Jiang Jingjing, Liu Zijian, Lu Hongzheng, Zhang Tao, Lyu Xiaofeng, Xu Xian, Wang Shuqi, Chu Qinshu, Li Weidong, Wang Duoquan
Anhui Provincial Center for Disease Control and Prevention, Hefei City, Anhui Province, China.
Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei City, Anhui Province, China.
China CDC Wkly. 2025 May 2;7(18):609-613. doi: 10.46234/ccdcw2025.101.
WHAT IS ALREADY KNOWN ABOUT THIS TOPIC?: Remote sensing information provides indirect insights into infectious disease dynamics. Public health practice has significantly benefited from the increasing availability and accessibility of remote sensing data.
WHAT IS ADDED BY THIS REPORT?: This study explores the relationship between meteorological and environmental factors and malaria vector abundance using remote sensing technology, establishing predictive models for population dynamics.
WHAT ARE THE IMPLICATIONS FOR PUBLIC HEALTH PRACTICE?: Identifying reliable predictors of malaria vector abundance enables policymakers to allocate resources more efficiently to regions at high risk of malaria transmission. In areas where an abnormal increase in malaria vector populations is predicted, proactive measures can be implemented, including environmental management, enhancement of local malaria diagnostic capabilities, and strengthening of targeted public health education campaigns.
关于该主题已知的信息有哪些？：遥感信息为传染病动态提供了间接见解。公共卫生实践已从遥感数据日益增加的可用性和可获取性中显著受益。
本报告新增了哪些内容？：本研究利用遥感技术探索气象和环境因素与疟疾媒介丰度之间的关系，建立了种群动态的预测模型。
对公共卫生实践有哪些启示？：确定疟疾媒介丰度的可靠预测指标，使政策制定者能够更有效地将资源分配到疟疾传播高风险地区。在预测疟疾媒介种群异常增加的地区，可以采取积极措施，包括环境管理、提高当地疟疾诊断能力以及加强有针对性的公共卫生教育活动。
