Epidemiology Project

总结 为确保亚太区域的疟疾传播继续下降，各国必须 疟疾控制项目能够更有效地针对特定的高传播地区和人群 最高的风险。为了做到这一点，他们需要能够准确地识别和描绘口袋的残余 传播和确定高风险群体的存在和性质。这将需要新的方法， 更有效的流行病学研究设计，基于对关键宿主的深入了解， 在不同情况下有助于维持残余传播的寄生虫因素。特别是， 解开生物学基础（如寄生虫种群遗传学，宿主遗传学，免疫力）的相对 无症状感染的高流行率现在比以往任何时候都更加重要。的总体目标 因此，亚太ICEMR流行病学项目旨在更好地了解宿主和寄生虫因素， 有助于在加强控制的情况下维持疟疾的残余传播，并将这一知识应用于 开发新的方法，准确地识别和划定残余传播的口袋。为了 为实现这一目标，将通过一项研究， 结合大型横断面和纵向队列研究，联合收割机结合严格的流行病学 采用最先进的疟原虫分子检测和基因分型的研究设计。感染和 评估宿主免疫反应及其与接触和预防临床症状的联系 疟疾这些信息将用于评估改进的监测战略， 计算机模拟和现场应用相结合。这种深入的疟疾流行病学， 生态学和应用分子和抗体分析喂养到数学建模， silico实验，然后在该领域的应用是高度创新的，以前已经收到了非常 在疟疾监测方面很少受到关注。

Summary To ensure that malaria transmission continues to decline in the Asia-Pacific region, it is critical that national malaria control programs be able to more efficiently target specific areas of high transmission and populations at highest risk. In order to do this they need to be able to accurately identify and delineate pockets of residual transmission and identify the presence and nature of high-risk groups. This will require new approaches and more efficient epidemiological study designs that are based on an in-depth understanding of key host and parasite factors that contribute to sustaining residual transmission in different scenarios. In particular, unraveling the biological basis (e.g. parasite population genetics, host genetics, immunity) for the relatively high prevalence of asymptomatic infections is now more important than ever before. The overall aim of the Asia-Pacific ICEMR Epidemiology Project is thus to better understand host and parasite factors that contribute to sustaining residual malaria transmission despite intensified control and to apply this knowledge to develop novel ways of accurately identifying and delineating pockets of residual transmission. In order to achieve this spatio-temporal patterns of risk of malaria infection and disease will be investigated through a combination of large cross-sectional and longitudinal cohort studies that combine rigorous epidemiological study designs with state-of-the-art molecular detection and genotyping of Plasmodium spp. infections and an assessment of host immune responses and their link to exposure and protection from clinical symptoms of malaria. This information will then be used to evaluate improved surveillance strategies through an innovative combination of computer simulations and field application. This combination of in-depth malaria epidemiology, ecology and application of molecular and antibody profiling feeding into mathematical modeling to allow in silico experimentation, followed by application in the field is highly innovative and has previously received very little attention in the context of malaria surveillance.