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人群测量以提高疫苗接种率。

Measuring populations to improve vaccination coverage.

机构信息

Biology Department; Center for Infectious Disease Dynamics, Pennsylvania State University, University Park PA, USA.

Woods Institute for the Environment, Stanford University, Stanford CA, USA.

出版信息

Sci Rep. 2016 Oct 5;5:34541. doi: 10.1038/srep34541.

Abstract

In low-income settings, vaccination campaigns supplement routine immunization but often fail to achieve coverage goals due to uncertainty about target population size and distribution. Accurate, updated estimates of target populations are rare but critical; short-term fluctuations can greatly impact population size and susceptibility. We use satellite imagery to quantify population fluctuations and the coverage achieved by a measles outbreak response vaccination campaign in urban Niger and compare campaign estimates to measurements from a post-campaign survey. Vaccine coverage was overestimated because the campaign underestimated resident numbers and seasonal migration further increased the target population. We combine satellite-derived measurements of fluctuations in population distribution with high-resolution measles case reports to develop a dynamic model that illustrates the potential improvement in vaccination campaign coverage if planners account for predictable population fluctuations. Satellite imagery can improve retrospective estimates of vaccination campaign impact and future campaign planning by synchronizing interventions with predictable population fluxes.

摘要

在低收入环境中,疫苗接种运动是常规免疫的补充,但由于目标人群规模和分布的不确定性,往往无法实现覆盖目标。准确、最新的目标人群估计数据非常罕见,但至关重要;短期波动会极大地影响人口规模和易感性。我们使用卫星图像来量化人口波动以及尼日尔城市麻疹暴发应对疫苗接种运动的覆盖情况,并将运动估计与运动后调查的测量结果进行比较。疫苗接种覆盖率被高估了,因为运动低估了居民人数,季节性迁徙进一步增加了目标人群。我们将人口分布波动的卫星衍生测量值与高分辨率麻疹病例报告相结合,开发了一个动态模型,说明了如果规划者考虑到可预测的人口波动,疫苗接种运动覆盖范围可能会得到改善。卫星图像可以通过将干预措施与可预测的人口流动同步,来提高疫苗接种运动效果的回顾性估计和未来的运动规划。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b07/5050518/0644dde6eaca/srep34541-f1.jpg

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