In low-middle-income countries, monitoring and estimating the burden of infectious diseases in a post-elimination setting can be quite challenging, due to the low levels of transmission. In this context the ability to assess the likelihood of resurgence through efficient surveillance becomes increasingly important. In this work, we illustrate how geostatistical and mathematical models can be used to design surveillance systems for neglected tropical diseases (NTDs). We present a case study on lymphatic filariasis (LF) in Malawi. LF is an NTD that has been identified as a leading cause of global disability, particularly in low-income regions. Using historical data from repeated cross-sectional surveys, we illustrate how the combined use of geostatistical methods and mechanistic models can inform the identification of sentinel sites. We then demonstrate the performance of this surveillance system under different scenarios of LF resurgence. Finally, we discuss an alternative approach for designing the surveillance system that avoids the use of mechanistic models and argue that this can be more generally applied to other environmentally derived diseases. This work is a joint collaboration from Lancaster University, Birmingham University and the University of Surrey. Dr Lucinda Hadley will be presenting on behalf of the three groups.