Authors

Discussion

A secondary analysis of epidemiological data collected from SAC in Mangochi District, Lake Malawi to assess age-co-infection profiles and follows on from investigations reported in Part A. Part B shows a visual interpretation of the age of SAC versus school prevalence for UGS, IS and co-infection using heatmaps. Further, disease trends across the schools were able to be drawn from these heatmaps. Next, a repeat of Part A using a generalized additive model was used to model the co-infection binary data using a logistic regression with Bernoulli distribution and predict the co-infection prevalence as SAC aged. 

Part B, study found a similar pattern to Part A, an increasing prevalence of IS and UGS co-infection for SAC up to around 11 before decreasing there afterwards. The peak in prevalence around age 11 requires further investigation with follow-up studies. In further consideration of Part A and Part B, to explore spatial heterogeneity, an analysis of malacological niche maps and a statistically-grounded dynamical infection model is planned. This hopes to frame the main local determinants of infection in SAC and how future praziquantel treatment targeted at schools could be better optimised.