A simulation model of African Anopheles ecology and population dynamics for the analysis of malaria transmission

Abstract Background Malaria is one of the oldest and deadliest infectious diseases in humans. Many mathematical models of malaria have been developed during the past century, and applied to potential interventions. However, malaria remains uncontrolled and is increasing in many areas, as are vector...

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Published in:Malaria Journal
Main Authors: Billingsley Peter, Dushoff Jonathan, Carlson John, Beier John, Knols Bart, Killeen Gerry, Mbogo Charles M, Depinay Jean-Marc O, Mwambi Henry, Githure John, Toure Abdoulaye M, Ellis McKenzie F
Format: Article in Journal/Newspaper
Language:English
Published: BMC 2004
Subjects:
Online Access:https://doi.org/10.1186/1475-2875-3-29
https://doaj.org/article/bc40633b37dd4ce4b28eb52343ce0b0e
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spelling ftdoajarticles:oai:doaj.org/article:bc40633b37dd4ce4b28eb52343ce0b0e 2023-05-15T15:11:45+02:00 A simulation model of African Anopheles ecology and population dynamics for the analysis of malaria transmission Billingsley Peter Dushoff Jonathan Carlson John Beier John Knols Bart Killeen Gerry Mbogo Charles M Depinay Jean-Marc O Mwambi Henry Githure John Toure Abdoulaye M Ellis McKenzie F 2004-07-01T00:00:00Z https://doi.org/10.1186/1475-2875-3-29 https://doaj.org/article/bc40633b37dd4ce4b28eb52343ce0b0e EN eng BMC http://www.malariajournal.com/content/3/1/29 https://doaj.org/toc/1475-2875 doi:10.1186/1475-2875-3-29 1475-2875 https://doaj.org/article/bc40633b37dd4ce4b28eb52343ce0b0e Malaria Journal, Vol 3, Iss 1, p 29 (2004) Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 article 2004 ftdoajarticles https://doi.org/10.1186/1475-2875-3-29 2022-12-30T22:09:51Z Abstract Background Malaria is one of the oldest and deadliest infectious diseases in humans. Many mathematical models of malaria have been developed during the past century, and applied to potential interventions. However, malaria remains uncontrolled and is increasing in many areas, as are vector and parasite resistance to insecticides and drugs. Methods This study presents a simulation model of African malaria vectors. This individual-based model incorporates current knowledge of the mechanisms underlying Anopheles population dynamics and their relations to the environment. One of its main strengths is that it is based on both biological and environmental variables. Results The model made it possible to structure existing knowledge, assembled in a comprehensive review of the literature, and also pointed out important aspects of basic Anopheles biology about which knowledge is lacking. One simulation showed several patterns similar to those seen in the field, and made it possible to examine different analyses and hypotheses for these patterns; sensitivity analyses on temperature, moisture, predation and preliminary investigations of nutrient competition were also conducted. Conclusions Although based on some mathematical formulae and parameters, this new tool has been developed in order to be as explicit as possible, transparent in use, close to reality and amenable to direct use by field workers. It allows a better understanding of the mechanisms underlying Anopheles population dynamics in general and also a better understanding of the dynamics in specific local geographic environments. It points out many important areas for new investigations that will be critical to effective, efficient, sustainable interventions. Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic Malaria Journal 3 1 29
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic Arctic medicine. Tropical medicine
RC955-962
Infectious and parasitic diseases
RC109-216
spellingShingle Arctic medicine. Tropical medicine
RC955-962
Infectious and parasitic diseases
RC109-216
Billingsley Peter
Dushoff Jonathan
Carlson John
Beier John
Knols Bart
Killeen Gerry
Mbogo Charles M
Depinay Jean-Marc O
Mwambi Henry
Githure John
Toure Abdoulaye M
Ellis McKenzie F
A simulation model of African Anopheles ecology and population dynamics for the analysis of malaria transmission
topic_facet Arctic medicine. Tropical medicine
RC955-962
Infectious and parasitic diseases
RC109-216
description Abstract Background Malaria is one of the oldest and deadliest infectious diseases in humans. Many mathematical models of malaria have been developed during the past century, and applied to potential interventions. However, malaria remains uncontrolled and is increasing in many areas, as are vector and parasite resistance to insecticides and drugs. Methods This study presents a simulation model of African malaria vectors. This individual-based model incorporates current knowledge of the mechanisms underlying Anopheles population dynamics and their relations to the environment. One of its main strengths is that it is based on both biological and environmental variables. Results The model made it possible to structure existing knowledge, assembled in a comprehensive review of the literature, and also pointed out important aspects of basic Anopheles biology about which knowledge is lacking. One simulation showed several patterns similar to those seen in the field, and made it possible to examine different analyses and hypotheses for these patterns; sensitivity analyses on temperature, moisture, predation and preliminary investigations of nutrient competition were also conducted. Conclusions Although based on some mathematical formulae and parameters, this new tool has been developed in order to be as explicit as possible, transparent in use, close to reality and amenable to direct use by field workers. It allows a better understanding of the mechanisms underlying Anopheles population dynamics in general and also a better understanding of the dynamics in specific local geographic environments. It points out many important areas for new investigations that will be critical to effective, efficient, sustainable interventions.
format Article in Journal/Newspaper
author Billingsley Peter
Dushoff Jonathan
Carlson John
Beier John
Knols Bart
Killeen Gerry
Mbogo Charles M
Depinay Jean-Marc O
Mwambi Henry
Githure John
Toure Abdoulaye M
Ellis McKenzie F
author_facet Billingsley Peter
Dushoff Jonathan
Carlson John
Beier John
Knols Bart
Killeen Gerry
Mbogo Charles M
Depinay Jean-Marc O
Mwambi Henry
Githure John
Toure Abdoulaye M
Ellis McKenzie F
author_sort Billingsley Peter
title A simulation model of African Anopheles ecology and population dynamics for the analysis of malaria transmission
title_short A simulation model of African Anopheles ecology and population dynamics for the analysis of malaria transmission
title_full A simulation model of African Anopheles ecology and population dynamics for the analysis of malaria transmission
title_fullStr A simulation model of African Anopheles ecology and population dynamics for the analysis of malaria transmission
title_full_unstemmed A simulation model of African Anopheles ecology and population dynamics for the analysis of malaria transmission
title_sort simulation model of african anopheles ecology and population dynamics for the analysis of malaria transmission
publisher BMC
publishDate 2004
url https://doi.org/10.1186/1475-2875-3-29
https://doaj.org/article/bc40633b37dd4ce4b28eb52343ce0b0e
geographic Arctic
geographic_facet Arctic
genre Arctic
genre_facet Arctic
op_source Malaria Journal, Vol 3, Iss 1, p 29 (2004)
op_relation http://www.malariajournal.com/content/3/1/29
https://doaj.org/toc/1475-2875
doi:10.1186/1475-2875-3-29
1475-2875
https://doaj.org/article/bc40633b37dd4ce4b28eb52343ce0b0e
op_doi https://doi.org/10.1186/1475-2875-3-29
container_title Malaria Journal
container_volume 3
container_issue 1
container_start_page 29
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