Snoeijer Berber T, Burger Mariska, Sun Shaoxiong, Dobson Richard J B, Folarin Amos A
ClinLine, Leiderdorp, The Netherlands.
OCS Life Sciences, 's Hertogenbosch, The Netherlands.
NPJ Digit Med. 2021 May 13;4(1):81. doi: 10.1038/s41746-021-00451-2.
The implementation of governmental Non-Pharmaceutical Interventions (NPIs) has been the primary means of controlling the spread of the COVID-19 disease. One of the intended effects of these NPIs has been to reduce population mobility. Due to the huge costs of implementing these NPIs, it is essential to have a good understanding of their efficacy. Using aggregated mobility data per country, released by Apple and Google we investigated the proportional contribution of NPIs to the magnitude and rate of mobility changes at a multi-national level. NPIs with the greatest impact on the magnitude of mobility change were lockdown measures; declaring a state of emergency; closure of businesses and public services and school closures. NPIs with the greatest effect on the rate of mobility change were implementation of lockdown measures and limitation of public gatherings. As confirmed by chi-square and cluster analysis, separately recorded NPIs like school closure and closure of businesses and public services were closely correlated with each other, both in timing and occurrence. This suggests that the observed significant NPI effects are mixed with and amplified by their correlated NPI measures. We observed direct and similar effects of NPIs on both Apple and Google mobility data. In addition, although Apple and Google data were obtained by different methods they were strongly correlated indicating that they are reflecting overall mobility on a country level. The availability of this data provides an opportunity for governments to build timely, uniform and cost-effective mechanisms to monitor COVID-19 or future pandemic countermeasures.
政府实施非药物干预措施(NPIs)一直是控制新冠疫情传播的主要手段。这些非药物干预措施的预期效果之一是减少人口流动。由于实施这些非药物干预措施成本巨大,因此充分了解其效果至关重要。我们利用苹果公司和谷歌发布的每个国家的汇总流动数据,在多国层面研究了非药物干预措施对流动变化幅度和速度的比例贡献。对流动变化幅度影响最大的非药物干预措施是封锁措施、宣布紧急状态、关闭企业和公共服务以及学校停课。对流动变化速度影响最大的非药物干预措施是实施封锁措施和限制公众集会。正如卡方检验和聚类分析所证实的那样,单独记录的非药物干预措施,如学校停课以及企业和公共服务关闭,在时间和发生情况上彼此密切相关。这表明观察到的显著非药物干预措施效果与其相关的非药物干预措施相互交织并被放大。我们观察到非药物干预措施对苹果和谷歌的流动数据都有直接且相似的影响。此外,尽管苹果和谷歌的数据是通过不同方法获得的,但它们高度相关,表明它们反映了一个国家层面的总体流动情况。这些数据的可用性为各国政府建立及时、统一且具有成本效益的机制以监测新冠疫情或未来大流行应对措施提供了契机。