Lancaster University

1. Development of spatio-temporal models and associated statistical methods to enable forward projections of the geographical distribution of prevalence, and hence the risk of resurgence, by combining model-based geostatistical analysis with mechanistic predictive modelling of disease transmission dynamics, using the most recent available data on disease prevalence and environmental risk-factors.

2. To use the results from aim 1 to derive statistically efficient and affordable designs for networks of sentinel sites to enable continued monitoring of prevalence in areas at high risk of resurgence."

Can geostatistical tools be used to develop a stop IDA strategy for LF that can measure <1% Mf prevalence in adults?

To develop a loa algorithm that can predict the risk of a community having great than a set threshold value of individuals who have high intensity microfilaremia.