In EDS ansehen

Spatial modeling of the population dynamics of Anopheles mosquitoes in Madagascar.

Gespeichert in:
Bibliographische Detailangaben
Titel: Spatial modeling of the population dynamics of Anopheles mosquitoes in Madagascar.
Autoren: Rakotoarison HA; Epidemiology and Clinical Research Unit, Institut Pasteur de Madagascar, Antananarivo, Madagascar. a.rakotoarison@gmail.com.; CIRAD, UMR TETIS, Montpellier, France. a.rakotoarison@gmail.com.; TETIS, Univ Montpellier, AgroParisTech, CIRAD, CNRS, INRAE, Montpellier, France. a.rakotoarison@gmail.com.; LGET, IOGA, Université d'Antananarivo, Antananarivo, Madagascar. a.rakotoarison@gmail.com., Nepomichene TN; Medical Entomology Unit, Institut Pasteur de Madagascar, Antananarivo, Madagascar., Guis H; Epidemiology and Clinical Research Unit, Institut Pasteur de Madagascar, Antananarivo, Madagascar.; CIRAD, UMR ASTRE, Antananarivo, Madagascar.; ASTRE, Univ Montpellier, CIRAD, INRAE, Montpellier, France.; Epidemiology and Public Health Unit, Institut Pasteur du Cambodge, Phnom Penh, Cambodia., Girod R; Medical Entomology Unit, Institut Pasteur de Madagascar, Antananarivo, Madagascar., Rakotoniaina S; LGET, IOGA, Université d'Antananarivo, Antananarivo, Madagascar., Rakotomanana F; Epidemiology and Clinical Research Unit, Institut Pasteur de Madagascar, Antananarivo, Madagascar., Tran A; CIRAD, UMR TETIS, Montpellier, France.; TETIS, Univ Montpellier, AgroParisTech, CIRAD, CNRS, INRAE, Montpellier, France.; ASTRE, Univ Montpellier, CIRAD, INRAE, Montpellier, France.; CIRAD, UMR ASTRE, Montpellier, France.
Quelle: International journal of health geographics [Int J Health Geogr] 2025 Nov 18; Vol. 24 (1), pp. 34. Date of Electronic Publication: 2025 Nov 18.
Publikationsart: Journal Article
Sprache: English
Info zur Zeitschrift: Publisher: BioMed Central Country of Publication: England NLM ID: 101152198 Publication Model: Electronic Cited Medium: Internet ISSN: 1476-072X (Electronic) Linking ISSN: 1476072X NLM ISO Abbreviation: Int J Health Geogr Subsets: MEDLINE
Imprint Name(s): Original Publication: London : BioMed Central, [2002]-
MeSH-Schlagworte: Anopheles*/growth & development , Population Dynamics* , Mosquito Vectors* , Malaria*/epidemiology , Malaria*/transmission, Animals ; Madagascar/epidemiology ; Humans ; Spatio-Temporal Analysis
Abstract: Competing Interests: Declarations. Ethics approval and consent to participate: Not applicable Consent for publication: Not applicable. Competing interests: The authors declare no competing interests.
Background: Malaria, whose parasites are transmitted by Anopheles mosquitoes, remains a major public health burden in Madagascar despite the control measures led by the National Malaria Control Program. Understanding the population dynamics of Anopheles mosquitoes is therefore essential to optimize malaria surveillance and control. This study aimed to develop a model incorporating environmental, climatic and agricultural determinants of Anopheles abundance to predict their spatiotemporal distribution.
Methods: We developed a model of spatiotemporal dynamics for four Anopheles species, vectors of malaria parasite in Madagascar: Anopheles arabiensis, Anopheles coustani, Anopheles funestus and Anopheles gambiae. This model was based on the life cycle of Anopheles and accounted for both the aquatic and aerial phases of their development. It used a system of differential equations to estimate the number of Anopheles mosquitoes at each stage of development. The Ocelet language, dedicated to the modeling of spatial dynamics, was used to produce simulations based on climate and environmental data. The model explicitly integrates the agricultural calendar to adjust the environmental carrying capacity of larval habitats. Model outputs were validated with entomological data collected in Vohimasy (Farafangana districts, 2014-2017).
Results: 24 simulation outputs, from three Anopheles species and eight sites, were obtained and the validation revealed a significant correlation between field observations and model predictions: the correlation coefficients obtained ranged from 0.70 to 0.76. The predicted abundance of host-seeking Anopheles varied seasonally influenced by precipitation, temperature and environmental carrying capacity. The model exhibited robustness across sites with diverse climates and accurately reproduced interannual dynamics. The integration of the agricultural calendar significantly reduced the overestimation of the density of host-seeking adult females.
Conclusion: The developed Anopheles dynamics model provides a valuable tool for predicting mosquito abundance and distribution over time and space. It correctly predicted the abundance at villages with contrasting climates and reproduced interannual dynamics well. A distinctive aspect of this work lies in the explicit integration of seasonal agricultural practices into the estimation of larval habitat availability. This allows for a more accurate and transferable modeling of Anopheles population dynamics.
(© 2025. The Author(s).)
References: Malar J. 2015 Dec 01;14:475. (PMID: 26620552)
Malar J. 2007 Aug 21;6:113. (PMID: 17711580)
Proc Natl Acad Sci U S A. 2009 Aug 18;106(33):13844-9. (PMID: 19666598)
Malar J. 2022 Jun 3;21(1):161. (PMID: 35658961)
Parasit Vectors. 2021 Jun 29;14(1):345. (PMID: 34187546)
Prev Vet Med. 2015 Jun 1;120(1):39-50. (PMID: 25623972)
Malar J. 2009 Nov 26;8:268. (PMID: 19941637)
Malar J. 2004 Jul 30;3:29. (PMID: 15285781)
Parasit Vectors. 2011 May 06;4:65. (PMID: 21548912)
Parasit Vectors. 2014 Dec 14;7:593. (PMID: 25496502)
Malar J. 2016 Oct 18;15(1):502. (PMID: 27756389)
Parasit Vectors. 2020 Aug 26;13(1):430. (PMID: 32843082)
J Vector Borne Dis. 2009 Dec;46(4):295-8. (PMID: 19959856)
Parasit Vectors. 2011 Jul 28;4:153. (PMID: 21798055)
Sci Rep. 2022 Aug 23;12(1):14392. (PMID: 35999450)
Malar J. 2023 Jun 22;22(1):192. (PMID: 37349819)
Wellcome Open Res. 2017 Nov 10;2:109. (PMID: 29387806)
Acta Trop. 2015 Feb;142:131-7. (PMID: 25438260)
Environ Health Perspect. 1995 May;103(5):458-64. (PMID: 7656875)
Malar J. 2016 Jul 15;15:364. (PMID: 27421769)
Parasit Vectors. 2012 Feb 09;5:33. (PMID: 22321562)
PLoS One. 2013 Nov 14;8(11):e79276. (PMID: 24244467)
J Appl Physiol. 1973 Dec;35(6):941-61. (PMID: 4765838)
Malar J. 2013 Feb 18;12:65. (PMID: 23419192)
Malar J. 2020 Sep 29;19(1):348. (PMID: 32993669)
Parasit Vectors. 2016 Aug 08;9(1):434. (PMID: 27502246)
Parasit Vectors. 2013 Apr 16;6:104. (PMID: 23590860)
Sci Rep. 2016 Jun 21;6:27771. (PMID: 27324146)
PLoS One. 2020 Jan 17;15(1):e0227407. (PMID: 31951601)
J Med Entomol. 2003 Nov;40(6):737-42. (PMID: 14765646)
PLoS One. 2020 Dec 11;15(12):e0236607. (PMID: 33306671)
Parasit Vectors. 2014 Nov 05;7:489. (PMID: 25367091)
R Soc Open Sci. 2017 Mar 8;4(3):160969. (PMID: 28405386)
PLoS One. 2019 Feb 6;14(2):e0211258. (PMID: 30726279)
Malar J. 2017 Jan 9;16(1):21. (PMID: 28069024)
Grant Information: 72068719CA00001 United States Agency for International Development; 72068719CA00001 United States Agency for International Development; 72068719CA00001 United States Agency for International Development; 72068719CA00001 United States Agency for International Development
Contributed Indexing: Keywords: Anopheles population dynamics; Agricultural calendar integration; Madagascar; Mechanistic model; Spatiotemporal simulation
Entry Date(s): Date Created: 20251119 Date Completed: 20251119 Latest Revision: 20251123
Update Code: 20251123
PubMed Central ID: PMC12625280
DOI: 10.1186/s12942-025-00424-8
PMID: 41254643
Datenbank: MEDLINE
Beschreibung
Abstract:Competing Interests: Declarations. Ethics approval and consent to participate: Not applicable Consent for publication: Not applicable. Competing interests: The authors declare no competing interests.<br />Background: Malaria, whose parasites are transmitted by Anopheles mosquitoes, remains a major public health burden in Madagascar despite the control measures led by the National Malaria Control Program. Understanding the population dynamics of Anopheles mosquitoes is therefore essential to optimize malaria surveillance and control. This study aimed to develop a model incorporating environmental, climatic and agricultural determinants of Anopheles abundance to predict their spatiotemporal distribution.<br />Methods: We developed a model of spatiotemporal dynamics for four Anopheles species, vectors of malaria parasite in Madagascar: Anopheles arabiensis, Anopheles coustani, Anopheles funestus and Anopheles gambiae. This model was based on the life cycle of Anopheles and accounted for both the aquatic and aerial phases of their development. It used a system of differential equations to estimate the number of Anopheles mosquitoes at each stage of development. The Ocelet language, dedicated to the modeling of spatial dynamics, was used to produce simulations based on climate and environmental data. The model explicitly integrates the agricultural calendar to adjust the environmental carrying capacity of larval habitats. Model outputs were validated with entomological data collected in Vohimasy (Farafangana districts, 2014-2017).<br />Results: 24 simulation outputs, from three Anopheles species and eight sites, were obtained and the validation revealed a significant correlation between field observations and model predictions: the correlation coefficients obtained ranged from 0.70 to 0.76. The predicted abundance of host-seeking Anopheles varied seasonally influenced by precipitation, temperature and environmental carrying capacity. The model exhibited robustness across sites with diverse climates and accurately reproduced interannual dynamics. The integration of the agricultural calendar significantly reduced the overestimation of the density of host-seeking adult females.<br />Conclusion: The developed Anopheles dynamics model provides a valuable tool for predicting mosquito abundance and distribution over time and space. It correctly predicted the abundance at villages with contrasting climates and reproduced interannual dynamics well. A distinctive aspect of this work lies in the explicit integration of seasonal agricultural practices into the estimation of larval habitat availability. This allows for a more accurate and transferable modeling of Anopheles population dynamics.<br /> (© 2025. The Author(s).)
ISSN:1476-072X
DOI:10.1186/s12942-025-00424-8