• 1.

    World Health Organization, 2001. Malaria Early Warning Systems, Concepts, Indicators and Partners: A Framework for Field Research in Africa. Geneva: World Health Organization/Roll Back Malaria/Technical Support Network for Prevention and Control of Malaria.

    • Search Google Scholar
    • Export Citation
  • 2.

    World Health Organization, 2004. Malaria Epidemics: Forecasting, Prevention, Early Detection and Control: From Policy to Practice. Geneva: World Health Organization.

    • Search Google Scholar
    • Export Citation
  • 3.

    World Health Organization, 2009. Protecting Health from Climate Change: Global Research Priorities. Geneva: World Health Organization.

  • 4.

    World Health Organization, 2010. Mathematical Modelling to Support Malaria Control and Elimination. Roll Back Malaria - Progress and Impact Series No. 5. Geneva: World Health Organization.

    • Search Google Scholar
    • Export Citation
  • 5.

    Pan American Health Organization, 2006. Regional Strategic Plan for Malaria in the Americas 2006–2010. Washington, DC: Pan American Health Organization.

    • Search Google Scholar
    • Export Citation
  • 6.

    Ruiz D, Connor SJ, Thomson MC, 2008. A multimodel framework in support of malaria surveillance and control. Thomson MC, García-Herrera R, Beniston M, eds. Seasonal Forecasts, Climatic Change, and Human Health – Health and Climate/Advances in Global Change Research. Volume 30. Springer Science + Business Media. Springer: Dordrecht, The Netherlands, 101125.

    • Search Google Scholar
    • Export Citation
  • 7.

    Thomson MC, Connor SJ, 2001. The development of malaria early warning systems for Africa. Trends Parasitol 17: 438445.

  • 8.

    Poveda G, Rojas W, Quiñones ML, Vélez ID, Mantilla RI, Ruiz D, Zuluaga JS, Rúa GL, 2001. Coupling between annual and ENSO timescales in the malaria-climate association in Colombia. Environ Health Perspect 109: 489493.

    • Search Google Scholar
    • Export Citation
  • 9.

    Thomson MC, Doblas-Reyes FJ, Mason SJ, Hagedorn R, Connor SJ, Phindela T, Morse AP, Palmer TN, 2006. Malaria early warnings based on seasonal climate forecasts from multi-model ensembles. Nature 439: 576579.

    • Search Google Scholar
    • Export Citation
  • 10.

    Ruiz D, Poveda G, Vélez ID, Quiñones ML, Rúa GL, Velásquez LE, Zuluaga JS, 2006. Modelling entomological-climatic interactions of Plasmodium falciparum malaria transmission in two Colombian endemic-regions: contributions to a National Malaria Early Warning System. Malar J 5: 66.

    • Search Google Scholar
    • Export Citation
  • 11.

    Poveda G, Quiñones ML, Vélez ID, Rojas W, Rúa GL, Ruiz D, Zuluaga JS, Velásquez LE, Zuluaga MD, Hernández O, 2008. Desarrollo de un Sistema de Alerta Temprana para la Malaria en Colombia. Malaga, Spain: Universidad Internacional de Andalucía.

    • Search Google Scholar
    • Export Citation
  • 12.

    Aron JL, May RM, 1982. The population dynamics of malaria. Anderson RM, ed. The Population Dynamics of Infectious Disease: Theory and Applications. London: Chapman and Hall, 139179.

    • Search Google Scholar
    • Export Citation
  • 13.

    Mantilla G, Oliveros H, Barnston A, 2009. The role of ENSO in understanding changes in Colombian's annual malaria burden by region, 1960–2006. Malar J 8: 6.

    • Search Google Scholar
    • Export Citation
  • 14.

    Bouma MJ, Poveda G, Rojas W, Chavasse D, Quiñones M, Cox J, Patz J, 1997. Predicting high risk years for malaria in Colombia using parameter of El Niño Southern Oscillation. Trop Med Int Health 2: 11221227.

    • Search Google Scholar
    • Export Citation
  • 15.

    Poveda G, Rojas W, 1997. Evidencias de la asociación entre brotes epidémicos de malaria en Colombia y el fenómeno El Niño-Oscilación del Sur. Revista de la Academia Colombiana de Ciencias 21: 421429.

    • Search Google Scholar
    • Export Citation
  • 16.

    Gagnon A, Smoyer-Tomic K, Bush A, 2002. The El Niño-Southern Oscillation and malaria epidemics in South America. Int J Biometeorol 46: 8189.

    • Search Google Scholar
    • Export Citation
  • 17.

    World Bank - Latin America and the Caribbean, 2006. Colombia: Integrated National Adaptation Program. Available at: http://web.worldbank.org/external/projects/. Accessed June 1, 2010.

    • Search Google Scholar
    • Export Citation
  • 18.

    Mejia LE, 2007. Adapting to the Impacts of Climate Change on Health via the Integrated National Adaptation Project. Environment Matters. Annual Review 2007. Washington, DC: World Bank, 1213.

    • Search Google Scholar
    • Export Citation
  • 19.

    World Health Organization, 2013. The World Malaria Report 2012. Geneva: World Health Organization.

  • 20.

    Roll Back Malaria, 2008. The Global Malaria Action Plan: for a Malaria Free World. The Roll Back Malaria Partnership. Geneva: World Health Organization.

    • Search Google Scholar
    • Export Citation
  • 21.

    Marco JB, Harboe R, Salas JD, 1993. Stochastic Hydrology and Its Use in Water Resources Systems Simulation and Optimization. NATO ASI Series, Series E: Applied Sciences. Volume 237. London: Kluwer Academic Publishers.

    • Search Google Scholar
    • Export Citation
  • 22.

    Bruce-Chwatt LJ, 1980. Essential Malariology. London: Heinemann.

  • 23.

    Ross R, 1911. The Prevention of Malaria. London: Murry.

  • 24.

    Macdonald G, 1957. The Epidemiology and Control of Malaria. Oxford, UK: Oxford University Press.

  • 25.

    Martens WJ, 1997. Health Impacts of Climate Change and Ozone Depletion. An Eco-epidemiological Modelling Approach. Maastricht, The Netherlands: Maastricht University.

    • Search Google Scholar
    • Export Citation
  • 26.

    Worrall E, Connor SJ, Thomson MC, 2007. A model to simulate the impact of timing, coverage and transmission intensity on the effectiveness of indoor residual spraying (IRS) for malaria control. Trop Med Int Health 12: 7588.

    • Search Google Scholar
    • Export Citation
  • 27.

    Kroeger A, Ordoñez-Gonzalez J, Aviña AI, 2002. Malaria control reinvented: health sector reform and strategy development in Colombia. Trop Med Int Health 7: 450458.

    • Search Google Scholar
    • Export Citation
  • 28.

    Valero M, 2006. Malaria in Colombia: retrospective glance during the past 40 years. Rev Salud Publica (Bogota) 8: 141149.

  • 29.

    Ruiz D, Molina AM, Quiñónes ML, Jiménez MM, Thomson MC, Connor SJ, Gutiérrez ME, Zapata PA, López C, Londoño A, 2011. Simulating Malaria Transmission Dynamics in the Pilot Areas of the Colombian Integrated National Adaptation Pilot Project. Medellin, Colombia: Escuela de Ingeniería de Antioquia.

    • Search Google Scholar
    • Export Citation
  • 30.

    Garrett-Jones C, 1964. The human blood index of malaria vectors in relation to epidemiological assessment. Bull World Health Organ 30: 241261.

    • Search Google Scholar
    • Export Citation
  • 31.

    Servicio de Erradicación de Malaria, 1957. Plan de Erradicación. Bogota, Colombia: Ministerio de Salud.

  • 32.

    Olano VA, Brochero HL, Sáenz R, Quiñones ML, Molina JA, 2001. Mapas preliminares de la distribución de especies de Anopheles vectores de malaria en Colombia. Biomedica 21: 402408.

    • Search Google Scholar
    • Export Citation
  • 33.

    Service Cordoba State Health, 2007. Informe de acciones desarrolladas por el Grupo de Entomología del Laboratorio Departamental de Salud Pública, Departamento de Córdoba.

    • Search Google Scholar
    • Export Citation
  • 34.

    Last M, Kandel A, 2001. Automated detection of outliers in real-world data. Proceedings of the 2nd International Conference on Intelligent Technologies, 2001.

    • Search Google Scholar
    • Export Citation
  • 35.

    Grubbs F, 1969. Procedures for detecting outlying observations in samples. Technometrics 11: 121.

  • 36.

    Quiñones ML, Suárez M, Fleming G, 1987. Distribución y bionomía de los anofelinos de la Costa Pacífica de Colombia. Colomb Med 18: 19.

  • 37.

    Olano VA, Carrasquilla G, Méndez F, 1997. Transmisión de la malaria urbana en Buenaventura, Colombia: aspectos entomológicos. Rev Panam Salud Publica 1: 287294.

    • Search Google Scholar
    • Export Citation
  • 38.

    Rúa GL, Quiñones ML, Vélez ID, Zuluaga JS, Rojas W, Poveda G, Ruiz D, 2005. Laboratory estimation of the effects of increasing temperatures on the duration of gonotrophic cycle of Anopheles albimanus (Diptera: Culicidae). Mem Inst Oswaldo Cruz 100: 515520.

    • Search Google Scholar
    • Export Citation
  • 39.

    Rúa G, Quiñones ML, Vélez ID, Poveda G, Ruiz D, Rojas W, Zuluaga JS, 2006. Diagnostics and Prediction of Climate Variability and Human Health Impacts in the Tropical Americas. Medellin, Colombia: Universidad Nacional de Colombia-Universidad de Antioquia-Corporación para Investigaciones Biológicas. Collaborative Research Network/Inter-American Institute for Global Change Research.

    • Search Google Scholar
    • Export Citation
 
 
 

 

 
 
 

 

 

 

 

 

 

Implementation of Malaria Dynamic Models in Municipality Level Early Warning Systems in Colombia. Part I: Description of Study Sites

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  • Grupo Investigación en Gestión Ambiental, Escuela de Ingeniería de Antioquia, Envigado, Antioquia, Colombia; International Research Institute for Climate and Society, and Department of Earth and Environmental Sciences, Columbia University, New York, New York; Subdirección de Vigilancia y Control en Salud Pública, Instituto Nacional de Salud, Bogotá, Colombia; Facultad de Medicina, Universidad Nacional de Colombia Sede Bogotá, Bogotá, Colombia; Instituto Colombiano de Medicina Tropical, Universidad CES, Antioquia, Colombia; School of Environmental Sciences, University of Liverpool, Liverpool, United Kingdom

As part of the Integrated National Adaptation Pilot project and the Integrated Surveillance and Control System, the Colombian National Institute of Health is working on the design and implementation of a Malaria Early Warning System framework, supported by seasonal climate forecasting capabilities, weather and environmental monitoring, and malaria statistical and dynamic models. In this report, we provide an overview of the local ecoepidemiologic settings where four malaria process-based mathematical models are currently being implemented at a municipal level. The description includes general characteristics, malaria situation (predominant type of infection, malaria-positive cases data, malaria incidence, and seasonality), entomologic conditions (primary and secondary vectors, mosquito densities, and feeding frequencies), climatic conditions (climatology and long-term trends), key drivers of epidemic outbreaks, and non-climatic factors (populations at risk, control campaigns, and socioeconomic conditions). Selected pilot sites exhibit different ecoepidemiologic settings that must be taken into account in the development of the integrated surveillance and control system.

Author Notes

* Address correspondence to Daniel Ruiz, Grupo Investigación en Gestión Ambiental, Unidad Académica Civil, Ambiental e Industrial, Escuela de Ingeniería de Antioquia, km 02+000, Vía al Aeropuerto José María Córdova, Municipio de Envigado, Antioquia, Colombia. E-mail: pfcarlos@eia.edu.co

Financial support: This study was supported by Conservation International Colombia, as part of the Integrated National Adaptation Pilot project. Daniel Ruiz has been partially supported by the Unidad Académica Civil, Ambiental e Industrial - Escuela de Ingeniería de Antioquia, the International Research Institute for Climate and Society and the Department of Earth and Environmental Sciences, Columbia University, New York, New York.

Authors' addresses: Daniel Ruiz, Grupo Investigación en Gestión Ambiental, Unidad Académica Civil, Ambiental e Industrial, Escuela de Ingeniería de Antioquia, km 02+000, Vía al Aeropuerto José María Córdova, Municipio de Envigado, Antioquia, Colombia, E-mail: pfcarlos@eia.edu.co, and International Research Institute for Climate and Society, Lamont-Doherty Earth Observatory, Columbia University, Palisades, NY, E-mail: pfcarlos@iri.columbia.edu. Viviana Cerón, Martha Ahumada, Patricia Gutiérrez, and Salua Osorio, Subdirección de Vigilancia y Control en Salud Pública, Instituto Nacional de Salud, Avenida Calle 26 No. 51-20, Zona 6 CAN, Bogotá, DC, Colombia, E-mails: vceron@ins.gov.co, mahumada@ins.gov.co, pgutierrezduenas@gmail.com, and sosorio@ins.gov.co. Adriana M. Molina, Grupo Investigación en Gestión Ambiental, Unidad Académica Civil, Ambiental e Industrial, Escuela de Ingeniería de Antioquia, km 02+000, Vía al Aeropuerto José María Córdova, Municipio de Envigado, Antioquia, Colombia, E-mail: pfamolina@eia.edu.co. Martha L. Quiñónes, acultad de Medicina, Universidad Nacional de Colombia Sede Bogotá, Universidad CES, Calle 10 A No. 22–04, Medellín, Colombia, E-mail: mmjimenez@ces.edu.co. Mónica M. Jiménez, Instituto Colombiano de Medicina Tropical, Universidad CES, Carrera 30 No 45-03, Edificio 471, Ciudad Universitaria, Bogotá DC, Colombia, E-mail: mlquinonesp@unal.edu.co. Gilma Mantilla and Madeleine C. Thomson, International Research Institute for Climate and Society, Lamont-Doherty Earth Observatory, Columbia University, Palisades, NY, E-mails: mantilla@iri.columbia.edu and mthomson@iri.columbia.edu. Stephen J. Connor, International Research Institute for Climate and Society, Lamont-Doherty Earth Observatory, Columbia University, Palisades, NY, E-mail: sjconnor@iri.columbia.edu, and School of Environmental Sciences, University of Liverpool, Liverpool L69 3BX, United Kingdom, E-mail: sjconnor@liv.ac.uk.

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