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

被引:2
作者
Azongnibo, Konan R. M. [1 ,2 ]
Guindo-Coulibaly, Negnorogo [3 ]
Bonnet, Emmanuel [4 ]
Kokro-Djahouri, Maimouna N. W. [2 ,3 ]
Assouho, Konan F. [2 ,3 ]
Niamke, Mathieu G. [1 ]
Fournet, Florence [5 ]
Anoh, Paul K. [1 ]
Assi, Serge-Brice [2 ]
Adja, Akre M. [2 ,3 ]
机构
[1] Univ Felix Houphouet Boigny, Inst Geog Trop, Abidjan, Cote Ivoire
[2] Inst Natl Sante Publ, Ctr Rech Pierre Richet, Bouake, Cote Ivoire
[3] Univ Felix Houphouet Boigny, UFR Biosci, Abidjan, Cote Ivoire
[4] Univ Paris, Univ Paris Pantheon Sorbonne 1, AgroParisTech Inst Rech Dev, PRODIG,CNRS,IRD, Paris, France
[5] Univ Montpellier, Inst Rech Dev, MIVEGEC, IRD,CNRS, Montpellier, France
关键词
Cote d'Ivoire; malaria; spatiotemporal analysis; TRANSMISSION; HEALTH;
D O I
10.1093/trstmh/trac112
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
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 Cote 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 Cote 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 parts per thousand to 229.8 parts per thousand. 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 Cote 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.
引用
收藏
页码:301 / 309
页数:9
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