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Spatial modelling of mosquito-borne diseases: a systematic review of data and methods used to inform spatial connectivity
Sophie Lee (London School of Hygiene & Tropical Medicine)
Mosquito-borne diseases, such as malaria and dengue, pose a high social and economic burden on many tropical and sub-tropical countries. Transmission of mosquito-borne diseases is spatially heterogeneous due to the movement of hosts and vectors, differences in vector control, and variation in environmental factors. When modelling transmission of these diseases, we make assumptions about how spatial connectivity arises. These assumptions depend on a number of factors and differ between diseases. For example, commuting patterns within a city may be more important for infections transmitted by day biting Aedes mosquitoes than Anopheles, which tend to bite at night.
To understand how modelling techniques account for spatial connectivity between regions, we have carried out a systematic review of studies that spatially model the transmission of mosquito-borne diseases to humans. 154 studies were found to meet eligibility criteria. We identified types of data used to inform models and assumptions researchers made about how spatial connectivity arises. Preliminary results show that the number of spatial modelling studies have increased exponentially in recent years. The majority of papers assumed that adjacent regions were connected or that connectivity decays as distance between observations increases. However, an increasing number of studies have explored the impact of human movement on transmission, using mobile phone GPS, flight data and mathematical models, such as radiation models, that aim to replicate human commuting behaviour. This work will provide the first comprehensive overview of spatial modelling techniques applied to mosquito-borne disease transmission, spatially explicit data used to inform those models, and assumptions researchers have made about how connectivity between geographical regions arises. This review will provide guidance to those embarking on understanding the role of spatial connectivity when modelling mosquito-borne disease transmission.