It is one thing to impose social distancing measures – but how do you ensure they are followed, and how do you know whether the approach is working? Florentin Blanc, OECD, and Maria De Benedetto, Roma Tre University, take a first glance at different approaches and possible sources of data.
The current Coronavirus pandemic is a trial by fire for regulatory enforcement.
The current health emergency has led to the imposition of a number of new rules, in particular for quarantine, lockdown and social distancing, as well as associated controls and enforcement measures. To be effective, rules need to be both correctly designed (i.e. “fit for purpose”, actually able to address the contagion risk), and complied with, at least to a significant level. A number of governments have put in place control activities that, in theory, could allow to obtain substantial data on the level of compliance with the Covid-specific rules.
Specifics of social distancing measures have followed different formulas among countries, but almost everywhere they consist in prohibitions, suspensions and restrictions of several economic/social activities and in restrictions of free movement for people. In theory, with sufficiently detailed and reliable data on Covid infections (if mass testing is conducted) or on Covid mortality (incorporating both “officially registered” Covid deaths and “additional deaths compared to baseline”, and correcting for differences in population structures etc. to be able to compare between regions and countries), the spread of the disease (speed and prevalence) can be compared. In turn, if other factors can be controlled for, this could allow to assess the relative effectiveness of control measures (lockdown etc.).
At least for some countries, data on Covid-related controls is available. If this data is sufficiently detailed in terms of “what is checked”, it may give a good insight into the level of compliance with social distancing measures. In turn, this could potentially (with many conditions) allow to try and investigate to which extent inspections and enforcement activities have been effective (at improving compliance), and (if good enough data on Covid spread can be obtained, and other factors controlled for) whether compliance levels, rules, and controls appear to have a meaningful impact on the disease. Thus, it could be an interesting real-life experiment to investigate regulatory effectiveness.
Some countries have relied more on trust and voluntary behaviour change rather than strict rules, or at least have initially done so, before sometimes gradually (or rapidly) moving towards more mandatory prescriptions (e.g. Netherlands, UK, Sweden). Some countries have imposed only partial lockdowns or regional-level measures (e.g. Italy initially, the US etc.). Some have left far more activities allowed (e.g. Germany, where many productive activities were allowed even before recent loosening of measures, as well as outdoors exercise etc.) – whereas others have been far stricter (e.g. Italy, Spain, France, Russia). Certain countries use or used very strict definitions of what range was or is authorized when going out (e.g. France, Russia), others have looser definitions. Several countries have used the self-certification approach (e.g. Italy, France), others require “electronic” permits (Greece, Russia etc.), and others have skipped such measures altogether (e.g. UK, Germany, Belgium etc.).
In terms of enforcement, likewise, very different approaches have been taken. This is true both for overall confinement measures (from relatively benign approaches e.g. in Germany, through far more rigid and “sanctions-based” ones such as in France, to some thankfully rare cases of use of lethal force in some countries) – and of quarantine control (with far more “technologically enabled” and strictly enforced compliance e.g. in East Asia than in Europe – though information systems for Covid response are being developed in all parts of the world, as visible from the database that the OECD and World Bank have developed).
While these different approaches to rules and enforcement reflect various visions of government-citizens interactions and trust (or absence thereof), different institutional and legal contexts, and diverging policy visions, they also often merely correspond to a high-level of path dependency (governments follow the “usual” approach without necessarily questioning it further). Investigating available data could allow to assess the relative effectiveness of different approaches, with due consideration being given of course to the many other factors contributing to the overall outcomes. It could also, at a minimum, give insights into the organization and implementation of control measures. Indeed, it is quite possible that, given sub-optimal design of rules and the presence of many “formal” requirements in some countries (e.g. self-certification “paperwork”), that some or many non-conformities relate to these formal requirements, and do not correspond to any real risk of contagion. If inspections (police controls) data does not sufficiently disaggregate between different types of non-compliance, it will be impossible (or very difficult) to properly assess the real level of compliance with actual, substantive rules (except if overall compliance is very high anyway, even including “paperwork violations”). At the very least, it will allow to shed light on what kind of data and what enforcement structure would be more adequate to help monitor the situation better, and thus steer the response more effectively.
A first opportunity to apply such analysis is offered by the Italian case, where the Ministry of the Interior publishes daily data on the results of police controls of citizens and businesses for compliance with the lockdown and social distancing measures. Based on published data, the controls only assess overall compliance (i.e. lumping together both formal non-compliance with self-certification rules, and substantive non-compliance with social distancing), but it remains to be verified whether internal (non-published) data exists with more details. Even if this were not the case, the aggregate levels of compliance/non-compliance can be assessed to consider both whether there are any trends to be observed over time, or between regions, and whether there are any correlations appearing between compliance levels and the evolution of the Covid situation in Italy. At the very least, the aggregate compliance levels could give an indication of what can be achieved with relatively “moderate” levels of control, and compared to outcomes (where available) for other countries with different approaches. Moreover, this study could form the basis for additional recommendations on what kind of data should be recorded in the future by police forces to allow for more meaningful assessment of the situation.
As of a few weeks ago, according to the Imperial College COVID-19 Response Team (in the Report “Estimating the number of infections and the impact of non- pharmaceutical interventions on COVID-19 in 11 European countries”), 38,000 deaths had already been averted by social distancing measures. Waiting for the quasi-unavoidable successive waves, and preparing for exiting (even gradually) lockdown regimes, it would be very important to know better how effective different measures and approaches have been. Looking at enforcement data is one first step in such direction, which our team will now attempt explore more systematically in Italy and other countries with comparable data.
This research is part of the work done by the OECD Regulatory Policy Division on regulatory inspections and enforcement practices and on measuring regulatory performance, as well as of the new work on Covid-19-specific regulatory issues, and the Italian part of the work is part of the European Commission-funded project “Construction of a Model to Rationalise and Simplify Controls on Businesses”. The team is looking forward to feedback, suggestions and comments, in particular on which indicators may be useful and relevant, specific country-level data sources, most relevant epidemiological data to consider for potential correlation etc. If you would like to provide feedback please contact Florentin Blanc and Maria De Benedetto.