Spatiotemporal analysis of malaria incidence in Côte d'Ivoire from 2015 to 2019

Author:

Azongnibo Konan R M12ORCID,Guindo-Coulibaly Negnorogo3,Bonnet Emmanuel4,Kokro-Djahouri Maimouna N W23,Assouho Konan F23,Niamke Mathieu G1,Fournet Florence5ORCID,Anoh Paul K1,Assi Serge-Brice2,Adja Akré M23

Affiliation:

1. Institut de Géographie Tropicale, Université Félix Houphouët-Boigny , Abidjan , Côte d'Ivoire

2. Centre de Recherche Pierre Richet, Institut National de Santé Publique , Bouaké , Côte d'Ivoire

3. UFR Biosciences, Université Félix Houphouët Boigny , Abidjan , Côte d'Ivoire

4. PRODIG (CNRS, Université Paris 1 Panthéon-Sorbonne, Université de Paris, IRD, AgroParisTech) Institut de Recherche pour le Développement , Paris , France

5. MIVEGEC (Université Montpellier, IRD, CNRS), Institut de Recherche pour le Développement , Montpellier , France

Abstract

ABSTRACT Background The collection of malaria cases over time allows the identification of areas with the highest incidence. Our objective was to characterize the spatial distribution of malaria in Côte d’Ivoire from 2015 to 2019 at the health district level. Methods Data on the number of reported malaria cases confirmed by rapid diagnostic test (RDT) in the general population, the number of patients attending medical consultations and the total population by health district and year were collected from the National Malaria Control Program in Côte d’Ivoire. Crude and adjusted incidence rates were estimated for each health district and year. Adjusted incidence rates were used to perform global (Moran's index) and local indicators of spatial autocorrelation (LISA) analyses. Results Between 2015 and 2019, mean crude incidence rates increased from 155.5‰ to 229.8‰. We observed significant heterogeneity in malaria incidence rates across the study period and within a given year. The overall Moran index showed spatial autocorrelation for every year analysed except 2017. The LISA analysis showed that the health districts with high incidence rates were concentrated in the western zone of Côte d'Ivoire. Conclusions The use of spatial analyses to identify the areas with the highest malaria incidence rates is a relevant approach to optimize control measures in targeted areas.

Funder

National Malaria Control Program

Department of Informatics and Health Information

Publisher

Oxford University Press (OUP)

Subject

Infectious Diseases,Public Health, Environmental and Occupational Health,General Medicine,Parasitology

Reference29 articles.

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