title: Advances in mapping malaria for elimination: fine resolution modelling of Plasmodium falciparum incidence.
abstract: The long-term goal of the global effort to tackle malaria is national and regional elimination and eventually eradication. Fine scale multi-temporal mapping in low malaria transmission settings remains a challenge and the World Health Organisation propose use of surveillance in elimination settings. Here, we show how malaria incidence can be modelled at a fine spatial and temporal resolution from health facility data to help focus surveillance and control to population not attending health facilities. Using Namibia as a case study, we predicted the incidence of malaria, via a Bayesian spatio-temporal model, at a fine spatial resolution from parasitologically confirmed malaria cases and incorporated metrics on healthcare use as well as measures of uncertainty associated with incidence predictions. We then combined the incidence estimates with population maps to estimate clinical burdens and show the benefits of such mapping to identifying areas and seasons that can be targeted for improved surveillance and interventions. Fine spatial resolution maps produced using this approach were then used to target resources to specific local populations, and to specific months of the season. This remote targeting can be especially effective where the population distribution is sparse and further surveillance can be limited to specific local areas.
authors.affiliation: WorldPop, Geography and Environment, University of Southampton, Southampton, UK.|Flowminder Foundation, Stockholm, Sweden.
authors.forename: Victor A
authors.initials: VA
authors.lastname: Alegana
authors.affiliation: WorldPop, Geography and Environment, University of Southampton, Southampton, UK.|Faculty of Science and Technology, Lancaster University, UK.|School of Geography, Archaeology and Palaeoecology, Queen's University Belfast, Belfast BT7 1NN, Northern Ireland, UK.
authors.forename: Peter M
authors.initials: PM
authors.lastname: Atkinson
authors.affiliation: WorldPop, Geography and Environment, University of Southampton, Southampton, UK.|Clinton Health Access Initiative, Boston, MA, USA.
authors.forename: Christopher
authors.initials: C
authors.lastname: Lourenço
authors.affiliation: WorldPop, Geography and Environment, University of Southampton, Southampton, UK.|Flowminder Foundation, Stockholm, Sweden.
authors.forename: Nick W
authors.initials: NW
authors.lastname: Ruktanonchai
authors.affiliation: WorldPop, Geography and Environment, University of Southampton, Southampton, UK.|Flowminder Foundation, Stockholm, Sweden.
authors.forename: Claudio
authors.initials: C
authors.lastname: Bosco
authors.affiliation: WorldPop, Geography and Environment, University of Southampton, Southampton, UK.|Flowminder Foundation, Stockholm, Sweden.
authors.forename: Elisabeth Zu
authors.initials: EZ
authors.lastname: Erbach-Schoenberg
authors.affiliation: Clinton Health Access Initiative, Boston, MA, USA.
authors.forename: Bradley
authors.initials: B
authors.lastname: Didier
authors.affiliation: Clinton Health Access Initiative, Boston, MA, USA.
authors.forename: Deepa
authors.initials: D
authors.lastname: Pindolia
authors.affiliation: Clinton Health Access Initiative, Boston, MA, USA.
authors.forename: Arnaud
authors.initials: A
authors.lastname: Le Menach
authors.affiliation: National Vector-borne Diseases Control Programme, Directorate of Special Programmes, Ministry of Health and Social Services, Windhoek, Namibia.
authors.forename: Stark
authors.initials: S
authors.lastname: Katokele
authors.affiliation: National Vector-borne Diseases Control Programme, Directorate of Special Programmes, Ministry of Health and Social Services, Windhoek, Namibia.
authors.forename: Petrina
authors.initials: P
authors.lastname: Uusiku
authors.affiliation: WorldPop, Geography and Environment, University of Southampton, Southampton, UK.|Flowminder Foundation, Stockholm, Sweden.
authors.forename: Andrew J
authors.initials: AJ
authors.lastname: Tatem
mesh_terms: D001499:Bayes Theorem; D006801:Humans; D015994:Incidence; D016778:Malaria, Falciparum / Q000453:epidemiology* / Q000635:transmission; D015233:Models, Statistical; D009276:Namibia / Q000453:epidemiology; D011159:Population Surveillance / Q000379:methods*; D012621:Seasons; D013029:Space-Time Clustering