一项为期七年的疟疾流行病学监测显示,旅行和性别是肯尼亚耐药基因型传播的主要驱动因素。

A seven-year surveillance of epidemiology of malaria reveals travel and gender are the key drivers of dispersion of drug resistant genotypes in Kenya.

作者信息

Maraka Moureen, Akala Hoseah M, Amolo Asito S, Juma Dennis, Omariba Duke, Cheruiyot Agnes, Opot Benjamin, Okello Okudo Charles, Mwakio Edwin, Chemwor Gladys, Juma Jackline A, Okoth Raphael, Yeda Redemptah, Andagalu Ben

机构信息

School of Health Sciences, Jaramogi Oginga Odinga University of Science and Technology, Bondo, Siaya, Kenya.

Department of Emerging Infectious Diseases (DEID), United States Army Medical Research Directorate-Africa Kenya (USAMRD-A Kenya)/Kenya Medical Research Institute (KEMRI), Kisumu, Kisumu, Kenya.

出版信息

PeerJ. 2020 Mar 12;8:e8082. doi: 10.7717/peerj.8082. eCollection 2020.

Abstract

Malaria drug resistance is a global public health concern. Though parasite mutations have been associated with resistance, other factors could influence the resistance. A robust surveillance system is required to monitor and help contain the resistance. This study established the role of travel and gender in dispersion of chloroquine resistant genotypes in malaria epidemic zones in Kenya. A total of 1,776 individuals presenting with uncomplicated malaria at hospitals selected from four malaria transmission zones in Kenya between 2008 and 2014 were enrolled in a prospective surveillance study assessing the epidemiology of malaria drug resistance patterns. Demographic and clinical information per individual was obtained using a structured questionnaire. Further, 2 mL of blood was collected for malaria diagnosis, parasitemia quantification and molecular analysis. DNA extracted from dried blood spots collected from each of the individuals was genotyped for polymorphisms in chloroquine transporter gene ( 76), multidrug resistant gene 1 (1 86 and 1 184) regions that are putative drug resistance genes using both conventional polymerase chain reaction (PCR) and real-time PCR. The molecular and demographic data was analyzed using Stata version 13 (College Station, TX: StataCorp LP) while mapping of cases at the selected geographic zones was done in QGIS version 2.18. Chloroquine resistant (CQR) genotypes across gender revealed an association with chloroquine resistance by both univariate model ( = 0.027) and by multivariate model ( = 0.025), female as reference group in both models. Prior treatment with antimalarial drugs within the last 6 weeks before enrollment was associated with carriage of CQR genotype by multivariate model ( = 0.034). Further, a significant relationship was observed between travel and CQR carriage both by univariate model ( = 0.001) and multivariate model ( = 0.002). These findings suggest that gender and travel are significantly associated with chloroquine resistance. From a gender perspective, males are more likely to harbor resistant strains than females hence involved in strain dispersion. On the other hand, travel underscores the role of transport network in introducing spread of resistant genotypes, bringing in to focus the need to monitor gene flow and establish strategies to minimize the introduction of resistance strains by controlling malaria among frequent transporters.

摘要

疟疾耐药性是一个全球公共卫生问题。虽然寄生虫突变与耐药性有关,但其他因素也可能影响耐药性。需要一个强大的监测系统来监测并帮助控制耐药性。本研究确定了旅行和性别在肯尼亚疟疾流行区氯喹耐药基因型传播中的作用。2008年至2014年期间,从肯尼亚四个疟疾传播区选定的医院中,共有1776名出现非复杂性疟疾的个体参加了一项前瞻性监测研究,评估疟疾耐药模式的流行病学情况。使用结构化问卷获取每个个体的人口统计学和临床信息。此外,采集2毫升血液用于疟疾诊断、疟原虫血症定量和分子分析。从每个个体采集的干血斑中提取的DNA,使用传统聚合酶链反应(PCR)和实时PCR对氯喹转运蛋白基因(76)、多药耐药基因1(186和1184)区域中的多态性进行基因分型,这些区域是假定的耐药基因。使用Stata 13版软件(德克萨斯州大学站:StataCorp LP公司)分析分子和人口统计学数据,同时在QGIS 2.18版软件中对选定地理区域的病例进行绘图。按性别划分的氯喹耐药(CQR)基因型,在单变量模型(P = 0.027)和多变量模型(P = 0.025)中均显示与氯喹耐药有关,两个模型均以女性作为参照组。在入组前最后6周内接受抗疟药物治疗与多变量模型中CQR基因型的携带有关(P = 0.034)。此外,在单变量模型(P = 0.001)和多变量模型(P = 0.002)中,均观察到旅行与CQR携带之间存在显著关系。这些发现表明,性别和旅行与氯喹耐药性显著相关。从性别角度来看,男性比女性更有可能携带耐药菌株,因此参与了菌株传播。另一方面,旅行凸显了交通网络在引入耐药基因型传播方面的作用,这使得有必要关注监测基因流动,并制定策略,通过控制频繁旅行者中的疟疾来尽量减少耐药菌株的引入。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f9e/7073242/967f6c594638/peerj-08-8082-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索