Temporal trends and climatic factors associated with bacterial enteric diseases in Vietnam, 1991-2001

The 2023 report of the MJA-Lancet Countdown on health and climate change: sustainability needed in Australia's health care sector

The MJA-Lancet Countdown on health and climate change in Australia was established in 2017 and produced its first national assessment in 2018 and annual updates in 2019, 2020, 2021 and 2022. It examines five broad domains: health hazards, exposures and impacts; adaptation, planning and resilience for health; mitigation actions and health co-benefits; economics and finance; and public and political engagement. In this, the sixth report of the MJA-Lancet Countdown, we track progress on an extensive suite of indicators across these five domains, accessing and presenting the latest data and further refining and developing our analyses. Our results highlight the health and economic costs of inaction on health and climate change. A series of major flood events across the four eastern states of Australia in 2022 was the main contributor to insured losses from climate-related catastrophes of $7.168 billion - the highest amount on record. The floods also directly caused 23 deaths and resulted in the displacement of tens of thousands of people. High red meat and processed meat consumption and insufficient consumption of fruit and vegetables accounted for about half of the 87 166 diet-related deaths in Australia in 2021. Correction of this imbalance would both save lives and reduce the heavy carbon footprint associated with meat production. We find signs of progress on health and climate change. Importantly, the Australian Government released Australia's first National Health and Climate Strategy, and the Government of Western Australia is preparing a Health Sector Adaptation Plan. We also find increasing action on, and engagement with, health and climate change at a community level, with the number of electric vehicle sales almost doubling in 2022 compared with 2021, and with a 65% increase in coverage of health and climate change in the media in 2022 compared with 2021. Overall, the urgency of substantial enhancements in Australia's mitigation and adaptation responses to the enormous health and climate change challenge cannot be overstated. Australia's energy system, and its health care sector, currently emit an unreasonable and unjust proportion of greenhouse gases into the atmosphere. As the Lancet Countdown enters its second and most critical phase in the leadup to 2030, the depth and breadth of our assessment of health and climate change will be augmented to increasingly examine Australia in its regional context, and to better measure and track key issues in Australia such as mental health and Aboriginal and Torres Strait Islander health and wellbeing.

The seroincidence of childhood Shigella sonnei infection in Ho Chi Minh City, Vietnam

BACKGROUND

Shigella sonnei is a pathogen of growing global importance as a cause of diarrhoeal illness in childhood, particularly in transitional low-middle income countries (LMICs). Here, we sought to determine the incidence of childhood exposure to S. sonnei infection in a contemporary transitional LMIC population, where it represents the dominant Shigella species.

METHODS

Participants were enrolled between the age of 12-36 months between June and December 2014. Baseline characteristics were obtained through standardized electronic questionnaires, and serum samples were collected at 6-month intervals over two years of follow-up. IgG antibody against S. sonnei O-antigen (anti-O) was measured using an enzyme-linked immunosorbent assay (ELISA). A four-fold increase in ELISA units (EU) with convalescent IgG titre >10.3 EU was taken as evidence of seroconversion between timepoints.

RESULTS

A total of 3,498 serum samples were collected from 748 participants; 3,170 from the 634 participants that completed follow-up. Measures of anti-O IgG varied significantly by calendar month (p = 0.03). Estimated S. sonnei seroincidence was 21,451 infections per 100,000 population per year (95% CI 19,307-23,834), with peak incidence occurring at 12-18 months of age. Three baseline factors were independently associated with the likelihood of seroconversion; ever having breastfed (aOR 2.54, CI 1.22-5.26), history of prior hospital admission (aOR 0.57, CI 0.34-0.95), and use of a toilet spray-wash in the household (aOR 0.42, CI 0.20-0.89).

CONCLUSIONS

Incidence of S. sonnei exposure in Ho Chi Minh City is substantial, with significant reduction in the likelihood of exposure as age increases beyond 2 years.

Heatwaves in South Asia: Characterization, Consequences on Human Health, and Adaptation Strategies

South Asia, with more than one-fifth of the world’s population, is highly vulnerable to heatwaves and associated health consequences. The population experiences considerably higher residential vulnerability due to limited infrastructural capacities, economic resources, and health and environmental quality deficiencies. However, a limited number of studies are available from the region to account for the health effects of heatwaves. Therefore, this study has conducted a comprehensive review to characterize heatwaves across South Asian countries. The review explicitly identifies the population’s vulnerability to heatwaves during recent years and heatwave management policies in the region. The literature review suggests increased heat-related deaths in most South Asian countries, with few exceptions. In addition, the analysis of historical temperature records identified an upward trend in annual average temperature across the South Asian countries. The study highlights various heatwave definitions that have been used in the region to facilitate comparative evidence. The review of policies identified that only a few South Asian countries have functional heatwave management plans and majorly lack community and residential preparedness for heatwaves. Therefore, this study identifies potential community- and residential-based adaptation strategies to mitigate heat discomfort. As prospective solutions, the study recommends adaptation strategies such as blue–green spaces, indoor passive cooling, infrastructural adjustments, heat action plans, etc. However, such adaptation measures require a holistic amalgamation of different stakeholders to fabricate heatwave-resilient cities.

Meteorological and social conditions contribute to infectious diarrhea in China

Infectious diarrhea in China showed a significant pattern. Many researchers have tried to reveal the drivers, yet usually only meteorological factors were taken into consideration. Furthermore, the diarrheal data they analyzed were incomplete and the algorithms they exploited were inefficient of adapting realistic relationships. Here, we investigate the impacts of meteorological and social factors on the number of infectious diarrhea cases in China. A machine learning algorithm called the Random Forest is utilized. Our results demonstrate that nearly half of infectious diarrhea occurred among children under 5 years old. Generally speaking, increasing temperature or relative humidity leads to increased cases of infectious diarrhea in China. Nevertheless, people from different age groups or different regions own different sensitivities to meteorological factors. The weight of feces that are harmfully treated could be a possible reason for infectious diarrhea of the elderly as well as children under 5 years old. These findings indicate that infectious diarrhea prevention for children under 5 years old remains a primary task in China. Personalized prevention countermeasures ought to be provided to different age groups and different regions. It is essential to bring the weight of feces that are harmfully treated to the forefront when considering infectious diarrhea prevention.

Role of extreme weather events and El Niño Southern Oscillation on incidence of Enteric Fever in Ahmedabad and Surat, Gujarat, India

INTRODUCTION

Enteric Fever (EF) affects over 14.5 million people every year globally, with India accounting for the largest share of this burden. The water-borne nature of the disease makes it prone to be influenced as much by unsanitary living conditions as by climatic factors. The detection and quantification of the climatic effect can lead to improved public health measures which would in turn reduce this burden.

METHODOLOGY

We obtained a list of monthly Widal positive EF cases from 1995 to 2017 from Ahmedabad and Surat Municipalities. We obtained population data, daily weather data, and Oceanic Niño Index values from appropriate sources. We quantified the association between extreme weather events, phases of El Niño Southern Oscillations (ENSO) and incidence of EF.

RESULTS

Both cities showed a seasonal pattern of EF, with cases peaking in early monsoon. Risk of EF was affected equally in both cities by the monsoon season -- Ahmedabad (35%) and Surat (34%). Extreme precipitation was associated with 5% increase in EF in Ahmedabad but not in Surat. Similarly, phases of ENSO had opposite effects on EF across the two cities. In Ahmedabad, strong El Niño months were associated with 64% increase in EF risk while strong La Niña months with a 41% reduction in risk. In Surat, strong El Niño was associated with 25% reduction in risk while moderate La Niña with 21% increase in risk.

CONCLUSIONS

Our results show that the risk of EF incidence in Gujarat is highly variable, even between the two cities only 260 kms apart. In addition to improvements in water supply and sewage systems, preventive public health measures should incorporate variability in risk across season and phases of ENSO. Further studies are needed to characterize nationwide heterogeneity in climate-mediated risk, and to identify most vulnerable populations that can benefit through early warning systems.

Transmission pattern of shigellosis in Wuhan City, China: a modelling study

The article aims to estimate and forecast the transmissibility of shigellosis and explore the association of meteorological factors with shigellosis. The mathematical model named Susceptible–Exposed–Symptomatic/Asymptomatic–Recovered–Water/Food (SEIARW) was used to explore the feature of shigellosis transmission based on the data of Wuhan City, China, from 2005 to 2017. The study applied effective reproduction number (R_eff) to estimate the transmissibility. Daily meteorological data from 2008 to 2017 were used to determine Spearman's correlation with reported new cases and R_eff. The SEIARW model fit the data well (χ² = 0.00046, p > 0.999). The simulation results showed that the reservoir-to-person transmission of the shigellosis route has been interrupted. The R_eff would be reduced to a transmission threshold of 1.00 (95% confidence interval (CI) 0.82–1.19) in 2035. Reducing the infectious period to 11.25 days would also decrease the value of R_eff to 0.99. There was a significant correlation between new cases of shigellosis and atmospheric pressure, temperature, wind speed and sun hours per day. The correlation coefficients, although statistically significant, were very low (<0.3). In Wuhan, China, the main transmission pattern of shigellosis is person-to-person. Meteorological factors, especially daily atmospheric pressure and temperature, may influence the epidemic of shigellosis.

Post-monsoon waterlogging-associated upsurge of cholera cases in and around Kolkata metropolis, 2015

The Infectious Diseases and Beliaghata General Hospital, Kolkata, India witnessed a sudden increase in admissions of diarrhoea cases during the first 2 weeks of August 2015 following heavy rainfall. This prompted us to investigate the event. Cases were recruited through hospital-based surveillance along with the collection of socio-demographic characteristics and clinical profile using a structured questionnaire. Stool specimens were tested at bacteriological laboratory of the National Institute of Cholera and Enteric Diseases (NICED), Kolkata. Admission of 3003 diarrhoea cases, clearly indicated occurrence of outbreak in Kolkata municipal area as it was more than two standard deviation of the mean number (911; s.d. = 111) of diarrhoea admissions during the same period in previous 7 years. Out of 164 recruited cases, 25% were under-5 children. Organisms were isolated from 80 (49%) stool specimens. Vibrio cholerae O1 was isolated from 50 patients. Twenty-eight patients had this organism as the sole pathogen. Among 14 infants, five had cholera. All V. cholerae O1 isolates were resistant to nalidixic acid, followed by co-trimoxazole (96%), streptomycin (92%), but sensitive to fluroquinolones. We confirmed the occurrence of a cholera outbreak in Kolkata during August 2015 due to V. cholerae O1 infection, where infants were affected.

Epidemiologic features of shigellosis and associated climatic factors in Taiwan

The consistent, sporadic transmission of shigellosis in Taiwan necessitates an exploration of risk factors for the occurrence of shigellosis. The purpose of this study was to study the epidemiologic characteristics and the relationship between climatic factors and the incidence of shigellosis in Taiwan. We collected data from cases of shigellosis reported to the Taiwan Centers for Disease Control (Taiwan CDC) from 2001 to 2016. Climatic data were obtained from the Taiwan Central Weather Bureau. The relationships between weather variability and the incidence of shigellosis in Taiwan were determined via Poisson regression analyses. During the 16-year study period, a total of 4171 clinical cases of shigellosis were reported to the Taiwan CDC. Among them, 1926 (46.2%) were classified as confirmed cases. The incidence of shigellosis showed significant seasonality, with the majority of cases occurring in summertime (for oscillation, P < .001). The number of shigellosis cases started to increase when temperatures reached 21°C (r = 0.88, P < .001). Similarly, the number of shigellosis cases began to increase at a relative humidity of 70-74% (r = 0.75, P < .005). The number of shigellosis cases was positively associated with the mean temperature and relative humidity in the period preceding the infection. In conclusion, the occurrence of shigellosis is significantly associated with increasing temperature and relative humidity in Taiwan. Therefore, these factors could be regarded as warning signals indicating the need to implement preventive measures.

Effects of ambient temperature on bacillary dysentery: A multi-city analysis in Anhui Province, China

BACKGROUND

Rising ambient temperature is expected to increase incidence of bacillary dysentery (BD), but few studies have compared the temperature-BD effects of different age groups and cities in China, especially in a multi-city setting.

OBJECTIVES

We used city-specific data including BD cases and meteorological variables to determine the relationship between BD incidence and temperature at provincial level.

METHODS

Weekly BD disease surveillance data and meteorological variables were collected in all 16 prefecture-level cities in Anhui Province of China. Firstly, city-specific weekly mean temperature-BD incidence associations were estimated with Distributed Lag Nonlinear Model (DLNM). Secondly, city-specific estimates were pooled at province-level through multivariate meta-analysis. Also, we conducted subgroup analyses for ages (children <5 years old and population of other ages) and urbanization of cities (high and low level), respectively.

RESULTS

In Anhui, BD morbidity risk increased with increasing weekly mean temperature. Relative risks (RR) at the 90th percentile (27.5 °C) versus the 50th percentile (17 °C) of weekly mean temperature were 1.42 (95% confidence interval (CI): 1.16, 1.75) and 2.02 (95% CI: 1.76, 2.32) for children <5 and population of other ages, respectively. The relative risk of high temperature on other ages group was higher than that of children under five years old (p = 0.006). Children under 5 in high urbanized cities appeared to be more vulnerable to the effects of ambient high temperature (RR: 1.56, 95% CI: 1.20, 1.92) than in low urbanized cities (RR: 1.01, 95% CI: 0.70, 1.46), the difference between two intervals was statistically significant (p = 0.044).

CONCLUSIONS

This study suggests that high temperatures may be an important trigger of BD incidence, and especially lead to a substantial burden of BD for high urbanized cities in Anhui Province of China.

An ecological study of eosinophilic meningitis caused by the nematode, Angiostrongylus cantonensis (Chen, 1935) (Nematoda: Metastrongylidae)

Climate change and other weather factors are associated with several infectious diseases, but are rarely reported as being associated with nematode infection. Eosinophilic meningitis (EOM) is an emerging disease worldwide caused by the nematode, Angiostrongylus cantonensis. It is transmitted through various agents such as snails and slugs. Temperature and rainfall are associated with snail population. There have been no previous studies on the relationship between weather and EOM. This was an ecological study. Numbers of EOM patients and weather data in Thailand's Loei province from 2006 to 2017 were obtained using a national database. A Spearman correlation was used to explore the relationship between EOM and weather variables. We developed a Poisson time series model combined with a distributed lag model (DLM) for estimating the effects of weather on EOM. We also created an autoregressive integrated moving average with exogeneous variable (ARIMAX) model for predicting future EOM cases over the following 12 months. There were 1126 EOM patients in the study. Among several weather factors, wind was significantly negatively correlated with the number of EOM patients (r_s: -0.204, 95% CI: -0.361 to -0.058; p value: 0.014). The ARIMAX(3, 0, 0) model with wind speed as a variable was appropriate for predicting the number of EOM patients. The predicted and actual numbers of EOM patients in 2018 were highly concordant. In conclusion, wind speed is significantly negatively correlated with the number of EOM patients.

The Epidemiological Influence of Climatic Factors on Shigellosis Incidence Rates in Korea

Research has shown the effects of climatic factors on shigellosis; however, no previous study has evaluated climatic effects in regions with a winter seasonality of shigellosis incidence. We examined the effects of temperature and precipitation on shigellosis incidence in Korea from 2002–2010. The incidence of shigellosis was calculated based on data from the Korean Center for Disease Control and Prevention (KCDC, Cheongju, Korea), and a generalized additive model (GAM) was used to analyze the associations between the incidence and climatic factors. The annual incidence rate of shigellosis was 7.9 cases/million persons from 2002–2010. During 2007–2010, high incidence rates and winter seasonality were observed among those aged ≥65 years, but not among lower age groups. Based on the GAM model, the incidence of shigellosis is expected to increase by 13.6% and 2.9% with a temperature increase of 1 °C and a lag of two weeks and with a mean precipitation increase of 1 mm and a lag of five weeks after adjustment for seasonality, respectively. This study suggests that the incidence of shigellosis will increase with global climate change despite the winter seasonality of shigellosis in Korea. Public health action is needed to prevent the increase of shigellosis incidence associated with climate variations.

The analysis of GM (1, 1) grey model to predict the incidence trend of typhoid and paratyphoid fevers in Wuhan City, China

Typhoid and paratyphoid fevers (TPF), systemic emerging infectious diseases, is a serious health problem for society. If the incidence trend of TPF can be predicted, prevention and control measures can be taken in advance to reduce the harm to the people's health.Grey Model First Order One Variable [GM (1, 1)] was applied to predict the incidence trend of TPF with the incidence data of TPF in Wuhan City of China from 2004 to 2015. The original data were acquired from the national surveillance system.The GM (1, 1) model was established as ŷ (t + 1) = 0.88 e + 0.15. The goodness-of-fit test indicated that the precision (degree 2) was qualified (C = 0.40, P = .91). We further compared actual values with predicted values in 2016 and found that GM (1, 1) model we built has excellent performance in incidence trend prediction.Our prediction shows that the TPF incidences in Wuhan City will be slowly decreasing in the next 3 years. It is, however, still necessary to strengthen the comprehensive prevention and control to reduce the incidence level of TPF.

Effect of increasing temperature on daily hospital admissions for schizophrenia in Hefei, China: a time-series analysis

OBJECTIVE

To investigate the relationship between ambient temperature and hospital admissions for schizophrenia in Hefei, China.

STUDY DESIGN

An ecological design was used to explore the effect of ambient temperature on hospital admissions for schizophrenia.

METHODS

Daily data on hospital admissions for schizophrenia and meteorological data for the warm season (May-October) in 2005-2014 were obtained from Anhui Mental Health Centre and Hefei Bureau of Meteorology, respectively. Poisson generalised linear regression model combined with a distributed lag non-linear model was used to analyse the effects of temperature on admissions for schizophrenia. Stratified analyses according to individual characteristics, such as age and sex, were also conducted.

RESULTS

A significant relationship was found between ambient temperature and admissions for schizophrenia. High temperature appeared to have a delayed effect on admissions for schizophrenia, and a temperature of 28°C (75th percentile) at lag 0-4 days was associated with a 7% (95% confidence interval: 4-11%) increase in admissions for schizophrenia. Stratified analyses showed that male patients, patients aged 21-60 years and married patients were more vulnerable to high temperature, and the temperature effects for those groups occurred at a lag of 1 day.

CONCLUSION

High temperature poses significant risks for schizophrenia in subtropical regions. Future preventive measures for reducing the occurrence of schizophrenia should be considered for susceptible populations.

Spatiotemporal Risk of Bacillary Dysentery and Sensitivity to Meteorological Factors in Hunan Province, China

Bacillary dysentery remains a public health concern in the world. Hunan Province is one of the provinces having the highest risk of bacillary dysentery in China, however, the spatial-temporal distribution, variation of bacillary dysentery and sensitivity to meteorological factors in there are unclear. In this paper, a Bayesian space-time hierarchical model (BSTHM) was used to detect space-time variation, and effects of meteorological factors between 2010 and 2015. The risk of bacillary dysentery showed apparent spatial-temporal heterogeneity. The highest risk occurred in the summer season. Economically undeveloped mountainous areas in the west and south of the province had the highest incidence rates. Twenty three (18.9%) and 20 (16.4%) counties were identified as hot and cold spots, respectively. Among the hotspots, 11 counties (47.8%) exhibited a rapidly decreasing trend, suggesting they may become low-risk areas in the future. Of the cold spot counties, six (30%) showed a slowly decreasing trend, and may have a higher risk in the future. Among meteorological factors, air temperature, relative humidity, and wind speed all played a significant role in the spatial-temporal distribution of bacillary dysentery risk. These findings can contribute to the implementation of an early warning system for controlling and preventing bacillary dysentery.

Bagtzoglou A, Anagnostou E. Effect of climatic variability on childhood diarrhea and its high risk periods in northwestern parts of Ethiopia

Background

Increasing climate variability as a result of climate change will be one of the public health challenges to control infectious diseases in the future, particularly in sub-Saharan Africa including Ethiopia.

Objective

To investigate the effect of climate variability on childhood diarrhea (CDD) and identify high risk periods of diarrheal diseases.

Methods

The study was conducted in all districts located in three Zones (Awi, West and East Gojjam) of Amhara Region in northwestern parts of Ethiopia. Monthly CDD cases for 24 months (from July 2013 to June 2015) reported to each district health office from the routine surveillance system were used for the study. Temperature, rainfall and humidity data for each district were extracted from satellite precipitation estimates and global atmospheric reanalysis. The space-time permutation scan statistic was used to identify high risk periods of CDD. A negative binomial regression was used to investigate the relationship between cases of CDD and climate variables. Statistical analyses were conducted using SaTScan program and StataSE v. 12.

Results

The monthly average incidence rate of CDD was 11.4 per 1000 (95%CI 10.8–12.0) with significant variation between males [12.5 per 1000 (95%CI 11.9 to 13.2)] and females [10.2 per 1000 (95%CI 9.6 to 10.8)]. The space-time permutation scan statistic identified the most likely high risk period of CDD between March and June 2014 located in Huletej Enese district of East Gojjam Zone. Monthly average temperature and monthly average rainfall were positively associated with the rate of CDD, whereas the relative humidity was negatively associated with the rate of CDD.

Conclusions

This study found that the most likely high risk period is in the beginning of the dry season. Climatic factors have an association with the occurrence of CDD. Therefore, CDD prevention and control strategy should consider local weather variations to improve programs on CDD.

Spatial and temporal patterns of diarrhoea in Bhutan 2003-2013

Background

To describe spatiotemporal patterns of diarrhoea in Bhutan, and quantify the association between climatic factors and the distribution and dynamics of the disease.

Methods

Nationwide data on diarrhoea were obtained for 2003 to 2013 from the Health Information and Management System (HIMS), Ministry of Health, Bhutan. Climatic variables were obtained from the Department of Hydro Met Services, Ministry of Economic Affairs, Bhutan. Seasonal trend decomposition was used to examine secular trends and seasonal patterns of diarrhoea. A Bayesian conditional autoregressive (CAR) model was used to quantify the relationship between monthly diarrhoea, maximum temperature, rainfall, age and gender.

Results

The monthly average diarrhoea incidence was highly seasonal. Diarrhoea incidence increased by 0.6% (95% CrI: 0.5–0.6%) for every degree increase in maximum temperature; and 5% (95 Cr I: 4.9–5.1%) for a 1 mm increase in rainfall. Children aged <5 years were found to be 74.2% (95% CrI: 74.1–74.4) more likely to experience diarrhoea than children and adults aged ≥5 years and females were 4.9% (95% CrI: 4.4–5.3%) less likely to suffer from diarrhoea as compared to males. Significant residual spatial clustering was found after accounting for climate and demographic variables.

Conclusions

Diarrhoea incidence was highly seasonal, with positive associations with maximum temperature and rainfall and negative associations with age and being female. This calls for public health actions to reduce future risks of climate change with great consideration of local climatic conditions. In addition, protection of <5 years children should be prioritize through provision of rotavirus vaccination, safe and clean drinking water, and proper latrines.

Electronic supplementary material

The online version of this article (doi:10.1186/s12879-017-2611-6) contains supplementary material, which is available to authorized users.

Seasonal and geographical distribution of bacillary dysentery (shigellosis) and associated climate risk factors in Kon Tam Province in Vietnam from 1999 to 2013

Background

Bacillary dysentery (BD) is an acute bacterial infection of the intestine caused by Shigella spp., with clinical symptoms ranging from fever to bloody diarrhoea to abdominal cramps to tenesmus. In Vietnam, enteric bacterial pathogens are an important cause of diarrhoea and most cases in children under 5 years of age are due to Shigella strains. The serogroups S. flexneri and S. sonnei are considered to be the most common. The main objective of this study was to, for the first time, assess the seasonal patterns and geographic distribution of BD in Vietnam, and to determine the climate risk factors associated with the incidence of BD in Kon Tum Province, where the highest rate of bacillary dysentery was observed from 1999 to 2013.

Methods

The seasonal patterns and geographic distribution of BD was assessed in Vietnam using a seasonal-trend decomposition procedure based on loess. In addition, negative binomial regression models were used to determine the climate risk factors associated with the incidence of BD in Kon Tum Province, from 1999 to 2013.

Results

Overall, incidence rates of BD have slightly decreased over time (except for an extremely high incidence in 2012 in the north of Vietnam). The central regions (north/south central coast and central highlands) had relatively high incidence rates, whereas the northwest/east and Red River Delta regions had low incidence rates. Overall, seasonal plots showed a high peak in the mid-rainy reason and a second smaller peak in the early or late rainy season. The incidence rates significantly increased between May and October (“wet season”) across the country. In Kon Tum Province, temperature, humidity, and precipitation were found to be positively associated with the incidence of BD.

Conclusions

Our findings provide insights into the seasonal patterns and geographic distribution of BD in Vietnam and its associated climate risk factors in Kon Tum Province. This study may help clinicians and the general public to better understand the timings of outbreaks and therefore equip them with the knowledge to plan better interventions (such as improving water, sanitation, and hygiene conditions) during peak seasons. This can, in turn, prevent or reduce outbreaks and onwards transmission during an outbreak.

Electronic supplementary material

The online version of this article (doi:10.1186/s40249-017-0325-z) contains supplementary material, which is available to authorized users.

Cholera returns to southern Vietnam in an outbreak associated with consuming unsafe water through iced tea: A matched case-control study

Background

After more than a decade of steadily declining notifications, the number of reported cholera cases has recently increased in Vietnam. We conducted a matched case-control study to investigate transmission of cholera during an outbreak in Ben Tre, southern Vietnam, and to explore the associated risk factors.

Methodology/Principal findings

Sixty of 71 diarrheal patients confirmed to be infected with cholera by culture and diagnosed between May 9 and August 3, 2010 in Ben Tre were consecutively recruited as case-patients. Case-patients were matched 1:4 to controls by commune, sex, and 5-year age group. Risk factors for cholera were examined by multivariable conditional logistic regression. In addition, environmental samples from villages containing case-patients were taken to identify contamination of food and water sources. The regression indicated that drinking iced tea (adjusted odds ratio (aOR) = 8.40, 95% confidence interval (CI): 1.84–39.25), not always boiling drinking water (aOR = 2.62, 95% CI: 1.03–6.67), having the main source of water for use being close to a toilet (aOR = 4.36, 95% CI: 1.37–13.88), living with people who had acute diarrhea (aOR = 13.72, 95% CI: 2.77–67.97), and little or no education (aOR = 4.89, 95% CI: 1.18–20.19) were significantly associated with increased risk of cholera. In contrast, drinking stored rainwater (aOR = 0.17, 95% CI: 0.04–0.63), eating cooked seafood (aOR = 0.27, 95% CI: 0.10–0.73), and eating steamed vegetables (aOR = 0.22, 95% CI: 0.07–0.70) were protective against cholera. Vibrio cholerae O1 Ogawa carrying ctxA was found in two of twenty-five river water samples and one of six wastewater samples.

Conclusions/Significance

The magnitude of the cholera outbreak in Ben Tre was lower than in other similar settings. This investigation identified several risk factors and underscored the importance of continued responses targeting cholera prevention in southern Vietnam. The association between drinking iced tea and cholera and the spread of V. cholerae O1, altered El Tor strains warrant further research. These findings might be affected by a number of limitations due to the inability to capture asymptomatic or mildly symptomatic infections, the possible underreporting of personal unhygienic behaviors, and the purposive selection of environmental samples.

Cholera is a highly contagious, acute diarrheal illness, which poses a profound health threat in many parts of the less developed world. The majority of cases are reported from Sub-Saharan Africa, South-East Asia, and the Americas (i.e., Haiti) where infections are primarily transmitted through ingestion of contaminated water. Today in the era of widely available rehydration therapies and antibiotics, deaths due to cholera are quite rare. Despite this, early detection of contaminated water sources is crucial for directing early interventions for curbing community-wide transmission. The authors found evidence linking an outbreak of cholera in southern Vietnam to consumption of unsafe water, especially drinking iced tea. This finding suggests the need for a water-monitoring system at ice-making plants. Further research is needed to confirm the biological link between iced tea consumption and cholera infection. Larger studies should also be conducted to understand the clinical consequences of infection with the new cholera agent (V. cholerae O1, altered El Tor strains).

Heavy rainfall and risk of infectious intestinal diseases in the most populous city in Vietnam

The association between heavy rainfall and infectious intestinal diseases (IID) has not been well described and little research has been conducted in developing countries. This study examines the association between heavy rainfall and hospital admissions for IID in Ho Chi Minh City, the most populous city in Vietnam. An interrupted time-series method was used to examine the effect of each individual heavy rainfall event (HRE) on IID. The percentage changes in post-HRE level and trends of IID were estimated for 30days following each HRE. Then a random-effect meta-analysis was used to quantify the pooled estimate of effect sizes of all HREs on IID. The pooled estimates were calculated over a 21day lag period. The effects of a HRE on IID varied across individual HREs. The pooled estimates indicate that the levels of IID following a HRE increased from 7.3% to 13.5% for lags from 0 to 21days, however statistically significant increases were only observed for lags from 4 to 6days (13.5%, 95%CI: 1.4-25.4; 13.3%, 95%CI: 1.5-25.0; and 12.9%, 95%CI: 1.6-24.1 respectively). An average decrease of 0.11% (95%CI: -0.55-0.33) per day was observed for the post-HRE trend. This finding has important implications for the projected impacts on residents living in this city which is highly vulnerable to increased heavy rainfall associated with climate change. Adaptation and intervention programs should be developed to prevent this additional burden of disease and to protect residents from the adverse impacts of extreme weather events.

Identification of weather variables sensitive to dysentery in disease-affected county of China

Climate change mainly refers to long-term change in weather variables, and it has significant impact on sustainability and spread of infectious diseases. Among three leading infectious diseases in China, dysentery is exclusively sensitive to climate change. Previous researches on weather variables and dysentery mainly focus on determining correlation between dysentery incidence and weather variables. However, the contribution of each variable to dysentery incidence has been rarely clarified. Therefore, we chose a typical county in epidemic of dysentery as the study area. Based on data of dysentery incidence, weather variables (monthly mean temperature, precipitation, wind speed, relative humidity, absolute humidity, maximum temperature, and minimum temperature) and lagged analysis, we used principal component analysis (PCA) and classification and regression trees (CART) to examine the relationships between the incidence of dysentery and weather variables. Principal component analysis showed that temperature, precipitation, and humidity played a key role in determining transmission of dysentery. We further selected weather variables including minimum temperature, precipitation, and relative humidity based on results of PCA, and used CART to clarify contributions of these three weather variables to dysentery incidence. We found when minimum temperature was at a high level, the high incidence of dysentery occurred if relative humidity or precipitation was at a high level. We compared our results with other studies on dysentery incidence and meteorological factors in areas both in China and abroad, and good agreement has been achieved. Yet, some differences remain for three reasons: not identifying all key weather variables, climate condition difference caused by local factors, and human factors that also affect dysentery incidence. This study hopes to shed light on potential early warnings for dysentery transmission as climate change occurs, and provide a theoretical basis for the control and prevention of dysentery.

Trends of diarrhoeal diseases in children under five years in the War Memorial Hospital-Navrongo, Ghana: 2010-2013

Introduction

Diarrhoea is the third leading cause of hospital morbidity in children under five years in the War Memorial Hospital (WMH). With the current changes in climate, little is known about the seasonal and spatial distribution of diarrhoeal diseases in the WMH. We determined trends of diarrhoeal diseases in children under five years in the WMH.

Methods

We reviewed secondary data of children under five years who attended the WMH and were diagnosed of diarrhoea. Diarrhoea was defined as a clinician's diagnosis of the passage of three or more watery stools a day in a child under five years in the WMH. Descriptive data analysis was done and expressed as frequencies and relative frequencies. Monthly proportions of diarrhoea and rainfall figures were presented to show seasonal distributions of cases. Geographical distribution of cases was determined using Epi Info and Arc GIS.

Results

A total of 865 diarrhoeal cases in children under five years reported to the hospital. Out of this, 425 (49.13%) were female children with 346 (40%) aged 0-11 months. The highest peak occurred in the rainy season from May to August. However, there was a weak negative relationship between diarrhoeal diseases and rainfall for the whole study period. Cases were clustered in the northeastern part of the Kassena Nankana Municipality (KNM).

Conclusion

The most affected age group was in 0-11months. Majority of cases were from the North Eastern part of the Municipality. There was seasonal variation of diarrhoeal diseases. Diarrhoeal diseases have the highest occurrence in the rainy season but an increase in rainfall does not necessarily lead to an increase in diarrhoeal cases. Intervention to reduce diarrhoea should be intensified before the rainy season and in the northeastern parts of the municipality.

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.

Seasonality of water quality and diarrheal disease counts in urban and rural settings in south India

The study examined relationships among meteorological parameters, water quality and diarrheal disease counts in two urban and three rural sites in Tamil Nadu, India. Disease surveillance was conducted between August 2010 and March 2012; concurrently water samples from street-level taps in piped distribution systems and from household storage containers were tested for pH, nitrate, total dissolved solids, and total and fecal coliforms. Methodological advances in data collection (concurrent prospective disease surveillance and environmental monitoring) and analysis (preserving temporality within the data through time series analysis) were used to quantify independent effects of meteorological conditions and water quality on diarrheal risk. The utility of a local calendar in communicating seasonality is also presented. Piped distribution systems in the study area showed high seasonal fluctuations in water quality. Higher ambient temperature decreased and higher rainfall increased diarrheal risk with temperature being the predominant factor in urban and rainfall in rural sites. Associations with microbial contamination were inconsistent; however, disease risk in the urban sites increased with higher median household total coliform concentrations. Understanding seasonal patterns in health outcomes and their temporal links to environmental exposures may lead to improvements in prospective environmental and disease surveillance tailored to addressing public health problems.

Association between climate factors and diarrhoea in a Mekong Delta area

The Mekong Delta is vulnerable to changes in climate and hydrological events which alter environmental conditions, resulting in increased risk of waterborne diseases. Research exploring the association between climate factors and diarrhoea, the most frequent waterborne disease in Mekong Delta region, is sparse. This study evaluated the climate-diarrhoea association in Can Tho city, a typical Mekong Delta area in Vietnam. Climate data (temperature, relative humidity, and rainfall) were obtained from the Southern Regional Hydro-Meteorological Centre, and weekly counts of diarrhoea visits were obtained from Can Tho Preventive Medicine Centre from 2004 to 2011. Analysis of climate and health variables was carried out using spline function to adjust for seasonal and long-term trends of variables. A distributed lag model was used to investigate possible delayed effects of climate variables on diarrhoea (considering 0-4 week lag periods), then the multivariate Poisson regression was used to examine any potential association between climate factors and diarrhoea. The results indicated that the diarrhoea incidence peaked within the period August-October annually. Significant positive associations were found between increased diarrhoea and high temperature at 4 weeks prior to the date of hospital visits (IRR = 1.07; 95 % CI = 1.04-1.08), high relative humidity (IRR = 1.13; 95 % CI = 1.12-1.15) and high (>90th percentile) cumulative rainfall (IRR = 1.05; 95 % CI = 1.05-1.08). The association between climate factors and diarrhoea was stronger in rural than urban areas. These findings in the context of the projected changes of climate conditions suggest that climate change will have important implications for residential health in Mekong Delta region.

Climate Change, Water Quality, and Water-Related Diseases in the Mekong Delta Basin

Mekong Delta Basin (MDB) is vulnerable to extreme climate and hydrological events. The objectives of this review are to understand of water related health effects exacerbated by climate change and the gaps of knowledge on the relationships between climate conditions, water quality, and water-related diseases in the MDB. The findings indicate that a few studies with qualitative emphases on the relationships between climate and water quality have been conducted in MDB, and they are insufficient to describe the pattern of climate-disease relationship. The diseases caused by chemical contaminants in relation to changes of climate conditions are neglected in MDB. We suggest further studies to examine the influence of short-term variation of climate conditions on water quality and water-related diseases for the purpose of public health and medical prevention, and due to the trans-boundary nature of MDB, developing partnership in data sharing and research collaboration among MDBs countries should be prioritized.

A cohort study to define the age-specific incidence and risk factors of Shigella diarrhoeal infections in Vietnamese children: a study protocol

BACKGROUND

Shigella spp. are one of the most common causes of paediatric dysentery globally, responsible for a substantial proportion of diarrhoeal disease morbidity and mortality, particularly in industrialising regions. Alarming levels of antimicrobial resistance are now reported in S. flexneri and S. sonnei, hampering treatment options. Little is known, however, about the burden of infection and disease due to Shigella spp. in the community.

METHODS/DESIGN

In order to estimate the incidence of this bacterial infection in the community in Ho Chi Minh City, Vietnam we have designed a longitudinal cohort to follow up approximately 700 children aged 12-60 months for two years with active and passive surveillance for diarrhoeal disease. Children will be seen at 6 month intervals for health checks where blood and stool samples will be collected. Families will also be contacted every two weeks for information on presence of diarrhoea in the child. Upon report of a diarrhoeal disease episode, study nurses will either travel to the family home to perform an evaluation or the family will attend a study hospital at a reduced cost, where a stool sample will also be collected. Case report forms collected at this time will detail information regarding disease history, risk factors and presence of disease in the household.Outcomes will include (i) age-specific incidence of Shigella spp. and other agents of diarrhoeal disease in the community, (ii) risk factors for identified aetiologies, (iii) rates of seroconversion to a host of gastrointestinal pathogens in the first few years of life. Further work regarding the longitudinal immune response to a variety of Shigella antigens, host genetics and candidate vaccine/diagnostic proteins will also be conducted.

DISCUSSION

This is the largest longitudinal cohort with active surveillance designed specifically to investigate Shigella infection and disease. The study is strengthened by the active surveillance component, which will likely capture a substantial proportion of episodes not normally identified through passive or hospital-based surveillance. It is hoped that information from this study will aid in the design and implementation of Shigella vaccine trials in the future.

Association between annual river flood pulse and paediatric hospital admissions in the Mekong Delta area

The Mekong Delta is the most vulnerable region to extreme climate and hydrological conditions however the association between these conditions and children's health has been little studied. We examine the association between annual river flood pulse and paediatric hospital admissions in a Vietnam Mekong Delta city. Daily paediatric hospital admissions (PHA) were collected from the City Paediatric Hospital, and daily river water level (RWL) and meteorological data were retrieved from the Southern Regional Hydro-Meteorological Centre from 2008 to 2011. We evaluated the association between annual river flood pulse (>=90th percentile of RWL) and PHA using the Poisson distributed lag model, controlling for temperature, relative humidity, day of week, seasonal and long-term trends. The seasonal pattern of PHA was examined using harmonic and polynomial regression models. The cumulative risk ratios estimated for a 15-day period following an extreme RWL was 1.26 (95%CI, 1.2-1.38) for all age groups, 1.27 (95%CI, 1.23-1.30) for under five-years and 1.15 (95%CI, 1.07-1.20) for school-aged children, 1.24 (95%CI, 1.21-1.27) for all-causes, 1.18 (95%CI, 1.12-1.21) for communicable infection, 1.66 (95%CI, 1.57-1.74) for respiratory infection and 1.06 (95%CI, 1.01-1.1) for other diseases. The peak PHA risk is in the September-October period corresponding to the highest RWL, and the PHA-RWL association was modified by temperature. An increase in PHA is significantly associated with annual river flood, and the pattern of PHA is seasonally correspondent to the RWL. These findings combined with projected changes in climate conditions suggest important implications of climate change for human health in the Mekong Delta region.

Spatiotemporal pattern of bacillary dysentery in China from 1990 to 2009: what is the driver behind?

Background

Little is known about the spatiotemporal pattern of bacillary dysentery (BD) in China. This study assessed the geographic distribution and seasonality of BD in China over the past two decades.

Methods

Data on monthly BD cases in 31 provinces of China from January 1990 to December 2009 obtained from Chinese Center for Disease Control and Prevention, and data on demographic and geographic factors, as well as climatic factors, were compiled. The spatial distributions of BD in the four periods across different provinces were mapped, and heat maps were created to present the seasonality of BD by geography. A cosinor function combined with Poisson regression was used to quantify the seasonal parameters of BD, and a regression analysis was conducted to identify the potential drivers of morbidity and seasonality of BD.

Results

Although most regions of China have experienced considerable declines in BD morbidity over the past two decades, Beijing and Ningxia still had high BD morbidity in 2009. BD morbidity decreased more slowly in North-west China than other regions. BD in China mainly peaked from July to September, with heterogeneity in peak time between regions. Relative humidity was associated with BD morbidity and peak time, and latitude was the major predictor of BD amplitude.

Conclusions

The transmission of BD was heterogeneous in China. Improved sanitation and hygiene in North-west China, and better access to clean water and food in the big floating population in some metropolises could be the focus of future preventive interventions against BD. BD control efforts should put more emphasis on those dry areas in summer.

Spatial analysis of Crimean Congo hemorrhagic fever in Iran

Crimean Congo hemorrhagic fever (CCHF) is a viral zoonotic disease. During 1999-2011, 871 human cases of CCHF were diagnosed in Iran. A history of serologic conversion for CCHF virus was seen in 58.7% of 2,447 sheep samples, 25.0% of 1,091 cattle samples and 24.8% of 987 goat samples from different parts of Iran. Spatial analysis showed that the main foci of this disease in humans during these years were in eastern Iran (P < 0.01) and the second most common foci were in northeastern and central Iran. Two livestock foci were detected in the northeastern northwestern Iran. On the basis of the results of this study, infection likely entered Iran from eastern and western neighboring countries.

Temporal modeling of Crimean-Congo hemorrhagic fever in eastern Iran

OBJECTIVES

This study was conducted to determine the predicting factors of Crimean Congo hemorrhagic fever (CCHF) in Zabol and Zahedan, from where more than 60% of all national cases are reported, in order to improve CCHF disease surveillance and to target control efforts.

METHODS

Data were collected from the National Reference Laboratory on Arboviruses and Viral Hemorrhagic Fevers, the national meteorology organization, the veterinary organization, and the national statistics center of Iran. A Poisson regression analysis was applied for the temporal modeling of human samples between 2000 and 2006. The modeling fitness was checked with data from 2007.

RESULTS

This modeling revealed that the disease occurrence followed a seasonal pattern. The maximum temperature and relative humidity in previous months was found to positively affect the occurrence of the disease. Variables such as the level of livestock imports and the number of slaughtered animals were also found to be influential in the occurrence of the disease. The pseudo R(2) was 0.51 in the final model.

CONCLUSIONS

The model predicted the number of cases 1 month in advance with more or less acceptable accuracy. Therefore, it appears that the model might be useful as part of an early warning system.

Effects of varying temporal scale on spatial models of mortality patterns attributed to pediatric diarrhea

Public health data is often highly aggregated in time and space. The consequences of temporal aggregation for modeling in support of policy decisions have largely been overlooked. We examine the effects of changing temporal scale on spatial regression models of pediatric diarrhea mortality patterns, mortality rates and mortality peak timing, in Mexico. We compare annual and decadal level univariate models that incorporate known risk factors. Based on normalized sums of squared differences we compare between annual and decadal coefficients for variables that were significant in decadal models. We observed that spurious relationships might be created through aggregating time scales; obscuring interannual variation and resulting in inflated model diagnostics. In fact, variable selection and coefficient values can vary with changing temporal aggregation. Some variables that were significant at the decadal level were not significant at the annual level. Implications of such aggregation should be part of risk communication to policy makers.

Association of Heavy Rainfall on Genotypic Diversity in V. cholerae Isolates from an Outbreak in India

The outbreak of waterborne disease cholera has been associated with rainfall and flooding events by contamination of potable water with environmental Vibrio cholerae. The continuation of the epidemic in a region, however, is often due to secondary transmission of the initial outbreak strain through human waste. This paper reports, on the contrary, a rapid shift of genotype from one V. cholerae strain to another one in an epidemic region. V. cholerae isolated from patients during 2005 cholera epidemic in Chennai, India were characterized using PCR identification of toxin genes, antibiogram, and genomic fingerprinting analysis. The results showed that in spite of the similarity of toxin genes and antibiogram, the Vibrio isolates grouped into two different clusters based on the ERIC-PCR fingerprinting. Each cluster corresponded to a distinct peak of cholera outbreak, which occurred after separate heavy rainfall. The results suggest that the rainfall event can bring various genotypes of V. cholerae strains causing multiple outbreaks.

An exploration of spatial patterns of seasonal diarrhoeal morbidity in Thailand

Studies of temporal and spatial patterns of diarrhoeal disease can suggest putative aetiological agents and environmental or socioeconomic drivers. Here, the seasonal patterns of monthly acute diarrhoeal morbidity in Thailand, where diarrhoeal morbidity is increasing, are explored. Climatic data (2003-2006) and Thai Ministry of Health annual reports (2003-2009) were used to construct a spatially weighted panel regression model. Seasonal patterns of diarrhoeal disease were generally bimodal with aetiological agents peaking at different times of the year. There is a strong association between daily mean temperature and precipitation and the incidence of hospitalization due to acute diarrhoea in Thailand leading to a distinct spatial pattern in the seasonal pattern of diarrhoea. Model performance varied across the country in relation to per capita GDP and population density. While climatic factors are likely to drive the general pattern of diarrhoeal disease in Thailand, the seasonality of diarrhoeal disease is dampened in affluent urban populations.

Spatio-temporal patterns of diarrhoeal mortality in Mexico

Diarrhoeal mortality rates in Mexican children dramatically declined during the 1980s and 1990s, concomitant with a temporal shift in peak deaths from summer to autumn-winter. The spatial dynamics of these patterns have not previously been studied. We first describe the seasonal features of paediatric diarrhoeal mortality in Mexico as a whole, then across individual states. While no geographical gradients in the magnitude of diarrhoeal mortality rates have been detected in recent years, we identified a distinct spatial pattern in the timing of peak mortality rate. In the 1980s the summer peak mortality was earliest around Mexico's capital and later in states to the southeast and northwest. Our results suggest that the direction and timing of those annual waves are related to the mean monthly precipitation and mean daily temperature. This pattern has disintegrated in recent years as the summer peak has diminished.

Use of oral cholera vaccines in an outbreak in Vietnam: a case control study

Background

Killed oral cholera vaccines (OCVs) are available but not used routinely for cholera control except in Vietnam, which produces its own vaccine. In 2007–2008, unprecedented cholera outbreaks occurred in the capital, Hanoi, prompting immunization in two districts. In an outbreak investigation, we assessed the effectiveness of killed OCV use after a cholera outbreak began.

Methodology/Principal Findings

From 16 to 28 January 2008, vaccination campaigns with the Vietnamese killed OCV were held in two districts of Hanoi. No cholera cases were detected from 5 February to 4 March 2008, after which cases were again identified. Beginning 8 April 2008, residents of four districts of Hanoi admitted to one of five hospitals for acute diarrhea with onset after 5 March 2008 were recruited for a matched, hospital-based, case-control outbreak investigation. Cases were matched by hospital, admission date, district, gender, and age to controls admitted for non-diarrheal conditions. Subjects from the two vaccinated districts were evaluated to determine vaccine effectiveness. 54 case-control pairs from the vaccinated districts were included in the analysis. There were 8 (15%) and 16 (30%) vaccine recipients among cases and controls, respectively. The vaccine was 76% protective against cholera in this setting (95% CI 5% to 94%, P = 0.042) after adjusting for intake of dog meat or raw vegetables and not drinking boiled or bottled water most of the time.

Conclusions/Significance

This is the first study to explore the effectiveness of the reactive use of killed OCVs during a cholera outbreak. Our findings suggest that killed OCVs may have a role in controlling cholera outbreaks.

Simple measures such as adequate sanitation and clean water stops the spread of cholera; however, in areas where these are not available, cholera spreads quickly and may lead to death in a few hours if treatment is not initiated immediately. The use of life-saving rehydration therapy is the mainstay in cholera control, however, the rapidity of the disease and the limited access to appropriate healthcare units in far-flung areas together result in an unacceptable number of deaths. The WHO has recommended the use of oral cholera vaccines as a preventive measure against cholera outbreaks since 2001, but this was recently updated so that vaccine use may also be considered once a cholera outbreak has begun. The findings from this study suggest that reactive use of killed oral cholera vaccines provides protection against the disease and may be a potential tool in times of outbreaks. Further studies must be conducted to confirm these findings.

Temporal fluctuation of multidrug resistant salmonella typhi haplotypes in the mekong river delta region of Vietnam

BACKGROUND

typhoid fever remains a public health problem in Vietnam, with a significant burden in the Mekong River delta region. Typhoid fever is caused by the bacterial pathogen Salmonella enterica serovar Typhi (S. Typhi), which is frequently multidrug resistant with reduced susceptibility to fluoroquinolone-based drugs, the first choice for the treatment of typhoid fever. We used a GoldenGate (Illumina) assay to type 1,500 single nucleotide polymorphisms (SNPs) and analyse the genetic variation of S. Typhi isolated from 267 typhoid fever patients in the Mekong delta region participating in a randomized trial conducted between 2004 and 2005.

PRINCIPAL FINDINGS

the population of S. Typhi circulating during the study was highly clonal, with 91% of isolates belonging to a single clonal complex of the S. Typhi H58 haplogroup. The patterns of disease were consistent with the presence of an endemic haplotype H58-C and a localised outbreak of S. Typhi haplotype H58-E2 in 2004. H58-E2-associated typhoid fever cases exhibited evidence of significant geo-spatial clustering along the Sông H u branch of the Mekong River. Multidrug resistance was common in the established clone H58-C but not in the outbreak clone H58-E2, however all H58 S. Typhi were nalidixic acid resistant and carried a Ser83Phe amino acid substitution in the gyrA gene.

SIGNIFICANCE

the H58 haplogroup dominates S. Typhi populations in other endemic areas, but the population described here was more homogeneous than previously examined populations, and the dominant clonal complex (H58-C, -E1, -E2) observed in this study has not been detected outside Vietnam. IncHI1 plasmid-bearing S. Typhi H58-C was endemic during the study period whilst H58-E2, which rarely carried the plasmid, was only transient, suggesting a selective advantage for the plasmid. These data add insight into the outbreak dynamics and local molecular epidemiology of S. Typhi in southern Vietnam.