Are Travel Bans the Answer to Stopping the Spread of COVID-19 Variants? Lessons from a Multi-Country SIR Model (preprint)

Background: Detections of mutations of the SARS-CoV-2 virus gave rise to new packages of interventions. Among them, international travel restrictions have been one of the fastest and most visible responses to limit the spread of the variants. While inducing large economic losses, the epidemiological consequences of such travel restrictions are highly uncertain. They may be poorly effective when the new highly transmissible strain of the virus already circulates in many regions. Assessing the effectiveness of travel bans is difficult given the paucity of data on daily cross-border mobility and on existing variant circulation. The question is topical and timely as the new omicron variant -- classified as a variant of concern by WHO -- has been detected in Southern Africa, and perceived as (potentially) more contagious than previous strains. In this study, we develop a multi-country compartmental model of the SIR type. We use it to simulate the spread of a new variant across European countries, and to assess the effectiveness of unilateral and multilateral travel bans. Results: : Multilateral travel bans do not buy much time, by increasing the time until the infection curve peaks by a few weeks at best. This can be achieved with drastic travel bans only, and this fails to stop the propagation when the virus is already circulating in the country, or in regions not included in the travel bans. Conclusion: Given their huge economic and freedom-killing consequences, travel bans have negligible effects on the timing and severity of the infection response. Managing new waves of COVID-19 with local sanitary measures applicable to cross-border movers is the most effective option. It induces better epidemiological outcomes and smaller economic cost for all parties concerned.

Are Travel Bans the Answer to Stopping the Spread of COVID-19 Variants? Lessons from a Multi-Country SIR Model (preprint)

Detections of mutations of the SARS-CoV-2 virus gave rise to new packages of interventions. Among them, international travel restrictions have been one of the fastest and most visible responses to limit the spread of the variants. While inducing large economic losses, the epidemiological consequences of such travel restrictions are highly uncertain. They may be poorly effective when the new highly transmissible strain of the virus already circulates in many regions. Assessing the effectiveness of travel bans is difficult given the paucity of data on daily cross-border mobility and on existing variant circulation. The question is topical and timely as the new omicron variant -- classified as a variant of concern by WHO -- has been detected in Southern Africa, and perceived as (potentially) more contagious than previous strains. In this study, we develop a multi-country compartmental model of the SIR type. We use it to simulate the spread of a new variant across European countries, and to assess the effectiveness of unilateral and multilateral travel bans.

Cross-Border Mobility Responses to Covid-19 in Europe: New Evidence from Facebook Data (preprint)

BackgroundWe use a unique database on Facebook users’ mobility to study the daily evolution of cross-border movements of people during the Covid-19 pandemic. To limit censoring issues, we focus on 45 pairs of European countries, and document the changes in daily traffic during an entire pandemic year. We rely on regression and machine learning models to identify the role of infection threats and containment policies. Permutation techniques allow us to compare the impact and predictive power of these two categories of variables. ResultsIn contrast with studies on within-border mobility, our models point to a stronger importance of containment policies in explaining changes in cross-border traffic as compared with international travel bans and fears of being infected. The latter are proxied by the numbers of Covid-19 cases and deaths at destination. Although the ranking among coercive policies varies across modelling techniques, containment measures in the destination country (such as cancelling of events, restrictions on internal movements and public gatherings), and school closures in the origin country (influencing parental leaves) have the strongest impacts on cross-border movements. ConclusionWhile descriptive in nature, our findings have policy-relevant implications. Cross-border movements of people predominantly consist of labor commuting flows and business travels. These economic and essential flows are marginally influenced by the fear of infection and international travel bans. They are mostly governed by the stringency of internal containment policies and the ability to travel.