A Multi‑Omics Profiling of Infectious Drivers of Miscarriage and Stillbirth in a High‑Burden Ugandan Population (OPIDMIS-Uganda) (360G-Wellcome-345983_Z_26_Z)

Globally, 1 in 10 babies is born preterm or lost through miscarriage or stillbirth, a statistic that has remained unchanged for two decades and continues to impede progress in maternal and newborn health. In Uganda, the introduction of Maternal and Perinatal Death Surveillance and Response (MPDSR) systems has contributed to reducing stillbirths from 24 to 17 per 1,000 live births, yet persistently low reporting rates limit their full impact. The Iganga–Mayuge Health and Demographic Surveillance Site offers a rare opportunity: with over 41,000 registered pregnancies, very high pregnancy loss rates, reporting rate(86%), enabling a more complete understanding of these outcomes. While the infectious causes remain poorly characterised, epidemiological patterns strongly suggest an important role of zoonotic pathogens. Therefore our multidisciplinary team seeks to co‑develop a multi‑level research programme with affected communities to a) leverage multi- omics to improve evidence used by MPDSR as clinical support system and b) map the social complexities that shape pregnancy outcomes “social autopsy” to inform the creation of a parallel community-level support system. Together, these arms will generate multi-level datasets to underpin machine‑learning analyses to identify drivers of miscarriage and stillbirth and inform actionable interventions.