Spatial Effects on the Multiplicity of Plasmodium falciparum Infections
Identifieur interne : 002804 ( Pmc/Curation ); précédent : 002803; suivant : 002805Spatial Effects on the Multiplicity of Plasmodium falciparum Infections
Auteurs : Stephan Karl [Australie, Papouasie-Nouvelle-Guinée] ; Michael T. White [Australie, Royaume-Uni] ; George J. Milne [Australie] ; David Gurarie [États-Unis] ; Simon I. Hay [États-Unis] ; Alyssa E. Barry [Australie] ; Ingrid Felger [Suisse] ; Ivo Mueller [Australie, France]Source :
- PLoS ONE [ 1932-6203 ] ; 2016.
Abstract
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:
DOI: 10.1371/journal.pone.0164054
PubMed: 27711149
PubMed Central: 5053403
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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.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Bousema, T" uniqKey="Bousema T">T Bousema</name></author><author><name sortKey="Drakeley, C" uniqKey="Drakeley C">C Drakeley</name></author><author><name sortKey="Gesase, S" uniqKey="Gesase S">S Gesase</name></author><author><name sortKey="Hashim, R" uniqKey="Hashim R">R Hashim</name></author><author><name sortKey="Magesa, S" uniqKey="Magesa S">S Magesa</name></author><author><name sortKey="Mosha, F" uniqKey="Mosha F">F Mosha</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Bejon, P" uniqKey="Bejon P">P Bejon</name></author><author><name sortKey="Williams, Tn" uniqKey="Williams T">TN 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<front><journal-meta><journal-id journal-id-type="nlm-ta">PLoS One</journal-id><journal-id journal-id-type="iso-abbrev">PLoS ONE</journal-id><journal-id journal-id-type="publisher-id">plos</journal-id><journal-id journal-id-type="pmc">plosone</journal-id><journal-title-group><journal-title>PLoS ONE</journal-title></journal-title-group><issn pub-type="epub">1932-6203</issn><publisher><publisher-name>Public Library of Science</publisher-name><publisher-loc>San Francisco, CA USA</publisher-loc></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">27711149</article-id><article-id pub-id-type="pmc">5053403</article-id><article-id pub-id-type="doi">10.1371/journal.pone.0164054</article-id><article-id pub-id-type="publisher-id">PONE-D-16-23772</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Medicine and Health Sciences</subject><subj-group><subject>Epidemiology</subject><subj-group><subject>Disease Vectors</subject><subj-group><subject>Insect Vectors</subject><subj-group><subject>Mosquitoes</subject></subj-group></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Biology and Life Sciences</subject><subj-group><subject>Organisms</subject><subj-group><subject>Animals</subject><subj-group><subject>Invertebrates</subject><subj-group><subject>Arthropoda</subject><subj-group><subject>Insects</subject><subj-group><subject>Mosquitoes</subject></subj-group></subj-group></subj-group></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Medicine and Health Sciences</subject><subj-group><subject>Parasitic Diseases</subject></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Medicine and Health Sciences</subject><subj-group><subject>Parasitic Diseases</subject><subj-group><subject>Malaria</subject></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Medicine and Health Sciences</subject><subj-group><subject>Tropical Diseases</subject><subj-group><subject>Malaria</subject></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Biology and Life Sciences</subject><subj-group><subject>Molecular Biology</subject><subj-group><subject>Molecular Biology Techniques</subject><subj-group><subject>Cloning</subject></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Research and Analysis Methods</subject><subj-group><subject>Molecular Biology Techniques</subject><subj-group><subject>Cloning</subject></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Biology and Life Sciences</subject><subj-group><subject>Organisms</subject><subj-group><subject>Protozoans</subject><subj-group><subject>Parasitic Protozoans</subject><subj-group><subject>Malarial Parasites</subject></subj-group></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Medicine and Health Sciences</subject><subj-group><subject>Infectious Diseases</subject><subj-group><subject>Vector-Borne Diseases</subject></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Earth Sciences</subject><subj-group><subject>Geography</subject><subj-group><subject>Human Geography</subject><subj-group><subject>Human Mobility</subject></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Social Sciences</subject><subj-group><subject>Human Geography</subject><subj-group><subject>Human Mobility</subject></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Biology and Life Sciences</subject><subj-group><subject>Population Biology</subject><subj-group><subject>Population Dynamics</subject><subj-group><subject>Geographic Distribution</subject></subj-group></subj-group></subj-group></subj-group></article-categories><title-group><article-title>Spatial Effects on the Multiplicity of <italic>Plasmodium falciparum</italic> Infections</article-title><alt-title alt-title-type="running-head">Spatial Effects on Multiplicity of Infection</alt-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Karl</surname><given-names>Stephan</given-names></name><xref ref-type="aff" rid="aff001"><sup>1</sup></xref><xref ref-type="aff" rid="aff002"><sup>2</sup></xref><xref ref-type="aff" rid="aff003"><sup>3</sup></xref><xref ref-type="corresp" rid="cor001">*</xref></contrib><contrib contrib-type="author"><name><surname>White</surname><given-names>Michael T.</given-names></name><xref ref-type="aff" rid="aff001"><sup>1</sup></xref><xref ref-type="aff" rid="aff004"><sup>4</sup></xref></contrib><contrib contrib-type="author"><name><surname>Milne</surname><given-names>George J.</given-names></name><xref ref-type="aff" rid="aff005"><sup>5</sup></xref></contrib><contrib contrib-type="author"><name><surname>Gurarie</surname><given-names>David</given-names></name><xref ref-type="aff" rid="aff006"><sup>6</sup></xref></contrib><contrib contrib-type="author"><name><surname>Hay</surname><given-names>Simon I.</given-names></name><xref ref-type="aff" rid="aff007"><sup>7</sup></xref><xref ref-type="aff" rid="aff008"><sup>8</sup></xref></contrib><contrib contrib-type="author"><name><surname>Barry</surname><given-names>Alyssa E.</given-names></name><xref ref-type="aff" rid="aff001"><sup>1</sup></xref><xref ref-type="aff" rid="aff002"><sup>2</sup></xref></contrib><contrib contrib-type="author"><name><surname>Felger</surname><given-names>Ingrid</given-names></name><xref ref-type="aff" rid="aff009"><sup>9</sup></xref><xref ref-type="aff" rid="aff010"><sup>10</sup></xref></contrib><contrib contrib-type="author"><name><surname>Mueller</surname><given-names>Ivo</given-names></name><xref ref-type="aff" rid="aff001"><sup>1</sup></xref><xref ref-type="aff" rid="aff002"><sup>2</sup></xref><xref ref-type="aff" rid="aff011"><sup>11</sup></xref></contrib></contrib-group><aff id="aff001"><label>1</label><addr-line>Population-Based Biology Division, Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia</addr-line></aff><aff id="aff002"><label>2</label><addr-line>Department of Medical Biology, University of Melbourne, Parkville, Victoria, Australia</addr-line></aff><aff id="aff003"><label>3</label><addr-line>Vector-borne Diseases Unit, Papua New Guinea Insititute of Medical Research, Madang, Madang Province, Papua New Guinea</addr-line></aff><aff id="aff004"><label>4</label><addr-line>MRC Centre for Outbreak Analysis & Modelling, Department of Infectious Disease Epidemiology, Imperial College, London, United Kingdom</addr-line></aff><aff id="aff005"><label>5</label><addr-line>School of Computer Science and Software Engineering, The University of Western Australia, Perth, WA, Australia</addr-line></aff><aff id="aff006"><label>6</label><addr-line>Department of Mathematics, Applied Mathematics and Statistics, Case Western Reserve University, Cleveland, Ohio, United States of America</addr-line></aff><aff id="aff007"><label>7</label><addr-line>Institute for Health Metrics and Evaluation, Seattle, Washington, United States of America</addr-line></aff><aff id="aff008"><label>8</label><addr-line>Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America</addr-line></aff><aff id="aff009"><label>9</label><addr-line>Department of Medical Parasitology and Infection Biology Swiss Tropical and Public Health Institute, Basel, Switzerland</addr-line></aff><aff id="aff010"><label>10</label><addr-line>University of Basel, Basel, Switzerland</addr-line></aff><aff id="aff011"><label>11</label><addr-line>Malaria: Parasites and Hosts Unit, Department of Parasites & Insect Vectors, Institut Pasteur, Paris, France</addr-line></aff><contrib-group><contrib contrib-type="editor"><name><surname>Marinho</surname><given-names>Claudio Romero Farias</given-names></name><role>Editor</role><xref ref-type="aff" rid="edit1"></xref></contrib></contrib-group><aff id="edit1"><addr-line>Universidade de Sao Paulo Instituto de Ciencias Biomedicas, BRAZIL</addr-line></aff><author-notes><fn fn-type="COI-statement" id="coi001"><p><bold>Competing Interests: </bold>The authors have declared that no competing interests exist.</p></fn><fn fn-type="con"><p><list list-type="simple"><list-item><p><bold>Conceptualization:</bold> SK MTW SIH IF AB IM.</p></list-item><list-item><p><bold>Data curation:</bold> SK IF AB MTW.</p></list-item><list-item><p><bold>Formal analysis:</bold> SK MTW.</p></list-item><list-item><p><bold>Funding acquisition:</bold> SK MTW IM AB IF.</p></list-item><list-item><p><bold>Investigation:</bold> SK MTW.</p></list-item><list-item><p><bold>Methodology:</bold> SK MTW GJM DG.</p></list-item><list-item><p><bold>Project administration:</bold> SK MTW IF AB IM.</p></list-item><list-item><p><bold>Resources:</bold> SK IM AB IF.</p></list-item><list-item><p><bold>Software:</bold> SK GJM DG.</p></list-item><list-item><p><bold>Supervision:</bold> SK MTW SIH IF AB IM.</p></list-item><list-item><p><bold>Validation:</bold> SK MTW DG IM.</p></list-item><list-item><p><bold>Visualization:</bold> SK MTW.</p></list-item><list-item><p><bold>Writing – original draft:</bold> SK MTW IF SIH AB IM.</p></list-item><list-item><p><bold>Writing – review & editing:</bold> SK MTW DG GJM SIH IF AB IM.</p></list-item></list></p></fn><corresp id="cor001">* E-mail: <email>karl@wehi.edu.au</email></corresp></author-notes><pub-date pub-type="epub"><day>6</day><month>10</month><year>2016</year></pub-date><pub-date pub-type="collection"><year>2016</year></pub-date><volume>11</volume><issue>10</issue><elocation-id>e0164054</elocation-id><history><date date-type="received"><day>5</day><month>7</month><year>2016</year></date><date date-type="accepted"><day>19</day><month>9</month><year>2016</year></date></history><permissions><copyright-statement>© 2016 Karl et al</copyright-statement><copyright-year>2016</copyright-year><copyright-holder>Karl et al</copyright-holder><license xlink:href="http://creativecommons.org/licenses/by/4.0/"><license-p>This is an open access article distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution License</ext-link>, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</license-p></license></permissions><self-uri content-type="pdf" xlink:href="pone.0164054.pdf"></self-uri><abstract><p>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.</p></abstract><funding-group><award-group id="award001"><funding-source><institution-wrap><institution-id institution-id-type="funder-id">http://dx.doi.org/10.13039/501100000925</institution-id><institution>National Health and Medical Research Council</institution></institution-wrap></funding-source><award-id>1052760</award-id><principal-award-recipient><name><surname>Karl</surname><given-names>Stephan</given-names></name></principal-award-recipient></award-group><award-group id="award002"><funding-source><institution-wrap><institution-id institution-id-type="funder-id">http://dx.doi.org/10.13039/501100000265</institution-id><institution>Medical Research Council</institution></institution-wrap></funding-source><principal-award-recipient><name><surname>White</surname><given-names>Michael T</given-names></name></principal-award-recipient></award-group><funding-statement>SK, AB and IM acknowledge support from the Victorian State Government Operational Infrastructure Support and Australian Government NHMRC IRIISS. SK was supported by an NHMRC (Australia) Early Career Fellowship (GNT 1052760). MTW was supported by an MRC (UK) Research Fellowship. The authors thank all researchers and study participants involved in the PNG studies. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.</funding-statement></funding-group><counts><fig-count count="8"></fig-count><table-count count="1"></table-count><page-count count="20"></page-count></counts><custom-meta-group><custom-meta id="data-availability"><meta-name>Data Availability</meta-name><meta-value>All relevant data are within the paper and its Supporting Information files.</meta-value></custom-meta></custom-meta-group></article-meta><notes><title>Data Availability</title><p>All relevant data are within the paper and its Supporting Information files.</p></notes></front></pmc></record>Pour manipuler ce document sous Unix (Dilib)
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