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Purpose: This paper aims to describe the impact of the COVID-19 containment measures on the provision of drug treatment and harm reduction services in European prisons in15 countries during the early phase of the pandemic (March -June 2020).Design/methodology/approach: The paper is based on a mixed method research approach that triangulates different data sources, including the results of an on-line survey, the outcome of a focus group and four national case studies.Findings: The emergence of COVID-19 led to a disruption in prison drug markets and resulted in a number of challenges for the drug services provision inside prison. Challenges for health services included the need to maintain the provision of drug-related interventions inside prison, while introducing a range of COVID-19 containment measures. To reduce contacts between people, many countries introduced measures for early release, resulted in around a 10% reduction of the prison population in Europe. Concerns were expressed around reduction of drug-related interventions, including group activities, services by external agencies, interventions in preparation for release and continuity of care.Practical Implications: Innovations aimed at improving drug service provision included telemedicine, better partnership between security and health staff and an approach to drug treatment more individualised. Future developments must be closely monitored.Originality/value: The paper provides a unique and timely overview of the main issues, challenges and initial adaptations implemented for drug services in European prisons in response to the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

This paper follows European countries as they struggled through the first wave of the Sars-CoV-2 pandemic. We analyze when countries were confronted with the virus, how long it took until the number of new infections peaked and at what level of infections that peak was achieved via social distancing and lockdown policies. Most European countries were able to successfully end the first wave of the pandemic – defined as a two-week incidence rate smaller than 10 cases per 100,000 people. We find that countries in which the virus made significant landfall later in time enjoyed a latecomer advantage that some of these countries squandered, however, by not responding quickly enough and that an early lockdown was more effective than a hard lockdown. [ABSTRACT FROM AUTHOR]

The recent COVID-19 pandemic affected various aspects of life. Several studies established the consequences of pandemic lockdown on air quality using satellite remote sensing. However, such studies have limitations, including low spatial resolution or incomplete spatial coverage. Therefore, in this paper, we propose a machine learning-based scheme to solve the pre-mentioned limitations by training an optimized space-time extra trees model for each year of the study period. The results have shown that our trained models reach a prediction accuracy up to 95% when predicting the missing values in the MODIS MCD19A2 Aerosol Optical Depth (AOD) product. The outcome of the mentioned scheme was a geo-harmonized atmospheric dataset for aerosol optical depth at 550 nm with 1 km spatial resolution and full coverage over Europe. As an application, we used the proposed machine learning based prediction approach in AOD levels analysis. We compared the mean AOD levels between the lockdown period from March to June in 2020 and the mean AOD values of the same period for the past 5 years. We found that AOD levels dropped over most European countries in 2020 but increased in several eastern and western countries. The Netherlands had the most significant average decrease in AOD levels (19%), while Spain had the highest average increase (10%). Moreover, we analyzed the relationship between the relative percentage difference of AOD and four meteorological variables. We found a positive correlation between AOD and relative humidity and a negative correlation between AOD and wind speed. The value of the proposed prediction scheme is further emphasized by taking into consideration that the reconstructed dataset can be used for future air quality studies concerning Europe. [ABSTRACT FROM AUTHOR]

This paper investigates the impacts of COVID-19 safer-at-home polices on collisions and pollution. We find that statewide safer-at-home policies lead to a 20% reduction in vehicular collisions and that the effect is entirely driven by less severe collisions. For pollution, we find particulate matter concentration levels approximately 1.5 μ g/m3 lower during the period of a safer-at-home order, representing a 25% reduction. We document a similar reduction in air pollution following the implementation of similar policies in Europe. We calculate that as of the end of June 2020, the benefits from avoided car collisions in the U.S. were approximately $16 billion while the benefits from reduced air pollution could be as high as $13 billion. [ABSTRACT FROM AUTHOR]