Cross-border mobility responses to COVID-19 in Europe: new evidence from facebook data.

BACKGROUND: Assessing the impact of government responses to Covid-19 is crucial to contain the pandemic and improve preparedness for future crises. We investigate here the impact of non-pharmaceutical interventions (NPIs) and infection threats on the daily evolution of cross-border movements of people during the Covid-19 pandemic. We use a unique database on Facebook users' mobility, and 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. RESULTS: In 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. CONCLUSION: While 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.

COVID-19 crisis management in Luxembourg: Insights from an epidemionomic approach.

We develop an epidemionomic model that jointly analyzes the health and economic responses to the COVID-19 crisis and to the related containment and public health policy measures implemented in Luxembourg. The model has been used to produce nowcasts and forecasts at various stages of the crisis. We focus here on two key moments in time, namely the deconfinement period following the first lockdown, and the onset of the second wave. In May 2020, we predicted a high risk of a second wave that was mainly explained by the resumption of social life, low participation in large-scale testing, and reduction in teleworking practices. Simulations conducted 5 months later reveal that managing the second wave with moderately coercive measures has been epidemiologically and economically effective. Assuming a massive third (or fourth) wave will not materialize in 2021, the real GDP loss due to the second wave will be smaller than 0.4 percentage points in 2020 and 2021.

Modeling the effects of physician emigration on human development.

We analyzed the effects of physician emigration on human development indicators in developing countries. First, the geographical distribution of physician brain drain was documented for the period 1991-2004. Second, random and fixed effects models were employed to investigate the effects of physicians in the home countries and abroad on child mortality and vaccination rates. Third, models were estimated to investigate migration-induced incentives in the medical sector that would increase the number of physicians. The results showed positive effects of migration prospects on medical training though the magnitude was too small for generating a net brain gain. Also, infant and child mortality rates were negatively associated with the number of physicians per capita after adult literacy rates exceeded 60%. The results for DPT and measles vaccinations underscored the importance of literacy rates and physicians per capita for higher vaccination rates. From the standpoint of Millennium Development Goals, reducing medical brain drain is likely to have only small benefits for child mortality and vaccination rates.