Effect of climatic variability on childhood diarrhea and its high risk periods in northwestern parts of Ethiopia

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.

Genomic characterization of norovirus and Sapovirus from a diarrhea outbreak in a school linked to heavy rainfall

Background

Diarrhea poses a serious threat to human health, and rainfall is known to increase the incidence of diarrheal diseases. On July 7, 2024, a diarrhea outbreak occurred in a school in Sishui County, Jining City, Shandong Province, China, following heavy rainfall. This study aimed to identify the pathogens responsible for the outbreak and characterize their whole genomes.

Methods

On July 8, 2024, a total of 21 stool samples from diarrhea cases, 2 water samples from private wells, and 1 drinking water sample from the school cafeteria were collected. Real-time quantitative PCR was used to detect Rotavirus A (RV-A), Norovirus genogroup I (NV GI), Norovirus genogroup II (NV GII), Sapovirus (SaV), Human Astrovirus (HAstV), and Human Adenovirus (HAdV). Whole-genome sequencing was performed for NV GI and SaV-positive samples to determine their genotypes, construct phylogenetic trees, and analyze amino acid variation sites in encoded proteins.

Results

Among the 21 case stool samples, 7 tested positive for both NV GI and SaV, 10 were positive for NV GI only, and 1 was positive for SaV only. Of the 2 private well water samples, one was positive for NV GI and the other for SaV. Whole-genome sequences were obtained for 11 NV GI strains and 2 SaV strains. The 11 NV GI sequences from the outbreak exhibited high homology, with whole-genome similarity ranging from 99.96% to 100%, and were all identified as the NV GI.6 [P11] genotype. Phylogenetic analysis showed that these 11 sequences clustered within the same evolutionary branch. Similarly, the 2 SaV sequences were highly homologous, with 99.97% similarity, and were identified as the SaV GI.6 genotype, clustering within the same phylogenetic branch.

Conclusions

This diarrhea outbreak was caused by the combined presence of NV GI and SaV following heavy rainfall. These findings provide valuable reference data for the prevention and control of diarrhea outbreaks caused by heavy rainfall or multiple pathogens.

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.

Prevalence and associated factors of norovirus infections among patients with diarrhea in the Amhara national regional state, Ethiopia

BACKGROUND

Noroviruses (NoVs) are the leading cause of diarrheal disease among all age groups worldwide, with an increased burden in developing countries. As there is no surveillance, epidemiological data is limited in Ethiopia. Hence, this study aimed to investigate the prevalence and associated factors of NoV infection among patients with diarrhea in the Amhara National Regional State, Ethiopia.

METHODS

A prospective health facility-based cross-sectional study was conducted from May 2021 to November 2021. A total of 550 study participants of all age groups with symptoms of diarrhea were proportionately assigned to the four study areas, area with three health facilities. Study participants were systematically sampled in each health facility. A fecal sample from each case was collected. The RNA was extracted and tested for NoV by one-step RT-PCR. Sociodemographic and other variables were gathered using a pre-tested questionnaire. A descriptive analysis was performed. Both binary and multiple logistic regressions were utilized to identify factors associated with NoV infection. Variables with a p-value < 0.05 in the final model were considered statistically significant.

RESULTS

Five hundred nineteen out of 550 samples were analyzed (94.4% response rate). The overall prevalence of NoV was 8.9% (46/519). The positivity rates were higher among the elderly (33.3%) and under-5 children (12.5%). Both genogroup I and genogroup II (GII) were identified, with GII being the predominant, at 82.6% (38/46). Of all participants, only 20% reported a history of vomiting. Norovirus infection was more prevalent among participants from Debre Tabor (AOR = 4, 95%CI: 1.2-14) and Bahir Dar areas (AOR = 3.6, 95%CI: 1.04-11) compared to Debre Markos. Additionally, older adults (AOR = 7, 95% CI: 2-24) and under-5 children (AOR = 3.5, 95% CI: 2.8-12) were disproportionately affected compared to adults. The previous history of diarrhea (AOR = 3.6, 95% CI: 1.7-7) was a significant factor contributing to NoV infections. Moreover, the odds of NoV infection were higher among individuals with a high frequency of diarrhea (AOR = 15.3, 95%CI: 7.6-43) and vomiting (AOR = 3.5, 95%CI: 1.5-8).

CONCLUSIONS

The prevalence of NoV was considerably high, with the predominance of NoV-GII. The positivity rate was higher among the extreme age groups and varied across the study areas. To obtain a comprehensive understanding of the virus`s epidemiology and its genetic diversity, further research is warranted.

Is heat wave a predictor of diarrhoea in Dhaka, Bangladesh? A time-series analysis in a South Asian tropical monsoon climate

While numerous studies have assessed the association between temperature and diarrhoea in various locations, evidence of relationship between heat wave and diarrhoea is scarce. We defined elevated daily mean and maximum temperature over the 95th and 99th percentiles lasting for at least one day between March to October 1981-2010 as TAV95 and TAV99 and D95 and D99 heat wave, respectively. We investigated the association between heat wave and daily counts of hospitalisations for all-cause diarrhoea in Dhaka, Bangladesh using time series regression analysis employing constrained distributed lag-linear models. Effects were assessed for all ages and children aged under 5 years of age. Diarrhoea hospitalisation increased by 6.7% (95% CI: 4.6%- 8.9%), 8.3% (3.7-13.1), 7.0 (4.8-9.3) and 7.4 (3.1-11.9) in all ages on a TAV95, TAV99, D95 and D99 heat wave day, respectively. These effects were more pronounced for under-5 children with an increase of 13.9% (95% CI: 8.3-19.9), 24.2% (11.3-38.7), 17.0 (11.0-23.5) and 19.5 (7.7-32.6) in diarrhoea hospitalisations on a TAV95, TAV99, D95 and D99 heat wave day, respectively. At lags of 3 days, we noticed a negative association indicating a 'harvesting' effect. Our findings suggest that heat wave was a significant risk factor for diarrhoea hospitalisation in Dhaka. Further research is needed to elucidate the causal pathways and identify the preventive measures necessary to mitigate the impacts of heat waves on diarrhoea. Given that no heat wave definitions exist for Dhaka, these results may help to define heat waves for Dhaka and trigger public health interventions including heat alerts to prevent heat-related morbidity in Dhaka, Bangladesh.

Impacts of climate change on diarrhoeal disease hospitalisations: How does the global warming targets of 1.5-2°C affect Dhaka, Bangladesh?

Dhaka is one of the world's densely populated cities and faces significant public health challenges including high burden of diarrhoeal diseases. Climate change is intensifying existing environmental problems including urban heat island effect and poor water quality. While numerous epidemiological studies have linked meteorological factors to diarrhoeal diseases in Bangladesh, assessment of the impacts of future climate change on diarrhoeal diseases is scarce. We provide the assessment of climate change impacts on diarrhoeal disease in Dhaka and project future health risks under climate change scenarios. About 3 million acute diarrhoea cases presenting to the Dhaka Hospital of the International Centre for Diarrhoeal Disease Research Bangladesh (icddr,b) during 1981-2010 were linked to daily temperature, rainfall and humidity and association investigated using time series adapted negative binomial regression models employing constrained distributed lag linear models. The findings were applied to climate projections to estimate future risks of diarrhoea under various global warming scenarios. There was a significantly raised risk of diarrhoea hospitalisation in all ages with daily mean temperature (RR: 3.4, 95% CI: 3.0-3.7) after controlling for the confounding effects of heavy rainfall, humidity, autocorrelations, day of the week effect, long-term time, and seasonal trends. Using the incidence rate ratio (IRR) of 1.034, temperature increases based on the global warming targets of 1.5-2°C could result in an increase of diarrhoea hospitalisations by 4.5-7.4% in all age groups by the 2100s. These effects were more pronounced among <5 children where the predicted temperature increases could raise diarrhoea hospitalisation by 5.7% - 9.4%. Diarrhoea hospitalisation will increase significantly in Dhaka even if the global warming targets adopted by the Paris Agreement is reached. This underscores the importance of preparing the city for management and prevention of diarrhoeal diseases.

Predictive modeling and socioeconomic determinants of diarrhea in children under five in the Amhara Region, Ethiopia

Background

Diarrheal disease, characterized by high morbidity and mortality rates, continues to be a serious public health concern, especially in developing nations such as Ethiopia. The significant burden it imposes on these countries underscores the importance of identifying predictors of diarrhea. The use of machine learning techniques to identify significant predictors of diarrhea in children under the age of 5 in Ethiopia's Amhara Region is not well documented. Therefore, this study aimed to clarify these issues.

Methods

This study's data have been extracted from the Ethiopian Population and Health Survey. We have applied machine learning ensemble classifier models such as random forests, logistic regression, K-nearest neighbors, decision trees, support vector machines, gradient boosting, and naive Bayes models to predict the determinants of diarrhea in children under the age of 5 in Ethiopia. Finally, Shapley Additive exPlanation (SHAP) value analysis was performed to predict diarrhea.

Result

Among the seven models used, the random forest algorithm showed the highest accuracy in predicting diarrheal disease with an accuracy rate of 81.03% and an area under the curve of 86.50%. The following factors were investigated: families who had richest wealth status (log odd of -0.04), children without a history of Acute Respiratory Infections (ARIs) (log odd of -0.08), mothers who did not have a job (log odd of -0.04), children aged between 23 and 36 months (log odd of -0.03), mothers with higher education (log odds ratio of -0.03), urban dwellers (log odd of -0.01), families using electricity as cooking material (log odd of -0.12), children under 5 years of age living in the Amhara region of Ethiopia who did not show signs of wasting, children under 5 years of age who had not taken medications for intestinal parasites unlike their peers and who showed a significant association with diarrheal disease.

Conclusion

We recommend implementing programs to reduce the incidence of diarrhea in children under the age of 5 in the Amhara region. These programs should focus on removing socioeconomic barriers that impede mothers' access to wealth, a favorable work environment, cooking fuel, education, and healthcare for their children.

Detection of spatial, temporal and spatiotemporal distribution of diarrhea incidence among under-five children in Central Gondar zone, Northwest Ethiopia: a time-series study (2019-2022)

Under-five children's diarrhea is a significant public health threat and the World Health Organization (WHO) reported it as the second leading cause of children's death worldwide. In this study area, little is known about the spatiotemporal distribution of under-5 diarrhea incidence. This study was therefore, conducted among all districts in the Central Gondar zone to assess the spatial, temporal, and spatiotemporal variation in diarrhea incidence among under-five children in the Central Gondar zone. The data for children under 5 years of age with diarrhea was obtained from Central Gondar Zone Health Department diarrhea reports from January 2019 to December 2022. All districts were included and geo-coded. The spatial data were created in ArcGIS 10.8.1. Global and local spatial autocorrelation were used to detect hot spots and cold spots. The Poisson model was generated by applying the Kulldorff method in SaTScan™9.6 to analyse the the purely temporal, spatial, and space-time clusters. The study revealed spatial variation of under-5 diarrhea where Gondar City, Gondar Zuria, East Dembia, and Lay Armacho districts were the high-rate spatial clusters during the study period. A year search window for temporal scan statistic identified 01 January 2020-30 December 2021 as risk periods across all districts. Spatiotemporal scan statistics detected high-rate clusters at Gondar City, Gondar Zuria, East Dembia, Lay Armacho, and Alefa between 2019 and 2022. In conclusion, there has been a spatial, temporal, and spatiotemporal variability of under-5 children's diarrhea in the Central Gondar Zone. Interventional and preventive strategies should be developed and given priority to the areas that has been detected as a hotspot in this study to reduce the mortality and morbidity of under 5 children.

Prevalence and correlates of diarrhoea among children under five in selected coastal communities in Ghana

INTRODUCTION

Diarrhoea is a preventable disease affecting children under five years disproportionately. Globally, thousands of children die from diarrhoea related diseases each year, most deaths occuring in sub-Saharan Africa where Ghana is located. Coastal communities bear the greatest brunt due to poor sanitary conditions. We assess the prevalence of diarrhoea in selected coastal communities along the eastern coast of Ghana.

METHODS

We conducted a cross-sectional study in Mumford, Opetekwei, Anyako, Anyauni and Ateteti communities in the Central, Greater Accra and Volta region respectively. We interviewed households with children under five years on the occurrence of diarrhoea and health seeking practices. We also used a checklist to assess the sanitary conditions of the household. Frequencies and proportions were generated. We determined significant differences using modified Poisson regression models at p < 0.05. Results were presented in tables and text.

RESULTS

The prevalence ratio of diarrhoea was 36% (95% CI 33-40%). Most cases were from Anyako community. All interviewed households in Mumford and Opetekwei used improved water sources whiles 94% in Atetetio used improved water sources. Children who were fully vaccinated had 32% lower prevalence of diarrhoea compared to those who were not (aPR: 0.68, 95% CI 0.55-0.84).

CONCLUSION

Diarrhoea prevalence was high inspite of the reported use of improved water sources and sanitation facilities by majority of households in the communities. Fully vaccinated children had a relatively lower prevalence of diarrhoea compared to children who were not fully vaccinated. We recommend in-depth analysis of the use of water and sanitation facilities in these settings to understand the reasons for the observed diarrhoea prevalence.

Genetic diversity and distribution of noroviruses among all age groups of patients with diarrhea in Amhara National Regional State, Ethiopia

BACKGROUND

Norovirus (NoV) is the leading cause of diarrheal disease worldwide and the impact is high in developing countries, including Ethiopia. Moreover, there is a significant and fluctuating global genetic diversity that varies across diverse environments over time. Nevertheless, there is a scarcity of data on the genetic diversity of NoV in Ethiopia.

OBJECTIVE

This study was aimed to assess the genetic diversity and distribution of NoVs circulating in the Amhara National Regional State, Ethiopia, by considering all age groups.

METHODS

A total of 519 fecal samples were collected from diarrheal patients from May 01/2021 to November 30/ 2021. The fecal samples were screened for the presence of NoVs using real-time RT-PCR by targeting a portion of the major capsid protein coding region. The positive samples were further amplified using conventional RT-PCR, and sequenced.

RESULTS

The positivity rate of NoV was (8.9%; 46/519). The detection rate of NoV genogroup II (GII) and genogroup I (GI) was 38 (82.6%) and 8 (17.4%), respectively. Overall, five distinct GII (GII.3, GII.6, GII.10, GII.17, and GII.21) and two GI (GI.3 and GI.5) genotypes were detected. Within the GII types, GII.3 was the predominant (34.2%) followed by GII.21 (15.8%), GII.17 (10.5%), GII.6 and GII.10 each (2.6%). Norovirus GII.21 is reported for the first time in Ethiopia. The genetic diversity and distribution of NoVs were significantly different across the four sampling sits and age groups. The phylogenetic analysis revealed close relatedness of the current strains with published strains from Ethiopia and elsewhere.

CONCLUSION

The distribution and genetic diversity of NoV was considerably high, with predominance of non-GII.4 genotypes. The GII.21 genotype is a new add on the growing evidences on the genetic diversity of NoVs in Ethiopia. Future nationwide surveillance studies are necessary to gain comprehensive data in Ethiopia.

Advancements in Predictive Microbiology: Integrating New Technologies for Efficient Food Safety Models

Predictive microbiology is a rapidly evolving field that has gained significant interest over the years due to its diverse application in food safety. Predictive models are widely used in food microbiology to estimate the growth of microorganisms in food products. These models represent the dynamic interactions between intrinsic and extrinsic food factors as mathematical equations and then apply these data to predict shelf life, spoilage, and microbial risk assessment. Due to their ability to predict the microbial risk, these tools are also integrated into hazard analysis critical control point (HACCP) protocols. However, like most new technologies, several limitations have been linked to their use. Predictive models have been found incapable of modeling the intricate microbial interactions in food colonized by different bacteria populations under dynamic environmental conditions. To address this issue, researchers are integrating several new technologies into predictive models to improve efficiency and accuracy. Increasingly, newer technologies such as whole genome sequencing (WGS), metagenomics, artificial intelligence, and machine learning are being rapidly adopted into newer-generation models. This has facilitated the development of devices based on robotics, the Internet of Things, and time-temperature indicators that are being incorporated into food processing both domestically and industrially globally. This study reviewed current research on predictive models, limitations, challenges, and newer technologies being integrated into developing more efficient models. Machine learning algorithms commonly employed in predictive modeling are discussed with emphasis on their application in research and industry and their advantages over traditional models.

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.

Rotavirus and bacterial diarrhoea among children in Ile-Ife, Nigeria: Burden, risk factors and seasonality

BACKGROUND

Diarrhoea is a leading cause of death among under-five children globally, with sub-Saharan Africa alone accounting for 1/3 episodes yearly. Viruses, bacteria and parasites may cause diarrhoea. Rotavirus is the most common viral aetiology of diarrhoea in children less than five years globally. In Nigeria, there is scarce data on the prevalence/importance, burden, clinical/risk factors and seasonality of rotavirus and bacteria and this study aims to determine the role of rotavirus and bacteria on diarrhoea cases in children less than five years in Ile-Ife, Nigeria.

METHODS

Socio-demographic data, environmental/risk factors and diarrhoiec stool samples were collected from children less than five years presenting with acute diarrhoea. Rotavirus was identified using ELISA. Bacteria pathogens were detected using cultural technique and typed using PCR. Diarrhoeagenic E. coli (DEC) isolates were subjected to antimicrobial susceptibility testing. Pathogen positive and negative samples were compared in terms of gender, age-group, seasonal distribution, and clinical/risk factors using chi-square with two-tailed significance. SPSS version 20.0.1 for Windows was used for statistical analysis.

RESULTS

At least one pathogen was detected from 63 (60.6%) children having gastroenteritis while 28 (44.4%) had multiple infections. Rotavirus was the most detected pathogen. Prevalence of rotavirus mono-infection was 22%, multiple infection with bacteria was 45%. Mono-infection prevalence of DEC, Shigella spp., and Salmonella spp. were 5.8% (6/104), 5.8% (6/104), and 2.9% (3/104) and co-infection with RVA were 23.1% (24/104), 21.2% (22/104) and 10.6% (11/104) respectively. All rotaviral infections were observed in the dry season. The pathotypes of DEC detected were STEC and EAEC. Parent earnings and mid-upper arm circumference measurement have statistical correlation with diarrhoea (p = 0.034; 0.035 respectively).

CONCLUSION

In this study, rotavirus was more prevalent than bacteria and occurred only in the dry season. Among bacteria aetiologies, DEC was the most common detected. Differences in seasonal peaks of rotavirus and DEC could be employed in diarrhoea management in Nigeria and other tropical countries to ensure optimal limited resources usage in preventing diarrhoea transmission and reducing indiscriminate use of antibiotics.

Understanding diarrhoeal diseases in response to climate variability and drought in Cape Town, South Africa: a mixed methods approach

BACKGROUND

The climate of southern Africa is expected to become hotter and drier with more frequent severe droughts and the incidence of diarrhoea to increase. From 2015 to 2018, Cape Town, South Africa, experienced a severe drought which resulted in extreme water conservation efforts. We aimed to gain a more holistic understanding of the relationship between diarrhoea in young children and climate variability in a system stressed by water scarcity.

METHODS

Using a mixed-methods approach, we explored diarrhoeal disease incidence in children under 5 years between 2010 to 2019 in Cape Town, primarily in the public health system through routinely collected diarrhoeal incidence and weather station data. We developed a negative binomial regression model to understand the relationship between temperature, precipitation, and relative humidity on incidence of diarrhoea with dehydration. We conducted in-depth interviews with stakeholders in the fields of health, environment, and human development on perceptions around diarrhoea and health-related interventions both prior to and over the drought, and analysed them through the framework method.

RESULTS

From diarrhoeal incidence data, the diarrhoea with dehydration incidence decreased over the decade studied, e.g. reduction of 64.7% in 2019 [95% confidence interval (CI): 5.5-7.2%] compared to 2010, with no increase during the severe drought period. Over the hot dry diarrhoeal season (November to May), the monthly diarrhoea with dehydration incidence increased by 7.4% (95% CI: 4.5-10.3%) per 1 °C increase in temperature and 2.6% (95% CI: 1.7-3.5%) per 1% increase in relative humidity in the unlagged model. Stakeholder interviews found that extensive and sustained diarrhoeal interventions were perceived to be responsible for the overall reduction in diarrhoeal incidence and mortality over the prior decade. During the drought, as diarrhoeal interventions were maintained, the expected increase in incidence in the public health sector did not occur.

CONCLUSIONS

We found that that diarrhoeal incidence has decreased over the last decade and that incidence is strongly influenced by local temperature and humidity, particularly over the hot dry season. While climate change and extreme weather events especially stress systems supporting vulnerable populations such as young children, maintaining strong and consistent public health interventions helps to reduce negative health impacts.

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.

Exploring the Association between Ambient Temperature and Daily Hospital Admissions for Diarrhea in Mopani District, Limpopo Province, South Africa

Diarrhea contributes significantly to global morbidity and mortality. There is evidence that diarrhea prevalence is associated with ambient temperature. This study aimed to determine if there was an association between ambient temperature and diarrhea at a rural site in South Africa. Daily diarrheal hospital admissions (2007 to 2016) at two large district hospitals in Mopani district, Limpopo province were compared to average daily temperature and apparent temperature (Tapp, 'real-feel' temperature that combined temperature, relative humidity, and wind speed). Linear regression and threshold regression, age-stratified to participants ≤5 years and >5 years old, considered changes in daily admissions by unit °C increase in Tapp. Daily ranges in ambient temperature and Tapp were 2-42 °C and -5-34 °C, respectively. For every 1 °C increase in average daily temperature, there was a 6% increase in hospital admissions for diarrhea for individuals of all ages (95% CI: 0.04-0.08; p < 0.001) and a 4% increase in admissions for individuals older than 5 years (95% CI: 0.02-0.05; p < 0.001). A positive linear relationship between average daily Tapp and all daily diarrheal admissions for children ≤5 years old was not statistically significant (95% CI: -0.00-0.03; p = 0.107). Diarrhea is common in children ≤5 years old, however, is more likely triggered by factors other than temperature/Tapp, while it is likely associated with increased temperature in individuals >5 years old. We are limited by lack of data on confounders and effect modifiers, thus, our findings are exploratory. To fully quantify how temperature affects hospital admission counts for diarrhea, future studies should include socio-economic-demographic factors as well as WASH-related data such as personal hygiene practices and access to clean water.

Effects of Ambient Temperature, Relative Humidity, and Precipitation on Diarrhea Incidence in Surabaya

BACKGROUND

Diarrhea remains a common infectious disease caused by various risk factors in developing countries. This study investigated the incidence rate and temporal associations between diarrhea and meteorological determinants in five regions of Surabaya, Indonesia.

METHOD

Monthly diarrhea records from local governmental health facilities in Surabaya and monthly means of weather variables, including average temperature, precipitation, and relative humidity from Meteorology, Climatology, and Geophysical Agency were collected from January 2018 to September 2020. The generalized additive model was employed to quantify the time lag association between diarrhea risk and extremely low (5th percentile) and high (95th percentile) monthly weather variations in the north, central, west, south, and east regions of Surabaya (lag of 0-2 months).

RESULT

The average incidence rate for diarrhea was 11.4 per 100,000 during the study period, with a higher incidence during rainy season (November to March) and in East Surabaya. This study showed that the weather condition with the lowest diarrhea risks varied with the region. The diarrhea risks were associated with extremely low and high temperatures, with the highest RR of 5.39 (95% CI 4.61, 6.17) in the east region, with 1 month of lag time following the extreme temperatures. Extremely low relative humidity increased the diarrhea risks in some regions of Surabaya, with the highest risk in the west region at lag 0 (RR = 2.13 (95% CI 1.79, 2.47)). Extremely high precipitation significantly affects the risk of diarrhea in the central region, at 0 months of lag time, with an RR of 3.05 (95% CI 2.09, 4.01).

CONCLUSION

This study identified a high incidence of diarrhea in the rainy season and in the deficient developed regions of Surabaya, providing evidence that weather magnifies the adverse effects of inadequate environmental sanitation. This study suggests the local environmental and health sectors codevelop a weather-based early warning system and improve local sanitation practices as prevention measures in response to increasing risks of infectious diseases.

Diarrhoeal prevalence and handwashing practices of children attending early childhood development centres in KwaZulu-Natal, South Africa

Background

Diarrhoea, a leading cause of childhood morbidity and mortality, spread through contaminated food or water or from person to person, is a major cause of hospitalisation in South African children.

Aim

To determine if hygiene practices of parents or guardians and early childhood development centre (ECD) educators contributed to diarrhoea in children attending the centres.

Setting

The study was conducted at ECD centres in Mpumalanga Township of KwaZulu-Natal province, South Africa.

Methods

A descriptive cross-sectional study was conducted at 10 ECD centres. Parents or guardians (n = 385) and educators (n = 121) answered self-administered questionnaires. Frequencies, bivariate associations and multivariate regression modelling were conducted.

Results

The prevalence of diarrhoea in children ≤ 5 years was 67.3%. Most parents or guardians washed their hands after defecating and handling a child's faeces as well as before preparing food. Handwashing after urination was low. Washing of children's hands after these events was lower. Although all educators reported always washing the child's hands after defecating and before handling or eating food, they were less likely to wash the children's hands after urination (p = 0.003). Childhood diarrhoea was associated with the type of toilet, households with pit latrines having a higher prevalence of diarrhoea (p < 0.001). It was also associated with washing of children's hands after urination (p = 0.014), before handling or eating food (p = 0.001) and with increased number of children in the household (p = 0.001).

Conclusion

In this population, the high prevalence of diarrhoea is related to the number of children in a household and handwashing practices.

Contribution

This study highlights the importance of handwashing practices in the prevention of diarrhoea in children.

Estimating the seasonally varying effect of meteorological factors on the district-level incidence of acute watery diarrhea among under-five children of Iran, 2014-2018: a Bayesian hierarchical spatiotemporal model

Under-five years old acute watery diarrhea (U5AWD) accounts for most diarrheal diseases' burden, but little is known about the adjusted effect of meteorological and socioeconomic determinants. A dataset containing the seasonal numbers of U5AWD cases at the district level of Iran is collected through MOHME. Accordingly, the district-level standardized incidence ratio and Moran's I values are calculated to detect the significant clusters of U5AWD over sixteen seasons from 2014 to 2018. Additionally, the author tested twelve Bayesian hierarchical models in order to determine which one was the most accurate at forecasting seasonal number of incidents. Iran features a number of U5AWD hotspots, particularly in the southeast. An extended spatiotemporal model with seasonally varying coefficients and space-time interaction outperformed other models, and so became the paper's proposal in modeling U5AWD. Temperature demonstrated a global positive connection with seasonal U5AWD in districts (IRR: 1.0497; 95% CrI: 1.0254-1.0748), owing to its varying effects during the winter ((IRR: 1.0877; 95% CrI: 1.0408-1.1375) and fall (IRR: 1.0866; 95% CrI: 1.0405-1.1357) seasons. Also, elevation (IRR: 0.9997; 95% CrI: 0.9996-0.9998), piped drinking water (IRR: 0.9948; 95% CrI: 0.9933-0.9964), public sewerage network (IRR: 0.9965; 95% CrI: 0.9938-0.9992), years of schooling (IRR: 0.9649; 95% CrI: 0.944-0.9862), infrastructure-to-household size ratio (IRR: 0.9903; 95% CrI: 0.986-0.9946), wealth index (IRR: 0.9502; 95% CrI: 0.9231-0.9781), and urbanization (IRR: 0.9919; 95% CrI: 0.9893-0.9944) of districts were negatively associated with seasonal U5AWD incidence. Strategically, developing geoinformation alarm systems based on meteorological data might help predict U5AWD high-risk areas. The study also anticipates increased rates of U5AWD in districts with poor sanitation and socioeconomic level. Therefore, governments should take appropriate preventative actions in these sectors.

Climate change and global health: A call to more research and more action

There is increasing understanding, globally, that climate change and increased pollution will have a profound and mostly harmful effect on human health. This review brings together international experts to describe both the direct (such as heat waves) and indirect (such as vector-borne disease incidence) health impacts of climate change. These impacts vary depending on vulnerability (i.e., existing diseases) and the international, economic, political, and environmental context. This unique review also expands on these issues to address a third category of potential longer-term impacts on global health: famine, population dislocation, and environmental justice and education. This scholarly resource explores these issues fully, linking them to global health in urban and rural settings in developed and developing countries. The review finishes with a practical discussion of action that health professionals around the world in our field can yet take.

The impact of diarrhoea measurement methods for under 5s in low- and middle-income countries on estimated diarrhoea rates at the population level: A systematic review and meta-analysis of methodological and primary empirical studies

Objective

We systematically reviewed all studies published between 2000 and June 2021 that estimated under 5 diarrhoea rates in low‐ and middle‐income countries and extracted data on diarrhoea rates, measurement methods and reactivity.

Methods

We summarised data from studies that performed direct comparisons of methods, and indirectly compared studies which utilised only one method using meta‐regression to determine the association between methods and estimated diarrhoea rates.

Results

In total, 288 studies met our inclusion criteria: 4 direct comparisons and 284 studies utilising only one measurement method. Meta‐regression across all studies showed that diarrhoea rates were sensitive to method of measurement. We estimated that passive surveillance methods were associated with a 97% lower estimated rate than active surveillance (IRR = 0.03, 95% CI [0.02, 0.06]). Among active surveillance studies, a doubling of recall period was associated with a 48% lower rate (IRR = 0.52 [0.46, 0.60]), while decreased questioning frequency was associated with a higher estimated rate: at the extreme, one time questioning yielded an over 4× higher rate than daily questioning (IRR = 4.22 [2.73, 6.52]).

Conclusions

Estimated diarrhoea rates are sensitive to their measurement methods. There is a need for a standardisation of diarrhoea measurement methods, and for the use of other outcomes in the measurement of population‐level gastrointestinal health.

Climate variability, water supply, sanitation and diarrhea among children under five in Sub-Saharan Africa: a multilevel analysis

Climate variability is expected to increase the risk of diarrhea diseases, a leading cause of child mortality and morbidity in Sub-Saharan Africa (SSA). The risk of diarrhea is more acute when populations have poor access to improved water and sanitation. This study seeks to determine individual and joint effects of climate variation, water supply and sanitation on the occurrence of diarrhea among children under five in SSA using multilevel mixed-effect Poisson regression including cross-level interaction. We merged 57 Demographic and Health Surveys (DHS) from 25 SSA countries covering the period 2000-2019 with climatic data from the DHS geolocation databases. The results of the research indicate that 77.7% of the variation in the occurrence of diarrhea in Sub-Saharan households is due to climatic differences between clusters. Also, a household residing in a cluster with a high incidence of diarrhea is 1.567 times more likely to have diarrhea cases than a household from a cluster with a low incidence. In addition, when average temperature and rainfall increase, households using unimproved sanitation or unimproved water have more cases of diarrhea. For SSA, the results of the multilevel analysis suggest the adoption at both levels; macro (national) and micro (household), of climate change adaption measures in the water sector to reduce the prevalence of diarrhea.

The impact of Ethiopian community-based health extension program on diarrheal diseases among under-five children and factors associated with diarrheal diseases in the rural community of Kalu district, Northeast Ethiopia: a cross-sectional study

Background

The health extension program is a community-based health care delivery program with eighteen defined packages. The main aim of the health extension program is to help to reduce child mortality. So, the aim of this study is to assess the impact of a health extension program on diarrheal disease under-five children in the rural community of Kalu district, Northeast Ethiopia, 2021.

Methods

A community-based cross-sectional study design was conducted from March to April/2021. A Multi-stage sampling technique was used to get a total sample size of 556 (182 model households and 374 non-model households) with a response rate of 92.22%. Binary logistic regression analysis was done, and P-value < 0.05 was considered statistically significant. Propensity score matching analysis was used to determine the contribution of health extension program “model households” on diarrhea diseases among under-five children. The average treatment effect on the treated was calculated to compare the means of outcomes across model and non-model households.

Results

Health extension program (HEP) model household contributed a 17.7% (t = -5.02) decrease in children’s diarrheal diseases among under-five children compared with HEP non-model households. Mothers from non-model households were 2.19 times more likely to develop under-five children diarrheal diseases AOR (Adjusted Odds Ratio): 2.19, 95% CI: 1.34–3.57 than mothers from model households. Households who got no frequent home visits were 3.28 times more likely to develop under-five diarrheal diseases AOR (Adjusted Odds Ratio): 3.28, 95% CI: 1.40–7.68.

Conclusion

When the health extension program is implemented fully (model household), the prevalence of under-five diarrheal disease in the rural community could decrease. The need to develop supportive strategies for the sustainability of model households and encouraging households to be model households is very important.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-022-07565-7.

Precipitation variability and risk of infectious disease in children under 5 years for 32 countries: a global analysis using Demographic and Health Survey data

BACKGROUND

Precipitation variability is a potentially important driver of infectious diseases that are leading causes of child morbidity and mortality worldwide. Disentangling the links between precipitation variability and disease risk is crucial in a changing climate. We aimed to investigate the links between precipitation variability and reported symptoms of infectious disease (cough, fever, and diarrhoea) in children younger than 5 years.

METHODS

We used nationally representative survey data collected between 2014 and 2019 from Demographic and Health Survey (DHS) surveys for 32 low-income to middle-income countries in combination with high-resolution precipitation data (via the Climate Hazards Group InfraRed Precipitation with Station dataset). We only included DHS data for which interview dates and GPS coordinates (latitude and longitude) of household clusters were available. We used a regression modelling approach to assess the relationship between different precipitation variability measures and infectious disease symptoms (cough, fever, and diarrhoea), and explored the effect modification of different climate zones and disease susceptibility factors.

FINDINGS

Our global analysis showed that anomalously wet conditions increase the risk of cough, fever, and diarrhoea symptoms in humid, subtropical regions. These health risks also increased in tropical savanna regions as a result of anomalously dry conditions. Our analysis of susceptibility factors suggests that unimproved sanitation and unsafe drinking water sources are exacerbating these effects, particularly for rural populations and in drought-prone areas in tropical savanna.

INTERPRETATION

Weather shifts can affect the survival and transmission of pathogens that are particularly harmful to young children. As our findings show, the health burden of climate-sensitive infectious diseases can be substantial and is likely to fall on populations that are already among the most disadvantaged, including households living in remote rural areas and those lacking access to safe water and sanitation infrastructure.

FUNDING

University of California, San Diego FY19 Center Launch programme.

Diarrhea and associated factors among under five children in sub-Saharan Africa: Evidence from demographic and health surveys of 34 sub-Saharan countries

INTRODUCTION

Diarrhea is responsible for the death of more than 90% of under-five children in low and lower-middle income countries. Regionally, South Asia and sub-Saharan Africa accounted for 88% of deaths with the same age group. Therefore, the aim of this study was to determine the prevalence and associated factors of diarrhea among children under-five years in sub-Saharan Africa.

METHODS

The appended, most recent demographic and health survey datasets of 34 sub-Saharan African countries were used to determine the prevalence and associated factors of diarrhea among under-five children in the region. A total weighted sample of 330,866 under-five children were included in the study. Both bivariable and multivariable multilevel logistic regression were done to determine the associated factors of diarrhea among under five children in sub-Saharan Africa. The Odds Ratio (OR) with a 95% Confidence Interval (CI) was calculated for those potential factors included in the final model.

RESULT

The overall prevalence of diarrhea in this study was 15.3% (95% CI: 15.1-15.4). Those children of mothers aged 15-24 (AOR = 1.26; 95% CI: 1.23, 1.30) and 25-34 years (AOR = 1.15; 95%CI: 1.12, 1.18), those children of mothers with no education (AOR = 1.69; 95%CI: 1.57-1.82), primary education (AOR = 1.73; 95%CI: 1.61-1.86) and secondary education (AOR = 1.49; 95%CI: 1.38-1.59) had higher odds of having diarrhea. Those children from poorest (AOR = 1.14; 95%CI: 1.10, 1.19), poorer (AOR = 1.12; 95%CI: 1.08-1.17), middle (AOR = 1.06; 95%CI: 1.02, 1.10), and richer (AOR = 1.14; 95%CI: 1.04-1.12) households had higher chance of having diarrhea compared to their counterparts.

CONCLUSION

This study found that the prevalence of childhood diarrhea morbidity in sub-Saharan Africa was high. Maternal age, wealth index, maternal education, maternal occupation, age of child, time of initiation of breast feeding and time to get water source were significantly associated with diarrhea. Therefore, intervention through health education and health promotion for mothers/caretakers who are poor, less educated, and young should be designed to prevent diarrhea in the region.

Microbial faecal pollution of river water in a watershed of tropical Ethiopian highlands is driven by diffuse pollution sources

Tropical communities in the developing world depend heavily on riverine systems for their socioeconomic development. However, these resources are poorly protected from diffuse pollution, and there is a lack of quantitative information regarding the microbial pollution characteristics of riverine water, despite frequently reported gastrointestinal diseases. The aim of our study was to apply faecal taxation (i.e., faecal pellet counting in representative test areas to estimate the potential availability of diffuse pollution sources) in combination with a detailed microbiological faecal pollution analysis in a riverine environment to elucidate the importance of diffuse pollution. To realize this approach, ambient faecal pellets, a multiparametric data set for standard faecal indicator bacteria (SFIB), including Escherichia coli, Clostridium perfringens spores and enterococci from catchment soil and river water, and a number of riverine water physicochemical variables were analysed during a one-year cycle. We demonstrated that the abundance of ambient faecal pellets, which were consistently counted at reference sites in the catchment, was associated with faecal pollution in the river water. Water SFIB, dissolved oxygen, nutrients, conductivity and total suspended solids were strongly linked with the abundance of ambient faecal pellets in the river catchment, as demonstrated by principal component analysis (PCA). Elevated concentrations of SFIB in the riverine water in the absence of rainfall also suggested the direct input of faecal bacteria into the riverine water by livestock (e.g., during watering) and humans (e.g., during bathing). Statistical analyses further revealed that the microbiological water quality of the investigated riverine water was not influenced by SFIB potentially occurring in the soil. This study demonstrates the importance of diffuse faecal pollution sources as major drivers of the microbiological quality of riverine water in the Ethiopian highlands. In addition, the new successfully applied integrated approach could be very useful for developing predictive models, which would aid in forecasting riverine microbiological quality in tropical developing countries.

Diarrhoea among Children Aged under Five Years and Risk Factors in Informal Settlements: A Cross-Sectional Study in Cape Town, South Africa

Background: There is limited data on the association between diarrhoea among children aged under five years (U5D) and water use, sanitation, hygiene, and socio-economics factors in low-income communities. The study investigated U5D and the associated risk factors in the Zeekoe catchment in Cape Town, South Africa. Methods: A cross-sectional study was conducted in 707 households in six informal settlements (IS) two formal settlements (FS) (March–June 2017). Results: Most IS households used public taps (74.4%) and shared toilets (93.0%), while FS households used piped water on premises (89.6%) and private toilets (98.3%). IS respondents had higher average hand-washing scores than those of FS (0.04 vs. −0.14, p = 0.02). The overall U5D prevalence was 15.3% (range: 8.6%–24.2%) and was higher in FS than in IS (21.2% vs. 13.4%, respectively, p = 0.01). Water storage >12 h was associated with increasing U5D (OR = 1.88, 95% CI 1.00–3.55, p = 0.05). Water treatment (OR = 0.57, 95%CI 0.34–0.97, p = 0.04), good hand-washing practices (OR = 0.59, 95%CI 0.42–0.82, p = 0.002) and Hepatitis A vaccination (OR = 0.51, 95%CI 0.28–0.9, p = 0.02) had significant preventing effects on U5D. Conclusions: The study highlights that good hygiene practice is a key intervention against U5D in informal settlements. The promotion of hand-washing, proper water storage, and hygienic breastfeeding is highly recommended.

Examining local perspectives on the influence of climate change on the health of Hamer pastoralists and their livestock in Ethiopia

This study explores the perceived influence of climate change on the health of Hamer pastoralists and their livestock in south-western Ethiopia. A combination of focus group discussions and key informant interviews were conducted with Hamer communities as well as local health workers, animal health workers and non-governmental organisation (NGO) staff. Thematic framework analysis was used to analyse the data. Reductions in rangeland, erratic rainfall, recurrent droughts and loss of seasonality were perceived to be the biggest climate challenges influencing the health and livelihoods of the Hamer. Communities were travelling greater distances to access sufficient grazing lands, and this was leading to livestock deaths and increases in ethnic violence. Reductions in suitable rangeland were also precipitating disease outbreaks in animals due to increased mixing of different herds. Negative health impacts in the community stemmed indirectly from decreases in livestock production, uncertain crop harvests and increased water scarcity. The remoteness of grazing lands has resulted in decreased availability of animal milk, contributing to malnutrition in vulnerable groups, including children. Water scarcity in the region has led to utilisation of unsafe water sources resulting in diarrhoeal illnesses. Further, seasonal shifts in climate-sensitive diseases such as malaria were also acknowledged. Poorly resourced healthcare facilities with limited accessibility combined with an absence of health education has amplified the community’s vulnerability to health challenges. The resilience and ambition for livelihood diversification amongst the Hamer was evident. The introduction of camels, increase in permanent settlements and new commercial ideas were transforming their livelihood strategies. However, the Hamer lack a voice to express their perspectives, challenges and ambitions. There needs to be collaborative dynamic dialogue between pastoral communities and the policy-makers to drive sustainable development in the area without compromising the values, traditions and knowledge of the pastoralists.

Climate Change and Health Preparedness in Africa: Analysing Trends in Six African Countries

Climate change is a global problem, which affects the various geographical regions at different levels. It is also associated with a wide range of human health problems, which pose a burden to health systems, especially in regions such as Africa. Indeed, across the African continent public health systems are under severe pressure, partly due to their fragile socioeconomic conditions. This paper reports on a cross-sectional study in six African countries (Ghana, Nigeria, South Africa, Namibia, Ethiopia, and Kenya) aimed at assessing their vulnerabilities to climate change, focusing on its impacts on human health. The study evaluated the levels of information, knowledge, and perceptions of public health professionals. It also examined the health systems’ preparedness to cope with these health hazards, the available resources, and those needed to build resilience to the country’s vulnerable population, as perceived by health professionals. The results revealed that 63.1% of the total respondents reported that climate change had been extensively experienced in the past years, while 32% claimed that the sampled countries had experienced them to some extent. Nigerian respondents recorded the highest levels (67.7%), followed by Kenya with 66.6%. South Africa had the lowest level of impact as perceived by the respondents (50.0%) when compared with the other sampled countries. All respondents from Ghana and Namibia reported that health problems caused by climate change are common in the two countries. As perceived by the health professionals, the inadequate resources reiterate the need for infrastructural resources, medical equipment, emergency response resources, and technical support. The study’s recommendations include the need to improve current policies at all levels (i.e., national, regional, and local) on climate change and public health and to strengthen health professionals’ skills. Improving the basic knowledge of health institutions to better respond to a changing climate is also recommended. The study provides valuable insights which may be helpful to other nations in Sub-Saharan Africa.

Effect of ambient temperatures on category C notifiable infectious diarrhea in China: An analysis of national surveillance data

BACKGROUND

Many studies have explored the association between meteorological factors and infectious diarrhea (ID) transmission but with inconsistent results, in particular the roles from temperatures. We aimed to explore the effects of temperatures on the transmission of category C ID, to identify its potential heterogeneity in different climate zones of China, and to provide scientific evidence to health authorities and local communities for necessary public health actions.

METHODS

Daily category C ID counts and meteorological variables were collected from 270 cities in China over the period of 2014-16. Distributed lag non-linear models (DLNMs) were applied in each city to obtain the city-specific temperature-disease associations, then a multivariate meta-analysis was implemented to pool the city-specific effects. Multivariate meta-regression was conducted to explore the potential effect modifiers. Attributable fraction was calculated for both low and high temperatures, defined as temperatures below the 5th percentile of temperature or above the 95th percentile of temperature.

RESULTS

A total of 2,715,544 category C ID cases were reported during the study period. Overall, a M-shaped curve relationship was observed between temperature and category C ID, with a peak at the 81st percentile of temperatures (RR = 1.723, 95% CI: 1.579-1.881) compared to 50th percentile of temperatures. The pooled associations were generally stronger at high temperatures compared to low ambient temperatures, and the attributable fraction due to heat was higher than cold. Latitude was identified as a possible effect modifier.

CONCLUSIONS

The overall positive pooled associations between temperature and category C ID in China suggest the increasing temperature could bring about more category C infectious diarrhea cases, which warrants further public health measurements.

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 Effect of Ambient Temperature on Infectious Diarrhea and Diarrhea-like Illness in Wuxi, China

Background:

The disease burden of infectious diarrhea cannot be underestimated. Its seasonal patterns indicate that weather patterns may play an important role and have an important effect on it. The objective of this study was to clarify the relationship between temperature and infectious diarrhea, and diarrhea-like illness.

Methods:

Distributed lag non-linear model, which was based on the definition of a cross-basis, was used to examine the effect.

Results:

Viral diarrhea usually had high incidence in autumn-winter and spring with a peak at -6°C; Norovirus circulated throughout the year with an insignificant peak at 8°C, while related bacteria usually tested positive in summer and peaked at 22°C. The lag-response curve of the proportion of diarrhea-like cases in outpatient and emergency cases revealed that at -6°C, with the lag days increasing, the proportion increased. Similar phenomena were observed at the beginning of the curves of virus and bacterial positive rate, showing that the risk increased as the lag days increased, peaking on days 16 and 9, respectively. The shape of lag-response curve of norovirus positive rate was different from others, presenting m-type, with 2 peaks on day 3 and day 18.

Conclusion:

Weather patterns should be taken into account when developing surveillance programs and formulating relevant public health intervention strategies.

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.

Climate and climate-sensitive diseases in semi-arid regions: a systematic review

OBJECTIVES

We aim to describe the relationships between climate variables and climate-sensitive diseases (CSDs) in semi-arid regions, highlighting the different main groups of CSDs and their climate patterns.

METHODS

This systematic review considered Medline, Science Direct, Scopus and Web of Science. The data collection period was August and September 2019 and included studies published between 2008 and 2019. This study followed a protocol based on the PRISMA statement. Data analysis was done in a qualitative way.

RESULTS

The most of works were from Africa, Asia and Iran (71%), where temperature was the main climatic variable. Although the studies provide climatic conditions that are more favorable for the incidence of vector-borne and respiratory diseases, the influence of seasonal patterns on the onset, development and end of CSDs is still poorly understood, especially for gastrointestinal disorders. Moreover, little is known about the impact of droughts on CSDs.

CONCLUSIONS

This review summarized the state of art of the relationship between climate and CSDs in semi-arid regions. Moreover, a research agenda was provided, which is fundamental for health policy development, priority setting and public health management.

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.

Diarrhea Patterns and Climate: A Spatiotemporal Bayesian Hierarchical Analysis of Diarrheal Disease in Afghanistan

Subject to a high burden of diarrheal diseases, Afghanistan is also susceptible to climate change. This study investigated the spatiotemporal distribution of diarrheal disease in the country and how associated it is with climate variables. Using monthly aggregated new cases of acute diarrhea reported between 2010 and 2016 and monthly averaged climate data at the district level, we fitted a hierarchical Bayesian spatiotemporal statistical model. We found aridity and mean daily temperature were positively associated with diarrhea incidence; every 1°C increase in mean daily temperature and 0.01-unit change in the aridity index were associated with a 0.70% (CI: 0.67%, 0.73%) increase and a 4.79% (CI: 4.30%, 5.26%) increase in the risk of diarrhea, respectively. Average annual temperature, on the other hand, was negatively associated, with a 3.7% (CI: 3.74%, 3.68) decrease in risk for every degree Celsius increase in annual average temperature. Temporally, most districts exhibited similar seasonal trends, with incidence peaking in summer, except for the eastern region where differences in climate patterns and population density may be associated with high rates of diarrhea throughout the year. The results from this study highlight the significant role of climate in shaping diarrheal patterns in Afghanistan, allowing policymakers to account for potential impacts of climate change in their public health assessments.

Disease burden and risk factors of diarrhoea in children under five years: Evidence from Kenya's demographic health survey 2014

OBJECTIVE

This study aimed at examining the socio-demographic, environmental and behavioural determinants of diarrhoea in children under five years in Kenya.

METHODS

The study entailed an analysis of secondary data from the Kenya Demographic Health Survey (DHS) 2014 using STATA Corp 2010. A total of 19,889 children <5 years were in the study, out of whom 2,906 had diarrhoea in the last two weeks prior to the survey. Descriptive analysis of independent variables and logistic regression model was used to analyse risk factors associated with diarrhoea in children <5 years.

RESULTS

The most significant risk factors (p < 0.05) associated with diarrhoea morbidity in children <5 years were child age (AOR 2.26 95% CI 1.64, 3.11), low level of caregiver's education (AOR 1.45 95% CI 1.11, 1.90) and unsafe disposal of children's faeces (AOR 1.29 95% CI 1.03, 1.61). Wealthier households (AOR 0.83 95% CI 0.68, 1) were protective for diarrhoea in children <5 years.

CONCLUSION

Increasing caregiver education, wealthier households and promoting hygienic behaviours in poor households were associated with reducing diarrhoea. Programmes aimed at reducing diarrhoea may achieve better results in targeting caregivers with children in high risk age cohorts of 6-23 months.

Comparing the performance of conventional PCR, RTQ-PCR, and droplet digital PCR assays in detection of Shigella

The incidence of foodborne infections caused by Shigella spp. is still very high in every year, which poses a great potential threat to public health. Conventional quantification methods based on culture techniques, biochemical, and serological identification are time-consuming and labor-intensive. To develop a more rapid and efficient detection method of Shigella spp., we compared the sensitivity and specificity of three different polymerase chain reaction (PCR) methods, including conventional PCR, quantitative real-time PCR (RTQ-PCR), and droplet digital PCR (ddPCR). Our results indicated that ddPCR method exhibited higher sensitivity, and the limit of detection was 10^-5 ng/μl for genomic DNA templates, 10^-1 cfu/ml for Shigella bacteria culture. In addition, we found that ddPCR was a time-saving method, which required a shorter pre-culturing time. Collectively, ddPCR assay was a reliable method for rapid and effective detection of Shigella spp.

Assessing Comorbidity of Diarrhea and Acute Respiratory Infections in Children Under 5 Years: Evidence From Kenya's Demographic Health Survey 2014

Background: Kenya is one among the 15 countries that account for three-quarters of the global mortality burden due to diarrhea and respiratory tract infections (RTIs). Comorbidity of diarrhea and acute respiratory infection (ARI) can either be simultaneous (both occurring at the same time) or sequential (where the occurrence of one leads to the occurrence of the other. This study aimed to determine the shared risks that influence comorbidity of diarrhea and RTIs among Kenya's children younger than 5 years. Methods: The study entailed an analysis of secondary data from the Kenya Demographic Health Survey (DHS) 2014 using STATA Corp 2010. Descriptive analysis of independent variables and logistic regression model was used to analyze risk factors associated with comorbidity from diarrhea and ARI in children <5 years. Results: A total of 18 702 children <5 years were in the study out of whom 411 had comorbidity from diarrhea and ARI in the 2 weeks prior to the survey. Comorbidity peaked at 6 to 11 months (4.6%). Child's age between 6 and 11 months (adjusted odds ratio [aOR] = 3.48, 95% CI = 2.02-5.99) and caregivers with incomplete primary education (aOR = 1.66, 95% CI = 1.11-2.50) were associated with higher odds of comorbidity from diarrhea and ARI. The main determinants associated with lower odds of combined morbidity from diarrhea and ARI were high wealth quintile (aOR = 0.58, 95% CI = 0.39-0.85) and older aged caregivers (aOR = 0.47, 95% CI = 0.23-0.95). However, we found no association between nutritional status of a child, sex, residence, exclusive breastfeeding between 0 and 6 months, and combined morbidity from diarrhea and ARI. Conclusion: Programs aimed at reducing comorbidity should target children between 6 and 11 months and deliberate emphasis should be placed on addressing barriers to wealth and caregivers' education.

A bellweather for climate change and disability: educational needs of rehabilitation professionals regarding disaster management and spinal cord injuries

Study design

Cross-sectional survey.

Objective

Persons with disabilities are disproportionately impacted by extreme weather disasters and climate change. Individuals with spinal cord injury (SCI) are especially at risk due to inability to control their body temperature and mobility concerns. We surveyed rehabilitation professionals in the field of SCI to determine their experiences, concerns and educational needs regarding natural disasters, climate change and sustainability and the effects on their clientele.

Setting

Online survey available to an international cohort.

Methods

The survey was developed by the authors and conducted in 2019. It was distributed amongst various international health care organizations whose members care for persons with SCI. Descriptive statistics and chi-square test for association were performed using Microsoft Excel 2016.

Results

Of 125 respondents, 50% were from Europe, 18% from North America, and 18% from Asia; 74% were physicians and 13% physical therapists. In total 57.6% believed climate change had impacted their client's health and well-being. Respondents from North America were significantly less likely to report climate change had an impact on their patient's health than those from Asia or Europe (p < 0.01). In total 82.5% of respondents thought professionals should be concerned with sustainability and 85.5% were interested in further education.

Conclusions

Most respondents acknowledged a need for more information related to the disasters, climate change, and disability. Results underscore the need for further research, professional, and consumer education.

Forecasting incidence of hand, foot and mouth disease using BP neural networks in Jiangsu province, China

Background

Hand, foot and mouth disease (HFMD) is a rising public health problem and has attracted considerable attention worldwide. The purpose of this study was to develop an optimal model with meteorological factors to predict the epidemic of HFMD.

Methods

Two types of methods, back propagation neural networks (BP) and auto-regressive integrated moving average (ARIMA), were employed to develop forecasting models, based on the monthly HFMD incidences and meteorological factors during 2009–2016 in Jiangsu province, China. Root mean square error (RMSE) and mean absolute percentage error (MAPE) were employed to select model and evaluate the performance of the models.

Results

Four models were constructed. The multivariate BP model was constructed using the HFMD incidences lagged from 1 to 4 months, mean temperature, rainfall and their one order lagged terms as inputs. The other BP model was fitted just using the lagged HFMD incidences as inputs. The univariate ARIMA model was specified as ARIMA (1,0,1)(1,1,0)¹² (AIC = 1132.12, BIC = 1440.43). And the multivariate ARIMAX with one order lagged temperature as external predictor was fitted based on this ARIMA model (AIC = 1132.37, BIC = 1142.76). The multivariate BP model performed the best in both model fitting stage and prospective forecasting stage, with a MAPE no more than 20%. The performance of the multivariate ARIMAX model was similar to that of the univariate ARIMA model. Both performed much worse than the two BP models, with a high MAPE near to 40%.

Conclusion

The multivariate BP model effectively integrated the autocorrelation of the HFMD incidence series. Meanwhile, it also comprehensively combined the climatic variables and their hysteresis effects. The introduction of the climate terms significantly improved the prediction accuracy of the BP model. This model could be an ideal method to predict the epidemic level of HFMD, which is of great importance for the public health authorities.

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.

Lay Field-worker-Led School Health Program for Primary Schools in Low- and Middle-Income Countries

BACKGROUND AND OBJECTIVES

School health programs are frequently attempted in low- and/or middle-income countries; however, programmatic scope and reach is limited by human resource constraints. We sought to determine if trained community members could implement a school health program that improved outcomes in rural primary schools in India.

METHODS

This was a mixed-methods, stepped-wedge, cluster-controlled study of schools pragmatically assigned to receive a multicomponent, comprehensive school health program delivered by lay field-workers.

RESULTS

All students in 22 primary schools (9 government schools and 13 low-cost private schools) participated in this study. A total of 3033 student-years were included in the analysis (2100 student-years in the intervention period and 933 student-years in the control period). Qualitative feedback was collected from 38 teachers, 49 parents, and 4 field-workers. In low-cost private schools, the diarrhea incidence was lower in students receiving the intervention (incidence rate ratio 0.58; 95% confidence interval [CI] 0.47 to 0.71; P < .001). There was no difference in diarrhea incidence for students in government schools (incidence rate ratio 0.87; 95% CI 0.68 to 1.12; P = .29). Health-knowledge acquisition was higher in intervention schools (mean difference 12.6%; 95% CI 8.8 to 16.4; P < .001) and similar in both school types. Intervention coverage rates were high (mean 93.9%; SD 2.0%), and performance assessment scores indicated fidelity (mean 3.45; SD 0.69). Stakeholders revealed favorable perceptions of the field-workers and high levels of perceived impact.

CONCLUSIONS

Lay field-worker-led school health programs offer a promising alternative for improving school health delivery in resource-constrained settings.

Trends for Diarrhea Morbidity in the Jasikan District of Ghana: Estimates from District Level Diarrhea Surveillance Data, 2012-2016

About 22% of childhood deaths in developing countries are attributable to diarrhea. In poor resource settings, diarrhea morbidities are correlated with poverty and socio-contextual factors. Diarrhea rates in Ghana are reported to be high, with cases estimated at 113,786 among children under-five years in 2011. This study analyzed the trends of diarrhea morbidity outcomes in the Jasikan District of Ghana. A retrospective analysis of records on diarrhea data for a five years' period (January 2012 to December 2016) was undertaken. There was a total of 17740 diarrhea case reports extracted from District Health Information Management System (DHIMS) II database in an Excel format which was then exported to Stata version 14 for data cleaning, verification, and analysis. Excel version 2016 was used to plot the actual observed cases by years to assess trends and seasonality. There was a period incidence rate of 272.02 per 1000 persons with a decreasing annual growth rate of 1.85%. Declines for diarrhea generally occurred from November to December and increased from January upwards, evidence that most cases of diarrhea in this study were reported in the harmattan season. High incidence of diarrhea was found to be common among under-five children and among females. Decreasing trend of diarrhea incidence which was identified in this research within the five years' period understudied shows that, by the year 2020, there will be a sharp decline in the incidence rate of diarrhea reported cases in Jasikan District, given improvements in the external environmental conditions in the district, all things being equal.

El Niño Southern Oscillation (ENSO) and Health: An Overview for Climate and Health Researchers

The El Niño Southern Oscillation (ENSO) is an important mode of climatic variability that exerts a discernible impact on ecosystems and society through alterations in climate patterns. For this reason, ENSO has attracted much interest in the climate and health science community, with many analysts investigating ENSO health links through considering the degree of dependency of the incidence of a range of climate diseases on the occurrence of El Niño events. Because of the mounting interest in the relationship between ENSO as a major mode of climatic variability and health, this paper presents an overview of the basic characteristics of the ENSO phenomenon and its climate impacts, discusses the use of ENSO indices in climate and health research, and outlines the present understanding of ENSO health associations. Also touched upon are ENSO-based seasonal health forecasting and the possible impacts of climate change on ENSO and the implications this holds for future assessments of ENSO health associations. The review concludes that there is still some way to go before a thorough understanding of the association between ENSO and health is achieved, with a need to move beyond analyses undertaken through a purely statistical lens, with due acknowledgement that ENSO is a complex non-canonical phenomenon, and that simple ENSO health associations should not be expected.

Longer-Term Outdoor Temperatures and Health Effects: A Review

PURPOSE OF REVIEW

Our goal was to assess current literature and knowledge on associations between characteristics (mean, variability, extremes) of ambient temperatures and human health. We were motivated by concerns that climate change, which operates on a time frame of decades or longer, may influence not only shorter-term associations between weather and health (daily/weekly) but also have enduring implications for population health. We reviewed papers published between 2010 and 2017 on the health effects of longer-term (3 weeks to years) exposures to ambient temperature. We sought to answer: 'What health outcomes have been associated with longer-term exposures?' We included studies on a diverse range of health outcomes, with the exception of vector borne diseases such as malaria. Longer-term exposures were considered to be exposures to annual and seasonal temperatures and temperature variability.

RECENT FINDINGS

We found 26 papers meeting inclusion criteria, which addressed mortality, morbidity, respiratory disease, obesity, suicide, infectious diseases and allergies among various age groups. In general, most studies found associations between longer-term temperature metrics and health outcomes. Effects varied by population subgroup. For example, associations with suicide differed by sex and underlying chronic illness modified effects of heat on mortality among the elderly.

SUMMARY

We found that regional and local temperatures, and changing conditions in weather due to climate change, were associated with a diversity of health outcomes through multiple mechanisms. Future research should focus on evidence for particular mechanistic pathways in order to inform adaptation responses to climate change.