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Table 2 Potential utility of weather and climate predictions for vector borne disease control

From: Climate drivers of vector-borne diseases in Africa and their relevance to control programmes

Time frame Climate driver Availability for operational use How forecast may be used in vector control
Weather forecasts Numerical weather predictions provide the most robust short term weather forecasts. In Africa few countries have capacities to skillfully predict the weather beyond 2 days. Extending such forecasts to 5 or even 10 days may be possible in some areas. Global weather forecasts are often poorly calibrated for local use. Short term weather forecasts give little additional time for a vector-borne disease early warning system although they might provide valuable information on extreme events that may impact the health system more broadly.
Sub- Seasonal weather forecast (S2S) The Madden-Julian Oscillation (MJO) is the dominant mode of sub-seasonal climate variability in the global tropics and a driver of predictability in S2S forecasts. S2S experimental forecasts are becoming available from global producers. S2S forecasts have yet to be shown as operationally useful for vector-borne disease control.
Seasonal climate forecasts Slow changes in sea surface temperature (eg. equatorial Pacific ENSO events). Operational seasonal forecasts are available from national, regional and global producrers. They are useful for predictable regions (Sahel, JAS), Eastern Africa, OND) and Southern Africa, DJF) - highest skill during ENSO periods. When predictability is high seasonal climate forecasts can add months to early warning system that are already developed based on monitored rainfall and temperature.
Transition time scale forecasts (1–9 years) Transition time scale between seasonal prediction and decadal variability.   Forecasts that are longer than seasonal climate forecast are highly desirable for planning purposes. However they are not operationally available for Africa.
Decadal forecasts (10–30 years) Decadal SSTs for example SST variations over the Pacific Ocean are highly correlated with decadal rainfall variations in Eastern Africa March–May season. Experimental forecasts only. Decadal predictions are at the forefront of climate research but operational forecasts may not be realistic any time soon. However, where decadal variations are limited temperature may follow long term climate change trend.
Climate change scenarios Long term changes in athropogenic gas emissions. IPCC scenarios for global and regional scale. - regions where models agree. Downscaling of climate change scenarios is essential to relate this information to national and subnational decision-making. Climate change scenarios provides some strong indication of long term warming trend but largely outside of operational vector-borne disease decision-time frames. Where the time line is relevant, e.g. in assessing climate risks to malaria eradication, rainfall scenarios are highly uncertain. Temperature trends, especially in the absence of strong decadal variability, may provide valuable information.
  1. S2S Sub-seasonal to seasonal, ENSO El Niño Southern Oscillation, JAS July–August-September, OND October–November-December, DJF December–January-February, SST sea surface temperatures