Accelerating the detection and treatment of perinatal depression and anxiety in low- and middle-income countries through advanced analytics

Perinatal mood disorders (depression and anxiety) are common worldwide and have major negative consequences for parent and child. Expanded screening, personalized medicine and risk-guided care have the potential to transform early identification and treatment of perinatal mood disorders, but research is needed in three areas. First, among women without antenatal depression, can risk-guided care that tailors the intensity of follow-up improve early identification of incident postnatal mood disorders? Second, among women with antenatal depression, can risk-guided care that tailors the intensity of treatment improve outcomes? Third, can risk-guided care achieve better overall mental health outcomes and improve resource efficiency for the health system overall? Such work is particularly critical in low-resource settings with limited mental health resources. Shaped by our collaborators with lived experience and guided by theory, we will apply advanced data science to four perinatal cohorts in low-resource countries to quantify the risk of perinatal mood disorder onset, early progression, and treatment non-response. We will then complete a randomized trial to test, compared to one-size-fits-all care, whether risk-guided perinatal care and follow-up improve outcomes and health system efficiency. This multi-country work will set the stage for a step- change in perinatal care to maximally impact mental health.