Dataset Information

Childhood Diarrhea Exhibits Spatiotemporal Variation in Northwest Ethiopia: A SaTScan Spatial Statistical Analysis.

ABSTRACT:

Background

Childhood diarrhea continues to be a public health problem in developing countries, including Ethiopia. Detecting clusters and trends of childhood diarrhea is important to designing effective interventions. Therefore, this study aimed to investigate spatiotemporal clustering and seasonal variability of childhood diarrhea in northwest Ethiopia.

Methods

Retrospective record review of childhood diarrhea was conducted using quarterly reported data to the district health office for the seven years period beginning July 1, 2007. Thirty three districts were included and geo-coded in this study. Spatial, temporal and space-time scan spatial statistics were employed to identify clusters of childhood diarrhea. Smoothing using a moving average was applied to visualize the trends and seasonal pattern of childhood diarrhea. Statistical analyses were performed using Excel® and SaTScan programs. The maps were plotted using ArcGIS 10.0.

Results

Childhood diarrhea in northwest Ethiopia exhibits statistical evidence of spatial, temporal, and spatiotemporal clustering, with seasonal patterns and decreasing temporal trends observed in the study area. A most likely purely spatial cluster was found in the East Gojjam administrative zone of Gozamin district (LLR = 7123.89, p <0.001). The most likely spatiotemporal cluster was detected in all districts of East Gojjam zone and a few districts of the West Gojjam zone (LLR = 24929.90, p<0.001), appearing from July 1, 2009 to June 30, 2011. One high risk period from July 1, 2008 to June 30, 2010 (LLR = 9655.86, p = 0.001) was observed in all districts. Peak childhood diarrhea cases showed a seasonal trend, occurring more frequently from January to March and April to June.

Conclusion

Childhood diarrhea did not occur at random. It has spatiotemporal variation and seasonal patterns with a decreasing temporal trend. Accounting for the spatiotemporal variation identified in the study areas is advised for the prevention and control of diarrhea.

SUBMITTER: Azage M

PROVIDER: S-EPMC4687002 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Publications

Childhood Diarrhea Exhibits Spatiotemporal Variation in Northwest Ethiopia: A SaTScan Spatial Statistical Analysis.

Azage Muluken M Kumie Abera A Worku Alemayehu A Bagtzoglou Amvrossios C AC

PloS one 20151221 12

<h4>Background</h4>Childhood diarrhea continues to be a public health problem in developing countries, including Ethiopia. Detecting clusters and trends of childhood diarrhea is important to designing effective interventions. Therefore, this study aimed to investigate spatiotemporal clustering and seasonal variability of childhood diarrhea in northwest Ethiopia.<h4>Methods</h4>Retrospective record review of childhood diarrhea was conducted using quarterly reported data to the district health off ...[more]

PMID: 26690058

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Project description:BackgroundDespite improvements in prevention efforts, childhood diarrhea remains a public health concern. However, there may be substantial variation influenced by place, time, and season. Description of diarrheal clusters in time and space and understanding seasonal patterns can improve surveillance and management. The present study investigated the spatial and seasonal distribution and purely spatial, purely temporal, and space-time clusters of childhood diarrhea in Southern Ethiopia.MethodsThe study was a retrospective analysis of data from the Health Management Information System (HMIS) under-five diarrheal morbidity reports from July 2011 to June 2017 in Sidama Zone. Annual diarrhea incidence at district level was calculated. Incidence rate calculation and seasonal trend analysis were performed. The Kulldorff SaTScan software with a discrete Poisson model was used to identify statistically significant special, temporal, and space-time diarrhea clusters. ArcGIS 10.1 was used to plot the maps.ResultsA total of 202,406 under-five diarrheal cases with an annual case of 5822 per 100,000 under-five population were reported. An increasing trend of diarrhea incidence was observed over the 6 years with seasonal variation picking between February and May. The highest incidence rate (135.8/1000) was observed in the year 2016/17 in Boricha district. One statistically significant most likely spatial cluster (Boricha district) and six secondary clusters (Malga, Hulla, Aleta Wondo, Shebedino, Loka Abaya, Dale, and Wondogenet) were identified. One statistically significant temporal cluster (LLR = 2109.93, p < 0.001) during December 2013 to May 2015 was observed in all districts. Statistically significant spatiotemporal primary hotspot was observed in December 2012 to January 2015 in Malga district with a likelihood ratio of 1214.67 and a relative risk of 2.03. First, second, third, and fourth secondary hotspots occurred from January 2012 to May 2012 in Loka Abaya, December 2011 in Bursa, from March to April 2014 in Gorchie, and March 2012 in Wonsho districts.ConclusionChildhood diarrhea was not distributed randomly over space and time and showed an overall increasing trend of seasonal variation peaking between February and May. The health department and other stakeholders at various levels need to plan targeted interventional activities at hotspot seasons and areas to reduce morbidity and mortality.

Project description:Malaria is one of Ethiopia's most targeted communicable diseases for elimination. Malaria transmission varies significantly across space and time; and Ethiopia had space-time disparity in its transmission intensities. Considering heterogeneity and transmission intensity at the district level could play a crucial role in malaria prevention and elimination. This study aimed to explore temporal, spatial, and spatiotemporal clusters of malaria incidence in northwest Ethiopia. The analysis is based on monthly malaria surveillance data of districts and collected from the Amhara public health institute. The Kulldorff's retrospective space-time scan statistics using a discrete Poisson model were used to detect temporal, spatial, and space-time clusters of malaria incidence with and without adjusting the altitude + LLIN arm. Monthly malaria incidence had seasonal variations, and higher seasonal indices occurred in October and November. The temporal cluster occurred in the higher transmission season between September and December annually. The higher malaria incidence risk occurred between July 2012 and December 2013 (LLR = 414,013.41, RR = 2.54, P < 0.05). The purely spatial clustering result revealed that the most likely cluster occurred in the north and northwest parts of the region while secondary clusters varied in years. The space-time clusters were detected with and without considering altitude + LLIN arm. The most likely space-time cluster was concentrated in northwestern and western parts of the region with a high-risk period between July 2012 and December 2013 (LLR = 880,088.3, RR = 5.5, P < 0.001). We found eight significant space-time clusters using the altitude + LLIN arm. The most likely space-time cluster occurred in the western and northwestern parts of the region in July 2012-December 2013 (LLR = 886,097.7, RR = 5.55, P < 0.05). However, secondary clusters were located in eastern, northwestern, western parts of regions, which had different cases and relative risks in each cluster. Malaria transmission had temporal, spatial, and space-time variation in the region at the district level. Hence, considering these variations and factors contributing to malaria stratification would play an indispensable role in preventing and controlling practices that ultimately leads to malaria eliminations.

Project description:BackgroundThe global burden of febrile illness and the contribution of many fever inducing pathogens have been difficult to quantify and characterize. However, in sub-Saharan Africa it is clear that febrile illness is a common cause of hospital admission, illness and death including in Ethiopia. Therefore the major aim of this study is to explore the spatial variation and associated factors of childhood febrile illness among under-five children in Ethiopia.MethodsThis study were based on the 2016 Ethiopian Demographic health survey data. A total weighted sample of 10,127 under- five children was included. Data management was done using Stata version-14, Arc-GIS version-10.8 and SatsScan version- 9.6 statistical software. Multi-level log binomial model was fitted to identify factors associated with childhood febrile illness. Variables with a p-value < 0.2 in the bi-variable analysis were considered for the multivariable analysis. In the multivariable multilevel log binomial regression analysis p-value< 0.05, the APR with the 95% CI was reported. Global spatial autocorrelation was done to assess the spatial pattern of childhood febrile illness. Spatial regression was done to identify factors associated with the spatial variations of childhood febrile illness and model comparison was based on adjusted R2 and AICc.ResultThe prevalence of febrile illness among under-five children was 13.6% (95% CI: 12.6%, 14 .7%) with significant spatial variation across regions of Ethiopia with Moran's I value of 0.148. The significant hotspot areas of childhood febrile illness were identified in the Tigray, Southeast of Amhara, and North SNPPR. In the GWR analysis, the proportion of PNC, children who had diarrhea, ARI, being 1st birth order, were significant explanatory variables. In the multilevel log binomial regression age of children 7-24 months(APR = 1.33, 95% CI: (1.03, 1.72)), maternal age 30-39 years (APR = 1.36 95% CI: 1.02, 1.80)), number of children (APR = 1.78, 95% CI: 0.96, 3.3), diarrhea(APR = 5.3% 95% CI: (4.09, 6.06)), ARI (APR = 11.5, 95% CI: (9.2, 14.2)) and stunting(APR = 1.21; 95% CI: (0.98, 1.49) were significantly associated with childhood febrile illness.ConclusionChildhood febrile illness remains public health problem in Ethiopia. On spatial regression analysis proportion of women who had PNC, proportion of children who had diarrhea, proportion of children who had ARI, and proportion of children who had being 1st birth order were associated factors. The detailed map of childhood febrile illness and its predictors could assist health program planners and policy makers to design targeted public health interventions for febrile illness.

Project description:IntroductionInstitutional delivery is crucial to reduce maternal and neonatal mortality as well as serious morbidities. However, in Ethiopia, home delivery (attended by an unskilled birth attendant) after antenatal care (ANC) visit is highly in practice. Therefore, this study aimed to assess the spatial variation and determinants of home delivery after antenatal care visits in Ethiopia.MethodA secondary data analysis was conducted using the 2019 mini Ethiopian demographic and health survey. A total of 2,923 women who had ANC visits were included. Spatial analysis was done by using GIS 10.7 and SaTscan 9.6. The risk areas for home delivery from GIS and spatial scan statistics results were reported. A multi-level logistic regression model was fitted using Stata14 to identify individual and community-level factors associated with home delivery after ANC visit. Finally, AOR with 95% CI and random effects were reported.ResultHome delivery after ANC visit was spatially clustered in Ethiopia(Moran's index = 0.52, p-value <0.01). The primary clusters were detected in Oromia and SNNP region (LLR = 37.48, p < 0.001 and RR = 2.30) and secondary clusters were located in Benishangul Gumuz, Amhara, Tigray and Afar (LLR = 29.45, p<0.001 and RR = 1.54). Being rural resident (AOR = 2.52; 95%CI 1.09-5.78), having no formal education (AOR = 3.19;95% CI 1.11-9.16), being in the poor (AOR = 2.20;95%CI 1.51-3.22) and middle wealth index (AOR = 2.07;95% CI 1.44-2.98), having one ANC visit (AOR = 2.64; 95% CI 1.41-4.94), and living in the agrarian region (AOR = 3.63; 95%CI 1.03-12.77) had increased the odds of home delivery after ANC visit.Conclusion and recommendationHome delivery after ANC visit was spatially clustered in Ethiopia. Factors like maternal education, wealth index, number of ANC visits, residency and region were significantly associated with home delivery after ANC visit. Therefore, it is better to increase the number of ANC contact by giving health education, especially for women with low levels of education and better to improve the wealth status of women. A special strategy is also vital to reduce home delivery after ANC visit in those high-risk regions.

Project description:BackgroundViral gastroenteritis belongs to the major public health problems of infant and children worldwide. The largest proportion of morbidity and mortality occurs in Sub-Saharan Africa.PurposeAimed to assess the burden and genetic diversity of enteric viruses among children with diarrhea.Patients and methodsA cross-sectional study was undertaken from December 2015 to April 2016 in Debre Tabor. A total of thirty-eight children, who presented with diarrhea at Debre Tabor health centers, were included. Fecal samples were collected and screened for enteric viruses by RT-PCR. Data were analyzed using SPSS software. Descriptive summary techniques were used to display the findings.ResultsOut of thirty-eight children screened, 52.6% were positive for at least one enteric virus. Six (30.0%) of the children had mixed enteric virus infections. Human adenovirus (HAdV) 7 (18.4%) was predominant followed by noroviruses (NoVs) 5 (13.2%), enterovirus (EV) 5 (13.2%), rotavirus A (RVA) 4 (10.5%), human astrovirus (HAstV) 2 (5.3%), and human parechovirus (HPeV) 1 (2.6%). Overall, nineteen different types of enteric virus genotypes were identified. Diverse adenovirus within species A (HAdV-12,-31), B (HAdV-3), C (HAdV-2), and F (HAdV-4) were detected. Norovirus II (GII.4 and GII.6) and norovirus I (GI.2, GI.3, and GI.5) genotypes were found. Sapovirus genotypes within genogroup II (GII.1, GII.5, and GII.6) were identified. Wild-type rotavirus G9 and P[8] genotypes were detected in one of the rotavirus positive samples. Non-polio enteroviruses within species A (coxsackie A virus (CAV) 5, CAV6, and CAV14) and C (enterovirus (EV-C) 99) were also identified. In two of the fecal samples classic HAstV-2 was detected.ConclusionDiverse enteric viruses were detected in fecal samples from under-five children with diarrhea. The detection of heterogeneous enteric viruses in this small data set highlights the need for extended multicenter studies to describe the burden and genetic diversity of enteric virus.

Project description:BACKGROUND:Understanding the geographical distribution of multidrug-resistant tuberculosis (MDR-TB) in high TB burden countries such as Ethiopia is crucial for effective control of TB epidemics in these countries, and thus globally. We present the first spatial analysis of multidrug resistant tuberculosis, and its relationship to socio-economic, demographic and household factors in northwest Ethiopia. METHODS:An ecological study was conducted using data on patients diagnosed with MDR-TB at the University of Gondar Hospital MDR-TB treatment centre, for the period 2010 to 2015. District level population data were extracted from the Ethiopia National and Regional Census Report. Spatial autocorrelation was explored using Moran's I statistic, Local Indicators of Spatial Association (LISA), and the Getis-Ord statistics. A multivariate Poisson regression model was developed with a conditional autoregressive (CAR) prior structure, and with posterior parameters estimated using a Bayesian Markov chain Monte Carlo (MCMC) simulation approach with Gibbs sampling, in WinBUGS. RESULTS:A total of 264 MDR-TB patients were included in the analysis. The overall crude incidence rate of MDR-TB for the six-year period was 3.0 cases per 100,000 population. The highest incidence rate was observed in Metema (21 cases per 100,000 population) and Humera (18 cases per 100,000 population) districts; whereas nine districts had zero cases. Spatial clustering of MDR-TB was observed in districts located in the Ethiopia-Sudan and Ethiopia-Eritrea border regions, where large numbers of seasonal migrants live. Spatial clustering of MDR-TB was positively associated with urbanization (RR: 1.02; 95%CI: 1.01, 1.04) and the percentage of men (RR: 1.58; 95% CI: 1.26, 1.99) in the districts; after accounting for these factors there was no residual spatial clustering. CONCLUSION:Spatial clustering of MDR-TB, fully explained by demographic factors (urbanization and percent male), was detected in the border regions of northwest Ethiopia, in locations where seasonal migrants live and work. Cross-border initiatives including options for mobile TB treatment and follow up are important for the effective control of MDR-TB in the region.

Dataset Information

Childhood Diarrhea Exhibits Spatiotemporal Variation in Northwest Ethiopia: A SaTScan Spatial Statistical Analysis.

Background

Methods

Results

Conclusion

Publications

Childhood Diarrhea Exhibits Spatiotemporal Variation in Northwest Ethiopia: A SaTScan Spatial Statistical Analysis.

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