ABSTRACT
Among the other diseases, malaria and diarrhoea have a large disease burden in India, especially among children. Changes in rainfall and temperature patterns likely play a major role in the increased incidence of these diseases across geographical locations. This study proposes a method for probabilistic forecasting of the disease incidences in extended range time scale (2-3 weeks in advance) over India based on an unsupervised pattern recognition technique that uses meteorological parameters as inputs and which can be applied to any geographical location over India. To verify the robustness of this newly developed early warning system, detailed analysis has been made in the incidence of malaria and diarrhoea over two districts of the State of Maharashtra. It is found that the increased probabilities of high (less) rainfall, high (low) minimum temperature and low (moderate) maximum temperature are more (less) conducive for both diseases over these locations, but have different thresholds. With the categorical probabilistic forecasts of disease incidences, this early health warning system is found to be a useful tool with reasonable skill to provide the climate-health outlook about possible disease incidence at least 2 weeks in advance for any location or grid over India.
ABSTRACT
Heat waves over India occur during the months of March-June. This study aims at the real-time monitoring and prediction of heat waves using a multi-model dynamical ensemble prediction system developed at Indian Institute of Tropical Meteorology, India. For this, a criterion has been proposed based on the observed daily gridded maximum temperature (Tmax) datasets, which can be used for real-time prediction as well. A heat wave day is identified when either (1) Tmax (a)≥ its climatological 95th percentile (calculated from daily values during March-June and for 1981-2010), (b) >36 °C, and (c) its departure from normal is >3.5 °C, Or, (2) when the Tmax >44 °C. Three heat wave prone regions, namely, northwest, southeast and northwest-southeast regions are recognized and heat wave spells of minimum consecutive six days are identified objectively for each region during 1981-2018. It is noticed that the prediction system has reasonable skill in predicting the heat waves over heat wave prone regions of India. Forecast verification of heat wave spells during 2003-2018 reveals that the prediction system has great potential in providing overall indication about the onset, duration and demise of the forthcoming heat wave spell with sufficient lead time albeit with some spatio-temporal error.
ABSTRACT
A systematic search was carried out in the databases of Pubmed, Indmed and Mausam for articles on the effect of ambient temperature on health. Relevant data were extracted using a standard data abstraction form by two authors independently. The overall effects of ambient air temperature are reported as odds ratio (OR) and 95% confidence intervals (CIs) on mortality. Of 812 records identified, only seven were included in the final review as per pre-defined criteria. An increase in the all-cause mortality rate of 41% are reported during a heat wave in India. Risk ratios for all-cause mortality was in the range of 1.7-2.1. The dose-response relationship of ambient temperature and all-cause mortality and cardiovascular diseases are been reported. Current evidence on the effect of ambient temperature and health is sufficient to initiate an integrated response from policy makers, climate scientists and public health practitioners in India. Continued advocacy and generation of more robust evidence is needed.
