Cholera in Bangladesh: climatic components of seasonal variation

Causal inference concepts can guide research into the effects of climate on infectious diseases

A pressing question resulting from global warming is how climate change will affect infectious diseases. Answering this question requires research into the effects of weather on the population dynamics of transmission and infection; elucidating these effects, however, has proved difficult due to the challenges of assessing causality from the predominantly observational data available in epidemiological research. Here we show how concepts from causal inference-the sub-field of statistics aiming at inferring causality from data-can guide that research. Through a series of case studies, we illustrate how such concepts can help assess study design and strategically choose a study's location, evaluate and reduce the risk of bias, and interpret the multifaceted effects of meteorological variables on transmission. More broadly, we argue that interdisciplinary approaches based on explicit causal frameworks are crucial for reliably estimating the effect of weather and accurately predicting the consequences of climate change.

Satellite-Derived, Smartphone-Delivered Geospatial Cholera Risk Information for Vulnerable Populations

Cholera, an acute waterborne diarrheal disease, remains a major global health challenge. Despite being curable and preventable, it can be fatal if left untreated, especially for children. Bangladesh, a cholera-endemic country with a high disease burden, experiences two peaks annually, during the dry pre-monsoon spring and the wet post-monsoon fall seasons. An early warning system for disseminating cholera risk, which has potential to reduce the disease burden, currently does not exist in Bangladesh. Such systems can raise timely awareness and allow households in rural, riverine areas like Matlab to make behavioral adjustments with water usage and around water resources to reduce contracting and transmitting cholera. Current dissemination approaches typically target local government and public health organizations; however, the vulnerable rural populations largely remain outside the information chain. Here, we develop and evaluate the accuracy of an early warning system-CholeraMap that uses high-resolution earth observations to forecast cholera risk and disseminate geocoded risk maps directly to Matlab's population via a mobile smartphone application. Instead of relying on difficult to obtain station-based environmental and hydroclimatological data, this study offers a new opportunity to use remote sensing data sets for designing and operating a disease early warning system. CholeraMap delivers monthly, color-coded geospatial maps (1 km × 1 km spatial resolution) with household and community cholera risk information. Our results demonstrate that the satellite-derived local-scale risk model satisfactorily captured the seasonal cholera pattern for the Matlab region, and a detailed high-resolution picture of the spatial progression of at-risk areas during outbreak months.

Mechanisms of cholera transmission via environment in India and Bangladesh: state of the science review

OBJECTIVES

Cholera has a long history in India and Bangladesh, the region where six out of the past seven global pandemics have been seeded. The changing climate and growing population have led to global cholera cases remaining high despite a consistent improvement in the access to clean water and sanitation. We aim to provide a holistic overview of variables influencing environmental cholera transmission within the context of India and Bangladesh, with a focus on the mechanisms by which they act.

CONTENT

We identified 56 relevant texts (Bangladesh n = 40, India n = 7, Other n = 5). The results of the review found that cholera transmission is associated with several socio-economic and environmental factors, each associated variable is suggested to have at least one mediating mechanism. Increases in ambient temperature and coastal sea surface temperature support cholera transmission via increases in plankton and a preference of Vibrio cholerae for warmer waters. Increased rainfall can potentially support or reduce transmission via several mechanisms.

SUMMARY AND OUTLOOK

Common issues in the literature are co-variance of seasonal factors, limited access to high quality cholera data, high research bias towards research in Dhaka and Matlab (Bangladesh). A specific and detailed understanding of the relationship between SST and cholera incidence remains unclear.

Cholera rages in Africa and the Middle East: A narrative review on challenges and solutions

Background and Aim

Cholera is a life-threatening infectious disease that is still one of the most common acute watery diarrheal diseases in the world today. Acute diarrhea and severe dehydration brought on by cholera can cause hypovolemic shock, which can be fatal in minutes. Without competent clinical therapy, the rate of case fatality surpasses 50%. The purpose of this review was to highlight cholera challenges in Africa and the Middle East and explain the reasons for why this region is currently a fertile environment for cholera. We investigated cholera serology, epidemiology, and the geographical distribution of cholera in Africa and the Middle East in 2022 and 2023. We reviewed detection methods, such as rapid diagnostic tests (RDTs), and treatments, such as antibiotics and phage therapy. Finally, this review explored oral cholera vaccines (OCVs), and the vaccine shortage crisis.

Methods

We carried out a systematic search in multiple databases, including PubMed, Web of Science, Google Scholar, Scopus, MEDLINE, and Embase, for studies on cholera using the following keywords: ((Cholera) OR (Vibrio cholera) and (Coronavirus) OR (COVID-19) OR (SARS-CoV2) OR (The Middle East) OR (Africa)).

Results and Conclusions

Cholera outbreaks have increased dramatically, mainly in Africa and many Middle Eastern countries. The COVID-19 pandemic has reduced the attention devoted to cholera and disrupted diagnosis and treatment services, as well as vaccination initiatives. Most of the cholera cases in Africa and the Middle East were reported in Malawi and Syria, respectively, in 2022. RDTs are effective in the early detection of cholera epidemics, especially with limited advanced resources, which is the case in much of Africa. By offering both direct and indirect protection, expanding the use of OCV will significantly reduce the burden of current cholera outbreaks in Africa and the Middle East.

Building a pathway to One Health surveillance and response in Asian countries

To detect and respond to emerging diseases more effectively, an integrated surveillance strategy needs to be applied to both human and animal health. Current programs in Asian countries operate separately for the two sectors and are principally concerned with detection of events that represent a short-term disease threat. It is not realistic to either invest only in efforts to detect emerging diseases, or to rely solely on event-based surveillance. A comprehensive strategy is needed, concurrently investigating and managing endemic zoonoses, studying evolving diseases which change their character and importance due to influences such as demographic and climatic change, and enhancing understanding of factors which are likely to influence the emergence of new pathogens. This requires utilisation of additional investigation tools that have become available in recent years but are not yet being used to full effect. As yet there is no fully formed blueprint that can be applied in Asian countries. Hence a three-step pathway is proposed to move towards the goal of comprehensive One Health disease surveillance and response.

Seasonality of cholera in Kolkata and the influence of climate

BACKGROUND

Cholera in Kolkata remains endemic and the Indian city is burdened with a high number of annual cases. Climate change is widely considered to exacerbate cholera, however the precise relationship between climate and cholera is highly heterogeneous in space and considerable variation can be observed even within the Indian subcontinent. To date, relatively few studies have been conducted regarding the influence of climate on cholera in Kolkata.

METHODS

We considered 21 years of confirmed cholera cases from the Infectious Disease Hospital in Kolkata during the period of 1999-2019. We used Generalised Additive Modelling (GAM) to extract the non-linear relationship between cholera and different climatic factors; temperature, rainfall and sea surface temperature (SST). Peak associated lag times were identified using cross-correlation lag analysis.

RESULTS

Our findings revealed a bi-annual pattern of cholera cases with two peaks coinciding with the increase in temperature in summer and the onset of monsoon rains. Variables selected as explanatory variables in the GAM model were temperature and rainfall. Temperature was the only significant factor associated with summer cholera (mean temperature of 30.3 °C associated with RR of 3.8) while rainfall was found to be the main driver of monsoon cholera (550 mm total monthly rainfall associated with RR of 3.38). Lag time analysis revealed that the association between temperature and cholera cases in the summer had a longer peak lag time compared to that between rainfall and cholera during the monsoon. We propose several mechanisms by which these relationships are mediated.

CONCLUSIONS

Kolkata exhibits a dual-peak phenomenon with independent mediating factors. We suggest that the summer peak is due to increased bacterial concentration in urban water bodies, while the monsoon peak is driven by contaminated flood waters. Our results underscore the potential utility of preventative strategies tailored to these seasonal and climatic patterns, including efforts to reduce direct contact with urban water bodies in summer and to protect residents from flood waters during monsoon.

Derivation and External Validation of a Clinical Prediction Model for Viral Diarrhea Etiology in Bangladesh

Background

Antibiotics are commonly overused for diarrheal illness in many low- and middle-income countries, partly due to a lack of diagnostics to identify viral cases, in which antibiotics are not beneficial. This study aimed to develop clinical prediction models to predict risk of viral-only diarrhea across all ages, using routinely collected demographic and clinical variables.

Methods

We used a derivation dataset from 10 hospitals across Bangladesh and a separate validation dataset from the icddr,b Dhaka Hospital. The primary outcome was viral-only etiology determined by stool quantitative polymerase chain reaction. Multivariable logistic regression models were fit and externally validated; discrimination was quantified using area under the receiver operating characteristic curve (AUC) and calibration assessed using calibration plots.

Results

Viral-only diarrhea was common in all age groups (<1 year, 41.4%; 18-55 years, 17.7%). A forward stepwise model had AUC of 0.82 (95% confidence interval [CI], .80-.84) while a simplified model with age, abdominal pain, and bloody stool had AUC of 0.81 (95% CI, .78-.82). In external validation, the models performed adequately although less robustly (AUC, 0.72 [95% CI, .70-.74]).

Conclusions

Prediction models consisting of 3 routinely collected variables can accurately predict viral-only diarrhea in patients of all ages in Bangladesh and may help support efforts to reduce inappropriate antibiotic use.

Climate Change and Cascading Risks from Infectious Disease

Climate change is adversely affecting the burden of infectious disease throughout the world, which is a health security threat. Climate-sensitive infectious disease includes vector-borne diseases such as malaria, whose transmission potential is expected to increase because of enhanced climatic suitability for the mosquito vector in Asia, sub-Saharan Africa, and South America. Climatic suitability for the mosquitoes that can carry dengue, Zika, and chikungunya is also likely to increase, facilitating further increases in the geographic range and longer transmission seasons, and raising concern for expansion of these diseases into temperate zones, particularly under higher greenhouse gas emission scenarios. Early spring temperatures in 2018 seem to have contributed to the early onset and extensive West Nile virus outbreak in Europe, a pathogen expected to expand further beyond its current distribution, due to a warming climate. As for tick-borne diseases, climate change is projected to continue to contribute to the spread of Lyme disease and tick-borne encephalitis, particularly in North America and Europe. Schistosomiasis is a water-borne disease and public health concern in Africa, Latin America, the Middle East, and Southeast Asia; climate change is anticipated to change its distribution, with both expansions and contractions expected. Other water-borne diseases that cause diarrheal diseases have declined significantly over the last decades owing to socioeconomic development and public health measures but changes in climate can reverse some of these positive developments. Weather and climate events, population movement, land use changes, urbanization, global trade, and other drivers can catalyze a succession of secondary events that can lead to a range of health impacts, including infectious disease outbreaks. These cascading risk pathways of causally connected events can result in large-scale outbreaks and affect society at large. We review climatic and other cascading drivers of infectious disease with projections under different climate change scenarios. Supplementary file1 (MP4 328467 KB).

Assessing seasonality and the role of its potential drivers in environmental epidemiology: a tutorial

Several methods have been used to assess the seasonality of health outcomes in epidemiological studies. However, little information is available on the methods to study the changes in seasonality before and after adjusting for environmental or other known seasonally varying factors. Such investigations will help us understand the role of these factors in seasonal variation in health outcomes and further identify currently unknown or unmeasured risk factors. This tutorial illustrates a statistical procedure for examining the seasonality of health outcomes and their changes, after adjusting for potential environmental drivers by assessing and comparing shape, timings and size. We recommend a three-step procedure, each carried out and compared before and after adjustment: (i) inspecting the fitted seasonal curve to determine the broad shape of seasonality; (ii) identifying the peak and trough of seasonality to determine the timings of seasonality; and (iii) estimating the peak-to-trough ratio and attributable fraction to measure the size of seasonality. Reporting changes in these features on adjusting for potential drivers allows readers to understand their role in seasonality and the nature of any residual seasonal pattern. Furthermore, the proposed approach can be extended to other health outcomes and environmental drivers.

Vibrio cholerae O139 persists in Dhaka, Bangladesh since 1993

BACKGROUND

After a multi-country Asian outbreak of cholera due to Vibrio cholerae serogroup O139 which started in 1992, it is rarely detected from any country in Asia and has not been detected from patients in Africa.

METHODOLOGY/PRINCIPAL FINDINGS

We extracted surveillance data from the Dhaka and Matlab Hospitals of International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b) to review trends in isolation of Vibrio cholerae O139 in Bangladesh. Data from the Dhaka Hospital is a 2% sample of > 100,000 diarrhoeal patients treated annually. Data from the Matlab Hospital includes all diarrhoeal patients who hail from the villages included in the Matlab Health and Demographic Surveillance System. Vibrio cholerae O139 was first isolated in Dhaka in 1993 and had been isolated every year since then except for a gap between 2005 and 2008. An average of thirteen isolates was detected annually from the Dhaka Hospital during the last ten years, yielding an estimated 650 cases annually at this hospital. During the last ten years, cases due to serogroup O139 represented 0.47% of all cholera cases; the others being due to serogroup O1. No cases with serogroup O139 were identified at Matlab since 2006. Clinical signs and symptoms of cholera due to serogroup O139 were similar to cases due to serogroup O1 though more of the O139 cases were not dehydrated. Most isolates of O139 remained sensitive to tetracycline, ciprofloxacin, and azithromycin, but they became resistant to erythromycin starting in 2009.

CONCLUSIONS/SIGNIFICANCE

Cholera due to Vibrio cholerae serogroup O139 continues to cause typical cholera in Dhaka, Bangladesh.

How climate change can affect cholera incidence and prevalence? A systematic review

Although the number of cholera infection decreased universally, climate change can potentially affect both incidence and prevalence rates of disease in endemic regions. There is considerable consistent evidence, explaining the associations between cholera and climatic variables. However, it is essentially required to compare and interpret these relationships globally. The aim of the present study was to carry out a systematic review in order to identify and appraise the literature concerning the relationship between nonanthropogenic climatic variabilities such as extreme weather- and ocean-related variables and cholera infection rates. The systematic literature review of studies was conducted by using determined search terms via four major electronic databases (PubMed, Web of Science, Embase, and Scopus) according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach. This search focused on published articles in English-language up to December 31, 2018. A total of 43 full-text studies that met our criteria have been identified and included in our analysis. The reviewed studies demonstrated that cholera incidence is highly attributed to climatic variables, especially rainfall, temperature, sea surface temperature (SST) and El Niño Southern Oscillation (ENSO). The association between cholera incidence and climatic variables has been investigated by a variety of data analysis methodologies, most commonly time series analysis, generalized linear model (GLM), regression analysis, and spatial/GIS. The results of this study assist the policy-makers who provide the efforts for planning and prevention actions in the face of changing global climatic variables.

Volcanic activity controls cholera outbreaks in the East African Rift

We hypothesized that Cholera (Vibrio cholerae) that appeared along Lake Kivu in the African Rift in the seventies, might be controlled by volcano-tectonic activity, which, by increasing surface water and groundwater salinity and temperature, may partly rule the water characteristics of Lake Kivu and promote V. cholerae proliferation. Volcanic activity (assessed weekly by the SO2 flux of Nyiragongo volcano plume over the 2007-2012 period) is highly positively correlated with the water conductivity, salinity and temperature of the Kivu lake. Over the 2007-2012 period, these three parameters were highly positively correlated with the temporal dynamics of cholera cases in the Katana health zone that border the lake. Meteorological variables (air temperature and rainfall), and the other water characteristics (namely pH and dissolved oxygen concentration in lake water) were unrelated to cholera dynamics over the same period. Over the 2016-2018 period, we sampled weekly lake water salinity and conductivity, and twice a month vibrio occurrence in lake water and fish. The abundance of V. cholerae in the lake was positively correlated with lake salinity, temperature, and the number of cholera cases in the population of the Katana health zone. V. cholerae abundance in fishes was positively correlated with V. cholerae abundance in lake water, suggesting that their consumption directly contaminate humans. The activity of the volcano, by controlling the physico-chemical characteristics of Lake Kivu, is therefore a major determinant of the presence of the bacillus in the lake. SO2 fluxes in the volcano plume can be used as a tool to predict epidemic risks.

Quantifying public health risks from exposure to waterborne pathogens during river bathing as a basis for reduction of disease burden

A Quantitative Microbial Risk Assessment (QMRA) technique was applied to assess the public health risk from exposure to infectious microorganisms at bathing areas of three rivers in Bangladesh. The QMRA assessed the probability of illness due to the accidental ingestion of river water impacted by untreated sewage. The simplified QMRA was based on average concentrations of four reference pathogens Escherichia coli (E. coli) O157:H7, Cryptosporidium spp, norovirus and rotavirus relative to indicator bacterium E. coli. Public health risk was estimated as the probability of infection and illness from a single exposure of bathers. The risks of illness were ranged from 7 to 10% for E. coli O157:H7, 13 to 19% for Cryptosporidium, 7 to 10% for norovirus and 12 to 17% for rotavirus. The overall risk of illness at the rivers was slightly higher in children (9-19%) compared to adults (7-16%). The risks of illness in individuals exposed to the river bathing were unacceptably high, exceeding the USEPA acceptable risk of 3-6 illnesses per hundred bathing events. This study gives a basis for reducing the burden of disease in the population by applying appropriate risk management. Findings and methods of this study will be helpful for other countries with similar socio-economic and geographic settings.

Stemming cholera tides in Zimbabwe through mass vaccination

BACKGROUND

In 2018, Zimbabwe declared another major cholera outbreak a decade after recording one of the worst cholera outbreaks in Africa.

METHODS

A mathematical model for cholera was used to estimate the magnitude of the cholera outbreak and vaccination coverage using cholera cases reported data. A Markov chain Monte Carlo method based on a Bayesian framework was used to fit the model in order to estimate the basic reproductive number and required vaccination coverage for cholera control.

RESULTS

The results showed that the outbreak had a basic reproductive number of 1.82 (95% credible interval [CrI] 1.53-2.11) and required vaccination coverage of at least 58% (95% Crl 45-68%) to be contained using an oral cholera vaccine of 78% efficacy. Sensitivity analysis demonstrated that a vaccine with at least 55% efficacy was sufficient to contain the outbreak but at higher coverage of 75% (95% Crl 58-88%). However, high-efficacy vaccines would greatly reduce the required coverage, with 100% efficacy vaccine reducing coverage to 45% (95% Crl 35-53%).

CONCLUSIONS

These findings reinforce the crucial need for oral cholera vaccines to control cholera in Zimbabwe, considering that the decay of water reticulation and sewerage infrastructure is unlikely to be effectively addressed in the coming years.

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.

The effect of climate change on cholera disease: The road ahead using artificial neural network

Climate change has been described to raise outbreaks of water-born infectious diseases and increases public health concerns. This study aimed at finding out these impacts on cholera infections by using Artificial Neural Networks (ANNs) from 2021 to 2050. Daily data for cholera infection cases in Qom city, which is located in the center of Iran, were analyzed from 1998 to 2016. To determine the best lag time and combination of inputs, Gamma Test (GT) was applied. General circulation model outputs were utilized to project future climate pattern under two scenarios of Representative Concentration Pathway (RCP2.6 and RCP8.5). Statistical downscaling was done to produce high-resolution synthetic time series weather dataset. ANNs were applied for simulating the impact of climate change on cholera. The observed climate variables including maximum and minimum temperatures and precipitation were tagged as predictors in ANNs. Cholera cases were considered as the target outcome variable. Projected future (2020–2050) climate in previous step was carried out to assess future cholera incidence. A seasonal trend in cholera infection was seen. Our results elucidated that the best lag time was 21 days. According to the results of downscaling tool, future climate in the study area by 2050 will be warmer and wetter. Simulation of cholera cases indicated that there is a clear trend of increasing cholera cases under the worst scenario (RCP8.5) by the year 2050 and the highest cholera cases observe in warmer months. The precipitation was recognized as the most effective input variable by sensitivity analysis. We observed a significant correlation between low precipitation and cholera infection. There is a strong evidence to show that cholera disease is correlated with environment variables, as low precipitation and high temperatures in warmer months could provide the swifter bacterial replication. These conditions in Iran, especially in the central parts, may raise the cholera infection rates. Furthermore, ANNs is an executive tool to simulate the impact of climate change on cholera to estimate the future trend of cholera incidence for adopting protective measures in endemic areas.

Descriptive epidemiology of cholera outbreak in Nigeria, January-November, 2018: implications for the global roadmap strategy

BACKGROUND

The cholera outbreak in 2018 in Nigeria reaffirms its public health threat to the country. Evidence on the current epidemiology of cholera required for the design and implementation of appropriate interventions towards attaining the global roadmap strategic goals for cholera elimination however seems lacking. Thus, this study aimed at addressing this gap by describing the epidemiology of the 2018 cholera outbreak in Nigeria.

METHODS

This was a retrospective analysis of surveillance data collected between January 1st and November 19th, 2018. A cholera case was defined as an individual aged 2 years or older presenting with acute watery diarrhoea and severe dehydration or dying from acute watery diarrhoea. Descriptive analyses were performed and presented with respect to person, time and place using appropriate statistics.

RESULTS

There were 43,996 cholera cases and 836 cholera deaths across 20 states in Nigeria during the outbreak period, with an attack rate (AR) of 127.43/100,000 population and a case fatality rate (CFR) of 1.90%. Individuals aged 15 years or older (47.76%) were the most affected age group, but the proportion of affected males and females was about the same (49.00 and 51.00% respectively). The outbreak was characterised by four distinct epidemic waves, with higher number of deaths recorded in the third and fourth waves. States from the north-west and north-east regions of the country recorded the highest ARs while those from the north-central recorded the highest CFRs.

CONCLUSION

The severity and wide-geographical distribution of cholera cases and deaths during the 2018 outbreak are indicative of an elevated burden, which was more notable in the northern region of the country. Overall, the findings reaffirm the strategic role of a multi-sectoral approach in the design and implementation of public health interventions aimed at preventing and controlling cholera in Nigeria.

Increase in Reported Cholera Cases in Haiti Following Hurricane Matthew: An Interrupted Time Series Model

Matthew, a category 4 hurricane, struck Haiti on October 4, 2016, causing widespread flooding and damage to buildings and crops, and resulted in many deaths. The damage caused by Matthew raised concerns of increased cholera transmission particularly in Sud and Grand'Anse departments, regions which were hit most heavily by the storm. To evaluate the change in reported cholera cases following Hurricane Matthew on reported cholera cases, we used interrupted time series regression models of daily reported cholera cases, controlling for the impact of both rainfall, following a 4-week lag, and seasonality, from 2013 through 2016. Our results indicate a significant increase in reported cholera cases after Matthew, suggesting that the storm resulted in an immediate surge in suspect cases, and a decline in reported cholera cases in the 46-day post-storm period, after controlling for rainfall and seasonality. Regression models stratified by the department indicate that the impact of the hurricane was regional, with larger surges in the two most highly storm-affected departments: Sud and Grand'Anse. These models were able to provide input to the Ministry of Health in Haiti on the national and regional impact of Hurricane Matthew and, with further development, could provide the flexibility of use in other emergency situations. This article highlights the need for continued cholera prevention and control efforts, particularly in the wake of natural disasters such as hurricanes, and the continued need for intensive cholera surveillance nationally.

Influences of heatwave, rainfall, and tree cover on cholera in Bangladesh

Cholera is a severe diarrheal disease and remains a global threat to public health. Climate change and variability have the potential to increase the distribution and magnitude of cholera outbreaks. However, the effect of heatwave on the occurrence of cholera at individual level is still unclear. It is also unknown whether the local vegetation could potentially mitigate the effects of extreme heat on cholera outbreaks. In this study, we designed a case-crossover study to examine the association between the risk of cholera and heatwaves as well as the modification effects of rainfall and tree cover. The study was conducted in Matlab, a cholera endemic area of rural Bangladesh, where cholera case data were collected between January 1983 and April 2009. The association between the risk of cholera and heatwaves was examined using conditional logistic regression models. The results showed that there was a higher risk of cholera two days after heatwaves (OR = 1.53, 95% CI: 1.07-2.19) during wet days (rainfall > 0 mm). For households with less medium-dense tree cover, the heatwave after a 2-day lag was positively associated (OR = 1.80, 95% CI: 1.01-3.22) with the risk of cholera during wet days. However, for households with more medium-dense tree cover, the association between the risk of cholera and heatwave in 2-day lag was not significant. These findings suggest that heatwaves might promote the occurrence of cholera, while this relationship was modified by rainfall and tree cover. Further investigations are needed to explore major mechanisms underlying the association between heatwaves and cholera as well as the beneficial effects of tree cover.

Cholera

PURPOSE OF REVIEW

This review describes the basic epidemiologic, clinical, and microbiologic aspects of cholera, highlights new developments within these areas, and presents strategies for applying currently available tools and knowledge more effectively.

RECENT FINDINGS

From 1990 to 2016, the reported global burden of cholera fluctuated between 74,000 and 595,000 cases per year; however, modeling estimates suggest the real burden is between 1.3 and 4.0 million cases and 95,000 deaths yearly. In 2018, the World Health Assembly endorsed a new initiative to reduce cholera deaths by 90% and eliminate local cholera transmission in 20 countries by 2030. New tools, including localized GIS mapping, climate modeling, whole genome sequencing, oral vaccines, rapid diagnostic tests, and new applications of water, sanitation, and hygiene interventions, could support this goal. Challenges include a high proportion of fragile states among cholera-endemic countries, urbanization, climate change, and the need for cholera treatment guidelines for pregnant women and malnourished children.

SUMMARY

Reducing cholera morbidity and mortality depends on real-time surveillance, outbreak detection and response; timely access to appropriate case management and cholera vaccines; and provision of safe water, sanitation, and hygiene.

Cholera epidemic in Yemen, 2016-18: an analysis of surveillance data

Background

In war-torn Yemen, reports of confirmed cholera started in late September, 2016. The disease continues to plague Yemen today in what has become the largest documented cholera epidemic of modern times. We aimed to describe the key epidemiological features of this epidemic, including the drivers of cholera transmission during the outbreak.

Methods

The Yemen Health Authorities set up a national cholera surveillance system to collect information on suspected cholera cases presenting at health facilities. Individual variables included symptom onset date, age, severity of dehydration, and rapid diagnostic test result. Suspected cholera cases were confirmed by culture, and a subset of samples had additional phenotypic and genotypic analysis. We first conducted descriptive analyses at national and governorate levels. We divided the epidemic into three time periods: the first wave (Sept 28, 2016, to April 23, 2017), the increasing phase of the second wave (April 24, 2017, to July 2, 2017), and the decreasing phase of the second wave (July 3, 2017, to March 12, 2018). We reconstructed the changes in cholera transmission over time by estimating the instantaneous reproduction number, R_t. Finally, we estimated the association between rainfall and the daily cholera incidence during the increasing phase of the second epidemic wave by fitting a spatiotemporal regression model.

Findings

From Sept 28, 2016, to March 12, 2018, 1 103 683 suspected cholera cases (attack rate 3·69%) and 2385 deaths (case fatality risk 0·22%) were reported countrywide. The epidemic consisted of two distinct waves with a surge in transmission in May, 2017, corresponding to a median R_t of more than 2 in 13 of 23 governorates. Microbiological analyses suggested that the same Vibrio cholerae O1 Ogawa strain circulated in both waves. We found a positive, non-linear, association between weekly rainfall and suspected cholera incidence in the following 10 days; the relative risk of cholera after a weekly rainfall of 25 mm was 1·42 (95% CI 1·31–1·55) compared with a week without rain.

Interpretation

Our analysis suggests that the small first cholera epidemic wave seeded cholera across Yemen during the dry season. When the rains returned in April, 2017, they triggered widespread cholera transmission that led to the large second wave. These results suggest that cholera could resurge during the ongoing 2018 rainy season if transmission remains active. Therefore, health authorities and partners should immediately enhance current control efforts to mitigate the risk of a new cholera epidemic wave in Yemen.

Funding

Health Authorities of Yemen, WHO, and Médecins Sans Frontières.

Cholera in Cameroon, 2000-2012: Spatial and Temporal Analysis at the Operational (Health District) and Sub Climate Levels

INTRODUCTION

Recurrent cholera outbreaks have been reported in Cameroon since 1971. However, case fatality ratios remain high, and we do not have an optimal understanding of the epidemiology of the disease, due in part to the diversity of Cameroon's climate subzones and a lack of comprehensive data at the health district level.

METHODS/FINDINGS

A unique health district level dataset of reported cholera case numbers and related deaths from 2000-2012, obtained from the Ministry of Public Health of Cameroon and World Health Organization (WHO) country office, served as the basis for the analysis. During this time period, 43,474 cholera cases were reported: 1748 were fatal (mean annual case fatality ratio of 7.9%), with an attack rate of 17.9 reported cases per 100,000 inhabitants per year. Outbreaks occurred in three waves during the 13-year time period, with the highest case fatality ratios at the beginning of each wave. Seasonal patterns of illness differed strikingly between climate subzones (Sudano-Sahelian, Tropical Humid, Guinea Equatorial, and Equatorial Monsoon). In the northern Sudano-Sahelian subzone, highest number of cases tended to occur during the rainy season (July-September). The southern Equatorial Monsoon subzone reported cases year-round, with the lowest numbers during peak rainfall (July-September). A spatial clustering analysis identified multiple clusters of high incidence health districts during 2010 and 2011, which were the 2 years with the highest annual attack rates. A spatiotemporal autoregressive Poisson regression model fit to the 2010-2011 data identified significant associations between the risk of transmission and several factors, including the presence of major waterbody or highway, as well as the average daily maximum temperature and the precipitation levels over the preceding two weeks. The direction and/or magnitude of these associations differed between climate subzones, which, in turn, differed from national estimates that ignored subzones differences in climate variables.

CONCLUSIONS/SIGNIFICANCE

The epidemiology of cholera in Cameroon differs substantially between climate subzones. Development of an optimal comprehensive country-wide control strategy for cholera requires an understanding of the impact of the natural and built environment on transmission patterns at the local level, particularly in the setting of ongoing climate change.

Untangling the Impacts of Climate Change on Waterborne Diseases: a Systematic Review of Relationships between Diarrheal Diseases and Temperature, Rainfall, Flooding, and Drought

Global climate change is expected to affect waterborne enteric diseases, yet to date there has been no comprehensive, systematic review of the epidemiological literature examining the relationship between meteorological conditions and diarrheal diseases. We searched PubMed, Embase, Web of Science, and the Cochrane Collection for studies describing the relationship between diarrheal diseases and four meteorological conditions that are expected to increase with climate change: ambient temperature, heavy rainfall, drought, and flooding. We synthesized key areas of agreement and evaluated the biological plausibility of these findings, drawing from a diverse, multidisciplinary evidence base. We identified 141 articles that met our inclusion criteria. Key areas of agreement include a positive association between ambient temperature and diarrheal diseases, with the exception of viral diarrhea and an increase in diarrheal disease following heavy rainfall and flooding events. Insufficient evidence was available to evaluate the effects of drought on diarrhea. There is evidence to support the biological plausibility of these associations, but publication bias is an ongoing concern. Future research evaluating whether interventions, such as improved water and sanitation access, modify risk would further our understanding of the potential impacts of climate change on diarrheal diseases and aid in the prioritization of adaptation measures.

Tracking Cholera through Surveillance of Oral Rehydration Solution Sales at Pharmacies: Insights from Urban Bangladesh

Background

In Bangladesh, pharmacy-purchased oral rehydration solution (ORS) is often used to treat diarrhea, including cholera. Over-the-counter sales have been used for epidemiologic surveillance in the past, but rarely, if ever, in low-income countries. With few early indicators for cholera outbreaks in endemic areas, diarrhea-related product sales may serve as a useful surveillance tool.

Methodology/Principal Findings

We tracked daily ORS sales at 50 pharmacies and drug-sellers in an urban Bangladesh community of 129,000 for 6-months while simultaneously conducting surveillance for diarrhea hospitalizations among residents. We developed a mobile phone based system to track the sales of ORS and deployed it in parallel with a paper-based system. Our objectives were to determine if the mobile phone system was practical and acceptable to pharmacists and drug sellers, whether data were reported accurately compared to a paper-based system, and whether ORS sales were associated with future incidence of cholera hospitalizations within the community. We recorded 47,215 customers purchasing ORS, and 315 hospitalized diarrhea cases, 22% of which had culture-confirmed cholera. ORS sales and diarrhea incidence were independently associated with the mean daily temperature; therefore both unadjusted and adjusted models were explored. Through unadjusted cross-correlation statistics and generalized linear models, we found increases in ORS sales were significantly associated with increases in hospitalized diarrhea cases up to 9-days later and hospitalized cholera cases up to one day later. After adjusting for mean daily temperature, ORS was significantly associated with hospitalized diarrhea two days later and hospitalized cholera one day later.

Conclusions/Significance

Pharmacy sales data may serve as a feasible and useful surveillance tool. Given the relatively short lagged correlation between ORS sales and diarrhea, rapid and accurate sales data are key. More work is needed in creating actionable algorithms that make use of this data and in understanding the generalizability of our findings to other settings.

In Bangladesh, people often purchase oral rehydration solution (ORS) at their neighborhood pharmacy to treat diarrhea, including cholera. Over-the-counter sales have been used for epidemiologic surveillance, but rarely in low-income countries. With few early indicators for cholera outbreaks in endemic areas, diarrhea-related product sales may be a useful surveillance tool. We tracked daily ORS sales at pharmacies and drug-sellers in an urban Bangladesh community with both a mobile phone and paper-based system while conducting surveillance for diarrhea hospitalizations among residents. We found that increases in ORS sales were significantly associated increases in hospitalized diarrhea cases up to two days later and hospitalized cholera cases up to one day later. Our findings suggest that surveillance systems based on over-the-counter product sales may be a feasible and useful way to detect outbreaks in low-income settings and that mobile technology may make it even easier to collect implement.

Impacts of El Niño Southern Oscillation and Indian Ocean Dipole on dengue incidence in Bangladesh

Dengue dynamics are driven by complex interactions between hosts, vectors and viruses that are influenced by environmental and climatic factors. Several studies examined the role of El Niño Southern Oscillation (ENSO) in dengue incidence. However, the role of Indian Ocean Dipole (IOD), a coupled ocean atmosphere phenomenon in the Indian Ocean, which controls the summer monsoon rainfall in the Indian region, remains unexplored. Here, we examined the effects of ENSO and IOD on dengue incidence in Bangladesh. According to the wavelet coherence analysis, there was a very weak association between ENSO, IOD and dengue incidence, but a highly significant coherence between dengue incidence and local climate variables (temperature and rainfall). However, a distributed lag nonlinear model (DLNM) revealed that the association between dengue incidence and ENSO or IOD were comparatively stronger after adjustment for local climate variables, seasonality and trend. The estimated effects were nonlinear for both ENSO and IOD with higher relative risks at higher ENSO and IOD. The weak association between ENSO, IOD and dengue incidence might be driven by the stronger effects of local climate variables such as temperature and rainfall. Further research is required to disentangle these effects.

Exploration of diarrhoea seasonality and its drivers in China

This study investigated the diarrhoea seasonality and its potential drivers as well as potential opportunities for future diarrhoea control and prevention in China. Data on weekly infectious diarrhoea cases in 31 provinces of China from 2005 to 2012, and data on demographic and geographic characteristics, as well as climatic factors, were complied. A cosinor function combined with a Poisson regression was used to calculate the three seasonal parameters of diarrhoea in different provinces. Regression tree analysis was used to identify the predictors of diarrhoea seasonality. Diarrhoea cases in China showed a bimodal distribution. Diarrhoea in children <5 years was more likely to peak in fall-winter seasons, while diarrhoea in persons > = 5 years peaked in summer. Latitude was significantly associated with spatial pattern of diarrhoea seasonality, with peak and trough times occurring earlier at high latitudes (northern areas), and later at low latitudes (southern areas). The annual amplitudes of diarrhoea in persons > = 5 years increased with latitude (r = 0.62, P<0.001). Latitude 27.8° N and 38.65° N were the latitudinal thresholds for diarrhoea seasonality in China. Regional-specific diarrhoea control and prevention strategies may be optimal for China. More attention should be paid to diarrhoea in children <5 years during fall-winter seasons.

Trends in water level and flooding in Dhaka, Bangladesh and their impact on mortality

Climate change is expected to impact flooding in many highly populated coastal regions, including Dhaka (Bangladesh), which is currently among the fastest growing cities in the world. In the past, high mortality counts have been associated with extreme flood events. We first analyzed daily water levels of the past 100 years in order to detect potential shifts in extremes. A distributed lag non-linear model was then used to examine the connection between water levels and mortality. Results indicate that for the period of 2003–2007, which entails two major flood events in 2004 and 2007, high water levels do not lead to a significant increase in relative mortality, which indicates a good level of adaptation and capacity to cope with flooding. However, following low water levels, an increase in mortality could be found. As our trend analysis of past water levels shows that minimum water levels have decreased during the past 100 years, action should be taken to ensure that the exposed population is also well-adapted to drought.

A systematic review of methodology: time series regression analysis for environmental factors and infectious diseases

BACKGROUND

Time series analysis is suitable for investigations of relatively direct and short-term effects of exposures on outcomes. In environmental epidemiology studies, this method has been one of the standard approaches to assess impacts of environmental factors on acute non-infectious diseases (e.g. cardiovascular deaths), with conventionally generalized linear or additive models (GLM and GAM). However, the same analysis practices are often observed with infectious diseases despite of the substantial differences from non-infectious diseases that may result in analytical challenges.

METHODS

Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, systematic review was conducted to elucidate important issues in assessing the associations between environmental factors and infectious diseases using time series analysis with GLM and GAM. Published studies on the associations between weather factors and malaria, cholera, dengue, and influenza were targeted.

FINDINGS

Our review raised issues regarding the estimation of susceptible population and exposure lag times, the adequacy of seasonal adjustments, the presence of strong autocorrelations, and the lack of a smaller observation time unit of outcomes (i.e. daily data). These concerns may be attributable to features specific to infectious diseases, such as transmission among individuals and complicated causal mechanisms.

CONCLUSION

The consequence of not taking adequate measures to address these issues is distortion of the appropriate risk quantifications of exposures factors. Future studies should pay careful attention to details and examine alternative models or methods that improve studies using time series regression analysis for environmental determinants of infectious diseases.

Examining rainfall and cholera dynamics in Haiti using statistical and dynamic modeling approaches

Haiti has been in the midst of a cholera epidemic since October 2010. Rainfall is thought to be associated with cholera here, but this relationship has only begun to be quantitatively examined. In this paper, we quantitatively examine the link between rainfall and cholera in Haiti for several different settings (including urban, rural, and displaced person camps) and spatial scales, using a combination of statistical and dynamic models. Statistical analysis of the lagged relationship between rainfall and cholera incidence was conducted using case crossover analysis and distributed lag nonlinear models. Dynamic models consisted of compartmental differential equation models including direct (fast) and indirect (delayed) disease transmission, where indirect transmission was forced by empirical rainfall data. Data sources include cholera case and hospitalization time series from the Haitian Ministry of Public Health, the United Nations Water, Sanitation and Health Cluster, International Organization for Migration, and Hôpital Albert Schweitzer. Rainfall data was obtained from rain gauges from the U.S. Geological Survey and Haiti Regeneration Initiative, and remote sensing rainfall data from the National Aeronautics and Space Administration Tropical Rainfall Measuring Mission. A strong relationship between rainfall and cholera was found for all spatial scales and locations examined. Increased rainfall was significantly correlated with increased cholera incidence 4-7 days later. Forcing the dynamic models with rainfall data resulted in good fits to the cholera case data, and rainfall-based predictions from the dynamic models closely matched observed cholera cases. These models provide a tool for planning and managing the epidemic as it continues.

A study on the geophylogeny of clinical and environmental Vibrio cholerae in Kenya

Cholera remains a significant public health challenge in many sub-Saharan countries including Kenya. We have performed a combination of phylogenetic and phenotypic analysis based on whole genome DNA sequences derived from 40 environmental and 57 clinical V. cholerae from different regions of Kenya isolated between 2005 and 2010. Some environmental and all clinical isolates mapped back onto wave three of the monophyletic seventh pandemic V. cholerae El Tor phylogeny but other environmental isolates were phylogenetically very distinct. Thus, the genomes of the Kenyan V. cholerae O1 El Tor isolates are clonally related to other El Tor V. cholerae isolated elsewhere in the world and similarly harbour antibiotic resistance-associated STX elements. Further, the Kenyan O1 El Tor isolates fall into two distinct clades that may have entered Kenya independently.

Cholera Outbreaks in Urban Bangladesh In 2011

BACKGROUND

In 2011, a multidisciplinary team investigated two diarrhoea outbreaks affecting urban Bangladeshi communities from the districts of Bogra and Kishorganj to identify etiology, pathways of transmission, and factors contributing to these outbreaks.

METHODS

We defined case-patients with severe diarrhoea as residents from affected communities admitted with ≥3 loose stools per day. We listed case-patients, interviewed and examined them, and collected rectal swabs. We visited the affected communities to explore the water and sanitation infrastructure. We tested the microbial load of water samples from selected case household taps, tube wells, and pump stations. We conducted anthropological investigations to understand community perceptions regarding the outbreaks.

RESULTS

We identified 21 case-patients from Bogra and 84 from Kishorganj. The median age in Bogra was 23 years, and 21 years in Kishorganj. There were no reported deaths. We isolated Vibrio in 29% (5/17) of rectal swabs from Bogra and in 40% (8/20) from Kishorganj. We found Vibrio in 1/8 tap water samples from Bogra and in both of the samples from Kishorganj. We did not find Vibrio in water samples from pumps or tube wells in either outbreak. Ground water extracted through deep tube wells was supplied intermittently through interconnected pipes without treatment in both areas. We found leakages in the water pipes in Bogra, and in Kishorganj water pipes passed through open sewers.

CONCLUSION

The rapid onset of severe diarrhoea predominantly affecting adults and the isolation of cholera in rectal swabs confirmed that these outbreaks were caused by Vibrio cholerae. The detection of Vibrio in water samples organisms from taps but not from pumps or tube wells, suggested contamination within the pipes. Safe water provision is difficult in municipalities where supply is intermittent, and where pipes commonly leak. Research to develop and evaluate water purification strategies could identify appropriate approaches for ensuring safe drinking water in resource-poor cities.

Dynamics of Vibrio with virulence genes detected in Pacific harbor seals (Phoca vitulina richardii) off California: implications for marine mammal health

Given their coastal site fidelity and opportunistic foraging behavior, harbor seals (Phoca vitulina) may serve as sentinels for coastal ecosystem health. Seals using urbanized coastal habitat can acquire enteric bacteria, including Vibrio that may affect their health. To understand Vibrio dynamics in seals, demographic and environmental factors were tested for predicting potentially virulent Vibrio in free-ranging and stranded Pacific harbor seals (Phoca vitulina richardii) off California. Vibrio prevalence did not vary with season and was greater in free-ranging seals (29 %, n = 319) compared with stranded seals (17 %, n = 189). Of the factors tested, location, turbidity, and/or salinity best predicted Vibrio prevalence in free-ranging seals. The relationship of environmental factors with Vibrio prevalence differed by location and may be related to oceanographic or terrestrial contributions to water quality. Vibrio parahaemolyticus, Vibrio alginolyticus, and Vibrio cholerae were observed in seals, with V. cholerae found almost exclusively in stranded pups and yearlings. Additionally, virulence genes (trh and tdh) were detected in V. parahaemolyticus isolates. Vibrio cholerae isolates lacked targeted virulence genes, but were hemolytic. Three out of four stranded pups with V. parahaemolyticus (trh+ and/or tdh+) died in rehabilitation, but the role of Vibrio in causing mortality is unclear, and Vibrio expression of virulence genes should be investigated. Considering that humans share the environment and food resources with seals, potentially virulent Vibrio observed in seals also may be of concern to human health.

The effectiveness of public health interventions to reduce the health impact of climate change: a systematic review of systematic reviews

BACKGROUND

Climate change is likely to be one of the most important threats to public health in the coming years. Yet despite the large number of papers considering the health impact of climate change, few have considered what public health interventions may be of most value in reducing the disease burden. We aimed to evaluate the effectiveness of public health interventions to reduce the disease burden of high priority climate sensitive diseases.

METHODS AND FINDINGS

For each disease, we performed a systematic search with no restriction on date or language of publication on Medline, Web of Knowledge, Cochrane CENTRAL and SCOPUS up to December 2010 to identify systematic reviews of public health interventions. We retrieved some 3176 records of which 85 full papers were assessed and 33 included in the review. The included papers investigated the effect of public health interventions on various outcome measures. All interventions were GRADE assessed to determine the strength of evidence. In addition we developed a systematic review quality score. The interventions included environmental interventions to control vectors, chemoprophylaxis, immunization, household and community water treatment, greening cities and community advice. For most reviews, GRADE showed low quality of evidence because of poor study design and high heterogeneity. Also for some key areas such as floods, droughts and other weather extremes, there are no adequate systematic reviews of potential public health interventions.

CONCLUSION

In conclusion, we found the evidence base to be mostly weak for environmental interventions that could have the most value in a warmer world. Nevertheless, such interventions should not be dismissed. Future research on public health interventions for climate change adaptation needs to be concerned about quality in study design and should address the gap for floods, droughts and other extreme weather events that pose a risk to health.

A differential effect of Indian ocean dipole and El Niño on cholera dynamics in Bangladesh

Background

A stationary (i.e., constant through time) association between El Niño Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD) and epidemics of cholera in Bangladesh has been widely assumed. However, whether or not elements of the local climate that are relevant for cholera transmission have stationary signatures of the IOD on their dynamics over different time scales is still not clear. Here we report results on the time-varying relationships between the various remote and local environmental drivers and cholera incidence in Bangladesh.

Methodology/Principal Findings

We performed a cross wavelet coherency analysis to examine patterns of association between monthly cholera cases in the hospitals in Dhaka and Matlab (1983–2008) and indices for both IOD and ENSO. Our results showed that the strength of both the IOD and ENSO associations with cholera hospitalizations changed across time scales during the study period. In Dhaka, 4-year long coherent cycles were observed between cholera and the index of IOD in 1988–1997. In Matlab, the effect of ENSO was more dominant while there was no evidence for an IOD effect on cholera hospitalizations.

Conclusions/Significance

Our results call for the consideration of non-stationary, possibly non-linear, patterns of association between cholera hospitalizations and climatic factors in cholera epidemic early warning systems.

Modeling gradually changing seasonal variation in count data using state space models: a cohort study of hospitalization rates of stroke in atrial fibrillation patients in Denmark from 1977 to 2011

BACKGROUND

Seasonal variation in the occurrence of cardiovascular diseases has been recognized for decades. In particular, incidence rates of hospitalization with atrial fibrillation (AF) and stroke have shown to exhibit a seasonal variation. Stroke in AF patients is common and often severe. Obtaining a description of a possible seasonal variation in the occurrence of stroke in AF patients is crucial in clarifying risk factors for developing stroke and initiating prophylaxis treatment.

METHODS

Using a dynamic generalized linear model we were able to model gradually changing seasonal variation in hospitalization rates of stroke in AF patients from 1977 to 2011. The study population consisted of all Danes registered with a diagnosis of AF comprising 270,017 subjects. During follow-up, 39,632 subjects were hospitalized with stroke. Incidence rates of stroke in AF patients were analyzed assuming the seasonal variation being a sum of two sinusoids and a local linear trend.

RESULTS

The results showed that the peak-to-trough ratio decreased from 1.25 to 1.16 during the study period, and that the times of year for peak and trough changed slightly.

CONCLUSION

The present study indicates that using dynamic generalized linear models provides a flexible modeling approach for studying changes in seasonal variation of stroke in AF patients and yields plausible results.

Dynamics of cholera outbreaks in Great Lakes region of Africa, 1978-2008

Cholera outbreaks have occurred in Burundi, Rwanda, Democratic Republic of Congo, Tanzania, Uganda, and Kenya almost every year since 1977-1978, when the disease emerged in these countries. We used a multiscale, geographic information system-based approach to assess the link between cholera outbreaks, climate, and environmental variables. We performed time-series analyses and field investigations in the main affected areas. Results showed that cholera greatly increased during El Nino warm events (abnormally warm El Ninos) but decreased or remained stable between these events. Most epidemics occurred in a few hotspots in lakeside areas, where the weekly incidence of cholera varied by season, rainfall, fluctuations of plankton, and fishing activities. During lull periods, persistence of cholera was explained by outbreak dynamics, which suggested a metapopulation pattern, and by endemic foci around the lakes. These links between cholera outbreaks, climate, and lake environments need additional, multidisciplinary study.

The health effects of climate change: a survey of recent quantitative research

In recent years there has been a large scientific and public debate on climate change and its direct as well as indirect effects on human health. In particular, a large amount of research on the effects of climate changes on human health has addressed two fundamental questions. First, can historical data be of some help in revealing how short-run or long-run climate variations affect the occurrence of infectious diseases? Second, is it possible to build more accurate quantitative models which are capable of predicting the future effects of different climate conditions on the transmissibility of particularly dangerous infectious diseases? The primary goal of this paper is to review the most relevant contributions which have directly tackled those questions, both with respect to the effects of climate changes on the diffusion of non-infectious and infectious diseases, with malaria as a case study. Specific attention will be drawn on the methodological aspects of each study, which will be classified according to the type of quantitative model considered, namely time series models, panel data and spatial models, and non-statistical approaches. Since many different disciplines and approaches are involved, a broader view is necessary in order to provide a better understanding of the interactions between climate and health. In this respect, our paper also presents a critical summary of the recent literature related to more general aspects of the impacts of climate changes on human health, such as: the economics of climate change; how to manage the health effects of climate change; the establishment of Early Warning Systems for infectious diseases.