Bayesian belief network modelling of household food security in rural South Africa

BMC Public Health

Thomas House¹  F. Xavier Gómez-Olivé²  Robert W. Eyre³  Frances E. Griffiths⁴ 

[1] Department of Mathematics, University of Manchester;Medical Research Council/Wits University Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand;Spectra Analytics;Warwick Medical School, University of Warwick;

关键词: Directed acyclic graph;    HDSS;    Expert elicitation;   

DOI  :  10.1186/s12889-021-10938-y

来源: DOAJ

【 摘 要 】

Abstract Background Achieving food security remains a key challenge for public policy throughout the world. As such, understanding the determinants of food insecurity and the causal relationships between them is an important scientific question. We aim to construct a Bayesian belief network model of food security in rural South Africa to act as a tool for decision support in the design of interventions. Methods Here, we use data from the Agincourt Health and Socio-demographic Surveillance System (HDSS) study area, which is close to the Mozambique border in a low-income region of South Africa, together with Bayesian belief network (BBN) methodology to address this question. Results We find that a combination of expert elicitation and learning from data produces the most credible set of causal relationships, as well as the greatest predictive performance with 10-fold cross validation resulting in a Briers score 0.0846, information reward of 0.5590, and Bayesian information reward of 0.0057. We report the resulting model as a directed acyclic graph (DAG) that can be used to model the expected effects of complex interventions to improve food security. Applications to sensitivity analyses and interventional simulations show ways the model can be applied as tool for decision support for human experts in deciding on interventions. Conclusions The resulting models can form the basis of the iterative generation of a robust causal model of household food security in the Agincourt HDSS study area and in other similar populations.

【 授权许可】

Unknown