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      A weather-driven model of malaria transmission

      research-article
      Author(s): 1 , , 2
      Publication date (Electronic):
      Journal: Malaria Journal
      Publisher: BioMed Central

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          Abstract

          Background

          Climate is a major driving force behind malaria transmission and climate data are often used to account for the spatial, seasonal and interannual variation in malaria transmission.

          Methods

          This paper describes a mathematical-biological model of the parasite dynamics, comprising both the weather-dependent within-vector stages and the weather-independent within-host stages.

          Results

          Numerical evaluations of the model in both time and space show that it qualitatively reconstructs the prevalence of infection.

          Conclusion

          A process-based modelling structure has been developed that may be suitable for the simulation of malaria forecasts based on seasonal weather forecasts.

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          Most cited references56

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          DEVELOPMENT OF A EUROPEAN MULTIMODEL ENSEMBLE SYSTEM FOR SEASONAL-TO-INTERANNUAL PREDICTION (DEMETER)

          T Palmer, F. J. Doblas-Reyes, R Hagedorn … (2004)
          Article 0 comments Cited 310 times – based on 0 reviews     Review now
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            A climate-based distribution model of malaria transmission in sub-Saharan Africa.

            M Craig, R Snow, D le Sueur (1999)
            Malaria remains the single largest threat to child survival in sub-Saharan Africa and warrants long-term investment for control. Previous malaria distribution maps have been vague and arbitrary. Marlies Craig, Bob Snow and David le Sueur here describe a simple numerical approach to defining distribution of malaria transmission, based upon biological constraints of climate on parasite and vector development. The model compared well with contemporary field data and historical 'expert opinion' maps, excepting small-scale ecological anomalies. The model provides a numerical basis for further refinement and prediction of the impact of climate change on transmission. Together with population, morbidity and mortality data, the model provides a fundamental tool for strategic control of malaria.
            Article 0 comments Cited 179 times – based on 0 reviews     Review now
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              PROGNOSIS FOR INTERRUPTION OF MALARIA TRANSMISSION THROUGH ASSESSMENT OF THE MOSQUITO'S VECTORIAL CAPACITY.

              C. Garrett (1964)
              Article 0 comments Cited 161 times – based on 0 reviews     Review now
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                Author and article information

                Journal
                Journal ID (nlm-ta): Malar J
                Title: Malaria Journal
                Publisher: BioMed Central (London )
                ISSN (Electronic): 1475-2875
                Publication date Collection: 2004
                Publication date (Electronic): 6 September 2004
                Volume: 3
                Page: 32
                Affiliations
                [1 ]Virtual Population Laboratory, Department of Physics, University of Liverpool, Liverpool L69 7ZE, UK
                [2 ]Department of Geography, University of Liverpool, P.O. Box 147, Liverpool, L69 3BX, UK
                Article
                Publisher ID: 1475-2875-3-32
                DOI: 10.1186/1475-2875-3-32
                PMC ID: 520827
                PubMed ID: 15350206
                SO-VID: 6de512f7-4dc4-4b53-8b7e-8b34bd27811c
                Copyright © Copyright © 2004 Hoshen and Morse; licensee BioMed Central Ltd.
                License:

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Date received : 4 March 2004
                Date accepted : 6 September 2004
                Categories
                Subject: Research

                ScienceOpen disciplines: Infectious disease & Microbiology
                Data availability:
                ScienceOpen disciplines: Infectious disease & Microbiology

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