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Weather and Climate Informatics for Pro-Active Healthcare (WACIPH)  
Wednesday, 26 November 2014, 10:00
To Thursday, 27 November 2014
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Weather and Climate Informatics for Pro-Active Healthcare (WACIPH)

26-27 November, 2014

CSIR C-MMACS, Bangalore


Background: Many diseases depend on weather and environmental conditions; shifts in the weather patterns due to climate change can also modulate vulnerability to these diseases. Thus accurate, precise and advance information on weather variables can help pro-active mitigation ensuring wellness against treatment; changes in the vulnerable regions due to climate change can be used for long-term planning.Response to outbreaks to many diseases like malaria is still mostly reactive, based on general schedule or post-outbreak decision; although measures like insecticide impregnated mosquito nets are being tried, there are serious issues related to emerging resistance among various mosquito species. On the other hand, proactive, preventive measures could significantly reduce disease burden and drug load.Many of these diseases, or disease vectors, depend critically on the environmental conditions, making a general prevention schedule less effective. Further, exposure of the human host to disease virus or vector also determines the intensity of the epidemic. Identification of potential sites and time of vector genesis, for example, can enable pro-active vector sanitation and reduction of encounters between mosquito and human through exposure advisories, thus ensuring wellness. Several works worldwide have also shown the appreciable roles of weather and climate in disease dynamics.

Such a platform for pro-active healthcare is implementable with current technology, with the important components tested and calibrated for a given region such as validated quantitative relations between weather variables and disease occurrence and prevalence, meteorological monitoring and meso-scale weather forecasting, integrating other critical components like GIS and communication.  A weather driven model of malaria has been developed at C-MMACS and validated over Arunachal Pradesh (PLOS One, 2013) under the CSIR Network project Integrated Analysis for Impact, Mitigation and Sustainability (IAIMS). Subsequently it been shown, under IAIMS, that the model was applicable over all the 28 states of India (PLOS One, 2014). In another work at C-MMACS, it has been shown that Acute Respiratory Disorders over Delhi are closely linked to weather conditions (Nature Reports, 2014). Under the UKIERI project Integrating disease prediction with weather and climate models seamlessly (INDRASS), feasibility of skilful seasonal of malaria has been shown (Malaria Journal, 2014). Similarly, promising results have been found in seasonal forecasting of malaria (Morse et al 2011). There have been several other recent developments that make such a platform implementable. Weather forecasts at village-cluster level have been generated and validated over Karnataka through a pioneering effort by C-MMACS and Karnataka Natural Disaster Monitoring Centre (Goswami et al 2012; Rakesh et al 2013). Similarly, long-term reliable projections of climate change can be used to map vulnerability to various diseases.

However, actual realization of such a platform is only possible through an effective synergy among a number of R&D and implementation agencies. For example, an agency can generate locations and timing of disease/vector onset using high-density monitoring and high-resolution forecasts of vector genesis; vector sanitation schedule as well as exposure advisories based on these data can be generated at required intervals and communicated to implementing agencies like the Public Health Centres for pro-active vector sanitation of the susceptible areas with risk (closeness to human habitat). The dissemination of the advisories can be through various communication channels in local language; in particular, voluntary organizations and women can be empowered for effective use of these pro-active healthcare products. As an additional benefit accumulation of such sustained monitoring and forecasting over a long period at daily scale will provide more reliable estimates of impact of regional climate change on disease dynamics.

The proposed Workshop, organized under the UKIERI project Integrating disease prediction with weather and climate models seamlessly (INDRASS) aims to bring together a number of active research groups and stake holders to develop an integrated and applicable platform for pro-active healthcare at short and long time scales. The aim of the Workshop is to identify available components, map expertise and strengths and plan an integrated platform for pro-active healthcare; a major objective would be to develop an implementable and effective functional proto-type (PHC Village) as a proof of concept that can be replicated and scaled up.


Contact Dr K C Gouda, 25051333


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