Data-Driven Approach to Understand the Mobility Patterns of the Portuguese Population during the COVID-19 Pandemic

Abstract

SARS-CoV-2 emerged in late 2019. Since then, it has spread to several countries, becoming classified as a pandemic. So far, there is no definitive treatment or vaccine, so the best solution is to prevent transmission between individuals through social distancing. However, it is not easy to measure the effectiveness of these distance measures. Therefore, this study uses data from Google COVID-19 Community Mobility Reports to understand the Portuguese population’s mobility patterns during the COVID-19 pandemic. In this study, the Rt value was modeled for Portugal. In addition, the changepoint was calculated for the population mobility patterns. Thus, the mobility pattern change was used to understand the impact of social distance measures on the dissemination of COVID-19. As a result, it can be stated that the initial Rt value in Portugal was very close to 3, falling to values close to 1 after 25 days. Social isolation measures were adopted quickly. Furthermore, it was observed that public transport was avoided during the pandemic. Finally, until the emergence of a vaccine or an effective treatment, this is the new normal, and it must be understood that new patterns of mobility, social interaction, and hygiene must be adapted to this reality.

Mobility Patterns of the Portuguese Population During the First Year of the COVID-19 Pandemic: A Longitudinal Study

“…As the framework uses the first seven days for the calculation and the first case of COVID-19 in Portugal was on 3 March 2020, the results for Rt are from 10 March 2020 through 9 March 2021. According to [9], at the beginning of the pandemic, transmission occurred exponentially, with Rt greater than 3. With the rapid response of the Portuguese government, this value quickly dropped to less than 1.…”

“…These values are anonymous and represent a portion of the population. Thus, it is considered that if the population decreases its presence in parks, restaurants, transport hubs, among others, the number of risk contacts will drop [9].…”

What Causes Changes in Passenger Behavior in South-East Europe during the COVID-19 Pandemic?

“…The COVID-19 pandemic has had a major impact on the public passenger transport system [10], as it was identified as a high-risk environment for the spread of the virus [11][12][13][14]. Compared to private vehicles and other modes of transport [15][16][17], public transport was the most strongly affected [5,6,17,18], since conducting social distancing and providing the necessary materials for safe travel required a great deal of material and organizational resources [18].…”

“…At the beginning of December 2019, a new coronavirus disease (COVID-19) ap-peared in the city of Wuhan, which then quickly spread to China and almost all coun-tries of the world [1][2][3][4][5][6][7]. Some studies have shown that the number of infections and deaths continues to increase, which has posed major public health and governance concerns.…”

COVID-19: A Comparative Study of Population Aggregation Patterns in the Central Urban Area of Tianjin, China

“…Under the concept of people-oriented urban design [ 1 ], the interaction between human behavior and urban material space is the most important dimension to study the regulation of urban processes [ 2 , 3 , 4 , 5 , 6 ]. Urban population distribution [ 7 , 8 , 9 ], like population activity density [ 10 ] and urban vitality distribution [ 11 ], is the dependent variable of urban spatial behavior that can be used to characterize the operational state of an urban area [ 12 ].…”