Molecular surveillance of antimalarial partner drug resistance in sub-Saharan Africa: a spatial-temporal evidence mapping study.
Molecular surveillance of antimalarial partner drug resistance in sub-Saharan Africa: a spatial-temporal evidence mapping study.
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DOI：
10.1016/s2666-5247(20)30094-x
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发表时间：
2020-09
期刊：
影响因子：
--
通讯作者：
Parikh S
中科院分区：
文献类型：
--
作者：
Ehrlich HY;Jones J;Parikh S
抗疟药物耐药性的分子标记可用于快速监测青蒿素类复方疗法耐药性的出现和空间分布。在分析分子监测工作或评估监测覆盖率方面做得很少。本研究旨在开发一个证据图，以确定撒哈拉以南非洲地区耐药性监测的时空分布和采样方法，特别关注与ACT伙伴药物相关的标志物。通过使用系统检索，我们确定了报告以下与ACT伴侣耐药相关的突变数据的研究：pfmdr 1 Asn 86 Tyr、Tyr 184 Phe、Asp 1246 Tyr和拷贝数变异以及pfcrt Lys 76 Thr，样本采集发生在2004年1月1日至2018年12月31日期间的撒哈拉以南非洲，对应于ACT的摄取。对于每一项确定的研究，我们提取了有关其采样和实验室方法、作者和出版单位、采样和出版年份、研究地点的地理坐标以及合作伙伴耐药相关标志物的患病率的信息。我们使用线性模型来检验城市化、人口密度和地方性是否是耐药调查地点的预测因子，并使用线性回归来确定给定国家内耐药调查数量与2010年疟疾高危人口、2010年人均GDP和疟疾平均资助金额之间的关联，并确定标志物流行率随时间的趋势。对于具有三个或更多数据点的国家案例研究，我们使用Moran's I评估了全球空间自相关。我们的搜索产生了254项研究，包括来自35个疟疾流行国家的492项特定年份和特定地点的调查，这是迄今为止最完整的分子伴侣药物监测数据集。我们观察到从最终样本采集到发表的中位时间滞后为3.1年（95%CI 1.0 - 7.7）。在研究区域的44个国家中，有22个国家（49%）平均每3年进行一项或更少的研究。监测点的位置与城市化程度呈正相关（p<0.0001），国家级数据的丰富程度与2004- 2018年报告的捐助资金（p= 0.0011）和2004- 2009年报告的地方政府资金（p= 0.014）有关。几乎所有的分子标记显示出显着的区域趋势，随着时间的推移和全球空间自相关的空间。对于监测数据覆盖面更广的选定国家，一些标志物也显示出空间异质性。在大多数撒哈拉以南非洲国家，抗疟药物耐药性的分子数据可能不能代表伙伴药物耐药性的时间和地理异质性，也可能不能代表伙伴药物耐药性的真正空间依赖性分布。我们的研究结果突出了几个可以改进的低效率，以开发更准确的数据景观，包括哨兵监测系统的扩展，研究样本的流行病学使用，以及更多地参与向集中平台报告已发表和未发表的数据。
Molecular markers for antimalarial drug resistance can be used to rapidly monitor the emergence and spatial distribution of resistance to artemisinin-based combination therapies (ACTs). Little has been done to analyse molecular surveillance efforts or to assess surveillance coverage. This study aimed to develop an evidence map to characterise the spatial-temporal distribution and sampling methodologies of drug resistance surveillance in sub-Saharan Africa, specifically focusing on markers associated with ACT partner drugs. By use of a systematic search, we identified studies that reported data on the following mutations associated with ACT partner drug resistance: pfmdr1 Asn86Tyr, Tyr184Phe, Asp1246Tyr, and copy number variation and pfcrt Lys76Thr, with sample collection occurring in sub-Saharan Africa between Jan 1, 2004, and Dec 31, 2018, corresponding to the uptake of ACTs. For each identified study, we extracted information on its sampling and laboratory methods, author and publication affiliations, years of sampling and of publication, geographic coordinates of the study sites, and prevalence of the partner drug resistance-associated markers. We used linear models to test whether urbanicity, population density, and endemicity were predictors of drug resistance survey sites and linear regressions to identify associations between the number of resistance surveys within a given country and the at-risk malaria population in 2010, the per-capita GDP in 2010, and the mean amount of funding directed to malaria and to determine trends in marker prevalence over time. For country case studies with three or more datapoints, we assessed global spatial autocorrelation using Moran’s I. Our search yielded 254 studies encompassing 492 year-specific and location-specific surveys from 35 malaria-endemic countries, the most complete set of molecular partner drug surveillance data to date. We observed a median time lag of 3·1 years (95% CI 1·0–7·7) from final sample acquisition to publication. 22 (49%) of the 44 countries in the study region conducted, on average, one or fewer studies every 3 years. The locations of surveillance sites were positively associated with urbanicity (p<0·0001), and the abundance of country-level data was associated with reported donor funding in 2004–18 (p=0·0011) and local government funding in 2004–09 (p=0·014). Nearly all molecular markers displayed significant regional trends over time and global spatial autocorrelation in space. For selected countries with more widespread coverage of surveillance data, some markers also displayed spatial heterogeneity. In most sub-Saharan countries, molecular data on antimalarial resistance might not be representative of the temporal and geographic heterogeneity of partner drug resistance, and likely do not represent the true spatially dependent distribution of partner drug resistance. Our results highlight several inefficiencies that can be improved upon to develop more accurate data landscapes, including the expansion of sentinel surveillance systems, syndemic usage of research samples, and increased participation in reporting published and unpublished data to centralised platforms.
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DOI：
10.1093/infdis/jiy223
发表时间：
2018-08-14
期刊：
The Journal of infectious diseases
影响因子：
--
作者：
Aydemir O;Janko M;Hathaway NJ;Verity R;Mwandagalirwa MK;Tshefu AK;Tessema SK;Marsh PW;Tran A;Reimonn T;Ghani AC;Ghansah A;Juliano JJ;Greenhouse BR;Emch M;Meshnick SR;Bailey JA
通讯作者：
Bailey JA
影响因子：
3.7
作者：
Nsanzabana C;Ariey F;Beck HP;Ding XC;Kamau E;Krishna S;Legrand E;Lucchi N;Miotto O;Nag S;Noedl H;Roper C;Rosenthal PJ;Schallig HDFH;Taylor SM;Volkman SK;Gonzalez IJ
通讯作者：
Gonzalez IJ
影响因子：
3
作者：
Pfeffer DA;Lucas TCD;May D;Harris J;Rozier J;Twohig KA;Dalrymple U;Guerra CA;Moyes CL;Thorn M;Nguyen M;Bhatt S;Cameron E;Weiss DJ;Howes RE;Battle KE;Gibson HS;Gething PW
通讯作者：
Gething PW
影响因子：
3
作者：
Otienoburu, Sabina Dahlstroem;Suay, Ignacio;Humphreys, Georgina S.
通讯作者：
Humphreys, Georgina S.
影响因子：
2.7
作者：
MORAN, PAP
通讯作者：
MORAN, PAP