Spatial and temporal patterns of diarrhoea in Bhutan 2003-2013

Meteorological factors association with under-five children diarrhea incidence in central Gondar zone, Northwest Ethiopia. A time series study

BACKGROUND

Under 5 children diarrhea has been one of the major public health concerns in countries with limited resources such as Ethiopia. Understanding the association between under-5 diarrhea and meteorological factors will contribute to safeguarding children from adverse health effects through early warning mechanisms. Thus, this study aimed to explore the association between under-5 diarrhea and meteorological factors to reduce health risks.

METHODS

A time-series ecological study was used to explore the association between meteorological factors and under-5 diarrhea incidence. Spearman's correlation was computed to test the correlation and a negative binomial regression model was fitted to determine the associations of meteorological factors with under-5 diarrhea incidence. The multicollinearity was checked using the variance inflation factor (VIF) before the multivariable regression analysis and the value was 5. aIRRs with 95% CIs and a significance level of 0.05 were used for all the statistical tests. Statistical analyses were conducted using STATA 14.2 software.

RESULTS

The highest under-5 diarrhea incidence morbidities was 180.9 per 1000 per year for under-five children. This study revealed a positive and negative correlation between the count of under-5 diarrhea and average monthly temperature and rainfall at 0 and 2 lag months with RRs of 1.0209 (95% CI: 1.0034-1.0387), RR 1.0202(95% CI:1.0022-1.0385), RR 0.999(95% CI:0.9985-0.9996), and RR 0.9992(95% CI:0.9987-0.9997) respectively.

CONCLUSION

There was an association between under 5 diarrhea incidence and meteorological factors in the Central Gondar Zone. The mean monthly temperature and rainfall were positively and negatively related to the incidence of diarrhea in children under 5 years old. The results showed that the observed association between meteorological factors and under-5 diarrhea incidence could be used as evidence for the use of early warning systems for the prevention of childhood diarrhea.

Spatiotemporal variation of under-5 children diarrhea incidence and associated meteorological factors in central Gondar zone, Northwest Ethiopia. A retrospective time series study

Under-5 children's diarrhea is a significant public health threat, and the World Health Organization (WHO) reported that it is the second leading cause of children's death worldwide. In this study area, little is known about the spatiotemporal distribution of under-5 children's diarrhea incidence rates. Therefore, this study was conducted to assess the spatiotemporal variation under-5 diarrhea incidence and associated meteorological factors in the Central Gondar Zone. The data for under-5 diarrhea were obtained from Central Gondar Zone Health Department diarrhea reports from January 2013 to December 2022. Climatic variables were obtained from the West Amhara Meteorological Agency. Every district was covered and given a geocode. The spatial data were created in ArcGIS 10.8.1. Global and local spatial autocorrelation were used to detect hot spots. The Poisson model, which applies the Kulldorff methods and SaTScan™9.6, was used to analyze the purely temporal, spatial, and space-time clusters. Spearman correlation and bivariate and multivariable negative binomial regressions were used to analyze the relationships between under-5 diarrhea cases and climatic factors. This study revealed spatial variation in the incidence of under-5 diarrhea, where Dembia, Gondar Zuria, and Chilga districts and Gondar Zuria, East Dembia, and Lay Armacho districts were high-rate spatial clusters between 2013 and 2018 and between 2019 and 2022, respectively. A temporal scan statistic identified 2014-2016 and 2020-2021 as risk periods across all districts. Spatiotemporal scan statistics revealed high-rate clusters in Dembia, Gondar Zuria, Chilga, Wegera, Alefa, Lay Armacho, and West Belesa between 2013 and 2018, and Gondar City, Gondar Zuria, East Dembia, Lay Armacho, and Alefa between 2019 and 2022. This study also revealed positive correlations between the number of individuals with under-5 diarrhea and the average monthly temperature at 0 and 2 lag months, with values of 1.0209 (1.0034-1.0387) and 1.0202 (1.0022-1.0385), respectively. In addition, there was a negative correlation between the number of under-5 diarrhea events and the average monthly rainfall at 0 and 2 lag months, with values of 0.999 (0.9985-0.9996) and 0.9992 (0.9987-0.9997), respectively. In conclusion, there has been spatiotemporal variability in the incidence of diarrhea in children under-5 years of age in the Central Gondar Zone. The mean monthly temperature and rainfall were positively and negatively related to the incidence of diarrhea in children under-5 years of age. Season-specific intervention strategies should be developed to reduce under-5 morbidity and mortality.

Impact of Climate Variability on Foodborne Diarrheal Disease: Systematic Review and Meta-Analysis

OBJECTIVE

To determine the impacts of climate variability on foodborne diarrhoeal disease worldwide.

METHODS

This work was performed based on PRISMA guideline. Articles were retrieved from the PubMed, MEDLINE, Web of Science, Scopus, DOAJ, and Google Scholar. The search was made using Boolean logic operators, medical subject headings, and main keywords related to foodborne diarrheal disease. STATA version 17 was used to perform an analysis. The quality of the articles was evaluated using Joanna Briggs Institute appraisal tools.

RESULTS

The present study included 54 articles with an estimates of 103 findings. An increases in temperature, relative humidity, precipitation, rainfall, and flooding were associated with 4% [RR: 1.04; 95% CI: 1.03, 1.05], 3% [RR: 1.03; 95% CI: 1.01, 1.06], 2% [RR: 1.02; 95% CI: 1.01, 1.03], 1% [RR: 1.01; 95% CI: 1.00, 1.02], and 42% [RR: 1.42; 95% CI: 1.26, 1.57] increases in foodborne diarrhoeal disease, respectively.

CONCLUSION

There was a significant association between foodborne diarrhoeal disease and climate variability, and indicate the need for building a climate-resilient food safety system to reduce foodborne diarrheal disease.

SYSTEMATIC REVIEW REGISTRATION

identifier CRD42024532430.

Short-term associations of diarrhoeal diseases in children with temperature and precipitation in seven low- and middle-income countries from Sub-Saharan Africa and South Asia in the Global Enteric Multicenter Study

BACKGROUND

Diarrhoeal diseases cause a heavy burden in developing countries. Although studies have described the seasonality of diarrhoeal diseases, the association of weather variables with diarrhoeal diseases has not been well characterized in resource-limited settings where the burden remains high. We examined short-term associations between ambient temperature, precipitation and hospital visits due to diarrhoea among children in seven low- and middle-income countries.

METHODOLOGY

Hospital visits due to diarrhoeal diseases under 5 years old were collected from seven sites in The Gambia, Mali, Mozambique, Kenya, India, Bangladesh, and Pakistan via the Global Enteric Multicenter Study from December 2007 to March 2011. Daily weather data during the same period were downloaded from the ERA5-Land. We fitted time-series regression models to examine the relationships of daily diarrhoea cases with daily ambient temperature and precipitation. Then, we used meta-analytic tools to examine the heterogeneity between the site-specific estimates.

PRINCIPAL FINDINGS

The cumulative relative risk (RR) of diarrhoea for temperature exposure (95th percentile vs. 1st percentile) ranged from 0.24 to 8.07, with Mozambique and Bangladesh showing positive associations, while Mali and Pakistan showed negative associations. The RR for precipitation (95th percentile vs. 1st percentile) ranged from 0.77 to 1.55, with Mali and India showing positive associations, while the only negative association was observed in Pakistan. Meta-analysis showed substantial heterogeneity in the association between temperature-diarrhoea and precipitation-diarrhoea across sites, with I2 of 84.2% and 67.5%, respectively.

CONCLUSIONS

Child diarrhoea and weather factors have diverse and complex associations across South Asia and Sub-Saharan Africa. Diarrhoeal surveillance system settings should be conceptualized based on the observed pattern of climate change in these locations.

Global Incidence of Diarrheal Diseases-An Update Using an Interpretable Predictive Model Based on XGBoost and SHAP: A Systematic Analysis

BACKGROUND

Diarrheal disease remains a significant public health issue, particularly affecting young children and older adults. Despite efforts to control and prevent these diseases, their incidence continues to be a global concern. Understanding the trends in diarrhea incidence and the factors influencing these trends is crucial for developing effective public health strategies.

OBJECTIVE

This study aimed to explore the temporal trends in diarrhea incidence and associated factors from 1990 to 2019 and to project the incidence for the period 2020-2040 at global, regional, and national levels. We aimed to identify key factors influencing these trends to inform future prevention and control strategies.

METHODS

The eXtreme Gradient Boosting (XGBoost) model was used to predict the incidence from 2020 to 2040 based on demographic, meteorological, water sanitation, and sanitation and hygiene indicators. SHapley Additive exPlanations (SHAP) value was performed to explain the impact of variables in the model on the incidence. Estimated annual percentage change (EAPC) was calculated to assess the temporal trends of age-standardized incidence rates (ASIRs) from 1990 to 2019 and from 2020 to 2040.

RESULTS

Globally, both incident cases and ASIRs of diarrhea increased between 2010 and 2019. The incident cases are expected to rise from 2020 to 2040, while the ASIRs and incidence rates are predicted to slightly decrease. During the observed (1990-2019) and predicted (2020-2040) periods, adults aged 60 years and above exhibited an upward trend in incidence rate as age increased, while children aged < 5 years consistently had the highest incident cases. The SHAP framework was applied to explain the model predictions. We identified several risk factors associated with an increased incidence of diarrhea, including age over 60 years, yearly precipitation exceeding 3000 mm, temperature above 20 °C for both maximum and minimum values, and vapor pressure deficit over 1500 Pa. A decreased incidence rate was associated with relative humidity over 60%, wind speed over 4 m/s, and populations with above 80% using safely managed drinking water services and over 40% using safely managed sanitation services.

CONCLUSIONS

Diarrheal diseases are still serious public health concerns, with predicted increases in the incident cases despite decreasing ASIRs globally. Children aged < 5 years remain highly susceptible to diarrheal diseases, yet the incidence rate in the older adults aged 60 plus years still warrants additional attention. Additionally, more targeted efforts to improve access to safe drinking water and sanitation services are crucial for reducing the incidence of diarrheal diseases globally.

Short-Term Effects of Climate Variability on Childhood Diarrhoea in Bangladesh: Multi-Site Time-Series Regression Analysis

The aim of this study was to estimate the effects of climate on childhood diarrhoea hospitalisations across six administrative divisions in Bangladesh and to provide scientific evidence for local health authorities for disease control and prevention. Fortnightly hospital admissions (August/2013-June/2017) for diarrhoea in children under five years of age, and fortnightly average maximum temperature, relative humidity and rainfall recordings for six administrative divisions were modelled using negative binomial regression with distributed lag linear terms. Flexible spline functions were used to adjust models for seasonality and long-term trends. During the study period, 25,385 diarrhoea cases were hospitalised. Overall, each 1 °C rise in maximum temperature increased diarrhoea hospitalisations by 4.6% (IRR = 1.046; 95% CI, 1.007-1.088) after adjusting for seasonality and long-term trends in the unlagged model. Using lagged effects of maximum temperature, and adjusting for relative humidity and rainfall for each of the six administrative divisions, the relationship between maximum temperature and diarrhoea hospitalisations varied between divisions, with positive and negative effect estimates. The temperature-diarrhoea association may be confounded by seasonality and long-term trends. Our findings are a reminder that the effects of climate change may be heterogeneous across regions, and that tailored diarrhoea prevention strategies need to consider region-specific recommendations rather than relying on generic guidelines.

A Systematic Review of Areal Units and Adjacency Used in Bayesian Spatial and Spatio-Temporal Conditional Autoregressive Models in Health Research

Advancements in Bayesian spatial and spatio-temporal modelling have been observed in recent years. Despite this, there are unresolved issues about the choice of appropriate spatial unit and adjacency matrix in disease mapping. There is limited systematic review evidence on this topic. This review aimed to address these problems. We searched seven databases to find published articles on this topic. A modified quality assessment tool was used to assess the quality of studies. A total of 52 studies were included, of which 26 (50.0%) were on infectious diseases, 10 (19.2%) on chronic diseases, 8 (15.5%) on maternal and child health, and 8 (15.5%) on other health-related outcomes. Only 6 studies reported the reasons for using the specified spatial unit, 8 (15.3%) studies conducted sensitivity analysis for prior selection, and 39 (75%) of the studies used Queen contiguity adjacency. This review highlights existing variation and limitations in the specification of Bayesian spatial and spatio-temporal models used in health research. We found that majority of the studies failed to report the rationale for the choice of spatial units, perform sensitivity analyses on the priors, or evaluate the choice of neighbourhood adjacency, all of which can potentially affect findings in their studies.

Identifying socio-ecological drivers of common cold in Bhutan: a national surveillance data analysis

The common cold is a leading cause of morbidity and contributes significantly to the health costs in Bhutan. The study utilized multivariate Zero-inflated Poisson regression in a Bayesian framework to identify climatic variability and spatial and temporal patterns of the common cold in Bhutan. There were 2,480,509 notifications of common cold between 2010 and 2018. Children aged < 15 years were twice (95% credible interval [CrI] 2.2, 2.5) as likely to get common cold than adults, and males were 12.4% (95 CrI 5.5%, 18.7%) less likely to get common cold than females. A 10 mm increase in rainfall lagged one month, and each 1 °C increase of maximum temperature was associated with a 5.1% (95% CrI 4.2%, 6.1%) and 2.6% (95% CrI 2.3%, 2.8%) increase in the risk of cold respectively. An increase in elevation of 100 m and 1% increase in relative humidity lagged three months were associated with a decrease in risk of common cold by 0.1% (95% CrI 0.1%, 0.2%) and 0.3% (95% CrI 0.2%, 0.3%) respectively. Seasonality and spatial heterogeneity can partly be explained by the association of common cold to climatic variables. There was statistically significant residual clustering after accounting for covariates. The finding highlights the influence of climatic variables on common cold and suggests that prioritizing control strategies for acute respiratory infection program to subdistricts and times of the year when climatic variables are associated with common cold may be an effective strategy.

Spatial patterns and climate drivers of malaria in three border areas of Brazil, Venezuela and Guyana, 2016-2018

In 2020, 77% of malaria cases in the Americas were concentrated in Venezuela, Brazil, and Colombia. These countries are characterized by a heterogeneous malaria landscape and malaria hotspots. Furthermore, the political unrest in Venezuela has led to significant cross-border population movement. Hence, the aim of this study was to describe spatial patterns and identify significant climatic drivers of malaria transmission along the Venezuela-Brazil-Guyana border, focusing on Bolivar state, Venezuela and Roraima state, Brazil. Malaria case data, stratified by species from 2016 to 2018, were obtained from the Brazilian Malaria Epidemiology Surveillance Information System, the Guyana Vector Borne Diseases Program, the Venezuelan Ministry of Health, and civil society organizations. Spatial autocorrelation in malaria incidence was explored using Getis-Ord (Gi*) statistics. A Poisson regression model was developed with a conditional autoregressive prior structure and posterior parameters were estimated using the Bayesian Markov chain Monte Carlo simulation with Gibbs sampling. There were 685,498 malaria cases during the study period. Plasmodium vivax was the predominant species (71.7%, 490,861). Malaria hotspots were located in eight municipalities along the Venezuela and Guyana international borders with Brazil. Plasmodium falciparum increased by 2.6% (95% credible interval [CrI] 2.1%, 2.8%) for one meter increase in altitude, decreased by 1.6% (95% CrI 1.5%, 2.3%) and 0.9% (95% CrI 0.7%, 2.4%) per 1 cm increase in 6-month lagged precipitation and each 1 °C increase of minimum temperature without lag. Each 1 °C increase of 1-month lagged maximum temperature increased P. falciparum by 0.6% (95% CrI 0.4%, 1.9%). P. vivax cases increased by 1.5% (95% CrI 1.3%, 1.6%) for one meter increase in altitude and decreased by  1.1% (95% CrI 1.0%, 1.2%) and 7.3% (95% CrI 6.7%, 9.7%) for each 1 cm increase of precipitation lagged at 6-months and 1 °C increase in minimum temperature lagged at 6-months. Each 1°C increase of two-month lagged maximum temperature increased P. vivax by 1.5% (95% CrI 0.6%, 7.1%). There was no significant residual spatial clustering after accounting for climatic covariates. Malaria hotspots were located along the Venezuela and Guyana international border with Roraima state, Brazil. In addition to population movement, climatic variables were important drivers of malaria transmission in these areas.

Aetiologies and Risk Factors of Prolonged Fever Admission in Samtse Hospital, Bhutan, 2020

Febrile illness is a common cause of hospital admission in developing countries, including Bhutan. Prolonged fever admission can add considerable strain on healthcare service delivery. Therefore, identifying the underlying cause of prolonged hospital stays can improve the quality of patient care by providing appropriate empirical treatment. Thus, the study’s aims were to evaluate the aetiologies and factors of prolonged fever admission in Samtse Hospital, Bhutan. Fever admission data from 1 January to 31 December 2020 were retrieved from the Samtse Hospital database. Prolonged hospital stay was defined as those with >5 days of hospital admission. Univariable and multivariable logistic regression was used to identify risk factors for a prolonged hospital stay. Of 290 records, 135 (46.6%) were children (≤12 years), 167 (57.6%) were males, and 237 (81.7%) patients were from rural areas. The common aetiologies for fever admissions were respiratory tract infection (85, 29.3%) and acute undifferentiated febrile illness (48, 16.6%). The prolonged stay was reported in 87 (30.0%) patients. Patients from rural areas (adjusted odds ratio [AOR] = 4.02, 95% CI = 1.58−10.24) and those with respiratory tract infections (AOR = 5.30, 95% CI = 1.11−25.39) and urinary tract infections and kidney disease (AOR = 8.16, 95% CI = 1.33−49.96) had higher odds of prolonged hospital stay. This epidemiological knowledge on prolonged hospital stay can be used by the physician for the management of fever admission in Samtse Hospital.

Effects of Climatic Factors on Diarrheal Diseases among Children below 5 Years of Age at National and Subnational Levels in Nepal: An Ecological Study

Introduction: The incidence of diarrhea, a leading cause of morbidity and mortality in low-income countries such as Nepal, is temperature-sensitive, suggesting it could be associated with climate change. With climate change fueled increases in the mean and variability of temperature and precipitation, the incidence of water and food-borne diseases are increasing, particularly in sub-Saharan Africa and South Asia. This national-level ecological study was undertaken to provide evidence linking weather and climate with diarrhea incidence in Nepal. Method: We analyzed monthly diarrheal disease count and meteorological data from all districts, spanning 15 eco-development regions of Nepal. Meteorological data and monthly data on diarrheal disease were sourced, respectively, from the Department of Hydrology and Meteorology and Health Management Information System (HMIS) of the Government of Nepal for the period from 2002 to 2014. Time-series log-linear regression models assessed the relationship between maximum temperature, minimum temperature, rainfall, relative humidity, and diarrhea burden. Predictors with p-values < 0.25 were retained in the fitted models. Results: Overall, diarrheal disease incidence in Nepal significantly increased with 1 °C increase in mean temperature (4.4%; 95% CI: 3.95, 4.85) and 1 cm increase in rainfall (0.28%; 95% CI: 0.15, 0.41). Seasonal variation of diarrheal incidence was prominent at the national level (11.63% rise in diarrheal cases in summer (95% CI: 4.17, 19.61) and 14.5% decrease in spring (95% CI: −18.81, −10.02) compared to winter season). Moreover, the effects of temperature and rainfall were highest in the mountain region compared to other ecological regions of Nepal. Conclusion: Our study provides empirical evidence linking weather factors and diarrheal disease burden in Nepal. This evidence suggests that additional climate change could increase diarrheal disease incidence across the nation. Mountainous regions are more sensitive to climate variability and consequently the burden of diarrheal diseases. These findings can be utilized to allocate necessary resources and envision a weather-based early warning system for the prevention and control of diarrheal diseases in Nepal.

Exploring the effect of the primary care health workers number on infectious diarrhea morbidity and where the health resources should go

We aimed to explore the association between the number of primary healthcare workers and infectious diarrhea morbidity at community levels and to provide evidence-based implications for optimizing primary healthcare manpower resource allocations. We collected annual infectious diarrhea morbidity and relevant data of 4321 communities in Sichuan Province, China, from 2017 to 2019. Global and local Moran’s I were calculated to detect the spatial clustering of infectious diarrhea morbidity and to identify areas where increased primary healthcare manpower resources should be allocated. The spatial lag fixed effects panel data model was adopted to explore the association between the number of primary healthcare workers per 1000 residents and infectious diarrhea morbidity. Significantly high–high and low–low clusters of infectious diarrhea cases were found to be mainly distributed in underdeveloped and developed areas during the studied period years, respectively. The infectious diarrhea morbidity was found to be statistically negatively associated with the number of primary healthcare workers per 1000 residents with a coefficient of − 0.172, indicating that a 0.172 reduction of infectious diarrhea morbidity (1/10,000) was associated with doubled amounts of primary healthcare workers per 1000 residents. Our findings highlighted the role of primary healthcare in the process of infectious diarrhea prevention and control, and implied that constant efforts should be addressed to facilitate infectious diarrhea prevention and control, especially in the underdeveloped areas.

Spatiotemporal patterns of diarrhea incidence in Ghana and the impact of meteorological and socio-demographic factors

BACKGROUND

Diarrhea remains a significant public health problem and poses a considerable financial burden on Ghana's health insurance scheme. In order to prioritize district-level hotspots of diarrhea incidence for effective targeted interventions, it is important to understand the potential drivers of spatiotemporal patterns of diarrhea. We aimed to identify the spatiotemporal heterogeneity of diarrhea incidence in Ghana and explore how meteorological and socio-demographic factors influence the patterns.

METHODS

We used monthly district-level clinically diagnosed diarrhea data between 2012 and 2018 obtained from the Centre for Health Information and Management of the Ghana Health Services. We utilized a hierarchical Bayesian spatiotemporal modeling framework to evaluate potential associations between district-level monthly diarrhea incidence and meteorological variables (mean temperature, diurnal temperature range, surface water presence) and socio-demographic factors (population density, Gini index, District League Table score) in Ghana. In addition, we investigated whether these associations were consistent across the four agro-ecological zones.

RESULTS

There was considerable spatial heterogeneity in diarrhea patterns across the districts, with clusters of high diarrhea risk areas mostly found in the transition and savannah zones. The average monthly temporal patterns of diarrhea revealed a weak biannual seasonality with major and minor peaks in June and October, respectively, coinciding with the major and minor rainy seasons. We found a significant association between both meteorological and socio-demographic factors and diarrhea risk, but the strength and direction of associations differed across the four agro-ecological zones. Surface water presence demonstrated consistently positive, while diurnal temperature range and population density demonstrated consistently negative associations with diarrhea both overall and across the agro-ecological zones.

CONCLUSIONS

Although overall diarrhea incidence is declining in Ghana, our results revealed high-risk districts that could benefit from district-specific tailored intervention strategies to improve control efforts. Ghana health sector policy-makers can use these results to assess the effectiveness of ongoing interventions at the district level and prioritize resource allocation for diarrhea control.

Associations Between Eight Earth Observation-Derived Climate Variables and Enteropathogen Infection: An Independent Participant Data Meta-Analysis of Surveillance Studies With Broad Spectrum Nucleic Acid Diagnostics

Diarrheal disease, still a major cause of childhood illness, is caused by numerous, diverse infectious microorganisms, which are differentially sensitive to environmental conditions. Enteropathogen-specific impacts of climate remain underexplored. Results from 15 studies that diagnosed enteropathogens in 64,788 stool samples from 20,760 children in 19 countries were combined. Infection status for 10 common enteropathogens-adenovirus, astrovirus, norovirus, rotavirus, sapovirus, Campylobacter, ETEC, Shigella, Cryptosporidium and Giardia-was matched by date with hydrometeorological variables from a global Earth observation dataset-precipitation and runoff volume, humidity, soil moisture, solar radiation, air pressure, temperature, and wind speed. Models were fitted for each pathogen, accounting for lags, nonlinearity, confounders, and threshold effects. Different variables showed complex, non-linear associations with infection risk varying in magnitude and direction depending on pathogen species. Rotavirus infection decreased markedly following increasing 7-day average temperatures-a relative risk of 0.76 (95% confidence interval: 0.69-0.85) above 28°C-while ETEC risk increased by almost half, 1.43 (1.36-1.50), in the 20-35°C range. Risk for all pathogens was highest following soil moistures in the upper range. Humidity was associated with increases in bacterial infections and decreases in most viral infections. Several virus species' risk increased following lower-than-average rainfall, while rotavirus and ETEC increased with heavier runoff. Temperature, soil moisture, and humidity are particularly influential parameters across all enteropathogens, likely impacting pathogen survival outside the host. Precipitation and runoff have divergent associations with different enteric viruses. These effects may engender shifts in the relative burden of diarrhea-causing agents as the global climate changes.

Spatio-temporal patterns of childhood pneumonia in Bhutan: a Bayesian analysis

Pneumonia is one of the top 10 diseases by morbidity in Bhutan. This study aimed to investigate the spatial and temporal trends and risk factors of childhood pneumonia in Bhutan. A multivariable Zero-inflated Poisson regression model using a Bayesian Markov chain Monte Carlo simulation was undertaken to quantify associations of age, sex, altitude, rainfall, maximum temperature and relative humidity with monthly pneumonia incidence and to identify the underlying spatial structure of the data. Overall childhood pneumonia incidence was 143.57 and 10.01 per 1000 persons over 108 months of observation in children aged < 5 years and 5–14 years, respectively. Children < 5 years or male sex were more likely to develop pneumonia than those 5–14 years and females. Each 1 °C increase in maximum temperature was associated with a 1.3% (95% (credible interval [CrI] 1.27%, 1.4%) increase in pneumonia cases. Each 10% increase in relative humidity was associated with a 1.2% (95% CrI 1.1%, 1.4%) reduction in the incidence of pneumonia. Pneumonia decreased by 0.3% (CrI 0.26%, 0.34%) every month. There was no statistical spatial clustering after accounting for the covariates. Seasonality and spatial heterogeneity can partly be explained by the association of pneumonia risk to climatic factors including maximum temperature and relative humidity.

Impact of Climate Change on Health and Well-Being of People in Hindu Kush Himalayan Region: A Narrative Review

Climate change and variability affect virtually everyone and every region of the world but the effects are nowhere more prominent than in mountain regions and people living therein. The Hindu Kush Himalayan (HKH) region is a vast expanse encompassing 18% of the world’s mountainous area. Sprawling over 4.3 million km², the HKH region occupies areas of eight countries namely Nepal, Bhutan, Afghanistan, Bangladesh, China, India, Myanmar, and Pakistan. The HKH region is warming at a rate higher than the global average and precipitation has also increased significantly over the last 6 decades along with increased frequency and intensity of some extreme events. Changes in temperature and precipitation have affected and will like to affect the climate-dependent sectors such as hydrology, agriculture, biodiversity, and human health. This paper aims to document how climate change has impacted and will impact, health and well-being of the people in the HKH region and offers adaptation and mitigation measures to reduce the impacts of climate change on health and well-being of the people. In the HKH region, climate change boosts infectious diseases, non-communicable diseases (NCDs), malnutrition, and injuries. Hence, climate change adaptation and mitigation measures are needed urgently to safeguard vulnerable populations residing in the HKH region.

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.

Spatio-temporal impact of self-financed rotavirus vaccination on rotavirus and acute gastroenteritis hospitalisations in the Valencia region, Spain

BACKGROUND

Several studies have shown a substantial impact of Rotavirus (RV) vaccination on the burden of RV and all-cause acute gastroenteritis (AGE). However, the results of most impact studies could be confused by a dynamic and complex space-time process. Therefore, there is a need to analyse the impact of RV vaccination on RV and AGE hospitalisations in a space-time framework to detect geographical-time patterns while avoiding the potential confusion caused by population inequalities in the impact estimations.

METHODS

A retrospective population-based study using real-world data from the Valencia Region was performed among children aged less than 3 years old in the period 2005-2016. A Bayesian spatio-temporal model was constructed to analyse RV and AGE hospitalisations and to estimate the vaccination impact measured in averted hospitalisations.

RESULTS

We found important spatio-temporal patterns in RV and AGE hospitalisations, RV vaccination coverage and in their associated adverted hospitalisations. Overall, ~ 1866 hospital admissions for RV were averted by RV vaccination during 2007-2016. Despite the low-medium vaccine coverage (~ 50%) in 2015-2016, relevant 36 and 20% reductions were estimated in RV and AGE hospitalisations respectively.

CONCLUSIONS

The introduction of the RV vaccines has substantially reduced the number of RV hospitalisations, averting ~ 1866 admissions during 2007-2016 which were space and time dependent. This study improves the methodologies commonly used to estimate the RV vaccine impact and their interpretation.

Diarrhea and associated factors among under-5 children in Ethiopia: A secondary data analysis

Objectives

Diarrhea is a major contributing factor for preventable childhood morbidity and death. Despite the occurrence of diarrhea is decreasing, its effect is increasing at an alarming rate among under-5 children particularly in developing countries. The survey was aimed to assess diarrhea and associated factors among children less than 5 years (0-59 months) in Ethiopia with nationally representative data.

Methods

The data were extracted from the Ethiopian National Survey of 2016. A logistic regression model was undertaken to identify the contributing factors for childhood diarrhea. Variables with p < 0.05 were considered as independent predictors of childhood diarrhea.

Results

From a total of 10,641 under-5 children, 5483(51.5%) were males and most of the children (62.3%) were above 24 months. About 10.2% had diarrhea 14 days before data collection, and the majority (93.1%) were born to married mothers. Receiving no treatment or advice for fever/cough (adjusted odd ratio (AOR) = 0.170, 95% confidence interval (CI): 0.139-0.208, p = 0.001), being permanent residence (AOR = 0.583, 95% CI: 0.347-0.982, p = 0.043), initiating breastfeeding after 24 h of birth (AOR = 1.553, 95% CI: 1.197-2.015, p = 0.001), and lack of prenatal care (AOR = 2.142, 95% CI: 0.624-0.875, p = 0.001) were independent predictors of diarrhea among under-5 children's in Ethiopia.

Conclusion

The result of this survey indicated that diarrhea is a significant health challenge among under-5 children. To tackle this illness, sufficient education on child and maternal health has to be provided for mothers focusing on predictive factors.

The effects of climate variability and seasonal influence on diarrhoeal disease in the tropical city-state of Singapore - A time-series analysis

BACKGROUND

Diarrhoeal disease is common and imposes substantial health and economic burdens across the globe, especially in the African and Southeast Asian regions. Besides causing high mortality and morbidity, diarrhoeal disease has also been associated with growth and cognitive shortfalls in children in low-resource settings. Extreme weather events brought about by climate change may increase diarrhoeal disease and impact vulnerable populations in countries regardless of levels of development. We examined the seasonal and climatic influences of acute diarrhoeal disease reports in Singapore, a city-state located in Southeast Asia.

METHODS

We used a time-series analysis, adjusting for time-varying potential confounders in a negative binomial regression model and fitting fractional polynomials to investigate the relationship between climatic factors (temperature, relative humidity and rainfall) and reported diarrhoeal disease.

RESULTS

We included 1,798,198 reports of diarrhoeal disease from 2005 to 2018. We observed annual trimodal peaks in the number of reports. Every 10% increase in relative humidity in the present week was positively associated with an increase in reports one week later [Incidence Rate Ratio (IRR): 1.030, 95% CI 1.004-1.057] and negatively associated with a decrease in reports six weeks later (IRR: 0.979, 95% CI 0.961-0.997). We observed effect modification of relative humidity on the risk of diarrhoeal disease in the first calendar quarter (January to March). There was weak evidence of a delayed effect of ambient air temperature on reports of diarrhoeal disease one week later (IRR: 1.013, 95% CI 0.998-1.027). No threshold effects of climatic factors were observed. Each week of school holidays was associated with a 14.4% reduction in diarrhoeal disease reports (IRR: 0.856, 95% CI: 0.840 to 0.871). Public holidays were associated with a reduction in reports in the same week and an increase a week later.

CONCLUSIONS

Diarrhoeal disease is highly seasonal and is associated with climate variability. Food safety and primary healthcare resource mitigation could be timed in anticipation of seasonal and climate driven increases in disease reports.

Diarrhea in under Five Year-Old Children in Nepal: A Spatiotemporal Analysis Based on Demographic and Health Survey Data

Background: Diarrhea in children under five years of age remains a challenge in reducing child mortality in Nepal. Understanding the spatiotemporal patterns and influencing factors of the disease is important for control and intervention. Methods: Data regarding diarrhea prevalence and its potential influencing factors were extracted from the Demographic and Health Surveys in Nepal and other open-access databases. A Bayesian logistic regression model with district-specific spatio-temporal random effects was applied to explore the space and time patterns of diarrhea risk, as well as the relationships between the risk and the potential influencing factors. Results: Both the observed prevalence and the estimated spatiotemporal effects show a decreasing diarrhea risk trend from 2006 to 2016 in most districts of Nepal, with a few exceptions, such as Achham and Rasuwa. The disease risk decreased with mothers’ years of education (OR 0.93, 95% Bayesian Credible Interval (BCI) 0.87, 0.997). Compared to spring, autumn and winter had lower risks of diarrhea. The risk firstly increased and then decreased with age and children under 12–24 months old were the highest risk group (OR 1.20, 95% BCI 1.04, 1.38). Boys had higher risk than girls (OR 1.24, 95% BCI 1.13, 1.39). Even though improved sanitation wasn’t found significant within a 95% BCI, there was 93.2% of chance of it being a protective factor. There were no obvious spatiotemporal clusters among districts and each district tended to have its own spatiotemporal diarrhea prevalence pattern. Conclusions: The important risk factors identified by our Bayesian spatial-temporal modeling provide insights for control and intervention on children diarrhea in Nepal. Special attention should be paid to high risk groups of children and high risk seasons, as well as districts with high risk or increased trend of risk. Effective actions should be implemented to improve sanitation and women’s education level. District-specific control planning is recommended for local governments for effective control of children diarrhea in Nepal.

Epidemiology of infectious diarrhoea and the relationship with etiological and meteorological factors in Jiangsu Province, China

We depicted the epidemiological characteristics of infectious diarrhoea in Jiangsu Province, China. Generalized additive models were employed to evaluate the age-specific effects of etiological and meteorological factors on prevalence. A long-term increasing prevalence with strong seasonality was observed. In those aged 0–5 years, disease risk increased rapidly with the positive rate of virus (rotavirus, norovirus, sapovirus, astrovirus) in the 20–50% range. In those aged > 20 years, disease risk increased with the positive rate of adenovirus and bacteria (Vibrio parahaemolyticus, Salmonella, Escherichia coli, Campylobacter jejuni) until reaching 5%, and thereafter stayed stable. The mean temperature, relative humidity, temperature range, and rainfall were all related to two-month lag morbidity in the group aged 0–5 years. Disease risk increased with relative humidity between 67–78%. Synchronous climate affected the incidence in those aged >20 years. Mean temperature and rainfall showed U-shape associations with disease risk (with threshold 15 °C and 100 mm per month, respectively). Meanwhile, disease risk increased gradually with sunshine duration over 150 hours per month. However, no associations were found in the group aged 6–19 years. In brief, etiological and meteorological factors had age-specific effects on the prevalence of infectious diarrhoea in Jiangsu. Surveillance efforts are needed to prevent its spread.

Bayesian spatial analysis of cholangiocarcinoma in Northeast Thailand

Cholangiocarcinoma (CCA) is a malignant neoplasm of the biliary tract. Thailand reports the highest incidence of CCA in the world. The aim of this study was to map the distribution of CCA and identify spatial disease clusters in Northeast Thailand. Individual-level data of patients with histopathologically confirmed CCA, aggregated at the sub-district level, were obtained from the Cholangiocarcinoma Screening and Care Program (CASCAP) between February 2013 and December 2017. For analysis a multivariate Zero-inflated, Poisson (ZIP) regression model was developed. This model incorporated a conditional autoregressive (CAR) prior structure, with posterior parameters estimated using Bayesian Markov chain Monte Carlo (MCMC) simulation with Gibbs sampling. Covariates included in the models were age, sex, normalized vegetation index (NDVI), and distance to water body. There was a total of 1,299 cases out of 358,981 participants. CCA incidence increased 2.94 fold (95% credible interval [CrI] 2.62–3.31) in patients >60 years as compared to ≤60 years. Males were 2.53 fold (95% CrI: 2.24–2.85) more likely to have CCA when compared to females. CCA decreased with a 1 unit increase of NDVI (Relative Risk =0.06; 95% CrI: 0.01–0.63). When posterior means were mapped spatial clustering was evident after accounting for the model covariates. Age, sex and environmental variables were associated with an increase in the incidence of CCA. When these covariates were included in models the maps of the posterior means of the spatially structured random effects demonstrated evidence of spatial clustering.

A retrospective mixed-methods evaluation of a national ORS and zinc scale-up program in Uganda between 2011 and 2016

Background

In Uganda, diarrhoea was the third leading cause of mortality among children under the age of five in 2010. To address this issue, the Ministry of Health (MOH) formed a national Diarrhoea and Pneumonia Coordination Committee (DPCC) in 2011. One of the objectives of the DPCC for reducing diarrhoea mortality was to increase the use of oral rehydration salts (ORS) and zinc. This study aimed to describe and evaluate efforts by the DPCC to increase ORS and zinc coverage.

Methods

We conducted a retrospective mixed-methods evaluation to describe the activities conducted under the DPCC and evaluate the extent to which the committee’s goal of increasing ORS and zinc use was achieved. We conducted secondary analysis using Uganda’s Demographic and Health Survey from 2011 and 2016, analyzed cross-sectional private medicine outlet surveys from 2014 and 2016, analyzed ORS and zinc distribution data from the Uganda National Medical Stores, and reviewed program documents from DPCC partners.

Results

Nationally, the proportion of children under five with diarrhoea treated with ORS and zinc increased from 1% (95% confidence interval (CI) = 1%, 2%) in 2011 to 30% (95% CI = 27%, 32%) in 2016. Among private medicine outlets, the adjusted odds of having any zinc in-stock was 1.5 (95% CI = 1.14, 1.97) times higher in 2016 than in 2014, and the retail price for a complete treatment (2 ORS sachets and 10 zinc tablets) declined by $0.19 (95% CI = -0.31, -0.06), or 14%.

Conclusions

Use of combined ORS and zinc for treatment of diarrhoea in children under five significantly increased in Uganda during the program period. The range of activities conducted by the various members of the DPCC likely contributed to the increase in the use of combined ORS and zinc.

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.

Spatial patterns and effects of air pollution and meteorological factors on hospitalization for chronic lung diseases in Beijing, China

Chronic obstructive pulmonary disease (COPD), lung cancer (LC) and tuberculosis (TB) are common chronic lung diseases that generate a large disease burden and significant health care resource use in China. The aim of this study was to quantify spatial patterns and effects of air pollution and meteorological factors on hospitalization of COPD, LC and TB in Beijing. Daily counts of hospitalization for 2010 were obtained from the Beijing Urban Employees Basic Medical Insurance (UEBMI) system. Bayesian hierarchical Poisson regression models were applied to identify spatial patterns of hospitalization for COPD, LC and TB at the district level and explore associations with inhalable particulate matter (aerodynamic diameter <10 μm, PM₁₀), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), mean temperature and relative humidity. There were 18,882, 14,295 and 2,940 counts of hospitalizations for COPD, LC and TB respectively, in Beijing in 2010. Clusters of high relative risk were in different locations for the three diseases. The effect of relative humidity on COPD hospitalization was most significant with a relative risk (RR) of 1.070 (95%CI: 1.054, 1.086) per one percent increase. For lung cancer hospitalization, exposure to ambient SO₂ was associated with a RR of 1.034 (95%CI: 1.011, 1.058) per μg m^-3 increase. For tuberculosis, the effect of mean temperature was significant with a RR of 1.107 (95%CI: 1.038, 1.180) per °C increase. Risk factors and spatial patterns were different for hospitalization of non-infectious and infectious chronic lung disease in Beijing. Even over a short time period (one year), associations were apparent with air pollution and meteorological factors.