Ventura Paulo C, Kummer Allisandra G, Wilke André B B, Chitturi Jagadeesh, Hill Megan D, Vasquez Chalmers, Unlu Isik, Mutebi John-Paul, Kluh Susanne, Vetrone Steve, Damian Dan, Townsend John, Litvinova Maria, Ajelli Marco
Laboratory for Computational Epidemiology and Public Health, Department of Epidemiology and Biostatistics, Indiana University School of Public Health, Bloomington, Indiana, United States of America.
Miami-Dade County Mosquito Control Division, Miami, Florida, United States of America.
PLoS Negl Trop Dis. 2024 Nov 25;18(11):e0012671. doi: 10.1371/journal.pntd.0012671. eCollection 2024 Nov.
Aedes-borne diseases represent a major public health threat and mosquito control operations represent a key line of defense. Improving the real-time awareness of mosquito control authorities by providing reliable forecasts of the relative abundance of mosquito vectors could greatly enhance control efforts. To this aim, we developed an analytical tool that forecasts Aedes aegypti relative abundance 1 to 4 weeks ahead. Forecasts were validated against mosquito surveillance data (2,760 data points) collected over multiple years in four jurisdictions in the US. The symmetric absolute percentage error was in the range 0.43-0.69, and the 90% interquantile range of the forecasts had a coverage of 83-92%. Our forecasts consistently outperformed a reference "naïve" model for all analyzed study sites, forecasting horizon, and for periods with medium/high Ae. aegypti activity. The developed tool can be instrumental to address the need for evidence-based decision making.
伊蚊传播的疾病是对公共卫生的重大威胁，而蚊虫控制行动是关键的防线。通过提供蚊虫媒介相对丰度的可靠预测来提高蚊虫控制部门的实时认知，可极大地加强控制工作。为此，我们开发了一种分析工具，可提前1至4周预测埃及伊蚊的相对丰度。我们根据在美国四个司法管辖区多年收集的蚊虫监测数据（2760个数据点）对预测结果进行了验证。对称绝对百分比误差在0.43 - 0.69范围内，预测的90%四分位数间距覆盖率为83 - 92%。对于所有分析的研究地点、预测期以及埃及伊蚊活动处于中/高水平的时期，我们的预测始终优于参考“简单”模型。所开发的工具有助于满足基于证据进行决策的需求。
