Typhoid fever is a major cause of death worldwide with a major part of the disease burden in developing regions such as the Indian sub-continent. Bangladesh is part of this highly endemic region, yet little is known about the spatial and temporal distribution of the disease at a regional scale. This research used a Geographic Information System to explore, spatially and temporally, the prevalence of typhoid in Dhaka Metropolitan Area (DMA) of Bangladesh over the period 2005–9. This paper provides the first study of the spatio-temporal epidemiology of typhoid for this region. The aims of the study were: (i) to analyse the epidemiology of cases from 2005 to 2009; (ii) to identify spatial patterns of infection based on two spatial hypotheses; and (iii) to determine the hydro-climatological factors associated with typhoid prevalence. Case occurrences data were collected from 11 major hospitals in DMA, geocoded to census tract level, and used in a spatio-temporal analysis with a range of demographic, environmental and meteorological variables. Analyses revealed distinct seasonality as well as age and gender differences, with males and very young children being disproportionately infected. The male-female ratio of typhoid cases was found to be 1.36, and the median age of the cases was 14 years. Typhoid incidence was higher in male population than female (χ2 = 5.88, p<0.05). The age-specific incidence rate was highest for the 0–4 years age group (277 cases), followed by the 60+ years age group (51 cases), then there were 45 cases for 15–17 years, 37 cases for 18–34 years, 34 cases for 35–39 years and 11 cases for 10–14 years per 100,000 people. Monsoon months had the highest disease occurrences (44.62%) followed by the pre-monsoon (30.54%) and post-monsoon (24.85%) season. The Student's t test revealed that there is no significant difference on the occurrence of typhoid between urban and rural environments (p>0.05). A statistically significant inverse association was found between typhoid incidence and distance to major waterbodies. Spatial pattern analysis showed that there was a significant clustering of typhoid distribution in the study area. Moran's I was highest (0.879; p<0.01) in 2008 and lowest (0.075; p<0.05) in 2009. Incidence rates were found to form three large, multi-centred, spatial clusters with no significant difference between urban and rural rates. Temporally, typhoid incidence was seen to increase with temperature, rainfall and river level at time lags ranging from three to five weeks. For example, for a 0.1 metre rise in river levels, the number of typhoid cases increased by 4.6% (95% CI: 2.4–2.8) above the threshold of 4.0 metres (95% CI: 2.4–4.3). On the other hand, with a 1°C rise in temperature, the number of typhoid cases could increase by 14.2% (95% CI: 4.4–25.0).

Satellite‐derived lightning data for 17 years (1998–2014) were used to evaluate the relation between environmental factors and lightning activity over the Bangladesh landmass. Time series convective available potential energy (CAPE) data were extracted from ERA‐40 reanalysis data while total and convective rainfalls were obtained from Tropical Rainfall Measuring Mission's monthly products. In addition, the product of CAPE and precipitation was computed and used as an additional variable. Three timescales – monthly, seasonal and annual – were utilized to determine the influence of precipitation and CAPE on lightning activity. The results indicated that CAPE stands out as an important variable at all of these timescales for predicting the occurrence of lightning. The correlation coefficient (r) between CAPE and lightning activity was found to be 0.902 (monthly), 0.703 (pre‐monsoon), 0.550 (monsoon) and 0.702 (annual), respectively. Total rain showed strong positive correlation with lightning on monthly scale (r = 0.734) and in the pre‐monsoon season (r = 0.701). However, such relationship was moderate during monsoon (r = 0.455). In contrast, convective rain showed slightly higher correlation during monsoon (r = 0.587) compared with that of pre‐monsoon season (r = 0.532). Because of strong seasonality in the data, convective rain did not exhibit strong relationship on annual scale (r = 0.227). The product variable (e.g. CAPE × precipitation) showed significant correlation on monthly (r = 0.895) and seasonal scales (r = 0.818 during pre‐monsoon and 0.686 in monsoon) but its influence appears to diminish on a longer timescale (r = 0.375). Spatial maps of correlation coefficient revealed significant positive correlation along relatively drier northern parts of Bangladesh. As lightning‐related fatality is on the rise, this study, first of its kind, is expected to inform public policy and provide information necessary for effective management of this atmospheric phenomenon to save lives and property in Bangladesh.

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