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

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.

Spatial, temporal, and spatiotemporal cluster detection of malaria incidence in Southwest Ethiopia

Background

Malaria is a major global health hazard, particularly in developing countries such as Ethiopia, where it contributes to high morbidity and mortality rates. According to reports from the South Omo Zone Health Bureau, despite various interventions such as insecticide-treated bed nets and indoor residual spraying, the incidence of malaria has increased in recent years. Therefore, this study aimed to assess the spatial, temporal, and spatiotemporal variation in malaria incidence in the South Omo Zone, Southwest Ethiopia.

Methods

A retrospective study was conducted using 4 years of malaria data from the South Omo Zone District Health Information Software (DHIS). The incidence rate of malaria per 1,000 people was calculated using Microsoft Excel software. Kulldorff SaTScan software with a discrete Poisson model was used to identify statistically significant spatial, temporal, and spatiotemporal malaria clusters. Graduated color maps depicting the incidence of malaria were generated using ArcGIS 10.7 software.

Results

Spatial clusters were identified in the districts of Dasenech (RR = 2.06, p < 0.0001), Hamer (RR = 1.90, p < 0.0001), Salamago (RR = 2.00, p < 0.0001), Bena Tsemay (RR = 1.71, p < 0.0001), Malie (RR = 1.50, p < 0.0001), Nyngatom (RR = 1.91, p < 0.0001) and North Ari (RR = 1.05, p < 0.0001) during the period from 08th July 2019 to 07th July 2023. A temporal cluster was identified as the risk period across all districts between 08th July 2022 and 07th July 2023 (RR = 1.59, p = 0.001). Spatiotemporal clusters were detected in Dasenech (RR = 2.26, p < 0.001) Salamago, (RR = 2.97, p < 0.001) Hamer (RR = 1.95, p < 0.001), Malie (RR = 2.03, p < 0.001), Bena Tsemay (RR = 1.80, p < 0.001), Nyngatom (RR = 2.65, p < 0.001), North Ari (RR = 1.50, p < 0.001), and Jinka town (RR = 1.19, p < 0.001).

Conclusion

Significant spatial, temporal, and spatiotemporal clusters in malaria incidence were identified in the South Omo Zone. To better understand the factors contributing to these high-risk areas, further research is needed to explore individual, household, geographical, and climatic factors. Targeted interventions based on these findings could help reduce malaria incidence and associated risks in the region.

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.

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.

Spatial analysis of food and water-borne diseases in Ahmedabad, India: Implications for urban public health planning

Spatial analysis of infectious diseases can play an important role in mapping the spread of diseases and can support policy making at local level. Moreover, identification of disease clusters based on local geography and landscape forms the basis for disease control and prevention. Therefore, this study aimed to examine the spatial-temporal variations, hotspot areas, and potential risk factors of infectious diseases (including Viral Hepatitis, Typhoid and Diarrhea) in Ahmedabad city of India. We used Moran's I and Local Indicators of Spatial Association (LISA) mapping to detect spatial clustering of diseases. Spatial and temporal regression analysis was used to identify the association between disease incidence and spatial risk factors. The Moran's I statistics identified presence of positive spatial autocorrelation within the considered diseases, with Moran's I from 0.09 for typhoid to 0.21 for diarrhea (p < 0.001). This indicates a clustering of affected wards for each disease, suggesting that cases were not randomly distributed across the city. LISA mapping demonstrated the clustering of hotspots in central regions of the city, especially towards the east of the river Sabarmati, highlighting key geographical areas with elevated disease risk. The spatial clusters of infectious diseases were consistently associated with slum population density and illiteracy. Furthermore, temporal analysis suggested illiteracy rates could increase risk of viral hepatitis by 13 % (95 % Confidence Interval (CI): 1.01-1.26) and of diarrhea by 18 % (95 % CI: 1.07-1.31). Significant inverse association was also seen between viral hepatitis incidence and the distance of wards from rivers. Conclusively, the study highlight the impact of socio-economic gradients, such as slum population density (indicative of poverty) and illiteracy, on the localized transmission of water and foodborne infections. The evident social stratification between impoverished and affluent households emerges as a notable contributing factor and a potential source of differences in the dynamics of infectious diseases in Ahmedabad.

Spatiotemporal distribution of climate-sensitive disease incidences in ethiopia: a longitudinal retrospective analysis of Malaria, Meningitis, Cholera, Dysentery, Leishmaniasis and Dengue fever between 2010 and 2022/2023

BACKGROUND

Understanding the temporal and geographic distribution of disease incidences is crucial for effective public health planning and intervention strategies. This study presents a comprehensive analysis of the spatiotemporal distribution of disease incidences in Ethiopia, focusing on six major diseases: Malaria, Meningitis, Cholera and Dysentery, over the period from 2010 to 2022, whereas Dengue Fever and Leishmaniasis from 2018 to 2023.

METHODS

Using data from Ethiopian public health institute: public health emergency management (PHEM), and Ministry of Health, we examined the occurrence and spread of each disease across different regions of Ethiopia. Spatial mapping and time series analysis were employed to identify hotspots, trends, and seasonal variations in disease incidence.

RESULTS

The findings reveal distinct patterns for each disease, with varying cases and temporal dynamics. Monthly wise, Malaria exhibits a cyclical pattern with a peak during the rainy and humid season, while Dysentery, Meningitis and Cholera displays intermittent incidences. Dysentery cases show a consistent presence throughout the years, while Meningitis remains relatively low in frequency but poses a potential threat due to its severity. Dengue fever predominantly occurs in the eastern parts of Ethiopia. A significant surge in reported incident cases occurred during the years 2010 to 2013, primarily concentrated in the Amhara, Sidama, Oromia, Dire Dawa, and Benishangul-Gumuz regions.

CONCLUSIONS

This study helps to a better understanding of disease epidemiology in Ethiopia and can serve as a foundation for evidence-based decision-making in disease prevention and control. By recognizing the patterns and seasonal changes associated with each disease, health authorities can implement proactive measures to mitigate the impact of outbreaks and safeguard public health in the region.

Epidemiological characteristics and spatio-temporal analysis of brucellosis in Shandong province, 2015-2021

BACKGROUND

Brucellosis is one of the major public health problems in China, it not only causes huge economic losses to the society, but also threatens the human's physical and mental health. The reported cases of brucellosis in Shandong province were at a high level, therefore, it is necessary for us to understand the epidemic characteristics and distribution trend of Brucellosis in Shandong province. This study aims to describe the epidemiological characteristics and spatial clustering characteristics of brucellosis in Shandong Province, provide a reference for the scientific prevention and control.

METHODS

Human brucellosis data in Shandong province from 2015 to 2021 were obtained from the China Information System for Disease Control and Prevention, the data were analyzed by descriptive epidemiological methods, spatial autocorrelation analysis and spatial-temporal cluster analysis methods use ArcGIS and SaTScan software, the results were presented in ArcMap.

RESULTS

A total of 22,251 human cases of brucellosis were reported, the annual incidence ranged between 2.41/100,000 and 4.07/100,000 from 2015 to 2021 in Shandong province, incidence has been decreasing year by year, while there was a significant increase in 2021. The distribution of brucellosis was of a seasonal trend, mainly concentrating during March to August. The age of the cases was mainly concentrated in the 30-74 age ranges, the average annual incidence rate was significantly higher in males than in females. The spatial analysis showed that the epidemics were mainly concentrated in the north and southwest. For the spatial autocorrelation analysis, a high global autocorrelation was observed at the county level, and the high-high clusters mainly distributed in the north and southwest region. For the spatio-temporal scanning, the most likely cluster areas mainly distributed in the north area, and then gradually moved southward, and the radius of clustered narrowed.

CONCLUSIONS

Human brucellosis remains a common challenge, particularly in northern region in spring and summer. More disease prevention and control measures should be taken in high-risk populations, and such higher-risk susceptible areas to reduce the incidence of brucellosis and ensure the health of the people.

One size does not fit all: an application of stochastic modeling to estimating primary healthcare needs in Ethiopia at the sub-national level

BACKGROUND

Primary healthcare systems require adequate staffing to meet the needs of their local population. Guidelines typically use population ratio targets for healthcare workers, such as Ethiopia's goal of two health extension workers for every five thousand people. However, fixed ratios do not reflect local demographics, fertility rates, disease burden (e.g., malaria endemicity), or trends in these values. Recognizing this, we set out to estimate the clinical workload to meet the primary healthcare needs in Ethiopia by region.

METHODS

We utilize the open-source R package PACE-HRH for our analysis, which is a stochastic Monte Carlo simulation model that estimates workload for a specified service package and population. Assumptions and data inputs for region-specific fertility, mortality, disease burden were drawn from literature, DHS, and WorldPop. We project workload until 2035 for seven regions and two charted cities of Ethiopia.

RESULTS

All regions and charted cities are expected to experience increased workload between 2021 and 2035 for a starting catchment of five thousand people. The expected (mean) annual clinical workload varied from 2,930 h (Addis) to 3,752 h (Gambela) and increased by 19-28% over fifteen years. This results from a decline in per capita workload (due to declines in fertility and infectious diseases), overpowered by total population growth. Pregnancy, non-communicable diseases, sick child care, and nutrition remain the largest service categories, but their priority shifts substantially in some regions by 2035. Sensitivity analysis shows that fertility assumptions have major implications for workload. We incorporate seasonality and estimate monthly variation of up to 8.9% (Somali), though most services with high variability are declining.

CONCLUSIONS

Regional variation in demographics, fertility, seasonality, and disease trends all affect the workload estimates. This results in differences in expected clinical workload, the level of uncertainty in those estimates, and relative priorities between service categories. By showing these differences, we demonstrate the inadequacy of a fixed population ratio for staffing allocation. Policy-makers and regulators need to consider these factors in designing their healthcare systems, or they risk sub-optimally allocating workforce and creating inequitable access to care.

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.

Joint effect of water and sanitation practices on childhood diarrhoea in sub-Saharan Africa

BACKGROUND

Diarrhoea remains the major cause of morbidity and mortality of children under five years in Africa. Several studies have shown that inadequate and unsafe water, lack of sanitation, and poor hygiene practices are complex issues for different pathogens and accountable for the occurrence of diarrhoea diseases. We assessed the combined effect of household's source of drinking water and type of toilet facility and residential wellbeing on the incidence of childhood diarrhoea in 33 Sub-Saharan Africa countries while accounting for relevant compositional and contextual factors.

METHODS

The 2010-2019 datasets from the Demographic and Health Surveys were drawn for analyses. The outcome variable used in this study was the incidence of childhood diarrhoea. Three negative log-log generalized linear regression models were then sequentially fitted to the data to examine the joint effect of household water and sanitation practices on child diarrhoea. The results were presented using crude odds ratios (CORs) and adjusted odds ratios (AORs) at 95% confidence intervals (CIs). Using ArcGIS software, maps were design to unveil the spatial distribution of key variables.

FINDINGS

Approximately 16% of the 307,741 mothers interviewed reported an incidence of diarrhoea disease among children under-five years in their households. The results showed that a household depending on an unimproved source of drinking water and with an unimproved type of toilet facility was not significantly associated with childhood diarrhoea. However, those with improved drinking water but an unimproved type of toilet facility had higher odds of reporting childhood diarrhoea (AOR = 1.020, 95% CI = 1.003-1-036) compared to those in households with both improved source of drinking water and type of toilet facility. Across the geographical regions, Eastern (aOR = 1.102, 95% CI = 1.084-1.120) and Central Africa (aOR = 1.102, 95% CI = 1.083-1.121) were more likely to experience child diarrhoea.

CONCLUSION

Water and sanitation practices such as the source of drinking water and toilet facility, and geographic region had significant effects on childhood diarrhoea in sub-Saharan Africax. The findings suggest the need for multi-sectoral actions that recognise the geo-spatial and temporal characteristics identified in the study through regional to national policies. Water and sanitation community-based interventions that seek to improve equitable access to safe water and sanitation in the sub-region should be intensified.

Spatiotemporal analysis of pertussis in Hunan Province, China, 2009-2019

OBJECTIVES

This study aims to explore the spatial and spatiotemporal distribution of pertussis in Hunan Province, and provide a scientific basis for targeting preventive measures in areas with a high incidence of pertussis.

DESIGN

In this retrospective spatial and spatiotemporal (ecological) study, the surveillance and population data of Hunan Province from 2009 to 2019 were analysed. The ArcGIS V.10.3 software was used for spatial autocorrelation analysis and visual display, and SaTScan V.9.6 software was used for statistical analysis of spatiotemporal scan data.

SETTINGS

Confirmed and suspected pertussis cases with current addresses in Hunan Province and onset dates between 1 January 2009 and 31 December 2019 were included in the study.

PARTICIPANTS

The study used aggregated data, including 6796 confirmed and suspected pertussis cases.

RESULTS

The seasonal peak occurred between March and September, and scattered children were at high risk. The global Moran's I was between 0.107 and 0.341 (p<0.05), which indicated that the incidence of pertussis in Hunan had a positive spatial autocorrelation. The results of local indicators of spatial autocorrelation analysis showed that the hot spots were mainly distributed in the northeast region of Hunan Province. Moreover, both purely space and spatiotemporal scans showed that the central and northeastern parts were the most likely cluster areas with an epidemic period between March and October in 2018 and 2019.

CONCLUSION

The distribution of the pertussis epidemic in Hunan Province from 2009 to 2019 shows spatiotemporal clustering. The clustering areas of the pertussis epidemic were concentrated in the central and northeastern parts of Hunan Province between March and October 2018 and 2019. In areas with low pertussis incidence, the strengthening of the monitoring system may reduce under-reporting. In areas with high pertussis incidence where we could study whether the genes of endemic pertussis strains are mutated and differ from vaccine strains.

The effects of seasonal variations on household water security and burden of diarrheal diseases among under 5 children in an urban community, Southwest Nigeria

BACKGROUND

Household water security encompasses water-related factors that pose threats to public health at the household level. It presents a reliable access to water in sufficient quantity and quality towards meeting basic human needs. This study assessed the dynamics of seasonal variations in household water security and the association between household water security and diarrheal disease across dry and wet seasons in an urban settlement in Southwest Nigeria.

METHODS

A panel study design was employed to study 180 households selected using a multistage sampling technique. The selected households were studied during dry and rainy seasons. Household water security was assessed through the application of the all or none principle to 9 indicators associated with household water security. The intensity of water insecurity was also assessed using the nine indicators. The higher the number of indicators a household failed, the higher the intensity of household water insecurity. The association between the intensity of household water insecurity and the burden of diarrheal disease across the seasons was assessed using the Mantel-Haenszel test.

RESULTS

No household was water-secure in both dry and rainy seasons; however, the intensity of insecurity was more pronounced during the dry season compared with the rainy season. Ninety households (52.0%), had water insecurity intensity scores above fifty percentiles during the dry season while 21 (12.1%) households had a water insecurity score above the 50th percentile during raining season, p < 0.001. The burden of diarrheal disease was significantly higher among households with a water insecurity intensity score above the 50th percentile, 9 (8.1%) compared to households with a water insecurity intensity score below the 50th percentile 7 (3.0%), p = 0.034. There was no statistically significant association between the intensity of water insecurity and diarrheal disease burden across the dry and rainy seasons, p = 0.218.

CONCLUSION

The high burden of household water insecurity deserves concerted efforts from all concerned stakeholders, a panacea to an important health threat in the developing world.

Understanding Domestic Food Safety: An Investigation into Self-Reported Food Safety Practice and Associated Factors in Southern Ethiopian Households

BACKGROUND

According to available studies, 12%-20% of reported foodborne outbreaks start in the household. It is projected that 1 out of every 10 persons will become ill as a result of consuming tainted food. Poor food handling practices cause 600 million foodborne illnesses each year. In a given year, this leads to 420 000 deaths. In Ethiopia, there is a scarcity of studies on home-food-safety practices and the factors that affect them. This has resulted in a shortage of relevant information on the status of home-food-related illnesses in the country.

METHODS

A community-based cross-sectional study was carried out from May to June 23, 2021. A standardized and pre-tested questionnaire was used to collect data from 622 households. The total plate count method was used to analyze bacteria on cleaned plates. Epi data version 3.1 was used to enter data, while SPSS version 25 was used to analyze the data. Descriptive statistics and multivariable regression were used to characterize the data and identify factors associated with food safety practices.

RESULT

51.1% of the study participants had a safe food handling practice. The mean total plate count was 2.34 CFU/cm². In the multivariable regression, Household wealth (AOR = 2.05, 95% CI [1.01-3.16]), Education (AOR = 3.33, 95% CI [1.41-6.31]), Training (AOR = 2.85, 95% CI: [1.31-3.19]), Knowledge of safe practices (AOR = 1.95, 95% CI [1.23-3.08], and Attitude (AOR = 2.04, 95% CI [1.09, 3.82]) were associated with safe food handling practices.

CONCLUSION

Although data gathering systems for food-borne diseases typically overlook a large number of home-based outbreaks of sporadic infection, it is now widely understood that many episodes of food-borne sicknesses are caused by individuals' inappropriate food handling and preparation in their kitchens. In the current study, educational status, household wealth, food safety training, attitude, and knowledge about FBDs were found to be strongly associated with safe practices. This implies that public education is a key factor in improving food safety practices at home.

Human distribution and spatial-temporal clustering analysis of human brucellosis in China from 2012 to 2016

Background

Brucellosis is a major public health issue in China, while its temporal and spatial distribution have not been studied in depth. This study aims to better understand the epidemiology of brucellosis in the mainland of China, by investigating the human, temporal and spatial distribution and clustering characteristics of the disease.

Methods

Human brucellosis data from the mainland of China between 2012 and 2016 were obtained from the China Information System for Disease Control and Prevention. The spatial autocorrelation analysis of ArcGIS10.6 and the spatial-temporal scanning analysis of SaTScan software were used to identify potential changes in the spatial and temporal distribution of human brucellosis in the mainland of China during the study period.

Results

A total of 244 348 human brucellosis cases were reported during the study period of 2012–2016. The average incidence of human brucellosis was higher in the 40–65 age group. The temporal clustering analysis showed that the high incidence of brucellosis occurred between March and July. The spatial clustering analysis showed that the location of brucellosis clustering in the mainland of China remained relatively fixed, mainly concentrated in most parts of northern China. The results of the spatial-temporal clustering analysis showed that Heilongjiang represents a primary clustering area, and the Tibet, Shanxi and Hubei provinces represent three secondary clustering areas.

Conclusions

Human brucellosis remains a widespread challenge, particularly in northern China. The clustering analysis highlights potential high-risk human groups, time frames and areas, which may require special plans and resources to monitor and control the disease.

Using routine health information data for research in low- and middle-income countries: a systematic review

BACKGROUND

Routine health information systems (RHISs) support resource allocation and management decisions at all levels of the health system, as well as strategy development and policy-making in many low- and middle-income countries (LMICs). Although RHIS data represent a rich source of information, such data are currently underused for research purposes, largely due to concerns over data quality. Given that substantial investments have been made in strengthening RHISs in LMICs in recent years, and that there is a growing demand for more real-time data from researchers, this systematic review builds upon the existing literature to summarize the extent to which RHIS data have been used in peer-reviewed research publications.

METHODS

Using terms 'routine health information system', 'health information system', or 'health management information system' and a list of LMICs, four electronic peer-review literature databases were searched from inception to February 202,019: PubMed, Scopus, EMBASE, and EconLit. Articles were assessed for inclusion based on pre-determined eligibility criteria and study characteristics were extracted from included articles using a piloted data extraction form.

RESULTS

We identified 132 studies that met our inclusion criteria, originating in 37 different countries. Overall, the majority of the studies identified were from Sub-Saharan Africa and were published within the last 5 years. Malaria and maternal health were the most commonly studied health conditions, although a number of other health conditions and health services were also explored.

CONCLUSIONS

Our study identified an increasing use of RHIS data for research purposes, with many studies applying rigorous study designs and analytic methods to advance program evaluation, monitoring and assessing services, and epidemiological studies in LMICs. RHIS data represent an underused source of data and should be made more available and further embraced by the research community in LMIC health systems.

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

Under-five children (U5-children) diarrhea is a significant public health threat, where the World Health Organisation (WHO) reported it as the second leading cause of children's death worldwide. Nearly 1.7 billion cases occur annually with varied temporal and spatial factors. Identification of the spatiotemporal pattern and hotspot areas of U5-children diarrhea can assist targeted intervention and provide an early warning for more effective response measures. This study aimed at examining spatiotemporal variability along with the detection of hotspot areas for U5-children diarrhea in the Bench Maji Zone of southwestern Ethiopia, where resources are limited and cultural heterogeneity is highest. Retrospective longitudinal data of ten years of diarrhea records from January 2008 to December 2017 were used to identify hotspot areas. The incidence rate per 1,000 per year among children was calculated along with seasonal patterns of cases. The spatiotemporal analysis was made using SaTScan version 9.4, while spatial autocorrelations and hotspot identification were generated using ArcGIS 10.5 software. A total of 90,716 U5-children diarrhea cases were reported with an annual incidence rate of 36.1 per 1,000 U5-children, indicating a relative risk (RR) of 1.6 and a log-likelihood ratio (LLR) of 1,347.32 (p < 0.001). The highest incidence of diarrhea illness was recorded during the dry season and showed incidence rate increment from October to February. The risky clusters (RR > 1) were in the districts of Bero, Maji, Surma, Minit Shasha, Guraferda, Mizan Aman Town, and Sheko with annual cases of 127.93, 68.5, 65.12, 55.03, 55.67, 54.14 and 44.97 per 1,000, respectively. The lowest annual cases reported were in the four districts of Shay Bench, South Bench, North Bench, and Minit Goldiya, where RR was less than a unit. Six most likely clusters (Bero, Minit Shasha, Surma, Guraferda, South Bench, and Maji) and one lower RR area (North Bench) were hotspot districts. The U5-children's diarrhea in the study area showed an overall increasing trend during the dry seasons with non-random distribution over space and time. The data recorded during ten years and analyzed with the proper statistical tools helped to identify the hotspot areas with risky seasons where diarrhea could increase.