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Malaria in Africa

Malaria in Africa. Botswana is a semi-arid country; the occurrence of malaria is restricted by lack of rainfall. Good surveillance ( malaria is a notifiable disease ) Laboratory confirmed data routinely available >20 years of data Incorporate climate information into malaria control planning

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Malaria in Africa

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  1. Malaria in Africa

  2. Botswana is a semi-arid country; the occurrence of malaria is restricted by lack of rainfall. Good surveillance (malaria is a notifiable disease) Laboratory confirmed data routinely available >20 years of data Incorporate climate information into malaria control planning Monitor routinely confounding factors such as drug and insecticide resistance Malaria in Botswana Botswana

  3. Long-term Trends Trends in malaria incidence may result from trends in climate but mostly indicate changes in vulnerability, e.g. drug or insecticide resistance, declining control services, etc. The long term increasing trend to 1996 ends when revisions to national control policy and practice occurred in 1997 (new drugs, new insecticide, revitalized programme).

  4. Seasonality The disease is highly seasonal and follows the rainy season with a lag of about 2–3 months.

  5. Relationship to Rainfall Malaria incidence in Botswana is strongly related to rainfall variability during the peak rainfall season December – February. The relationship is non-linear: incidence peaks at about 4 mm per day.

  6. DEMETER Forecasts Seasonal Predictions Observation (CMAP) DJF precipitation composites High Malaria years 88, 89, 93, 96, 97 Low Malaria years 82, 83, 87, 92, 02 Thomson, M. C., F. J. Doblas-Reyes, S. J. Mason, R. Hagedorn, S. J. Connor, T. Phindela, A. P. Morse, and T. N. Palmer, 2006: Multi-model ensemble seasonal climate forecasts for malaria early warning. Nature, 439, 576‑579.

  7. Operational Use of MEWS National Malaria Control Programmes strengthen vector control measures, prepare emergency containers with mobile treatment centers and mobilize localized response

  8. Exercise • Prepare malaria data for analysis against climate data. • Model the relationship between malaria occurrence in Botswana and rainfall variability. • Predict malaria occurrence based on updated rainfall data.

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