Dataset Information

Human Mobility Restrictions and COVID-19 Infection Rates: Analysis of Mobility Data and Coronavirus Spread in Poland and Portugal.

ABSTRACT: This study examines the possibility of correlation between the data on human mobility restrictions and the COVID-19 infection rates in two European countries: Poland and Portugal. The aim of this study is to verify the correlation and causation between mobility changes and the infection spread as well as to investigate the impact of the introduced restrictions on changes in human mobility. The data were obtained from Google Community Mobility Reports, Apple Mobility Trends Reports, and The Humanitarian Data Exchange along with other reports published online. All the data were organized in one dataset, and three groups of variables were distinguished: restrictions, mobility, and intensity of the disease. The causal-comparative research design method is used for this study. The results show that in both countries the state restrictions reduced human mobility, with the strongest impact in places related to retail and recreation, grocery, pharmacy, and transit stations. At the same time, the data show that the increase in restrictions had strong positive correlation with stays in residential places both in Poland and Portugal.

SUBMITTER: Strzelecki A

PROVIDER: S-EPMC9655221 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature

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Human Mobility Restrictions and COVID-19 Infection Rates: Analysis of Mobility Data and Coronavirus Spread in Poland and Portugal.

Strzelecki Artur A Azevedo Ana A Rizun Mariia M Rutecka Paulina P Zagała Kacper K Cicha Karina K Albuquerque Alexandra A

International journal of environmental research and public health 20221104 21

This study examines the possibility of correlation between the data on human mobility restrictions and the COVID-19 infection rates in two European countries: Poland and Portugal. The aim of this study is to verify the correlation and causation between mobility changes and the infection spread as well as to investigate the impact of the introduced restrictions on changes in human mobility. The data were obtained from Google Community Mobility Reports, Apple Mobility Trends Reports, and The Human ...[more]

PMID: 36361333

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Project description:BackgroundRestricting human mobility is an effective strategy used to control disease spread. However, whether mobility restriction is a proportional response to control the ongoing COVID-19 pandemic is unclear. We aimed to develop a model that can quantify the potential effects of various intracity mobility restrictions on the spread of COVID-19.MethodsIn this modelling study, we used anonymous and aggregated mobile phone sightings data to build a susceptible-exposed-infectious-recovered transmission model for COVID-19 based on the city of Shenzhen, China. We simulated how disease spread changed when we varied the type and magnitude of mobility restrictions in different transmission scenarios, with variables such as the basic reproductive number (R 0), length of infectious period, and the number of initial cases.Findings331 COVID-19 cases distributed across the ten regions of Shenzhen were reported on Feb 7, 2020. In our basic scenario (R 0 of 2·68), mobility reduction of 20-60% within the city had a notable effect on controlling COVID-19 spread: a flattening of the peak number of cases by 33% (95% UI 21-42) and delay to the peak number by 2 weeks with a 20% restriction, 66% (48-75) reduction and 4 week delay with a 40% restriction, and 91% (79-95) reduction and 14 week delay with a 60% restriction. The effects of mobility restriction were increased when combined with reductions of 25% or 50% in transmissibility of the virus. In specific analyses of mobility restrictions for individuals with symptomatic infections and for high-risk regions, these measures also had substantial effects on reducing the spread of COVID-19. For example, the peak of the epidemic was delayed by 2 weeks if the proportion of individuals with symptomatic infections who could move freely was maintained at 20%, and by 4 weeks if two high-risk regions were locked down. The simulation results were also affected by various transmission parameters.InterpretationOur model shows the effects of various types and magnitudes of mobility restrictions on controlling COVID-19 outbreaks at the city level in Shenzhen, China. The model could help policy makers to establish the optimal combinations of mobility restrictions during the COVID-19 pandemic, especially to assess the potential positive effects of mobility restriction on public health in view of the potential negative economic and societal effects.FundingGuangdong Medical Science Fund, and National Natural Science Foundation of China.

Dataset Information

Human Mobility Restrictions and COVID-19 Infection Rates: Analysis of Mobility Data and Coronavirus Spread in Poland and Portugal.

Publications

Human Mobility Restrictions and COVID-19 Infection Rates: Analysis of Mobility Data and Coronavirus Spread in Poland and Portugal.

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