A geostatistical method for analysing data from multiple Loa loa diagnostic tools Seminar

The elimination of onchocerciasis through community-based Mass Drug Administration (MDA) of ivermectin (Mectizan) is hampered by co-endemicity of Loa loa, as individuals who are highly co-infected with Loa loa parasites can suffer serious and occasionally fatal neurological reactions from the drug. Testing all individuals participating in MDA has some operational constraints ranging from the cost to limited availability of diagnostic tools. Therefore, there is a need for a way to establish whether an area is safe for MDA using the prevalence of loiasis derived from multiple diagnostic tools. Existing statistical methods only focus on using data from one diagnostic tool and ignore the potential information that could be derived from other datasets. In this talk, I will talk about how we address this issue by developing a joint geostatistical model that combines data from multiple Loa loa diagnostic tools. I will present how we developed the model and our method for inference. We applied this framework to Loa loa data from Gabon. We also propose a two-stage strategy to identify areas that are safe for MDA. Lastly, I will discuss how this work contributes to the global effort towards the elimination of onchocerciasis as a public health problem by potentially reducing the time and cost required to establish whether an area is safe for MDA.

Speaker Information

Dr Olatunji Johnson – Lecturer in Statistics, The University of Manchester

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