Spatial Effects on the Multiplicity of Plasmodium falciparum Infections.

As malaria is being pushed back on many frontiers and global case numbers are declining, accurate measurement and prediction of transmission becomes increasingly difficult. Low transmission settings are characterised by high levels of spatial heterogeneity, which stands in stark contrast to the wide...

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Main Authors: Stephan Karl, Michael T White, George J Milne, David Gurarie, Simon I Hay, Alyssa E Barry, Ingrid Felger, Ivo Mueller
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2016-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC5053403?pdf=render
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spelling doaj-e1c1096773ba47088a9c31ba4d9c310b2020-11-25T01:24:21ZengPublic Library of Science (PLoS)PLoS ONE1932-62032016-01-011110e016405410.1371/journal.pone.0164054Spatial Effects on the Multiplicity of Plasmodium falciparum Infections.Stephan KarlMichael T WhiteGeorge J MilneDavid GurarieSimon I HayAlyssa E BarryIngrid FelgerIvo MuellerAs malaria is being pushed back on many frontiers and global case numbers are declining, accurate measurement and prediction of transmission becomes increasingly difficult. Low transmission settings are characterised by high levels of spatial heterogeneity, which stands in stark contrast to the widely used assumption of spatially homogeneous transmission used in mathematical transmission models for malaria. In the present study an individual-based mathematical malaria transmission model that incorporates multiple parasite clones, variable human exposure and duration of infection, limited mosquito flight distance and most importantly geographically heterogeneous human and mosquito population densities was used to illustrate the differences between homogeneous and heterogeneous transmission assumptions when aiming to predict surrogate indicators of transmission intensity such as population parasite prevalence or multiplicity of infection (MOI). In traditionally highly malaria endemic regions where most of the population harbours malaria parasites, humans are often infected with multiple parasite clones. However, studies have shown also in areas with low overall parasite prevalence, infection with multiple parasite clones is a common occurrence. Mathematical models assuming homogeneous transmission between humans and mosquitoes cannot explain these observations. Heterogeneity of transmission can arise from many factors including acquired immunity, body size and occupational exposure. In this study, we show that spatial heterogeneity has a profound effect on predictions of MOI and parasite prevalence. We illustrate, that models assuming homogeneous transmission underestimate average MOI in low transmission settings when compared to field data and that spatially heterogeneous models predict stable transmission at much lower overall parasite prevalence. Therefore it is very important that models used to guide malaria surveillance and control strategies in low transmission and elimination settings take into account the spatial features of the specific target area, including human and mosquito vector distribution.http://europepmc.org/articles/PMC5053403?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Stephan Karl
Michael T White
George J Milne
David Gurarie
Simon I Hay
Alyssa E Barry
Ingrid Felger
Ivo Mueller
spellingShingle Stephan Karl
Michael T White
George J Milne
David Gurarie
Simon I Hay
Alyssa E Barry
Ingrid Felger
Ivo Mueller
Spatial Effects on the Multiplicity of Plasmodium falciparum Infections.
PLoS ONE
author_facet Stephan Karl
Michael T White
George J Milne
David Gurarie
Simon I Hay
Alyssa E Barry
Ingrid Felger
Ivo Mueller
author_sort Stephan Karl
title Spatial Effects on the Multiplicity of Plasmodium falciparum Infections.
title_short Spatial Effects on the Multiplicity of Plasmodium falciparum Infections.
title_full Spatial Effects on the Multiplicity of Plasmodium falciparum Infections.
title_fullStr Spatial Effects on the Multiplicity of Plasmodium falciparum Infections.
title_full_unstemmed Spatial Effects on the Multiplicity of Plasmodium falciparum Infections.
title_sort spatial effects on the multiplicity of plasmodium falciparum infections.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2016-01-01
description As malaria is being pushed back on many frontiers and global case numbers are declining, accurate measurement and prediction of transmission becomes increasingly difficult. Low transmission settings are characterised by high levels of spatial heterogeneity, which stands in stark contrast to the widely used assumption of spatially homogeneous transmission used in mathematical transmission models for malaria. In the present study an individual-based mathematical malaria transmission model that incorporates multiple parasite clones, variable human exposure and duration of infection, limited mosquito flight distance and most importantly geographically heterogeneous human and mosquito population densities was used to illustrate the differences between homogeneous and heterogeneous transmission assumptions when aiming to predict surrogate indicators of transmission intensity such as population parasite prevalence or multiplicity of infection (MOI). In traditionally highly malaria endemic regions where most of the population harbours malaria parasites, humans are often infected with multiple parasite clones. However, studies have shown also in areas with low overall parasite prevalence, infection with multiple parasite clones is a common occurrence. Mathematical models assuming homogeneous transmission between humans and mosquitoes cannot explain these observations. Heterogeneity of transmission can arise from many factors including acquired immunity, body size and occupational exposure. In this study, we show that spatial heterogeneity has a profound effect on predictions of MOI and parasite prevalence. We illustrate, that models assuming homogeneous transmission underestimate average MOI in low transmission settings when compared to field data and that spatially heterogeneous models predict stable transmission at much lower overall parasite prevalence. Therefore it is very important that models used to guide malaria surveillance and control strategies in low transmission and elimination settings take into account the spatial features of the specific target area, including human and mosquito vector distribution.
url http://europepmc.org/articles/PMC5053403?pdf=render
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