Abstract
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.
Highlights
The pandemic caused by the coronavirus disease 2019 (COVID-19) has had a huge impact on global health and economies, with costs of $11 trillion, projected by the International Monetary Fund (IMF)[1]
We hypothesise that the magnitude of mobility loss describes the capacity for a given country’s population to self-isolate and the rate of the mobility loss reflects the degree of urgency at which Non-Pharmaceutical Interventions (NPIs) are enacted
The Apple data and Google (RAR and transit and stations (TS)) data are derived from npj Digital Medicine (2021) 81 different mobility sources, the magnitude of change, represented model was more specific with 45.7% unattributable loss in by the mean average % mobility lost after stabilizing for these mobility
Summary
The pandemic caused by the coronavirus disease 2019 (COVID-19) has had a huge impact on global health and economies, with costs of $11 trillion, projected (as of June 2020) by the International Monetary Fund (IMF)[1]. ACAPS NPIs were standardised and included a secondary review and categorisation into five groups: social distancing, movement restrictions, public health measures, social and economic measures and lockdowns. These standardised NPIs and the corresponding methodology and data coding insights of ACAPS are freely available along with the actual interventions issued per country and the corresponding classifications[2]. The main parameters governing communication of infectious disease are duration of infectious period, infectiousness, susceptibility and opportunity. Of these parameters, opportunity is the most readily modulated without use of pharmaceuticals. Apple mobility data reflect requests for directions in Apple Maps for driving, walking and train transit, while Google mobility data shows movement trends by country across different categories of places, like retail and recreation (RAR), grocery and pharmacy, transit and stations (TS), parks, workplaces and residential
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