title: The applications of model-based geostatistics in helminth epidemiology and control.
abstract: Funding agencies are dedicating substantial resources to tackle helminth infections. Reliable maps of the distribution of helminth infection can assist these efforts by targeting control resources to areas of greatest need. The ability to define the distribution of infection at regional, national and subnational levels has been enhanced greatly by the increased availability of good quality survey data and the use of model-based geostatistics (MBG), enabling spatial prediction in unsampled locations. A major advantage of MBG risk mapping approaches is that they provide a flexible statistical platform for handling and representing different sources of uncertainty, providing plausible and robust information on the spatial distribution of infections to inform the design and implementation of control programmes. Focussing on schistosomiasis and soil-transmitted helminthiasis, with additional examples for lymphatic filariasis and onchocerciasis, we review the progress made to date with the application of MBG tools in large-scale, real-world control programmes and propose a general framework for their application to inform integrative spatial planning of helminth disease control programmes.
authors.affiliation: University of Queensland, School of Population Health, Herston, Queensland, Australia.
authors.forename: Ricardo J Soares
authors.initials: RJ
authors.lastname: Magalhães
authors.forename: Archie C A
authors.initials: AC
authors.lastname: Clements
authors.forename: Anand P
authors.initials: AP
authors.lastname: Patil
authors.forename: Peter W
authors.initials: PW
authors.lastname: Gething
authors.forename: Simon
authors.initials: S
authors.lastname: Brooker
mesh_terms: D000818:Animals; D003140:Communicable Disease Control; D006373:Helminthiasis / Q000453:epidemiology* / Q000517:prevention & control; D006376:Helminths / Q000502:physiology*; D015233:Models, Statistical; D015995:Prevalence