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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.

As the world's longest running pandemic, cholera poses a substantial public health burden in Bangladesh, where human vulnerability intersects with climatic variability. Barriers to safe water and sanitation place the health of millions of Bangladeshis in jeopardy – especially those who have highly constrained choices in preventing and responding to cholera. In this paper we investigate demand for cholera prevention among residents in the Mirpur and Karail slum areas of urban Dhaka. Using survey data from 2023 households in two slum areas, we analyze responses from a contingent valuation questionnaire that elicited willingness to pay (WTP) for cholera vaccines across household members and under varying disease risk scenarios, finding higher valuation for cholera prevention for children and under scenarios of greater epidemic risk. We estimate the average WTP for a cholera vaccine for a child ranges from TK 134–167 (US$ 1.58–1.96). Consistently, respondents with prior knowledge of the cholera vaccine reported lower WTP valuations, providing suggestive evidence of concerns about vaccine effectiveness and preferences for cholera treatment over prevention. We supplement the contingent valuation analysis with cost of illness estimates from both our household sample as well as from administrative hospital records of over 34,000 cholera patients. We estimate that a household incurs costs of TK 801–922 (US$ 9.43–10.50) per episode of cholera that requires medical treatment. Taken together, these findings indicate higher WTP for cholera treatment compared to prevention, but increased interest in prevention under early warning system scenarios of high disease risk.

Background Lymphatic filariasis is a neglected tropical disease that can cause permanent disability through disruption of the lymphatic system. This disease is caused by parasitic filarial worms that are transmitted by mosquitos. Mass drug administration (MDA) of antihelmintics is recommended by WHO to eliminate lymphatic filariasis as a public health problem. This study aims to produce the first geospatial estimates of the global prevalence of lymphatic filariasis infection over time, to quantify progress towards elimination, and to identify geographical variation in distribution of infection. Methods A global dataset of georeferenced surveyed locations was used to model annual 2000–18 lymphatic filariasis prevalence for 73 current or previously endemic countries. We applied Bayesian model-based geostatistics and time series methods to generate spatially continuous estimates of global all-age 2000–18 prevalence of lymphatic filariasis infection mapped at a resolution of 5 km2 and aggregated to estimate total number of individuals infected. Findings We used 14 927 datapoints to fit the geospatial models. An estimated 199 million total individuals (95% uncertainty interval 174–234 million) worldwide were infected with lymphatic filariasis in 2000, with totals for WHO regions ranging from 3·1 million (1·6–5·7 million) in the region of the Americas to 107 million (91–134 million) in the South-East Asia region. By 2018, an estimated 51 million individuals (43–63 million) were infected. Broad declines in prevalence are observed globally, but focal areas in Africa and southeast Asia remain less likely to have attained infection prevalence thresholds proposed to achieve local elimination. Interpretation Although the prevalence of lymphatic filariasis infection has declined since 2000, MDA is still necessary across large populations in Africa and Asia. Our mapped estimates can be used to identify areas where the probability of meeting infection thresholds is low, and when coupled with large uncertainty in the predictions, indicate additional data collection or intervention might be warranted before MDA programmes cease. Funding Bill & Melinda Gates Foundation.

Occurrence and growth of Vibrio cholerae, the causative agent of cholera, is linked to modalities of elevated temperatures and heavy precipitation. Previous studies have employed temperature- and s...

The association of cholera and climate has been extensively documented. However, determining the effects of changing climate on the occurrence of disease remains a challenge. Bimodal peaks of cholera in Bengal Delta are hypothesized to be linked to asymmetric flow of the Ganges and Brahmaputra rivers. Spring cholera is related to intrusion of bacteria-laden coastal seawater during low flow seasons, while autumn cholera results from cross-contamination of water resources when high flows in the rivers cause massive inundation. Coarse resolution of General Circulation Model (GCM) output (usually at 100 – 300 km)cannot be used to evaluate variability at the local scale(10–20 km),hence the goal of this study was to develop a framework that could be used to understand impacts of climate change on occurrence of cholera. Instead of a traditional approach of downscaling precipitation, streamflow of the two rivers was directly linked to GCM outputs, achieving reasonable accuracy (R2 = 0.89 for the Ganges and R2 = 0.91 for the Brahmaputra)using machine learning algorithms (Support Vector Regression-Particle Swarm Optimization). Copula methods were used to determine probabilistic risks of cholera under several discharge conditions. Key results, using model outputs from ECHAM5, GFDL, andHadCM3for A1B and A2 scenarios, suggest that the combined low flow of the two rivers may increase in the future, with high flows increasing for first half of this century, decreasing thereafter. Spring and autumn cholera, assuming societal conditions remain constant e.g., at the current rate, may decrease. However significant shifts were noted in the magnitude of river discharge suggesting that cholera dynamics of the delta may well demonstrate an uncertain predictable pattern of occurrence over the next century.

Changes in human water use, along with temperature and rainfall patterns, are facilitating habitat spread and distribution of Aedes aegypti and Aedes albopictus mosquitoes, the primary vectors for the transmission of Dengue, Chikungunya, and Zika viruses in the Americas. Artificial containers and wet spots provide major sources of mosquito larval habitat in residential areas. Mosquito abatement and control strategies remain the most effective public health interventions for minimizing the impact of these vector‐borne diseases. Understanding how water insecurity is conducive to the establishment and elimination of endemic mosquito populations, particularly in arid or semiarid regions, is a vital component in shaping these intervention strategies., Key Points Water insecurity facilitated vector habitats are on the rise in arid and semiarid regions of Mexico and the AmericasTemperature and rainfall changes are facilitating habitat spread and distribution of the Aedes aegypti and the Aedes albopictus mosquitoesFocus should be on improved water management, vector surveillance, and disease awareness among the most vulnerable and migrant populations

Dengue Fever (DF) is a mosquito vector transmitted flavivirus and a reemerging global public health threat. Although several studies have addressed the relation between climatic and environmental factors and the epidemiology of DF, or looked at purely spatial or time series analysis, this article presents a joint spatio-temporal epidemiological analysis. Our approach accounts for both temporal and spatial autocorrelation in DF incidence and the effect of temperatures and precipitation by using a hierarchical Bayesian approach. We fitted several space-time areal models to predict relative risk at the municipality level and for each month from 1990 to 2014. Model selection was performed according to several criteria: the preferred models detected significant effects for temperature at time lags of up to four months and for precipitation up to three months. A boundary detection analysis is incorporated in the modeling approach, and it was successful in detecting municipalities with historically anomalous risk.

Rotavirus is the most common cause of diarrheal disease among children under 5. Especially in South Asia, rotavirus remains the leading cause of mortality in children due to diarrhea. As climatic extremes and safe water availability significantly influence diarrheal disease impacts in human populations, hydroclimatic information can be a potential tool for disease preparedness. In this study, we conducted a multivariate temporal and spatial assessment of 34 climate indices calculated from ground and satellite Earth observations to examine the role of temperature and rainfall extremes on the seasonality of rotavirus transmission in Bangladesh. We extracted rainfall data from the Global Precipitation Measurement and temperature data from the Moderate Resolution Imaging Spectroradiometer sensors to validate the analyses and explore the potential of a satellite‐based seasonal forecasting model. Our analyses found that the number of rainy days and nighttime temperature range from 16°C to 21°C are particularly influential on the winter transmission cycle of rotavirus. The lower number of wet days with suitable cold temperatures for an extended time accelerates the onset and intensity of the outbreaks. Temporal analysis over Dhaka also suggested that water logging during monsoon precipitation influences rotavirus outbreaks during a summer transmission cycle. The proposed model shows lag components, which allowed us to forecast the disease outbreaks 1 to 2 months in advance. The satellite data‐driven forecasts also effectively captured the increased vulnerability of dry‐cold regions of the country, compared to the wet‐warm regions., Key Points Rotavirus shows strong mortality and morbidity, as well as strong spatial and temporal variability in South AsiaStrong winter and weak monsoon transmission cycles dominate South Asia, modulated by regional climatic extremesSatellite‐derived hydroclimatic information has potential to help forecasting of rotavirus risk over Bengal Delta

Letter to the Editor Environmental Factors Influencing Epidemic Cholera Dear Sir: We have concerns with the recent publication by Jutla and colleagues, which aims to describe the environmental factors influencing epidemic cholera. 1 Regarding cholera in Haiti, the authors challenged the findings of many studies showing that the epidemic likely originated from the importation of toxi-genic Vibrio cholerae by Nepalese peacekeepers in October 2010. 2–5 Instead, they attempted to show that environmental conditions conducive to rapid growth and transmission of V. cholerae played a substantial role in epidemic onset. Their hypothesis is based on the claim that increased temperatures and rainfall during the months preceding the epidemic favored the proliferation of V. cholerae in the Haitian waters and its subsequent transmission to the local population 1 ; we believe their claims are based on misinterpretations of our published data and statistical correlations that fail to establish causality. Our field investigation of the Haitian cholera epidemic has clearly indicated that outbreaks started in Meye, near Mirebalais, before subsequently spreading downstream, following the Artibonite River. 2 Using a Spearman's rank statistical test, Jutla and colleagues stated that the correlation between cholera cases in Mirebalais and the Lower Artibonite was " very high, " thereby inferring that the epidemic started simultaneously in the two locations. 1 According to our report, each of the Lower Artibonite communes displayed a markedly higher correlation with the other Lower Artibonite communes than with Mirebalais. 2 Therefore, we did not report a strong correlation between Mirebalais and the Lower Artibonite communes , as claimed by Jutla and colleagues. 1 Nevertheless, correlation analyses are irrelevant to question the chronological progression of the epidemic. Indeed, our field investigation revealed that no suspected cases of cholera or severe diarrhea were reported in the Lower Artibonite before October 19, although the epidemic began on October 14 near Mirebalais. 2

Cholera remains one of the most prevalent water-related infections in many tropical regions of the world. Macro-environmental processes provide a natural ecological niche for Vibrio cholerae and because powerful evidence of new biotypes is emerging, it is unlikely that the bacteria will be fully eradicated. Consequently, to develop effective intervention and mitigation strategies, it is necessary to develop cholera prediction models with several months' lead time. Almost all cholera outbreaks originate near the coastal areas and cholera bacteria exhibit a strong relationship with coastal plankton. Using chlorophyll as a surrogate for plankton bloom in coastal areas, recent studies have postulated a relationship between chlorophyll and cholera incidence. Here, we show that seasonal cholera outbreaks in the Bengal Delta can be predicted two to three months in advance with an overall prediction accuracy of over 75% by using satellite-derived chlorophyll and air temperature data. Such high prediction accuracy is achievable because the two seasonal peaks of cholera are predicted using two separate models representing distinctive macro-scale environmental processes. We have shown that interannual variability of pre-monsoon cholera outbreaks can be satisfactorily explained with coastal plankton blooms and a cascade of hydro-coastal processes. Post-monsoon cholera outbreaks, on the other hand, are related to macro-scale monsoon processes and subsequent breakdown of sanitary conditions. Our results demonstrate that satellite data over a range of space and time scales are effective in developing a cholera prediction model for the Bengal Delta with several months' lead time. We anticipate our modeling framework and findings will provide the impetus to explore the utility of satellite derived macro-scale variables for cholera prediction in other cholera endemic regions. Two seasonal peaks of Bengal cholera can be predicted using two separate models.Two to three months prediction lead time achievable.Prediction accuracy exceeds 75% using combinations of chlorophyll and air temperature data.Cascade of hydro-coastal processes may result in cholera outbreaks.

The ability to predict an occurrence of cholera, a water-related disease, offers a significant public health advantage. Satellite based estimates of chlorophyll, a surrogate for plankton abundance, have been linked to cholera incidence. However, cholera bacteria can survive under a variety of coastal ecological conditions, thus constraining the predictive ability of the chlorophyll, since it provides only an estimate of greenness of seawater. Here, a new remote sensing based index is proposed: Satellite Water Marker (SWM), which estimates condition of coastal water, based on observed variability in the difference between blue (412 nm) and green (555 nm) wavelengths that can be related to seasonal cholera incidence. The index is bounded between physically separable wavelengths for relatively clear (blue) and turbid (green) water. Using SWM, prediction of cholera with reasonable accuracy, with at least two month in advance, can potentially be achieved in the endemic coastal regions.

The Eastern Mediterranean Region (EMR) is witnessing an increase in chronic disorders, including mental illness. With ongoing unrest, this is expected to rise. This is the first study to quantify the burden of mental disorders in the EMR. We used data from the Global Burden of Disease study (GBD) 2013. DALYs (disability-adjusted life years) allow assessment of both premature mortality (years of life lost-YLLs) and nonfatal outcomes (years lived with disability-YLDs). DALYs are computed by adding YLLs and YLDs for each age-sex-country group. In 2013, mental disorders contributed to 5.6% of the total disease burden in the EMR (1894 DALYS/100,000 population): 2519 DALYS/100,000 (2590/100,000 males, 2426/100,000 females) in high-income countries, 1884 DALYS/100,000 (1618/100,000 males, 2157/100,000 females) in middle-income countries, 1607 DALYS/100,000 (1500/100,000 males, 1717/100,000 females) in low-income countries. Females had a greater proportion of burden due to mental disorders than did males of equivalent ages, except for those under 15 years of age. The highest proportion of DALYs occurred in the 25-49 age group, with a peak in the 35-39 years age group (5344 DALYs/100,000). The burden of mental disorders in EMR increased from 1726 DALYs/100,000 in 1990 to 1912 DALYs/100,000 in 2013 (10.8% increase). Within the mental disorders group in EMR, depressive disorders accounted for most DALYs, followed by anxiety disorders. Among EMR countries, Palestine had the largest burden of mental disorders. Nearly all EMR countries had a higher mental disorder burden compared to the global level. Our findings call for EMR ministries of health to increase provision of mental health services and to address the stigma of mental illness. Moreover, our results showing the accelerating burden of mental health are alarming as the region is seeing an increased level of instability. Indeed, mental health problems, if not properly addressed, will lead to an increased burden of diseases in the region.

Cholera bacteria exhibit strong association with coastal plankton. Characterization of space–time variability of chlorophyll, a surrogate for plankton abundance, in the northern Bay of Bengal is an essential first step to develop any methodology for predicting cholera outbreaks in the Bengal Delta region using remote sensing. This study quantifies the space–time distribution of chlorophyll, using the data from SeaWiFS, in the Bay of Bengal region using 10 years of satellite data. Variability of chlorophyll at daily scale, irrespective of spatial averaging, resembles white noise. At a monthly scale, chlorophyll shows distinct seasonality and chlorophyll values are significantly higher close to the coast than in the offshore regions. At pixel level (9 km) on monthly scale, on the other hand, chlorophyll does not exhibit much persistence in time. With increased spatial averaging, temporal persistence of chlorophyll increases and lag 1 autocorrelation stabilizes around 0.60 for 1296 km 2 or larger areal averages. In contrast to the offshore regions, spatial analyses of chlorophyll suggest that only coastal region has a stable correlation length of 100 km. Presence (absence) of correlation length in the coastal (offshore) regions indicate that the two regions may have two separate processes controlling the production of phytoplankton. This study puts a lower limit on space–time averaging of satellite measured plankton at 1296 km 2 monthly scale to establish relationships with cholera incidence in Bengal Delta.

To increase preparedness and improve response to floods in Bangladesh, a streamflow forecasting lead time of 7–10 days is desired at the international border entry points of the major rivers. The accuracy of available streamflow forecast products is currently limited to 3–5 days, which is much shorter than the desired lead time for floods. Several initiatives continue to develop and refine hydrologic and flood forecasting models without adequately exploring the utility of precipitation forecasts to obtain longer flood forecasting lead time. For large basins with a strong seasonality, such as the Ganges, simple but carefully designed linear regression models may provide great value to operational flood forecasting. Here, a simple linear model with observed streamflow and gridded precipitation data for the upstream basin areas is introduced to provide satisfactory forecasts for the Ganges flow at the Hardinge Bridge point with up to 10-day lead time. The proposed linear model can provide 3- to 5-day forecasting lead time using only lagged values of flow with skill comparable to published results of detailed hydrological or statistical models. The results also suggest that 5–6 days forecasted rainfall and observed streamflow are able to enhance streamflow forecasting accuracy for a lead time up to 10 days. The proposed framework can be of great value to operationalize flood forecasting in large basins, where upstream data are scarce or inaccessible due to political boundaries, and detailed forecasting model setups are prohibitively expensive.

Outbreaks of diarrheal diseases, including cholera, are related to floods and droughts in regions where water and sanitation infrastructure are inadequate or insufficient. However, availability of data on water scarcity and abundance in transnational basins, are a prerequisite for developing cholera forecasting systems. With more than a decade of terrestrial water storage (TWS) data from the Gravity Recovery and Climate Experiment, conditions favorable for predicting cholera occurrence may now be determined. We explored lead-lag relationships between TWS in the Ganges-Brahmaputra-Meghna basin and endemic cholera in Bangladesh. Since bimodal seasonal peaks in cholera in Bangladesh occur during spring and autumn seasons, two separate logistical models between TWS and disease time series (2002-2010) were developed. TWS representing water availability showed an asymmetrical, strong association with cholera prevalence in the spring (τ = -0.53; P < 0.001) and autumn (τ = 0.45; P < 0.001) up to 6 months in advance. One unit (centimeter of water) decrease in water availability in the basin increased odds of above normal cholera by 24% (confidence interval [CI] = 20-31%; P < 0.05) in the spring, while an increase in regional water by 1 unit, through floods, increased odds of above average cholera in the autumn by 29% (CI = 22-33%; P < 0.05).

IntroductionCholera, an infectious diarrheal disease, has been shown to be associated with large scale hydroclimatic processes. The sudden and sporadic occurrence of epidemic cholera is linked with high mortality rates, in part, due to uncertainty in timing and location of outbreaks. Improved understanding of the relationship between pathogenic abundance and climatic processes allows prediction of disease outbreak to be an achievable goal. In this study, we show association of large scale hydroclimatic processes with the cholera epidemic in Zimbabwe reported to have begun in Chitungwiza, a city in Mashonaland East province, in August, 2008.Principal findingsClimatic factors in the region were found to be associated with triggering cholera outbreak and are shown to be related to anomalies of temperature and precipitation, validating the hypothesis that poor conditions of sanitation, coupled with elevated temperatures, and followed by heavy rainfall can initiate outbreaks of cholera. Spatial estimation by satellite of precipitation and global gridded air temperature captured sensitivities in hydroclimatic conditions that permitted identification of the location in the region where the disease outbreak began.DiscussionSatellite derived hydroclimatic processes can be used to capture environmental conditions related to epidemic cholera, as occurred in Zimbabwe, thereby providing an early warning system. Since cholera cannot be eradicated because the causative agent, Vibrio cholerae, is autochthonous to the aquatic environment, prediction of conditions favorable for its growth and estimation of risks of triggering the disease in a given population can be used to alert responders, potentially decreasing infection and saving lives.

The highly populated floodplains of the Bengal Delta have a long history of endemic and epidemic cholera outbreaks, both coastal and inland. Previous studies have not addressed the spatio-temporal dynamics of population vulnerability related to the influence of underlying large-scale processes. We analyzed spatial and temporal variability of cholera incidence across six surveillance sites in the Bengal Delta and their association with regional hydroclimatic and environmental drivers. More specifically, we use salinity and flood inundation modeling across the vulnerable districts of Bangladesh to test earlier proposed hypotheses on the role of these environmental variables. Our results show strong influence of seasonal and interannual variability in estuarine salinity on spring outbreaks and inland flooding on fall outbreaks. A large segment of the population in the Bengal Delta floodplains remain vulnerable to these biannual cholera transmission mechanisms that provide ecologic and environmental conditions for outbreaks over large geographic regions.

In this chapter, we provide a physical understanding based on the regional large-scale environmental and hydroclimatic processes of how the first outbreaks of cholera may be related to low flow discharge of the Ganges, Brahmaputra, and Meghna rivers and subsequent and salinity intrusion during spring. Cholera incidence values in this season are inversely related to streamflow volumes, that is, bigger spring cholera peaks are seen in strong drought years. On the other hand, autumn cholera outbreaks are positively correlated to peak streamflow volumes, that is, bigger autumn peaks are seen in high flood years. Evidence points to large-scale population vulnerability to biannual cholera transmission mechanisms that provide ecological and environmental “conditions” for cholera outbreaks in the Bengal Delta floodplains.

[1] Cholera remains a major public health threat in many developing countries around the world. The striking seasonality and annual recurrence of this infectious disease in endemic areas remain of considerable interest to scientists and public health workers. Despite major advances in the ecological and microbiological understanding of Vibrio cholerae, the causative agent of the disease, the role of underlying large-scale hydroclimatic processes in propagating the disease for different seasons and spatial locations is not well understood. Here we show that the cholera outbreaks in the Bengal Delta region are propagated from the coastal to the inland areas and from spring to fall by two distinctly different transmission cycles, premonsoon and postmonsoon, influenced by coastal and terrestrial hydroclimatic processes, respectively. A coupled analysis of the regional hydroclimate and cholera incidence reveals a strong association of the space-time variability of incidence peaks with seasonal processes and extreme climatic events. We explain how the asymmetric seasonal hydroclimatology affects regional cholera dynamics by providing a coastal growth environment for bacteria in spring, while propagating the disease to fall by monsoon flooding. Our findings may serve as the basis for “climate-informed” early warnings and for prompting effective means for intervention and preempting epidemic cholera outbreaks in vulnerable regions.

[1] Cholera has reemerged as a global killer with the world witnessing an unprecedented rise in cholera infection and transmission since the 1990s. Cholera outbreaks across most affected areas show infection patterns with a single annual peak. However, cholera incidences in the Bengal Delta region, the native homeland of cholera, show bi-annual peaks. The mechanisms behind this unique seasonal dual peak phenomenon in cholera dynamics, especially the role of climatic and hydrologic variables, are not fully understood. Here, we show that low flow in the Brahmaputra and the Ganges during spring is associated with the first outbreaks of cholera in Bangladesh; elevated spring cholera outbreaks are seen in low discharge years. Peak streamflow of these rivers, on the other hand, create a different cholera transmission environment; peak flood volumes and extent of flood-affected areas during monsoon are responsible for autumn cholera outbreaks. Our results demonstrate how regional hydroclimatology may explain the seasonality and dual peaks of cholera incidence in the Bengal Delta region. A quantitative understanding of the relationships among the hydroclimatological drivers and seasonal cholera outbreaks will help early cholera detection and prevention efforts.

This article was published in the Bulletin of the World Health Organization [ © 2012 Bulletin of the World Health Organization ] and the definite version is available at : http://dx.doi.org/10.2471/BLT.11.092189 The Journal's website is at: http://www.who.int/bulletin/volumes/90/3/11-092189.pdf

Vibrio cholerae is an estuarine bacterium associated with a single peak of cholera (March-May) in coastal villages of Bangladesh.For anunknownreason, however, cholera occurs in a unique dual peak (March-May and September-November) pattern in the city of Dhakathat is bordered by a heavily polluted freshwater river system and flood embankment. In August 2007, extreme flooding was accompanied by an unusually severe diarrhea outbreak in Dhaka that resulted in a record high illness. This study was aimed to understand the unusual outbreak and if it was related to the circulation of a new V. cholerae clone. Nineteen V. cholerae isolated during the peak of the 2007 outbreak were subjected to extensive phenotypic and molecular analyses, including multilocus genetic screening by polymerase chain reaction (PCR), sequence-typing of the ctxB gene, and pulsed-field gel electrophoresis (PFGE). Factors associated with the unusual incidence of cholera were determined and analysis of the disease severity was done. Overall, microbiological and molecular data confirmed that the hypervirulent V. cholerae was O1 biotype El Tor (ET) that possessed cholera toxin (CT) of the classical biotype. The PFGE ( Not I) and dendrogram clustering confirmed that the strains were clonal and related to the pre-2007 variant ET from Dhaka and Matlab and resembled one of two distinct clones of the variant ETconfirmed to be present in the estuarine ecosystem of Bangladesh. Results of the analyses of both diarrheal case data for three consecutive years (2006-2008) and regional hydroclimatology over three decades (1980-2009) clearly indicate that the pattern of cholera occurring in Dhaka, and not seen at other endemic sites, was associated with flood waters transmitting the infectious clone circulating via the fecal-oral route during and between the dual seasonal cholera peaks in Dhaka. Circular river systems and flood embankment likely facilitate transmission of infectious V. cholerae throughout the year that leads to both sudden and off-season outbreaks in the densely populated urban ecosystem of Dhaka. Clonal recycling of hybrid ElTor with increasing virulence in a changing climate and in a region with a growing urban population represents a serious public health concern for Bangladesh. Keywords: Cholera; Vibrio cholerae; dual peak; flood; off-season; fecal-oral; clonal transmission (Published: 8 August 2011) Citation: Infection Ecology and Epidemiology 2011, 1 : 7273 - DOI: 10.3402/iee.v1i0.7273