The effect of mobility restrictions on the SARS-CoV-2 diffusion during the first wave: what are the impacts in Sweden, USA, France and Colombia.
Telle, O.; Benkimoun, S.; Paul, R. E.
Show abstract
ResumeCombined with sanitation and social distancing measures, control of human mobility has quickly been targeted as a major leverage to contain the spread of SARS-CoV-2 in a great majority of countries worldwide. The extent to which such measures were successful, however, is uncertain (Gibbs et al. 2020; Kraemer et al. 2020). Very few studies are quantifying the relation between mobility, lockdown strategies and the diffusion of the virus in different countries. Using the anonymised data collected by one of the major social media platforms (Facebook) combined with spatial and temporal Covid-19 data, the objective of this research is to understand how mobility patterns and SARS-CoV-2 diffusion during the first wave are connected in four different countries: the west coast of the USA, Colombia, Sweden and France. Our analyses suggest a relatively modest impact of lockdown on the spread of the virus at the national scale. Despite a varying impact of lockdown on mobility reduction in these countries (83% in France and Colombia, 55% in USA, 10% in Sweden), no country successfully implemented control measures to stem the spread of the virus. As observed in Hubei (Chinazzi et al. 2020), it is likely that the virus had already spread very widely prior to lockdown; the number of affected administrative units in all countries was already very high at the time of lockdown despite the low testing levels. The second conclusion is that the integration of mobility data considerably improved the epidemiological model (as revealed by the QAIC). If inter-individual contact is a fundamental element in the study of the spread of infectious diseases, it is also the case at the level of administrative units. However, this relational dimension is little understood beyond the individual scale mostly due to the lack of mobility data at this scale. Fortunately, these types of data are getting increasingly provided by social media or mobile operators, and they can be used to help administrations to observe changes in movement patterns and/or to better locate where to implement disease control measures such as vaccination (Pollina & Busvine 2020; Pullano et al. 2020; Romm et al. 2020).
Matching journals
The top 9 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Assessing the nationwide impact of COVID-19 mitigation policies on the transmission rate of SARS-CoV-2 in Brazil 94%
- Covid-19 Belgium: Extended SEIR-QD model with nursing homes and long-term scenarios-based forecasts 92%
- Assessing the effects of non-pharmaceutical interventions on SARS-CoV-2 transmission in Belgium by means of an extended SEIQRD model and public mobility data 92%
Similar papers in this journal
- Assessing the Impact of Human Mobility to Predict Regional Excess Death in Ecuador 95%
- Evaluating the policy of closing bars and restaurants in Cataluña and its effects on mobility and COVID19 incidence 94%
- How well does societal mobility restriction help control the COVID-19 pandemic? Evidence from real-time evaluation 94%
Similar papers in this journal
- Impact of contact tracing on COVID-19 mortality: An impact evaluation using surveillance data from Colombia. 93%
- Investigating the ‘ Bolsonaro effect ’ on the spread of the Covid-19 pandemic: an empirical analysis of observational data in Brazil 93%
- Application of Elastic Net Regression for Modeling COVID-19 Sociodemographic Risk Factors 93%
Similar papers in this journal
- Mobility was a Significant Determinant of Reported COVID-19 Incidence During the Omicron Surge in the Most Populous U.S. Counties 93%
- The Long-Term Impact of COVID-19 Non-Pharmaceutical Interventions on Notifiable Infectious Diseases in Poland: A Comprehensive Analysis from 2014-2022 92%
- A nationwide joint spatial modelling of simultaneous epidemics of dengue, chikungunya, and Zika in Colombia 92%
Similar papers in this journal
- Multiple introductions followed by ongoing community spread of SARS-CoV-2 at one of the largest metropolitan areas in the Northeast of Brazil 91%
- Risk and Spatial Spread of a Measles Outbreak in Texas 91%
- Quantifying arbovirus disease and transmission risk at the municipality level in the Dominican Republic: the inception of Rm 91%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.