Distancing during the COVID-19 Pandemic

The COVID-19 pandemic, started in December 2019 in Wuhan, China, has resulted in a devastating public health crisis across the globe. As of July 20, 2021, the death toll is over 4 million, and around 190 million cases have been confirmed worldwide.

The COVID-19 is caused by a virus called SARS-Cov-2 (also known as the Novel Coronavirus). This virus transmits from person to person mainly through respiratory droplets. Hence, an effective way to decrease the transmission rate is through exercising physical distancing. To this end, governments across the globe have responded to the pandemic by taking measures that aim to decrease mobility and contact of people in public spheres. These measures (or non-pharmaceutical interventions) include school closures, teleworking, cancellation of public events, and travel restrictions.

Do people effectively participate in physical distancing? This is an intriguing question because unobserved distancing decisions have important ramifications for the progression of the pandemic in any country.

The Model-Inferred DIStancing (MIDIS) project has been developed by economists M. Aykut Attar and Ayça Tekin-Koru to derive a model-based measure of unobserved distancing across countries and time. The identification methodology uses a compartmental epidemiology model and daily epidemiological data. It exploits the notion that, while some of the model parameters are country-independent and fixed due to the nature of the disease, there is daily variation in each country's infection, death, and recovery rates.

MIDIS is available for 120 countries. For each country in the sample, MIDIS is calculated for the first 30 days after the 500th case has been confirmed in that country. To view the current working paper of the MIDIS project, please click here.

Acknowledgments. We are grateful to two anonymous reviewers for their helpful comments and suggestions on an earlier version of this paper. We wish to thank Ben McWilliams and Georg Zachmann for sharing their daily electricity data with us. We also wish to thank the participants of the Science Academy’s COVID-19 Modeling Workshop, the 19th International Conference of the Middle East Economic Association, and the 47th Annual Conference of the Eastern Economic Association for their helpful comments and suggestions on an earlier version of this paper. Finally, we thank Joe Spearing who has pointed out to us that our results are robust under the presence of measurement errors; his blogpost has been the original inspiration for the Section 5 of the July 2020 version. Any remaining errors are our own.