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利用手机数据校正2021年7月至9月法兰西岛大区的人口估计数和严重急性呼吸综合征冠状病毒2(SARS-CoV-2)发病率:一项概念验证研究。

Use of cell phone data to correct Île-de-France population estimates and SARS-CoV-2 incidence, July to September, 2021: a proof-of-concept exercise.

作者信息

Tarantola Arnaud, Hamidouche Mohamed

机构信息

Direction des Régions, Santé Publique France, Saint-Maurice, France.

出版信息

Euro Surveill. 2025 Jun;30(22). doi: 10.2807/1560-7917.ES.2025.30.22.2400530.

Abstract

BackgroundDuring the COVID-19 pandemic, Santé publique France (SpF) published incidence (SpF) rates based on census denominators. Denominators using cell phone connection (CPC) data can better reflect the population present and seasonal mobilities.AimGiven uncertainties regarding the actual number of Île-de-France (IdF) residents present in IdF during summer 2021, we aimed to better approximate true incidence rates from positive SARS-CoV-2 tests in IdF using CPC-derived population denominators.MethodThis longitudinal study used the daily number of positive tests (PCR and Ag) on IdF residents in IdF as the numerator and the estimated resident population present in IdF at midnight as the denominator. We computed the mean corrected incidence rate (MCIR) per moving week between 4 July and 9 September 2021.ResultsThe MCIR showed higher incidence rates than initially estimated, especially during August when residents had left IdF for the holidays. Incidence rates reached a peak on 16 August when the SpF rate per moving week was 200.9 per 100,000 compared with 315.6 per 100,000 with the MCIR, representing a 57% increase.ConclusionUsing local SARS-CoV-2 testing data and real-time population denominators, we showed that indicators using non-geographically referenced test results and fixed population denominators that ignore seasonal mobility can significantly underestimate incidence rates in IdF. New data sources using CPC data provide the opportunity to calculate more accurate and dynamic incidence rates and to map epidemics more precisely and in real time.

摘要

背景

在新冠疫情期间,法国公共卫生署(Santé publique France,SpF)发布了基于人口普查分母的发病率(SpF)数据。使用手机连接(CPC)数据的分母能够更好地反映当地实际人口数量和季节性人口流动情况。

目的

鉴于2021年夏季法兰西岛(Île-de-France,IdF)实际居民数量存在不确定性,我们旨在利用基于CPC数据得出的人口分母,更准确地估算IdF地区新冠病毒检测呈阳性病例的真实发病率。

方法

这项纵向研究以IdF地区IdF居民每日新冠病毒检测阳性数(PCR和抗原检测)作为分子,以午夜时IdF地区的估计常住人口作为分母。我们计算了2021年7月4日至9月9日期间每移动一周的平均校正发病率(MCIR)。

结果

MCIR显示的发病率高于最初估计值,尤其是在8月居民外出度假期间。8月16日发病率达到峰值,此时SpF每移动一周的发病率为每10万人200.9例,而MCIR为每10万人315.6例,增幅达57%。

结论

通过使用当地新冠病毒检测数据和实时人口分母,我们发现,使用未考虑地理因素的检测结果和忽略季节性流动的固定人口分母的指标,可能会显著低估IdF地区的发病率。利用CPC数据的新数据源为计算更准确、动态的发病率以及更精确、实时地绘制疫情地图提供了机会。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f8c/12143120/f4b95a7cf254/2400530-f1.jpg

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