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Spatial effects on the multiplicity of Plasmodium falciparum infections

Karl, Stephan, White, Michael T., Milne, George J., Gurarie, David, Hay, Simon I., Barry, Alyssa E., Felger, Ingrid and Mueller, Ivo 2016, Spatial effects on the multiplicity of Plasmodium falciparum infections, PLoS ONE, vol. 11, no. 10, pp. 1-20, doi: 10.1371/journal.pone.0164054.

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Title Spatial effects on the multiplicity of Plasmodium falciparum infections
Author(s) Karl, Stephan
White, Michael T.
Milne, George J.
Gurarie, David
Hay, Simon I.
Barry, Alyssa E.ORCID iD for Barry, Alyssa E. orcid.org/0000-0002-1189-2310
Felger, Ingrid
Mueller, Ivo
Journal name PLoS ONE
Volume number 11
Issue number 10
Start page 1
End page 20
Total pages 20
Publisher Public Libraries of Science
Place of publication San Francisco, Calif.
Publication date 2016-10-06
ISSN 1932-6203
Keyword(s) Science & Technology
Multidisciplinary Sciences
Science & Technology - Other Topics
MARK-RELEASE-RECAPTURE
ANOPHELES-GAMBIAE
MALARIA TRANSMISSION
VECTOR CONTROL
HOST-SEEKING
POPULATION
DIPTERA
DISEASE
VIVAX
CULICIDAE
Summary © 2016 Karl et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 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.
Language eng
DOI 10.1371/journal.pone.0164054
Indigenous content off
Field of Research 110799 Immunology not elsewhere classified
HERDC Research category C1 Refereed article in a scholarly journal
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30136657

Document type: Journal Article
Collections: Faculty of Health
School of Medicine
Open Access Collection
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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.