Evidence map›Paper›PMID 26690058›Full record

ArticlePloS one2015

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

Muluken Azage, Abera Kumie, Alemayehu Worku, Amvrossios C Bagtzoglou

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Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 1 of them a synthesis that pooled it.

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44citing papers in PubMed, 1 pooled it
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

44 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  11. Spatiotemporal analysis of diarrhea-related hospitalizations of children in Brazil's Midwest region from 2011 to 2020.Revista brasileira de epidemiologia = Brazilian journal of epidemiology · 2024
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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Muluken AzageEthiopian Institute of Water Resources, Addis Ababa University, Addis Ababa, Ethiopia.
Abera KumieSchool of Public Health, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia.
Alemayehu WorkuSchool of Public Health, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia.
Amvrossios C BagtzoglouDepartment of Civil and Environmental Engineering, School of Engineering, University of Connecticut, Storrs, CT 06269, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundChildhood 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.

methodsRetrospective 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.

resultsChildhood 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.

conclusionChildhood 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.

Indexed as

Models, BiologicalAdolescentChildChild, PreschoolDiarrheaEthiopiaFemaleHumansInfantMaleRetrospective Studies

Identifiers

PMID26690058
PMCPMC4687002

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.