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Small-area spatial statistical analysis of malaria clusters and hotspots in Cameroon;2000–2015
Authors: Tewara MA, Mbah-Fongkimeh PN, Dayimu A, Kang F, and Xue F
Source: BMC Infectious Diseases , 18(1): 636; DOI: 10.1186/s12879-018-3534-6
Topic(s): GIS/GPS
Malaria
Rural-urban differentials
Country: Africa
  Cameroon
Published: DEC 2018
Abstract: BACKGROUND: Malaria prevalence in Cameroon is a major public health problem both at the regional and urban-rural geographic scale. In 2016, an estimated 1.6 million confirmed cases, and 18,738 cases were reported in health facilities and communities respectively, with about 8000 estimated deaths. Several studies have estimated malaria prevalence in Cameroon using the analytical techniques at the regional scale. We aimed at identifying malaria clusters and hotspots at the urban-rural geographic scale from the Demographic and Health Survey (DHS) data for households between 2000 and 2015 using ArcGIS for intervention programs. METHODS: To identify malaria hotspots and analyze the pattern of distribution, we used the optimized hotspots toolset and spatial autocorrelation respectively in ArcGIS 10.3 for desktop. We also used Pearson's Correlation analysis to identify associative environmental factors using the R-software 3.4.1. RESULTS: The spatial distribution of malaria showed statistically significant clustered pattern for the year 2000 and 2015 with Moran's indexes 0.126 (P?
Web: https://bmcinfectdis.biomedcentral.com/track/pdf/10.1186/s12879-018-3534-6