Developing a forecasting model for cholera incidence in Dhaka megacity through time series climate data.

Cholera, an acute diarrheal disease spread by lack of hygiene and contaminated water, is a major public health risk in many countries. As cholera is triggered by environmental conditions influenced by climatic variables, establishing a correlation between cholera incidence and climatic variables would provide an opportunity to develop a cholera forecasting model. Considering the auto-regressive nature and the seasonal behavioral patterns of cholera, a seasonal-auto-regressive-integrated-moving-average (SARIMA) model was used for time-series analysis during 2000-2013. As both rainfall (r = 0.43) and maximum temperature (r = 0.56) have the strongest influence on the occurrence of cholera incidence, single-variable (SVMs) and multi-variable SARIMA models (MVMs) were developed, compared and tested for evaluating their relationship with cholera incidence. A low relationship was found with relative humidity (r = 0.28), ENSO (r = 0.21) and SOI (r = -0.23). Using SVM for a 1 °C increase in maximum temperature at one-month lead time showed a 7% increase of cholera incidence (p < 0.001). However, MVM (AIC = 15, BIC = 36) showed better performance than SVM (AIC = 21, BIC = 39). An MVM using rainfall and monthly mean daily maximum temperature with a one-month lead time showed a better fit (RMSE = 14.7, MAE = 11) than the MVM with no lead time (RMSE = 16.2, MAE = 13.2) in forecasting. This result will assist in predicting cholera risks and better preparedness for public health management in the future.

Modelling the increased frequency of extreme sea levels in the Ganges-Brahmaputra-Meghna delta due to sea level rise and other effects of climate change.

Coastal flooding due to storm surge and high tides is a serious risk for inhabitants of the Ganges-Brahmaputra-Meghna (GBM) delta, as much of the land is close to sea level. Climate change could lead to large areas of land being subject to increased flooding, salinization and ultimate abandonment in West Bengal, India, and Bangladesh. IPCC 5th assessment modelling of sea level rise and estimates of subsidence rates from the EU IMPACT2C project suggest that sea level in the GBM delta region may rise by 0.63 to 0.88 m by 2090, with some studies suggesting this could be up to 0.5 m higher if potential substantial melting of the West Antarctic ice sheet is included. These sea level rise scenarios lead to increased frequency of high water coastal events. Any effect of climate change on the frequency and severity of storms can also have an effect on extreme sea levels. A shelf-sea model of the Bay of Bengal has been used to investigate how the combined effect of sea level rise and changes in other environmental conditions under climate change may alter the frequency of extreme sea level events for the period 1971 to 2099. The model was forced using atmospheric and oceanic boundary conditions derived from climate model projections and the future scenario increase in sea level was applied at its ocean boundary. The model results show an increased likelihood of extreme sea level events through the 21st century, with the frequency of events increasing greatly in the second half of the century: water levels that occurred at decadal time intervals under present-day model conditions occurred in most years by the middle of the 21st century and 3-15 times per year by 2100. The heights of the most extreme events tend to increase more in the first half of the century than the second. The modelled scenarios provide a case study of how sea level rise and other effects of climate change may combine to produce a greatly increased threat to life and property in the GBM delta by the end of this century.