Emerging Pathogens Institute, University of Florida, Gainesville, USA.
Malar J. 2012 Jun 18;11:205. doi: 10.1186/1475-2875-11-205.
Recent increases in funding for malaria control have led to the reduction in transmission in many malaria endemic countries, prompting the national control programmes of 36 malaria endemic countries to set elimination targets. Accounting for human population movement (HPM) in planning for control, elimination and post-elimination surveillance is important, as evidenced by previous elimination attempts that were undermined by the reintroduction of malaria through HPM. Strategic control and elimination planning, therefore, requires quantitative information on HPM patterns and the translation of these into parasite dispersion. HPM patterns and the risk of malaria vary substantially across spatial and temporal scales, demographic and socioeconomic sub-groups, and motivation for travel, so multiple data sets are likely required for quantification of movement. While existing studies based on mobile phone call record data combined with malaria transmission maps have begun to address within-country HPM patterns, other aspects remain poorly quantified despite their importance in accurately gauging malaria movement patterns and building control and detection strategies, such as cross-border HPM, demographic and socioeconomic stratification of HPM patterns, forms of transport, personal malaria protection and other factors that modify malaria risk. A wealth of data exist to aid filling these gaps, which, when combined with spatial data on transport infrastructure, traffic and malaria transmission, can answer relevant questions to guide strategic planning. This review aims to (i) discuss relevant types of HPM across spatial and temporal scales, (ii) document where datasets exist to quantify HPM, (iii) highlight where data gaps remain and (iv) briefly put forward methods for integrating these datasets in a Geographic Information System (GIS) framework for analysing and modelling human population and Plasmodium falciparum malaria infection movements.
近年来，疟疾控制资金的增加导致许多疟疾流行国家的传播减少，促使 36 个疟疾流行国家的国家控制规划设定消除目标。在规划控制、消除和消除后监测时考虑到人口流动（HPM）非常重要，因为以前的消除尝试因 HPM 导致疟疾再次传入而受到破坏。因此，战略控制和消除规划需要有关 HPM 模式的定量信息，并将其转化为寄生虫扩散。HPM 模式和疟疾风险在空间和时间尺度、人口统计学和社会经济亚组以及旅行动机方面有很大差异，因此可能需要多个数据集来量化移动。虽然基于移动电话通话记录数据并结合疟疾传播图的现有研究已经开始解决国内 HPM 模式，但其他方面仍然缺乏量化，尽管它们对于准确衡量疟疾传播模式和构建控制和检测策略非常重要，例如跨境 HPM、HPM 模式的人口统计学和社会经济分层、交通方式、个人疟疾保护和其他改变疟疾风险的因素。存在大量数据可以帮助填补这些空白，当与交通基础设施、交通和疟疾传播的空间数据结合使用时，可以回答相关问题，为战略规划提供指导。本综述旨在：（i）讨论不同时空尺度的相关 HPM 类型；（ii）记录可用于量化 HPM 的数据集；（iii）突出数据空白仍然存在的地方；（iv）简要提出将这些数据集整合到地理信息系统（GIS）框架中的方法，以分析和模拟人口和恶性疟原虫疟疾感染的流动。
