Studying multiple causes of death in LMICs in the absence of death certificates : taking advantage of probabilistic cause-of-death estimation methods (InterVA-4)

In low- and middle-income countries (LMICs), the burden of non-communicable diseases is increasing due to the combination of population aging and lifestyle changes. While interest in multimorbidity has been rising to study more precisely the complex morbid processes that adults experience, health data in LMICs are scarce and rarely allow such investigations. Focusing on multimorbidity leading to death, we aim to develop an approach to estimate multiple causes of death using available data. In settings where certification of death by physicians is not available, verbal autopsies (VAs) have been developed to diagnose likely causes of death from information collected via a structured interview with final caregivers about the signs and symptoms leading up to death. With an increasing use of probabilistic models to interpret VAs, we investigate their potential for identifying multiple causes using a database of 72,330 adult deaths (15 and older) from 22 Health and Demographic Surveillance System (HDSS) sites located in Asia and Africa, and detailed VA data from the Ouagadougou HDSS in Burkina Faso (1,700 deaths). The Bayesian model InterVA-4 attributes multiple likely causes to 11% of deaths. However, some combinations result more from uncertain diagnosis than from multimorbidity. Elaborating an index of similarity between causes based on the InterVA’s probability matrix, we aim to differentiate competing causes (uncertainty) from co-occurring causes (multimorbidity). Selecting the most dissimilar associations of causes, we highlight the importance of associations between infectious and non-communicable diseases, as well as the burden of diabetes and cardiovascular diseases among the identified multimorbidity.