Abstract

BackgroundMalaria 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.MethodsTo 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.ResultsThe spatial distribution of malaria showed statistically significant clustered pattern for the year 2000 and 2015 with Moran’s indexes 0.126 (P < 0.001) and 0.187 (P < 0.001) respectively. Meanwhile, the years 2005 and 2010 with Moran’s indexes 0.001 (P = 0.488) and 0.002 (P = 0.318) respectively, had a random malaria distribution pattern. There exist varying degrees of malaria clusters and statistically significant hotspots in the urban-rural areas of the 12 administrative regions. Malaria cases were associated with population density and some environmental covariates; rainfall, enhanced vegetation index and composite lights (P < 0.001).ConclusionThis study identified urban-rural areas with high and low malaria clusters and hotspots. Our maps can be used as supportive tools for effective malaria control and elimination, and investments in malaria programs and research, malaria prevention, diagnosis and treatment, surveillance, should pay more attention to urban-rural geographic scale.

Highlights

  • Malaria prevalence in Cameroon is a major public health problem both at the regional and urban-rural geographic scale

  • Global Positioning System (GPS) data The GPS point data for each sampled urban-rural cluster residence was linked to all the households and individual level attributes such as survey information for Malaria Indicator Survey (MIS) and AIDS Indicator Survey to be analyzed with ArcGIS

  • General malaria distribution In this study, we looked at the average number of people per year suffering from malaria between the years 2000 and 2015

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Summary

Introduction

Malaria prevalence in Cameroon is a major public health problem both at the regional and urban-rural geographic scale. Tewara et al BMC Infectious Diseases (2018) 18:636 cases reported in health facilities and 18,738 cases at the community level and 8000 (6000-10,000) estimated deaths in 2016 [3]. Malaria intervention policies and control strategies in both the regional and urban-rural scales in Cameroon, have been reported to focus on the use of insecticide treated bed-nets (ITNs), indoor residual spray (IRS),larval control, diagnostic testing, treatments, disease surveillance, and national campaigns [3,4,5,6]. Malaria prevention strategies based on the use of ITNs and or IRS in Cameroon, has been a great method in the reduction of incident cases of the disease as about 13.6 million ITNs deliveries of the 80% ITNs deliveries in SSA, was made in Cameroon between 2014 and 2016 [1]

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