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Forecasting Malaria Incidence in Botswana Using the DEMETER Data

Forecasting Malaria Incidence in Botswana Using the DEMETER Data. Simon Mason International Research Institute for Climate and Society The Earth Institute of Columbia University ECMWF Users’ Meeting Reading, England, 15 – 17 June, 2005. Malaria in Africa. Climate controls on

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Forecasting Malaria Incidence in Botswana Using the DEMETER Data

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  1. Forecasting Malaria Incidencein Botswana Using the DEMETER Data Simon Mason International Research Institute for Climate and Society The Earth Institute of Columbia University ECMWF Users’ Meeting Reading, England, 15 – 17 June, 2005

  2. Malaria in Africa Climate controls on malaria in Africa: • Temperature – “highland malaria” • Precipitation – “desert-fringe malaria” Botswana

  3. Malaria in Botswana Botswana straddles the southern margins of malaria transmission in sub-Saharan Africa. The incidence of malaria varies considerably from district to district – showing a general decreasing north-south pattern from more stable to less stable malaria. In Botswana the incidence of malaria varies considerably from year to year – and as such malaria is considered to be ‘unstable’ and prone to periodic epidemics.

  4. Malaria in Botswana • Constraints to studying impact of climate variability on malaria incidence: • Inadequate surveillance: but in Botswana, malaria is a notifiable disease. • Lack of confirmed case data: but laboratory-confirmed cases are recorded in Botswana. • Short time-series for analysis: but Botswana has annual records from 1982. • Many confounding factors: dates of changes in drug policies in Botswana are known.

  5. Malaria in Botswana The disease is highly seasonal and follows the rainy season with a lag of about 2 months

  6. Malaria in Botswana 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 1982–1996 ends when revisions to national control policy and practice occurred in 1997 (new drugs, new insecticide, revitalized programme.

  7. Malaria in Africa Recent increases in incidence have been attributed to global warming, but they are much more likely a result of increases in drug resistance, and declines in control activities. Chloroquine resistance was first reported in East Africa in 1979 – since spread throughout Africa

  8. Malaria in Botswana Other factors driving trend and/or interannual variability: • Intrinsic population dynamics • Access to health facilities/reporting • Drug sensitivity • Insecticide sensitivity • Seasonal and long term migration • HIV

  9. Evidence for Efficacy of Policy Change The ratio of confirmed to unconfirmed malaria cases increases markedly after 1996.

  10. Detrended Malaria Index The skewness of the log-incidence is small (-0.3) compared to that for the raw incidence (1.5). Detrending accounts for the policy change. Climate-related trends are not removed. High and low years are defined by the upper and lower quartiles.

  11. Relationship to Observed 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.

  12. Relationship to Observed Rainfall Correlations with the quadratic rainfall index are strong:

  13. Relationship to Observed Rainfall ROC or low incidence years:

  14. DEMETER Forecasts Observations Forecasts High malaria years Low malaria years

  15. DEMETER Forecasts

  16. DEMETER Forecasts Ensemble-mean forecasts compared to incidence.

  17. DEMETER Forecasts ROC At shorter lead-times the forecasts improve.

  18. Malaria Early Warning System

  19. Using Seasonal Climate Forecasts for Malaria Control Planning The First Malaria Epidemic Outlook Forum for SADC was held in September 2004, and an updated rainfall forecast was provided in December 2004.

  20. Summary • The use of seasonal climate forecasts for malaria in Southern Africa is demand led. • But seasonal forecasts form only part of the inputs to a malaria early warning system. • Institutions are already organised and policies in place for the use of seasonal forecasts. • Causal relationship between climate and malaria known. • There is a strong influence of seasonal rainfall on detrended malaria incidence. • There is high predictability of detrended malaria incidence using DEMETER forecasts.

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