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

Spatio-temporal distributions and determinants of diarrhea among under-five children in Ethiopia

Objective

The purpose of this study was to evaluate the spatio-temporal pattern of Ethiopia's childhood diarrheal disease and identify its contributing factors.

Methods

We conducted analyses on secondary data from four Ethiopian Demographic and Health Surveys conducted between 2000 and 2016. Moran's I was used to determine spatial dependence and spatial models were used to evaluate variables associated with diarrhea in under-five children at the zonal level.

Results

Childhood diarrhea showed spatial clustering in Ethiopia (Moran's I; p < 0.05). The spatial regression model revealed significant factors at the zonal level: children born at home (e θ = 1.355, 95% CI: 1.052-1.544, p < 0.001), low birth weight (e θ = 1.18, 95% CI: 1.017-1.691, p < 0.05), and unimproved source of water (e θ = 0.8568, 95% CI: 0.671-1.086, p < 0.01).

Conclusion

The prevalence of diarrhea among under-five children varied over time by zone, with the Assosa, Hundene, and Dire Diwa zones having the highest rates. Home births and low birth weight contributed to the prevalence of childhood diarrhea. In high-risk zones of Ethiopia, reducing childhood diarrhea requires integrated child health interventions and raising awareness about the potential hazards associated with unimproved water sources.

Monitoring of enteropathogenic Gram-negative bacteria in wastewater treatment plants: a multimethod approach

The wastewater treatment processes are associated with the emission of microbial aerosols, including enteropathogenic bacteria. Their presence in this work environment poses a real threat to the health of employees, both through the possibility of direct inhalation of the contaminated air and indirectly through the pollution of all types of surfaces with such bioaerosol particles. This study aimed to investigate the prevalence of enteropathogenic bacteria in the air, on surfaces, and in wastewater samples collected in four wastewater treatment plants (WWTPs). The effectiveness of conventional culture-biochemical, as well as spectrometric and molecular methods for the rapid detection of enteropathogenic bacteria at workstations related to particular stages of wastewater processing, was also evaluated. Bioaerosol, surface swab, and influent and effluent samples were collected from wastewater plants employing mechanical-biological treatment technologies. The air samples were collected using MAS-100 NT impactor placed at a height of 1.5 m above the floor or ground, simulating aspiration from the human breathing zone. Surface samples were collected with sterile swabs from different surfaces (valves, handles, handrails, and coveyor belts) at workplaces. The raw influent and treated effluent wastewater samples were aseptically collected using sterile bottles. The identification of bacterial entheropathogens was simultaneously conducted using a culture-based method supplemented with biochemical (API) tests, mass-spectrometry (MALDI TOF MS), and molecular (multiplex real-time PCR) methods. This study confirmed the common presence of bacterial pathogens (including enteropathogenic and enterotoxigenic Escherichia coli, Salmonella spp., Campylobacter spp., and Yersinia enterocolitica) in all air, surface, and wastewater samples at studied workplaces. Higher concentrations of enteropathogenic bacteria were observed in the air and on surfaces at workplaces where treatment processes were not hermetized. The results of this study underline that identification of enteropathogenic bacteria in WWTPs is of great importance for the correct risk assessment at workplaces. From the analytical point of view, the control of enteropathogenic bacterial air and surface pollution using rapid multiplex-PCR method should be routinely performed as a part of hygienic quality assessment in WWTPs.

Peak timing of slowest growth velocity among young children coincides with highest ambient temperatures in Burkina Faso: a longitudinal study

BACKGROUND

Seasonal cycles in climatic factors affect drivers of child growth and contribute to seasonal fluctuations in undernutrition. Current growth seasonality models are limited by categorical definitions of seasons that rely on assumptions about their timing and fail to consider their magnitude.

OBJECTIVE

We disentangle the relationship between climatic factors and growth indicators, using harmonic regression to determine how child growth is related to peaks in temperature, precipitation, and vegetation.

METHODS

Longitudinal anthropometric data collected between August 2014 and December 2016 from 5039 Burkinabè children measured monthly from age 6 to 28 mo (108,580 observations) were linked with remotely sensed daily precipitation, vegetation, and maximum air temperature. Our models parsimoniously extract a cyclic signal with multiple potential peaks, to compare the magnitude and timing of seasonal peaks in climatic factors and morbidity with that of nadirs in growth velocity (cm/mo, kg/mo).

RESULTS

Length and weight velocity were slowest twice a year, coinciding both times with the highest temperatures, and peak fever incidence. Length velocity is slowest 13 d after the first temperature peak in April, and 5 d after the second. Similarly, weight velocity is slowest 13 d before the first temperature peak, and 11 d before the second. The statistical relationship between temperature and anthropometry shows that when the current temperature is higher, weight velocity is lower (β = -0.0048; 95% CI: -0.0059, -0.0038), and length velocity is higher (β = 0.0088; 95% CI: 0.0070, 0.0105).

CONCLUSIONS

Results suggest that child health and development are more affected by high temperatures than by other aspects of climatic seasonality such as rainfall. Emerging shifts in climatic conditions will pose challenges to optimal growth, highlighting the importance of changes that optimize the timing of nutrition interventions and address environmental growth-limiting conditions.

CLINICAL TRIAL REGISTRY

Clinicaltrials.gov: NCT02071563.

The Complexity of the Seasonality of Nutritional Status: Two Annul Peaks in Child Wasting in Eastern Chad

BACKGROUND

Understanding seasonal patterns in nutritional status is critical for achieving and tracking global nutrition goals. However, the majority of nutrition seasonality research design draws on 2 or 3 within-year time points based on existing assumptions of seasonality, missing a more nuanced pattern.

OBJECTIVE

We aimed to identify the intra-year variability of childhood wasting, severe wasting, and weight-for-height z-scores (WHZ) in a dryland single wet-season context and illustrate an analytical approach for improving analysis of the seasonality of nutritional status.

METHODS

To quantify the intra-year variability in nutritional status, we use data from a 23-month panel study (May 2018 to March 2020) following 231 children (6-59 months of age) in eastern Chad. We apply a mixed-effects harmonic regression with child- and village-level fixed effects on the odds of being wasted, severely wasted, and on WHZ, testing for multiple and nonsymmetrical seasonal peaks, adjusted for child sex and age. We triangulate our findings using climate data on temperature, vegetation, and precipitation.

RESULTS

We identify 2 annual peaks of wasting and severe wasting. Wasting peaks at 14.7% (confidence interval [CI], 11.8-18.2) at the end of the dry season, while the smaller peak corresponds to the start of the harvest period at 13.4% (CI, 10.7-16.6). The odds of being wasted decline during the rainy season to 11.8% (CI, 9.4-14.7), with the lowest prevalence of 8.8% (CI, 6.9-11.1) occurring during the start of the dry season. In addition, a 1°C monthly increase in temperature is significantly associated with a 5% (CI, 1.4-8.7) and 12% (CI, 3.0-20.3) increase in the odds that a child is wasted and severely wasted, respectively.

CONCLUSIONS

Intra-year variability of child wasting is far more complex and nuanced than identified by the literature, with 2 peaks, as opposed to 1, likely corresponding to different seasonal drivers, such as food insecurity, disease, water contamination, and care practices at different times of year. Better seasonality analysis can go a long way in improving the timing and content of programming with the goal of reducing child wasting.

Seasonality of Acute Malnutrition in African Drylands: Evidence From 15 Years of SMART Surveys

Reduction of wasting, or low weight-for-height, is a critical target for the Zero Hunger Sustainable Development Goal, yet robust evidence establishing continuous seasonal patterns of wasting is presently lacking. The current consensus of greatest hunger during the preharvest period is based on survey designs and analytical methods, which discretize time frame into preharvest/postharvest, dry/wet, or lean/plenty seasons. We present a spatiotemporally nuanced study of acute malnutrition seasonality in African drylands using a 15-year data set of Standardized Monitoring and Assessment of Relief and Transition surveys (n = 412,370). Climatological similarity was ensured by selecting subnational survey regions with 1 rainy season and by spatially matching each survey to aridity and livelihood zones. Harmonic logit regression models indicate 2 peaks of wasting during the calendar year. Greatest wasting prevalence is estimated in April to May, coincident with the primary peak of temperature. A secondary peak of wasting is observed in August to October, coinciding with the primary peak of rainfall and secondary peak of temperature. This pattern is retained across aridity and livelihood zones and is sensitive to temperature, precipitation, and vegetation. Improved subnational estimation of acute malnutrition seasonality can thus assist decision makers and practitioners in data-sparse settings and facilitate global progress toward Zero Hunger.

Water quality, WASH, and gender: differential impacts on health and well-being in Abeokuta City, Nigeria

It is often assumed that humans experience the effect of poor water quality like multiple health and socioeconomic impacts in the same way. But these impacts are not gender neutral due to inequalities caused by physiological composition, age marginalization, and socioeconomic conditions, among others. A mixed method, comprising water quality assessment, a survey of 456 individuals, and medical record collection, was applied to examine the differential impacts of water quality and WASH practices in Abeokuta City, Nigeria. The assessment shows that without point-of-use water treatment, the water sources in the area are not safe for potable purposes, as the waters are hard in the sequence of borehole > surface water > hand-dug well > sachet water, with elevated levels of calcium (> 75 mg/L) and not free from microbial contamination. Among the area population segments, men and boys (relative to women and girls) may be more susceptible (55%) to the compounding health effects associated with the hardness and high calcium concentration in water. Girls are the most affected by the associated impacts of water collection. Men and boys are more vulnerable to the consequences of poor hygiene, while women are more susceptible to the health effects of toilet cleaning and the sharing of sanitation facilities, among others. We conclude that there are differential impacts of unsafe water, WASH services, and practices on human health. Gendered statistics through sex-disaggregated data is crucial to unmasking the differential impacts, which are neither gender neutral nor evenly distributed between women and men, and boys and girls.

Meteorological Factors Affecting Infectious Diarrhea in Different Climate Zones of China

Meteorological factors and the increase in extreme weather events are closely related to the incidence rate of infectious diarrhea. However, few studies have explored whether the impact of the same meteorological factors on the incidence rate of infectious diarrhea in different climate regions has changed and quantified these changes. In this study, the time series fixed-effect Poisson regression model guided by climate was used to quantify the relationships between the incidence rate of various types of infectious diarrhea and meteorological factors in different climate regions of China from 2004 to 2018, with a lag of 0-2 months. In addition, six social factors, including per capita Gross Domestic Product (GDP), population density, number of doctors per 1000 people, proportion of urbanized population, proportion of children aged 0-14 years old, and proportion of elderly over 65 years old, were included in the model for confounding control. Additionally, the intercept of each province in each model was analyzed by a meta-analysis. Four climate regions were considered in this study: tropical monsoon areas, subtropical monsoon areas, temperate areas and alpine plateau areas. The results indicate that the influence of meteorological factors and extreme weather in different climate regions on diverse infectious diarrhea types is distinct. In general, temperature was positively correlated with all infectious diarrhea cases (0.2 ≤ r ≤ 0.6, p < 0.05). After extreme rainfall, the incidence rate of dysentery in alpine plateau area in one month would be reduced by 18.7% (95% confidence interval (CI): -27.8--9.6%). Two months after the period of extreme sunshine duration happened, the incidence of dysentery in the alpine plateau area would increase by 21.9% (95% CI: 15.4-28.4%) in that month, and the incidence rate of typhoid and paratyphoid in the temperate region would increase by 17.2% (95% CI: 15.5-18.9%) in that month. The meta-analysis showed that there is no consistency between different provinces in the same climate region. Our study indicated that meteorological factors and extreme weather in different climate areas had different effects on various types of infectious diarrhea, particularly extreme rainfall and extreme sunshine duration, which will help the government develop disease-specific and location-specific interventions, especially after the occurrence of extreme weather.

Seasonal variation of diarrheal diseases and drinking water quality in resettlement colony in Delhi, India: A community-based cross-sectional study

Seasonal variation plays an important role in the occurrence of diarrheal diseases and distinct seasonal occurrence of diarrheal diseases, with bacterial diarrhea occurring more during the warm seasons and viral diarrhea occurring during the drier cool months, has been observed due to seasonal variation. Time-series cross-sectional study was conducted from January to December 2018 among 553 under-five children to assess seasonal variation of diarrheal diseases and its association with the drinking water quality in a resettlement colony of Delhi. The prevalence of diarrhea was 40.7% and was highest during the rainy season (67.6%). Majority of the water samples were found to be unsatisfactory for human consumption during the rainy and summer seasons. Significant and moderate relationship was found between the seasonal variation and occurrence of diarrhea (r = 0.728, P < 0.05) and most probable number count (r = 0.50, P < 0.05), respectively. Understanding the environmental factors that influences the occurrence of diarrheal diseases is warranted.

Seasonal Variability Influence on the Prevalence of Diarrhoea among Under-Five-Year-old Children in Kersa District, Eastern Ethiopia: A Community-Based Longitudinal Study

BACKGROUND

The health effects of climate change have been found to be a global concern for the last 2 centuries. However, the effect of climate variability on diarrhoea among under-five-year-old children is perhaps undocumented or otherwise unknown. The aim of the present study was to determine the effect of climate variability on diarrhoea among children under 5 years of age.

METHODS

A community-based longitudinal study was conducted over 8 repeated visits from June 2016 to May 2018 at the Kersa Demographic Surveillance and Health Research Center. A total of 500 randomly selected households and their 48 improved water sources were included in the survey from 3 agro-ecological zones, the rural and urban areas of the study area. Data was collected on household characteristics, diarrhoea, WASH practices, water quality and quantity in households, and improved water sources. A structured pre-tested questionnaire, an observational check list and laboratory tests were used for data collection. The data was entered into Epi Data Version 3.01 and transferred to Stata Version 12 for analysis. Multilevel mixed-effect Poisson regression was used to determine the relationship between predictors and outcome variables. A P-value of less than .05 was the cut-off point for statistically significant.

RESULTS

The prevalence of diarrhoea in 2 weeks among children under 5 years of age was 17.2% (95% CI: 15.8-19.71). Rainfall, E. coli contamination of drinking water at the source and in the home, 20 L of water consumption per capita per day, sharing water sources with animals and home water treatment by residents of the mid- and lowlands were all predictors of diarrhoea. The space-time scan statistic confirmed that child diarrhoea had random variation in both space and time.

CONCLUSION

Climate variability has influenced the prevalence of diarrhoea among under-five-year-old children. Climate-resilient measures should be taken to reduce the burden of diarrhoea in the community.

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.

Environmental determinants of E. coli, link with the diarrheal diseases, and indication of vulnerability criteria in tropical West Africa (Kapore, Burkina Faso)

In 2017, diarrheal diseases were responsible for 606 024 deaths in Sub-Saharan Africa. This situation is due to domestic and recreational use of polluted surface waters, deficits in hygiene, access to healthcare and drinking water, and to weak environmental and health monitoring infrastructures. Escherichia coli (E. coli) is an indicator for the enteric pathogens that cause many diarrheal diseases. The links between E. coli, diarrheal diseases and environmental parameters have not received much attention in West Africa, and few studies have assessed health risks by taking into account hazards and socio-health vulnerabilities. This case study, carried out in Burkina Faso (Bagre Reservoir), aims at filling this knowledge gap by analyzing the environmental variables that play a role in the dynamics of E. coli, cases of diarrhea, and by identifying initial vulnerability criteria. A particular focus is given to satellite-derived parameters to assess whether remote sensing can provide a useful tool to assess the health hazard. Samples of surface water were routinely collected to measure E. coli, enterococci and suspended particulate matter (SPM) at a monitoring point (Kapore) during one year. In addition, satellite data were used to estimate precipitation, water level, Normalized Difference Vegetation Index (NDVI) and SPM. Monthly epidemiological data for cases of diarrhea from three health centers were also collected and compared with microbiological and environmental data. Finally, semi-structured interviews were carried out to document the use of water resources, contact with elements of the hydrographic network, health behavior and condition, and water and health policy and prevention, in order to identify the initial vulnerability criteria. A positive correlation between E. coli and enterococci in surface waters was found indicating that E. coli is an acceptable indicator of fecal contamination in this region. E. coli and diarrheal diseases were strongly correlated with monsoonal precipitation, in situ SPM, and Near Infra-Red (NIR) band between March and November. Partial least squares regression showed that E. coli concentration was strongly associated with precipitation, Sentinel-2 reflectance in the NIR and SPM, and that the cases of diarrhea were strongly associated with precipitation, NIR, E. coli, SPM, and to a lesser extent with NDVI. Moreover, E. coli dynamics were reproduced using satellite data alone, particularly from February to mid-December (R2 = 0.60) as were cases of diarrhea throughout the year (R2 = 0.76). This implies that satellite data could provide an important contribution to water quality monitoring. Finally, the vulnerability of the population was found to increase during the rainy season due to reduced accessibility to healthcare and drinking water sources and increased use of water of poor quality. During this period, surface water is used because it is close to habitations, easy to use and free from monetary or political constraints. This vulnerability is aggravated by marginality and particularly affects the Fulani, whose concessions are often close to surface water (river, lake) and far from health centers.

A Review of the Environmental Trigger and Transmission Components for Prediction of Cholera

Climate variables influence the occurrence, growth, and distribution of Vibrio cholerae in the aquatic environment. Together with socio-economic factors, these variables affect the incidence and intensity of cholera outbreaks. The current pandemic of cholera began in the 1960s, and millions of cholera cases are reported each year globally. Hence, cholera remains a significant health challenge, notably where human vulnerability intersects with changes in hydrological and environmental processes. Cholera outbreaks may be epidemic or endemic, the mode of which is governed by trigger and transmission components that control the outbreak and spread of the disease, respectively. Traditional cholera risk assessment models, namely compartmental susceptible-exposed-infected-recovered (SEIR) type models, have been used to determine the predictive spread of cholera through the fecal–oral route in human populations. However, these models often fail to capture modes of infection via indirect routes, such as pathogen movement in the environment and heterogeneities relevant to disease transmission. Conversely, other models that rely solely on variability of selected environmental factors (i.e., examine only triggers) have accomplished real-time outbreak prediction but fail to capture the transmission of cholera within impacted populations. Since the mode of cholera outbreaks can transition from epidemic to endemic, a comprehensive transmission model is needed to achieve timely and reliable prediction with respect to quantitative environmental risk. Here, we discuss progression of the trigger module associated with both epidemic and endemic cholera, in the context of the autochthonous aquatic nature of the causative agent of cholera, V. cholerae, as well as disease prediction.

Weaponizing water as an instrument of war in Syria: Impact on diarrhoeal disease in Idlib and Aleppo governorates, 2011-2019

OBJECTIVES

Investigate the weaponization of water during the Syrian conflict and the correlation of attacks on water, sanitation, and hygiene (WASH) infrastructure in Idlib and Aleppo governorates with trends in waterborne diseases reported by Early Warning and Response surveillance systems.

METHODS

We reviewed literature and databases to obtain information on attacks on WASH in Aleppo and Idlib governorates between 2011 and 2019. We plotted weekly trends in waterborne diseases from two surveillance systems operational in Aleppo and Idlib governorates between 2015 and early 2020.

RESULTS

The literature review noted several attacks on water and related infrastructure in both governorates, suggesting that WASH infrastructure was weaponized by state and non-state actors. Most interference with WASH in the Aleppo governorate occurred before 2019 and in the Idlib governorate in the summer of 2020. Other acute diarrhea represented >90% of cases of diarrhea; children under 5 years contributed 50% of cases. There was substantial evidence (p < 0.001) of an overall upward trend in cases of diarrheal disease.

CONCLUSIONS

Though no direct correlation can be drawn between the weaponization of WASH and the burden of waterborne infections due to multiple confounders, this research introduces important concepts on attacks on WASH and their potential impacts on waterborne diseases.

Prevalence of Field-Collected House Flies and Stable Flies With Bacteria Displaying Cefotaxime and Multidrug Resistance

Antibiotic use in livestock accounts for 80% of total antibiotic use in the United States and has been described as the driver for resistance evolution and spread. As clinical infections with multidrug-resistant pathogens are rapidly rising, there remains a missing link between agricultural antibiotic use and its impact on human health. In this study, two species of filth flies from a livestock operation were collected over the course of 11 mo: house flies Musca domestica (L.) (Diptera: Muscidae), representing a generalist feeder, and stable flies Stomoxys calcitrans (L.) (Diptera: Muscidae), representing a specialist (blood) feeder. The prevalence of flies carrying cefotaxime-resistant (CTX-R) bacteria in whole bodies and dissected guts were assayed by culturing on antibiotic-selective media, with distinct colonies identified by Sanger sequencing. Of the 149 flies processed, including 81 house flies and 68 stable flies, 18 isolates of 12 unique bacterial species resistant to high-level cefotaxime were recovered. These isolates also showed resistance to multiple classes of antibiotics. The CTX-R isolates were predominantly recovered from female flies, which bore at least two resistant bacterial species. The majority of resistant bacteria were isolated from the guts encompassing both enteric pathogens and commensals, sharing no overlap between the two fly species. Together, we conclude that house flies and stable flies in the field could harbor multidrug-resistant bacteria. The fly gut may serve as a reservoir for the acquisition and dissemination of resistance genes.

Fecal Indicator Bacteria Data to Characterize Drinking Water Quality in Low-Resource Settings: Summary of Current Practices and Recommendations for Improving Validity

Fecal indicator bacteria (FIB) values are widely used to assess microbial contamination in drinking water and to advance the modeling of infectious disease risks. The membrane filtration (MF) testing technique for FIB is widely adapted for use in low- and middle-income countries (LMICs). We conducted a systematic literature review on the use of MF-based FIB data in LMICs and summarized statistical methods from 172 articles. We then applied the commonly used statistical methods from the review on publicly available datasets to illustrate how data analysis methods affect FIB results and interpretation. Our findings indicate that standard methods for processing samples are not widely reported, the selection of statistical tests is rarely justified, and, depending on the application, statistical methods can change risk perception and present misleading results. These results raise concerns about the validity of FIB data collection, analysis, and presentation in LMICs. To improve evidence quality, we propose a FIB data reporting checklist to use as a reminder for researchers and practitioners.

Household practices in accessing drinking water and post collection contamination: A seasonal cohort study in Malawi

Lack of access to safe drinking water on premises remains widespread in low- and middle-income countries. Interventions to improve access to safe water at the point of collection are essential, but water safety at the point of consumption is also an important consideration. This research aimed to 1) improve understanding of household practices in collecting water with respect to seasonality, and 2) to further assess risk associated with post-collection contamination from the point of collection to the point of consumption. A seasonal cohort study, including 115 households, was conducted in Malawi. Along with household surveys and observations, samples of water were tested for microbial water quality at four different stages of water collection: water source, collection container, storage container, cup of drinking water. Using E. coli as an indicator of contamination (cfu/100 ml), the risk of post-collection contamination was assessed. The results indicate that most water sources were free from contamination; contamination was proportionally lower in the dry season when more sources were found to be classified as having a very low risk of contamination. However, the level of risk of contamination was more likely to increase following collection in water sources that were initially free from contamination. Results show that the degradation in water quality from the point of collection to the point of consumption was more important in the rainy season, which is likely to be driven by the effect of seasonality on the household environment. Filling the collection container at the point of collection and storage at the point of consumption were found to be critical stages for an increased risk of E. coli contamination. Understanding household practices in accessing and handling water during both rainy and dry season is necessary to target appropriate interventions to reduce post-collection contamination.

Understanding the Impact of Rainfall on Diarrhea: Testing the Concentration-Dilution Hypothesis Using a Systematic Review and Meta-Analysis

BACKGROUND

Projected increases in extreme weather may change relationships between rain-related climate exposures and diarrheal disease. Whether rainfall increases or decreases diarrhea rates is unclear based on prior literature. The concentration-dilution hypothesis suggests that these conflicting results are explained by the background level of rain: Rainfall following dry periods can flush pathogens into surface water, increasing diarrhea incidence, whereas rainfall following wet periods can dilute pathogen concentrations in surface water, thereby decreasing diarrhea incidence.

OBJECTIVES

In this analysis, we explored the extent to which the concentration-dilution hypothesis is supported by published literature.

METHODS

To this end, we conducted a systematic search for articles assessing the relationship between rain, extreme rain, flood, drought, and season (rainy vs. dry) and diarrheal illness.

RESULTS

A total of 111 articles met our inclusion criteria. Overall, the literature largely supports the concentration-dilution hypothesis. In particular, extreme rain was associated with increased diarrhea when it followed a dry period [incidence rate ratio ( IRR ) = 1.26 ; 95% confidence interval (CI): 1.05, 1.51], with a tendency toward an inverse association for extreme rain following wet periods, albeit nonsignificant, with one of four relevant studies showing a significant inverse association (IRR = 0.911 ; 95% CI: 0.771, 1.08). Incidences of bacterial and parasitic diarrhea were more common during rainy seasons, providing pathogen-specific support for a concentration mechanism, but rotavirus diarrhea showed the opposite association. Information on timing of cases within the rainy season (e.g., early vs. late) was lacking, limiting further analysis. We did not find a linear association between nonextreme rain exposures and diarrheal disease, but several studies found a nonlinear association with low and high rain both being associated with diarrhea.

DISCUSSION

Our meta-analysis suggests that the effect of rainfall depends on the antecedent conditions. Future studies should use standard, clearly defined exposure variables to strengthen understanding of the relationship between rainfall and diarrheal illness. https://doi.org/10.1289/EHP6181.

The phenomenon of summer diarrhea and its waning, 1910-1930

During the first two decades of the 20th century, diarrheal deaths among American infants and children surged every summer. Although we still do not know what pathogen (or pathogens) caused this phenomenon, the consensus view is that it was eventually controlled through public health efforts at the municipal level. Using data from 26 major American cities for the period 1910-1930, we document the phenomenon of summer diarrhea and explore its dissipation. We find that water filtration is associated with a 15 percent reduction in diarrheal mortality among children under the age of two during the non-summer months, but does not seem to have had an effect on diarrheal mortality during the summer. In general, we find little evidence to suggest that public health interventions undertaken at the municipal level contributed to the dissipation of summer diarrhea.

Are There Seasonal Variations in Faecal Contamination of Exposure Pathways? An Assessment in a Low-Income Settlement in Uganda

Sanitation infrastructure are not able to cope with the increasing population in low-income countries, which leaves populations exposed to faecal contamination from multiple pathways. This study evaluated public health risk (using SaniPath) in a low-income community during the dry season, to identify the dominant exposure pathways, and compare this data to existing data for the rainy season, questioning the assumption that risk of faecal contamination is higher in the rainy season. SaniPath was used to collect and assess exposure and environmental data, and to generate risk profiles for each pathway. In the dry season the highest exposure frequency was for bathing and street food, exposure frequency generally increased, and seasonal variation was found in five pathways. The highest hazards in the dry season were through contact with drains, soil, and street food. Seasonal variation was found in the contamination of open drains and street food, with higher levels of Escherichia coli (E. coli) in the dry season. Open drains were identified as the most dominant risk pathway in both seasons, but risk was higher in the dry season. This highlights the complex nature of seasonal variation of faecal risk, and questions the assumption that risk is higher in the rainy season.

Assessing Drinking Water Quality at the Point of Collection and within Household Storage Containers in the Hilly Rural Areas of Mid and Far-Western Nepal

Accurate assessments of drinking water quality, household hygenic practices, and the mindset of the consumers are critical for developing effective water intervention strategies. This paper presents a microbial quality assessment of 512 samples from household water storage containers and 167 samples from points of collection (POC) in remote rural communities in the hilly area of western Nepal. We found that 81% of the stored drinking water samples (mean log₁₀ of all samples = 1.16 colony-forming units (CFU)/100 mL, standard deviation (SD) = 0.84) and 68% of the POC samples (mean log₁₀ of all samples = 0.57 CFU/100 mL, SD = 0.86) had detectable E. coli. The quality of stored water was significantly correlated with the quality at the POC, with the majority (63%) of paired samples showing a deterioration in quality post-collection. Locally applied household water treatment (HWT) methods did not effectively improve microbial water quality. Among all household sanitary inspection questions, only the presence of livestock near the water storage container was significantly correlated with its microbial contamination. Households' perceptions of their drinking water quality were mostly influenced by the water's visual appearance, and these perceptions in general motivated their use of HWT. Improving water quality within the distribution network and promoting safer water handling practices are proposed to reduce the health risk due to consumption of contaminated water in this setting.

Influence of Fluid Properties on Intensity of Hydrodynamic Cavitation and Deactivation of Salmonella typhimurium

In this study, three microfluidic devices with different geometries are fabricated on silicon and are bonded to glass to withstand high-pressure fluid flows in order to observe bacteria deactivation effects of micro cavitating flows. The general geometry of the devices was a micro orifice with macroscopic wall roughness elements. The width of the microchannel and geometry of the roughness elements were varied in the devices. First, the thermophysical property effect (with deionized water and phosphate-buffered saline (PBS)) on flow behavior was revealed. The results showed a better performance of the device in terms of cavitation generation and intensity with PBS due to its higher density, higher saturation vapor pressure, and lower surface tension in comparison with water. Moreover, the second and third microfluidic devices were tested with water and Salmonella typhimurium bacteria suspension in PBS. Accordingly, the presence of the bacteria intensified cavitating flows. As a result, both devices performed better in terms of the intensity of cavitating flow with the presence of bacteria. Finally, the deactivation performance was assessed. A decrease in the bacteria colonies on the agar plate was detected upon the tenth cycle of cavitating flows, while a complete deactivation was achieved after the fifteenth cycle. Thus, the proposed devices can be considered as reliable hydrodynamic cavitation reactors for “water treatment on chip” applications.

Influences of Land-Use Dynamics and Surface Water Systems Interactions on Water-Related Infectious Diseases—A Systematic Review

Human interactions with surface water systems, through land-use dynamics, can influence the transmission of infectious water-related diseases. As a result, the aim of our study was to explore and examine the state of scientific evidence on the influences of these interactions on water-related infectious disease outcomes from a global perspective. A systematic review was conducted, using 54 peer-reviewed research articles published between 1995 and August 2019. The study revealed that there has been an increase in the number of publications since 2009; however, few of these publications (n = 6) made explicit linkages to the topic. It was found that urban and agricultural land-use changes had relatively high adverse impacts on water quality, due to high concentrations of fecal matter, heavy metals, and nutrients in surface water systems. Water systems were found as the common “vehicle” for infectious disease transmission, which in turn had linkages to sanitation and hygiene conditions. The study found explicit linkages between human–surface water interaction patterns and the transmission of water-based disease. However, weak and complex linkages were found between land-use change and the transmission of water-borne disease, due to multiple pathways and the dynamics of the other determinants of the disease. Therefore, further research studies, using interdisciplinary and transdisciplinary approaches to investigate and enhance a deeper understanding of these complexities and linkages among land use, surface water quality, and water-related infectious diseases, is crucial in developing integrated measures for sustainable water quality monitoring and diseases prevention.

Bayesian Random Effect Modeling for analyzing spatial clustering of differential time trends of diarrhea incidences

In 2012, nearly 644,000 people died from diarrhea in sub-Saharan Africa. This is a significant obstacle towards the achievement of the Sustainable Development Goal 3 of ensuring a healthy life and promoting the wellbeing at all ages. To enhance evidence-based site-specific intervention and mitigation strategies, especially in resource-poor countries, we focused on developing differential time trend models for diarrhea. We modeled the logarithm of the unknown risk for each district as a linear function of time with spatially varying effects. We induced correlation between the random intercepts and slopes either by linear functions or bivariate conditional autoregressive (BiCAR) priors. In comparison, models which included correlation between the varying intercepts and slopes outperformed those without. The convolution model with the BiCAR correlation prior was more competitive than the others. The inclusion of correlation between the intercepts and slopes provided an epidemiological value regarding the response of diarrhea infection dynamics to environmental factors in the past and present. We found diarrhea risk to increase by 23% yearly, a rate far exceeding Ghana’s population growth rate of 2.3%. The varying time trends widely varied and clustered, with the majority of districts with at least 80% chance of their rates exceeding the previous years. These findings can be useful for active site-specific evidence-based planning and interventions for diarrhea.

Drinking water accessibility and quantity in low and middle-income countries: A systematic review

BACKGROUND

Increasing the quantity of water available for consumption and hygiene is recognized to be among the most efficient interventions to reduce the risk of water-related infectious diseases in low and middle-income countries. Such impacts are often associated with water supply accessibility (e.g. distance or collection time) and used to justify investment in improving access.

OBJECTIVE

To assess the relationship between the water source location and the quantity of water available in households from low and middle-income countries by identifying the effects of interventions aiming to improve access, and to compare the indicators and measures used to collect information.

METHODS

We systematically searched seven databases (i.e. Cairn, Cochrane Library, Embase, MEDLINE, PubMed, Web of Science, Women's Studies International) along with grey literature for articles reporting indicators and measures of accessibility and quantity. We found 6492 records, of which 20 studies were retained that met the review's inclusion criteria.

RESULTS

Most studies were conducted in rural settings and provided suggestive findings to describe an inverse relationship between accessibility and quantity. Overall, a wide range of indicators and measures were used to assess water accessibility and quantity in the selected studies along with their association. The lack of consistency raised concerns regarding comparability and reliability of these methods.

CONCLUSIONS

The review findings support the hypothesis that the quantity of water available in households is a function of the source location, but the inconsistency in study outcomes highlights the need to further investigate the strength and effects of the relationship.

The use of remotely sensed environmental parameters for spatial and temporal schistosomiasis prediction across climate zones in Ghana

Schistosomiasis control in sub-Saharan Africa is enacted primarily through preventive chemotherapy. Predictive models can play an important role in filling knowledge gaps in the distribution of the disease and help guide the allocation of limited resources. Previous modeling approaches have used localized cross-sectional survey data and environmental data typically collected at a discrete point in time. In this analysis, 8 years (2008-2015) of monthly schistosomiasis cases reported into Ghana's national surveillance system were used to assess temporal and spatial relationships between disease rates and three remotely sensed environmental variables: land surface temperature (LST), normalized difference vegetation index (NDVI), and accumulated precipitation (AP). Furthermore, the analysis was stratified by three major and nine minor climate zones, defined using a new climate classification method. Results showed a downward trend in reported disease rates (~ 1% per month) for all climate zones. Seasonality was present in the north with two peaks (March and September), and in the middle of the country with a single peak (July). Lowest disease rates were observed in December/January across climate zones. Seasonal patterns in the environmental variables and their associations with reported schistosomiasis infection rates varied across climate zones. Precipitation consistently demonstrated a positive association with disease outcome, with a 1-cm increase in rainfall contributing a 0.3-1.6% increase in monthly reported schistosomiasis infection rates. Generally, surveillance of neglected tropical diseases (NTDs) in low-income countries continues to suffer from data quality issues. However, with systematic improvements, our approach demonstrates a way for health departments to use routine surveillance data in combination with publicly available remote sensing data to analyze disease patterns with wide geographic coverage and varying levels of spatial and temporal aggregation.

Climate Change Impacts on Waterborne Diseases: Moving Toward Designing Interventions

PURPOSE

Climate change threatens progress achieved in global reductions of infectious disease rates over recent decades. This review summarizes literature on potential impacts of climate change on waterborne diseases, organized around a framework of questions that can be addressed depending on available data.

RECENT FINDINGS

A growing body of evidence suggests that climate change may alter the incidence of waterborne diseases, and diarrheal diseases in particular. Much of the existing work examines historical relationships between weather and diarrhea incidence, with a limited number of studies projecting future disease rates. Some studies take social and ecological factors into account in considerations of historical relationships, but few have done so in projecting future conditions. The field is at a point of transition, toward incorporating social and ecological factors into understanding the relationships between climatic factors and diarrheal diseases and using this information for future projections. The integration of these components helps identify vulnerable populations and prioritize adaptation strategies.

Associations between High Temperature, Heavy Rainfall, and Diarrhea among Young Children in Rural Tamil Nadu, India: A Prospective Cohort Study

BACKGROUND

The effects of weather on diarrhea could influence the health impacts of climate change. Children have the highest diarrhea incidence, especially in India, where many lack safe water and sanitation.

OBJECTIVES

In a prospective cohort of 1,284 children under 5 y of age from 900 households across 25 villages in rural Tamil Nadu, India, we examined whether high temperature and heavy rainfall was associated with increased all-cause diarrhea and water contamination.

METHODS

Seven-day prevalence of diarrhea was assessed monthly for up to 12 visits from January 2008 to April 2009, and hydrogen sulfide ([Formula: see text]) presence in drinking water, a fecal contamination indicator, was tested in a subset of households. We estimated associations between temperature and rainfall exposures and diarrhea and [Formula: see text] using binomial regressions, adjusting for potential confounders, random effects for village, and autoregressive-1 error terms for study week.

RESULTS

There were 259 cases of diarrhea. The prevalence of diarrhea during the 7 d before visits was 2.95 times higher (95% CI: 1.99, 4.39) when mean temperature in the week before the 7-d recall was in the hottest versus the coolest quartile of weekly mean temperature during 1 December 2007 to 15 April 2009. Diarrhea prevalence was 1.50 times higher when the 3 weeks before the diarrhea recall period included [Formula: see text] (vs. 0 d) with rainfall of [Formula: see text] (95% CI: 1.12, 2.02), and 2.60 times higher (95% CI: 1.55, 4.36) for heavy rain weeks following a 60-d dry period. The [Formula: see text] prevalence in household water was not associated with heavy rain prior to sample collection.

CONCLUSIONS

The results suggest that, in rural Tamil Nadu, heavy rainfall may wash pathogens that accumulate during dry weather into child contact. Higher temperatures were positively associated with diarrhea 1-3 weeks later. Our findings suggest that diarrhea morbidity could worsen under climate change without interventions to reduce enteric pathogen transmission through multiple pathways. https://doi.org/10.1289/EHP3711.

Spatial, temporal, and spatiotemporal analysis of under-five diarrhea in Southern Ethiopia

Background

Despite improvements in prevention efforts, childhood diarrhea remains a public health concern. However, there may be substantial variation influenced by place, time, and season. Description of diarrheal clusters in time and space and understanding seasonal patterns can improve surveillance and management. The present study investigated the spatial and seasonal distribution and purely spatial, purely temporal, and space-time clusters of childhood diarrhea in Southern Ethiopia.

Methods

The study was a retrospective analysis of data from the Health Management Information System (HMIS) under-five diarrheal morbidity reports from July 2011 to June 2017 in Sidama Zone. Annual diarrhea incidence at district level was calculated. Incidence rate calculation and seasonal trend analysis were performed. The Kulldorff SaTScan software with a discrete Poisson model was used to identify statistically significant special, temporal, and space-time diarrhea clusters. ArcGIS 10.1 was used to plot the maps.

Results

A total of 202,406 under-five diarrheal cases with an annual case of 5822 per 100,000 under-five population were reported. An increasing trend of diarrhea incidence was observed over the 6 years with seasonal variation picking between February and May. The highest incidence rate (135.8/1000) was observed in the year 2016/17 in Boricha district. One statistically significant most likely spatial cluster (Boricha district) and six secondary clusters (Malga, Hulla, Aleta Wondo, Shebedino, Loka Abaya, Dale, and Wondogenet) were identified. One statistically significant temporal cluster (LLR = 2109.93, p < 0.001) during December 2013 to May 2015 was observed in all districts. Statistically significant spatiotemporal primary hotspot was observed in December 2012 to January 2015 in Malga district with a likelihood ratio of 1214.67 and a relative risk of 2.03. First, second, third, and fourth secondary hotspots occurred from January 2012 to May 2012 in Loka Abaya, December 2011 in Bursa, from March to April 2014 in Gorchie, and March 2012 in Wonsho districts.

Conclusion

Childhood diarrhea was not distributed randomly over space and time and showed an overall increasing trend of seasonal variation peaking between February and May. The health department and other stakeholders at various levels need to plan targeted interventional activities at hotspot seasons and areas to reduce morbidity and mortality.

Access to Household Water Quality Information Leads to Safer Water: A Cluster Randomized Controlled Trial in india

Household-specific feedback on the microbiological safety of drinking water may result in changes to water management practices that reduce exposure risks. We conducted a randomized, controlled trial in India to determine if information on household drinking water quality could change behavior and improve microbiological quality as indicated by Escherichia coli counts. We randomly assigned 589 participating households to one of three arms: (1) a messaging-only arm receiving messaging on safe water management ( n = 237); (2) a standard testing arm receiving the same messaging plus laboratory E. coli testing results specific to that household's drinking water ( n = 173); and (3) a test kit arm receiving messaging plus low-cost E. coli tests that could be used at the household's discretion ( n = 179). Self-reported water treatment increased significantly in both the standard testing arm and the test kit arm between baseline and follow-up one month later. Mean log₁₀ E. coli counts per 100 mL in household stored drinking water increased in the messaging-only arm from 1.42 to 1.87, while decreasing in the standard testing arm (1.38 to 0.89, 65% relative reduction) and the test kit arm (1.08 to 0.65, 76% relative reduction). Findings indicate that household-specific water quality information can improve both behaviors and drinking water quality.

Chemical, microbial and antibiotic susceptibility analyses of groundwater after a major flood event in Chennai

During floods, human exposure to pathogens through contaminated water leads to the outbreak of epidemic diseases. This research presents the first extensive assessment of surface and groundwater samples collected immediately after a flood (December 2015) and post-flood (April 2016) from the Adyar River of Chennai, a major city in India, for major ions, trace metals, bacterial population, and pathogens. Severe rains in a short period of time resulted in flooding which inundated the wells, allowing the entry of sewage contaminated river water into the groundwater zone. This has led to bacterial counts and chemical ions exceeding Bureau of Indian Standard's recommended limits in most flood affected areas. Pathogens isolated from the groundwater showed resistance to antibiotics, namely ceftriaxone, doxycycline and nalidixic acid. However, they were sensitive to chloramphenicol, ciprofloxacin, norfloxacin, and tetracycline. Determining the antibiotic susceptibility of pathogens will help in the treatment of humans affected by contaminated water through an appropriate selection of prescribed medication.

Hydrological Regime and Water Shortage as Drivers of the Seasonal Incidence of Diarrheal Diseases in a Tropical Montane Environment

BACKGROUND

The global burden of diarrhea is a leading cause of morbidity and mortality worldwide. In montane areas of South-East Asia such as northern Laos, recent changes in land use have induced increased runoff, soil erosion and in-stream suspended sediment loads, and potential pathogen dissemination. To our knowledge, few studies have related diarrhea incidences to catchment scale hydrological factors such as river discharge, and loads of suspended sediment and of Fecal Indicator Bacteria (FIB) such as Escherichia coli, together with sociological factors such as hygiene practices. We hypothesized that climate factors combined with human behavior control diarrhea incidence, either because higher rainfall, leading to higher stream discharges, suspended sediment loads and FIB counts, are associated with higher numbers of reported diarrhea cases during the rainy season, or because water shortage leads to the use of less safe water sources during the dry season. Using E. coli as a FIB, the objectives of this study were thus (1) to characterize the epidemiological dynamics of diarrhea in Northern Laos, and (2) to identify which hydro-meteorological and sociological risk factors were associated with diarrhea epidemics.

METHODS

Considering two unconnected river catchments of 22 and 7,448 km2, respectively, we conducted a retrospective time series analysis of meteorological variables (rainfall, air temperature), hydrological variables (discharge, suspended sediments, FIB counts, water temperature), and the number of diarrheal disease cases reported at 6 health centers located in the 5 southern districts of the Luang Prabang Province, Lao PDR. We also examined the socio-demographic factors potentially affecting vulnerability to the effect of the climate factors, such as drinking water sources, hygiene habits, and recreational water exposure.

RESULTS

Using thus a mixed methods approach, we found E. coli to be present all year long (100-1,000 Most Probable Number or MPN 100 mL-1) indicating that fecal contamination is ubiquitous and constant. We found that populations switch their water supply from wells to surface water during drought periods, the latter of which appear to be at higher risk of bacterial contamination than municipal water fountains. We thus found that water shortage in the Luang Prabang area triggers diarrhea peaks during the dry and hot season and that rainfall and aquifer refill ends the epidemic during the wet season. The temporal trends of reported daily diarrhea cases were generally bimodal with hospital admissions peaking in February-March and later in May-July. Annual incidence rates were higher in more densely populated areas and mostly concerned the 0-4 age group and male patients.

CONCLUSIONS

We found that anthropogenic drivers, such as hygiene practices, were at least as important as environmental drivers in determining the seasonal pattern of a diarrhea epidemic. For diarrheal disease risk monitoring, discharge or groundwater level can be considered as relevant proxies. These variables should be monitored in the framework of an early warning system provided that a tradeoff is found between the size of the monitored catchment and the frequency of the measurement.

Quantifying tap-to-household water quality deterioration in urban communities in Vellore, India: The impact of spatial assumptions

Municipal water sources in India have been found to be highly contaminated, with further water quality deterioration occurring during household storage. Quantifying water quality deterioration requires knowledge about the exact source tap and length of water storage at the household, which is not usually known. This study presents a methodology to link source and household stored water, and explores the effects of spatial assumptions on the association between tap-to-household water quality deterioration and enteric infections in two semi-urban slums of Vellore, India. To determine a possible water source for each household sample, we paired household and tap samples collected on the same day using three spatial approaches implemented in GIS: minimum Euclidean distance; minimum network distance; and inverse network-distance weighted average. Logistic and Poisson regression models were used to determine associations between water quality deterioration and household-level characteristics, and between diarrheal cases and water quality deterioration. On average, 60% of households had higher fecal coliform concentrations in household samples than at source taps. Only the weighted average approach detected a higher risk of water quality deterioration for households that do not purify water and that have animals in the home (RR=1.50 [1.03, 2.18], p=0.033); and showed that households with water quality deterioration were more likely to report diarrheal cases (OR=3.08 [1.21, 8.18], p=0.02). Studies to assess contamination between source and household are rare due to methodological challenges and high costs associated with collecting paired samples. Our study demonstrated it is possible to derive useful spatial links between samples post hoc; and that the pairing approach affects the conclusions related to associations between enteric infections and water quality deterioration.

Piped water consumption in Ghana: A case study of temporal and spatial patterns of clean water demand relative to alternative water sources in rural small towns

Continuous access to adequate quantities of safe water is essential for human health and socioeconomic development. Piped water systems (PWSs) are an increasingly common type of water supply in rural African small towns. We assessed temporal and spatial patterns in water consumption from public standpipes of four PWSs in Ghana in order to assess clean water demand relative to other available water sources. Low water consumption was evident in all study towns, which manifested temporally and spatially. Temporal variability in water consumption that is negatively correlated with rainfall is an indicator of rainwater preference when it is available. Furthermore, our findings show that standpipes in close proximity to alternative water sources such as streams and hand-dug wells suffer further reductions in water consumption. Qualitative data suggest that consumer demand in the study towns appears to be driven more by water quantity, accessibility, and perceived aesthetic water quality, as compared to microbiological water quality or price. In settings with chronic under-utilization of improved water sources, increasing water demand through household connections, improving water quality with respect to taste and appropriateness for laundry, and educating residents about health benefits of using piped water should be prioritized. Continued consumer demand and sufficient revenue generation are important attributes of a water service that ensure its function over time. Our findings suggest that analyzing water consumption of existing metered PWSs in combination with qualitative approaches may enable more efficient planning of community-based water supplies and support sustainable development.