine health data will provide ongoing understanding of CHEU/CHU disparities in the context of evolving interventions to address them and facilitate iterative improvement of maternal/child health programs to address intervention gaps and maximize opportunities for all mothers and children to survive and thrive.