Genetic epidemiology of malaria in the Democratic Republic of the Congo

描述(申请人提供)：疟疾在刚果民主共和国非常流行。我们建议使用刚果民主共和国2007年和2012年人口与健康调查(DHS)中的16,000个干血点来进行第一次纵向的、全国范围的疟疾遗传流行病学研究。我们已经通过高通量实时聚合酶链式反应测量并绘制了2007年国土安全部在刚果民主共和国的疟疾地图。我们的第一个目标是确定疟疾控制工作对恶性疟原虫和其他疟疾物种流行的影响。我们现在有一个独特的机会来做到这一点；疟疾控制项目在2007年还很少，但今年正在大幅扩大规模(由全球基金、美国国际开发署和其他机构)。将使用多水平建模来确定与疟疾流行率增加或减少有关的个人和群集级变量。我们的第二个目标是测量2007-2012年恶性疟原虫样本中耐药的分子标记(dhps、pfcrt和pfmdr1)，并确定与耐药性流行变化相关的个体和集群水平的因素。我们的第三个目标是测量2007至2012年间恶性疟原虫的中性微卫星标记。景观遗传分析将测量恶性疟原虫种群在集群之间和随时间推移的遗传距离。这将有助于确定疏散走廊和障碍。它还将允许估计基因流动的速度。后者可以用来预测疟疾可能再次侵袭一个消灭疟疾的地区的速度。综上所述，我们的发现可以为疟疾控制项目提供科学基础。

DESCRIPTION (provided by applicant): Malaria is very highly endemic in the Democratic Republic of the Congo (DRC). We propose to use >16,000 dried blood spots from the 2007 and 2012 Demographic and Health Surveys (DHS) in the DRC to conduct the first longitudinal, nation-wide study of malaria genetic epidemiology. We have already measured and mapped malaria in the DRC from the 2007 DHS by high-throughput real-time PCR. Our first aim is to determine the effects of malaria control efforts on the prevalence of P. falciparum and other malaria species. We have a unique opportunity to do this now; malaria control programs were minimal in 2007 but are being dramatically scaled up this year (by the Global Fund, USAID and other agencies). Multilevel modeling will be used to identify individual- and cluster-level variables associated with increases or decreases in malaria prevalence. Our second aim is to measure molecular markers of drug resistance (dhps, pfcrt and pfmdr1) in P. falciparum samples from 2007 and 2012, and identify individual- and cluster-level factors associated with changes in the prevalence of drug resistance. Our third aim is to measure neutral microsatellite markers in P.falciparum from 2007 and 2012. Landscape genetic analyses will measure genetic distances in the P. falciparum populations between clusters and over time. This will allow the identification of dispersal corridors and barriers. It will also permit estimation of the rate of gene flow. The latter could be used to predict the rate at which malaria might reinvade an area from which it was eliminated. Taken together, our findings could offer a scientific foundation for malaria control programs.