This study aims to address critical diagnostic and data gaps in tuberculosis (TB) care among pregnant and postpartum women in Guinea-Bissau, a high-burden, resource-limited setting. Recognising that current TB screening during antenatal care (ANC) relies largely on unstructured symptom questions, the study will integrate more systematic and innovative approaches into routine maternal health services.
The project will implement the Bandim TBscore II as a structured triage tool to classify symptom severity and guide referrals. To strengthen diagnostic capacity, two novel tools will be evaluated: stool-based GeneXpert testing (a method recommended in children and explored here as a feasible alternative for pregnant women) and artificial intelligence-powered chest X-ray interpretation software designed to enhance TB detection where radiological expertise is lacking.
The study will also generate comprehensive, population-based data on TB and TB infection (TBI) among pregnant, postpartum women and women of reproductive age in Guinea-Bissau. The results are intended to inform health policy, both locally and in high-income countries, by providing evidence to improve TB screening protocols and care for this vulnerable group. Ultimately, the study seeks to develop scalable strategies that can be replicated across low- and middle-income countries to advance maternal and child health and support global TB eradication efforts.