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尼日利亚霍乱模式的地理空间分析:一项横断面研究的结果。

Geospatial analysis of cholera patterns in Nigeria: findings from a cross-sectional study.

机构信息

Department of Geography and Environmental Management, University of Waterloo, 200 University Avenue West, Waterloo, ON, N2L 3G1, Canada.

出版信息

BMC Infect Dis. 2021 Feb 23;21(1):202. doi: 10.1186/s12879-021-05894-2.

DOI:10.1186/s12879-021-05894-2
PMID:33622264
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7903613/
Abstract

BACKGROUND

Persistence of cholera outbreaks in developing countries calls for concern and more targeted intervention measures for long-term control. This research undertook spatial analysis of cholera incidence in Nigeria over a seventeen-year period to determine the existence of regional hotspots and predictors.

METHODS

A cross-sectional study design was used for the research. Cholera data for each of the thirty-six states and the federal capital territory (FCT) were obtained from the Nigeria Centre for Disease Control (NCDC) of the Federal Ministry of Health, Nigeria. Socioeconomic data including proportion of households using solid waste disposal (unapproved dumpsite, refuse burying, refuse burning, public dumpsite, and refuse collectors), water sources (pipe borne water, well, borehole, rain water, surface waters and water vendors), sewage disposal (water closet, pit latrines, bucket/pan, public toilet and nearby bush/stream), living in a single room and earning less than minimum wage (18,000 naira) were obtained from National Population Commission. On the other hand, proportion of illiterate adults (15 years and above) and poor people; and population density were obtained from National Bureau of Statistics. Each socioeconomic data was obtained at state level. Cholera patterns were analysed at state level using Global Moran's I while specific locations of cholera clusters were determined using Local Moran's I. Stepwise multiple regression was used to determine socioeconomic predictors of cholera incidence.

RESULTS

Local Moran's I revealed significant cluster patterns in 1999, 2001, 2002, 2009 and 2010 in Adamawa, Gombe, Katsina, Bauchi, Borno, Yobe, and Kano states. Households using surface water was the significant predictor (23%) of the observed spatial variations in cholera incidence.

CONCLUSIONS

Persistence of cholera outbreaks in some north east and north western states calls for more targeted, long-term and effective intervention measures especially on provision of safe sources of water supply by government and other stakeholders.

摘要

背景

发展中国家霍乱疫情的持续存在令人担忧,需要采取更有针对性的干预措施来进行长期控制。本研究对尼日利亚十七年来的霍乱发病率进行了空间分析,以确定是否存在区域性热点和预测因素。

方法

本研究采用了横断面研究设计。从尼日利亚联邦卫生部的尼日利亚疾病控制中心(NCDC)获得了尼日利亚 36 个州和联邦首都特区(FCT)的霍乱数据。从尼日利亚国家人口委员会获得了包括家庭使用固体废物处理方式(未经批准的垃圾场、垃圾掩埋、垃圾焚烧、公共垃圾场和垃圾收集者)、水源(管道水、井、钻孔、雨水、地表水和水供应商)、污水排放(坐便器、坑式厕所、桶/盆、公共厕所和附近的灌木丛/溪流)、居住在一个房间和收入低于最低工资(18,000 奈拉)等方面的社会经济数据。另一方面,从国家统计局获得了成年人(15 岁及以上)文盲率和贫困人口率以及人口密度数据。在州一级获得了每一个社会经济数据。利用全局 Moran's I 分析了各州的霍乱模式,利用局部 Moran's I 确定了霍乱集群的具体位置。采用逐步多元回归分析确定了霍乱发病率的社会经济预测因素。

结果

局部 Moran's I 显示,在 1999 年、2001 年、2002 年、2009 年和 2010 年,阿达马瓦、贡贝、卡齐纳、包奇、博尔诺、约贝和卡诺州存在显著的集群模式。使用地表水是霍乱发病率观测空间变化的显著预测因素(23%)。

结论

东北部和西北部一些州的霍乱疫情持续存在,需要政府和其他利益相关者采取更有针对性、长期和有效的干预措施,特别是提供安全的供水来源。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0787/7903613/6b71db41658f/12879_2021_5894_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0787/7903613/e8e398ef04fa/12879_2021_5894_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0787/7903613/3714e8171c39/12879_2021_5894_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0787/7903613/0baf48bb00ba/12879_2021_5894_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0787/7903613/e42b26cbaadf/12879_2021_5894_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0787/7903613/6b71db41658f/12879_2021_5894_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0787/7903613/e8e398ef04fa/12879_2021_5894_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0787/7903613/3714e8171c39/12879_2021_5894_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0787/7903613/0baf48bb00ba/12879_2021_5894_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0787/7903613/e42b26cbaadf/12879_2021_5894_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0787/7903613/6b71db41658f/12879_2021_5894_Fig5_HTML.jpg

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