Climate-Driven Modeling of Malaria and Other Infectious Diseases (Core Science Keynote)

The major meteorological centres around the world produce extensive numerical weatherprediction (NWP)forecastsand climate projections. Few of these outputs are ever tailored into products for use by asingle sector of users or for multi-sectorialchallenges. These users will range from expert to the public. There isaparticulargap when it comestomodelling the riskof infectious diseases,especiallyforvector borne diseases, in the tropics. Some sectors, insome regions and with specific lead times do better with tailored productsexamples can be foundforagriculture, energydemand and supply, water and large river system management.

This paper will focus on malaria and the development of malaria models,and their subsequent use when driven bynumerical forecasts of weather and climate variability. The pioneering work on malaria ofRoss(Noble Prize,1902) andthat of MacDonald in the1950s,has allowed over time the development of mathematical models adapting the Ross-MacDonald modelconcept. NWPtook off in the 1970s, this wasfollowed by multiplemodelclimate projectionsin the 1980sthat are nowinternationally organisedendeavours. In contrast fordisease modelling, after such aninspiringstart,wesaw a failure to develop actionable malaria model outputsfor users,especiallythose driven by observations,forecast weather conditions,or climatevariability. However, things started to change slowly, initially in the 1980s with the tentative use of climate model outputs and then in the 2000s with the use of seasonal ensemble prediction systems to drive malaria models.

This paperwill cover some of thehistory and presentup to date developments, especiallyin operationalising climate-disease modelsand the tailored production of outputs,it will discuss why there has been a failure to take theactions required to make operationalclimate driven disease risk modelling, andfinallya look forward to what could be achieved in the futurewhich will be open fordiscussion.