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Characterising malaria connectivity using malaria indicator survey data

Guerra, Carlos A ; Citron, Daniel T ; García, Guillermo A ; Smith, David L

Malaria journal, 2019-12, Vol.18 (1), p.440-12, Article 440 [Periódico revisado por pares]

England: BioMed Central Ltd

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Título:
Characterising malaria connectivity using malaria indicator survey data
Autor: Guerra, Carlos A ; Citron, Daniel T ; García, Guillermo A ; Smith, David L
Assuntos: Aquatic insects ; Data ; Equatorial Guinea ; Equatorial Guinea - epidemiology ; Health aspects ; Human diseases ; Human mobility ; Human movement ; Human travel ; Humans ; Importation ; Incidence ; Infections ; Islands ; Malaria ; Malaria - epidemiology ; Malaria connectivity ; Malaria importation ; Malaria indicator survey ; Medical research ; Mobility ; Mosquitoes ; Parasites ; Polls & surveys ; Prevalence ; Risk ; Subpopulations ; Surveying ; Surveys ; Travel ; Travel - statistics & numerical data ; Travelers ; Vector-borne diseases
É parte de: Malaria journal, 2019-12, Vol.18 (1), p.440-12, Article 440
Descrição: Malaria connectivity describes the flow of parasites among transmission sources and sinks within a given landscape. Because of the spatial and temporal scales at which parasites are transported by their hosts, malaria sub-populations are largely defined by mosquito movement and malaria connectivity among them is largely driven by human movement. Characterising malaria connectivity thus requires characterising human travel between areas with differing levels of exposure to malaria. Whilst understanding malaria connectivity is fundamental for optimising interventions, particularly in areas seeking or sustaining elimination, there is a dearth of human movement data required to achieve this goal. Malaria indicator surveys (MIS) are a generally under utilised but potentially rich source of travel data that provide a unique opportunity to study simple associations between malaria infection and human travel in large population samples. This paper shares the experience working with MIS data from Bioko Island that revealed programmatically useful information regarding malaria importation through human travel. Simple additions to MIS questionnaires greatly augmented the level of detail of the travel data, which can be used to characterise human travel patterns and malaria connectivity to assist targeting interventions. It is argued that MIS potentially represent very important and timely sources of travel data that need to be further exploited.
Editor: England: BioMed Central Ltd
Idioma: Inglês

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Characterising malaria connectivity using malaria indicator survey data

Guerra, Carlos A ; Citron, Daniel T ; García, Guillermo A ; Smith, David L

England: BioMed Central Ltd

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