Mapping and predicting the potential spread of malaria in Southeast Asia and Bangladesh to better inform targeting of malaria control and elimination interventions

Background Spread of malaria and antimalarial resistance through human movement presents major threats to current goals to eliminate the disease. It is a WHO priority to understand and target mobile and migrant groups and travel hotpots to reduce malaria risk from human mobility. Bordering the Greater Mekong Subregion (GMS), Southeast Bangladesh is a potentially important route of spread to India and beyond, but information on travel patterns in this area is lacking. The aims were to collect field data and develop methodology to map and understand sources and sinks of malaria spread to inform malaria surveillance and elimination strategies first in Bangladesh and then apply the methods to other countries in the GMS. Methods A systematic review of infectious diseases in relation to spread of infection was carried out to identify the main gaps in methods of measurement of human mobility data. A standardised short travel survey was then used to interview patients with a toolkit and software developed to analyse it and inform malaria elimination strategies of malaria control programmes. Results An initial pilot study in Bangladesh identified key routes of transmission, demographic groups, sources, and sinks predicting spread of malaria. This was then extended to India and the GMS, with a multi-country standardised dataset of 7790 travel surveys collected and analysed to understand the source and sink of artemisinin resistance spread. Finally, software to visualize travel patterns, TraVis was developed to review transmission routes of malaria for national malaria control programmes. Conclusion The epidemiology of malaria is complex and spatially heterogeneous, especially in low transmission setting bordered by high transmission areas. As interventions are targeted at a higher resolution granular level, targeting mobile groups, it is essential that it is backed by high quality human population movement data systematically with simplified surveys that provide combined information on location – who, where and why one is travelling.