Spatiotemporal and hotspot detection of U5-children diarrhea in resource-limited areas of Ethiopia

Space-time distribution of intestinal infectious diseases and their association with socioeconomic variables in Ecuador

Background

Intestinal infectious diseases are a global concern in terms of morbidity, and they are closely linked to socioeconomic variables such as quality of life, weather and access to healthcare services. Despite progress in spatial analysis tools and geographic information systems in epidemiology, studies in Ecuador that evaluate temporal trends, specific geographic groups, and their correlation with socioeconomic variables are lacking. The absence of such information makes it challenging to formulate public health policies. This study sought to identify the spatial and temporal patterns of these diseases in Ecuador, along with their correlation with socioeconomic variables.

Methods

In Ecuador, the study was carried out in a continental territory, focusing on data related to intestinal infectious diseases collected from the National Institute of Statistics and Census (Instituto Nacional de Estadística y Censos) during the period from 2014 to 2019. This study involved spatial and temporal analyses using tools such as the global Moran's index and Local Indicators of Spatial Association to identify spatial clustering patterns and autocorrelation. Additionally, correlations between morbidity rates and socioeconomic variables were examined.

Results

During the investigated period, Ecuador registered 209,668 cases of these diseases. Notable variations in case numbers were identified, with a 9.2% increase in 2019 compared to the previous year. The most impacted group was children under 5 years old, and the highest rates were centered in the southern and southwestern regions of the country, with Limón Indanza and Chunchi being the cantons with the highest rates, notably showing a significant increase in Limón Indanza. Additionally, there were significant correlations between morbidity rates and socioeconomic variables, school dropout rates, low birth weight, and access to water services.

Conclusion

This study emphasizes the importance of considering socioeconomic variables when addressing these diseases in Ecuador. Understanding these correlations and geospatial trends can guide the development of health policies and specific intervention programs to reduce the incidence in identified high-risk areas. More specific research is needed to understand the underlying causes of variability in morbidity and develop effective prevention strategies.

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.

Spatiotemporal analysis of diarrhea-related hospitalizations of children in Brazil's Midwest region from 2011 to 2020

OBJECTIVE

To examine spatiotemporal variability and identify clustering patterns of hospitalization rates for diarrhea in children younger than five years in Mato Grosso, Brazil, from 2011 to 2020.

METHODS

An ecological study was conducted using hospitalization records associated with diarrhea from the Brazilian Hospital Information System/Unified Health System. The relative risk of hospitalization for diarrhea in each municipality was calculated using SaTScan software considering a statistical significance level of 5% and 999 Monte Carlo replications.

RESULTS

A total of 13,315 diarrhea-associated hospitalizations for 5-year-old children were recorded. From 2011 to 2020, the annual rates for hospitalizations related to diarrhea decreased from 8.50 to 3.45/1,000 live births among children younger than one year and from 4.99 to 1.57 for children aged 1-4 years. Clusters of municipalities with high relative risk for hospitalizations due to diarrhea, statistically significant, predominated in the North, Northeast, and Southwest health administrative macro-regions of Mato Grosso for both age groups until 2016. From 2016 to 2020, clusters of the lowest relative risk were identified in the North and Center South health administrative macro-regions for children younger than five years.

CONCLUSION

Results showed that hospitalization rates for diarrhea in children younger than five years reduced with the presence of low-risk clusters in Mato Grosso in the final years of the study. Public health surveillance should incorporate spatial analysis to investigate the diarrhea-related morbidity.

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

Objective

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

Methods

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

Results

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

Conclusion

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

Seasonal variation of diarrhoeal pathogens among Guinea-Bissauan children under five years of age

BACKGROUND

Diarrhoea remains a major cause of childhood morbidity and mortality in low-income countries (LICs). The frequency of diarrhoeal episodes may vary by season, yet few prospective cohort studies have examined seasonal variation among various diarrhoeal pathogens using multiplex qPCR to analyse bacterial, viral and parasitic pathogens.

METHODS

We combined our recent qPCR data of diarrhoeal pathogens (nine bacterial, five viral and four parasitic) among Guinea-Bissauan children under five years old with individual background data, dividing by season. The associations of season (dry winter and rainy summer) and the various pathogens were explored among infants (0-11 months) and young children (12-59 months) and those with and without diarrhoea.

RESULTS

Many bacterial pathogens, especially EAEC, ETEC and Campylobacter, and parasitic Cryptosporidium, prevailed in the rainy season, whereas many viruses, particularly the adenovirus, astrovirus and rotavirus proved common in the dry season. Noroviruses were found constantly throughout the year. Seasonal variation was observed in both age groups.

CONCLUSION

In childhood diarrhoea in a West African LIC, seasonal variation appears to favour EAEC, ETEC, and Cryptosporidium in the rainy and viral pathogens in the dry season.

Correlation Between Different Antidiarrheal Treatments and Changes in Chemical Components of Allii Sativi Bulbus Before and After Steaming Treatment Based on Flora Sequencing and In Vitro Experiments

We investigated the changes in the main active ingredients and pharmacodynamic differences in the therapeutic effect of garlic before and after steaming and the correlation between them. The main active ingredients in raw garlic products (RGPs) and steamed garlic products (SGPs) were determined by high-pressure liquid chromatography and ultraviolet spectroscopy. Acute rapid diarrhea (AD) and antibiotic-induced diarrhea (DD) models were established in rats, and each group was treated with RGP and SGP, respectively. The main chemical components of garlic changed before and after steaming. Garlicin and alliinase were only found in RGP, whereas only alliin was found in SGP. Both RGP and SGP contained garlic polysaccharides. For in vivo experiments on AD, the average rate of loose stools was 100.00 ± 0.00, 31.55 ± 11.76, and 19.14 ± 6.62 in the RGP high-dose and SGP high-dose treatment groups, respectively; in DD, the rates were 91.11 ± 14.40, 19.33 ± 3.63, and 30.56 ± 4.30, respectively (P < .01, treatment vs. model groups). In AD, the average grade of loose stools was 2.33 ± 0.52 and 1.83 ± 0.75 in the model and RGP high-dose treatment groups, respectively (P < .05); in DD, the values were 2.17 ± 0.41 in the model group and 1.67 ± 0.52 in the SGP high-dose treatment group (P < .05). RGP had a better therapeutic effect on AD, mainly related to the antibacterial effect of garlicin in RGP. SGP had a better therapeutic effect on DD, mainly related to the alliin and garlic polysaccharide in SGP. This study could provide evidence to support the clinical use of garlic.

Spatiotemporal Analysis of the Proportion of Unimproved Drinking Water Sources in Rural Ethiopia: Evidence from Ethiopian Socioeconomic Surveys (2011 to 2019)

Currently, around 36% of the rural Ethiopian population is accessing drinking water from unimproved sources and it is unevenly distributed through time and geographic regions. Therefore, this study aimed to analyze the spatiotemporal patterns of unimproved drinking water sources and identify hotspot areas in rural Ethiopia. Ethiopian Socioeconomic Survey (ESS) data obtained from the Central Statistical Agency were used. It was conducted in four waves from 2011 to 2019. A two-stage probability sampling design was applied. The sample of enumeration areas and households were taken as the first and second stages of sampling, respectively. A total of 3912, 3775, 3698, and 3115 sample households with complete information on drinking water sources were taken in each wave of ESS data, respectively. Weighted proportions, autocorrelation (Moran's “I”) statistic, and hotspot analyses were applied to estimate the prevalence, test the presence of clustering, and identify vulnerable areas with unimproved drinking water sources. The STATA version 14, Excel, and ArcGIS 10.6 were used to manage and analyze data. The proportions of households with unimproved drinking water sources were 0.497, 0.385, 0.298, and 0.363 in consecutive waves of ESS data. The results also revealed the existence of geographical and temporal variations of access to drinking water from unimproved sources, and the most recent vulnerable (hotspot) areas in the borders of the West and East Gojjam zones in the western Amhara region, Zone one in southern Afar region, and Liben, Afder, Shebelle, Korahe, and Nobob zones in Somali region were identified. In conclusion, this study reveals significant geographic inequalities in the use of improved drinking water sources. This may be necessary for policies and coverage targeting the most vulnerable regions. The presented map and analytical approaches can provide a mechanism to monitor future reductions in inequality within countries by reflecting resource allocation priorities.