Kirsty Le Doare and colleagues at the MRC/UVRI & LSHTM Uganda Research Unit and Makarere University John’s Hopkins University in Uganda will develop a model using data collected in real-time to identify the risk factors for adverse pregnancy and infant outcomes caused by the COVID-19 pandemic that can be used to rapidly inform interventions. Lockdowns can severely impact women giving birth and access to maternal, neonatal, and child healthcare. They will apply a Bayesian multivariate network meta-analysis, (a methodology that simultaneously analyses multiple outcomes and multiple treatments, allowing more studies to contribute towards each outcome and treatment comparison) to electronic medical records, leveraging existing data on the effect of the lockdown on antenatal and delivery services for over 30,000 pregnancies, vaccination data, and information on COVID-19 infection in pregnancy and infancy. They will also build a user-friendly data dashboard to support decision-making on infection prevention and control at the Ministry of Health.
To improve maternal, neonatal, and child health in Uganda during pandemics by using a modelling approach on existing data from 30,000 pregnancies to identify risk factors for adverse outcomes.