Where do we get our data?

To perform our analysis, we had to use data from different sources. All the relevant databases are in open access and will be provided on this webpage. We will also provide all the code underlying our statistical analysis for replicability purpose. In this section, we describe and explain some features of the different sources used. Links to the websites hosting those data are provided.

1- Data on the coronavirus infections and deaths

We use data from the European Center for Diseases Prevention and Control (ECDPC). Those data can be retrieved in the following website: https://www.ecdc.europa.eu/en/publications-data/download-todays-data-geographic-distribution-covid-19-cases-worldwide

Those data compiles all the reported cases and deaths from Coronavirus around the world. This dataset is updated on a daily basis. The advantage of this dataset is that it can be directly downloaded in a panel format and that it can be used directly with any statistical software.

The other source of data on COVID-19 infections and deaths that is widely used comes from the Johns Hopkins University (https://github.com/CSSEGISandData/COVID-19 ). Those data are equally reliable than the ones from the ECDPC. The only drawback of this database is that it is not provided in a usual panel format. Also, they do not use the international ISO code for each country. It must be said that using the John Hopkins’s university dataset requires more effort in order to match this dataset with the ones that will be described as follows.

2 – Data on the governments' response to coronavirus

In order to estimate the impact of the government measures (such as lockdown, school closings, …) on the spread of the virus, we use the governments' response tracker database: https://www.bsg.ox.ac.uk/research/research-projects/oxford-covid-19-government-response-tracker .

The Oxford COVID-19 Government Response Tracker (OxCGRT) provides systematic cross-national and cross-temporal measure to understand how governments' responses have evolved. This database provides information on 17 indicators of governments' responses. These indicators are:

- C1: School and universities closing

- C2: Workplace closings

- C3: Cancellation of public events

- C4: Restriction on gatherings

-C5: Closing public transportation

- S5: Public information campaign on COVID-19

-C6: Stay at home policies

- C7: Restriction on internal movement

- C8: Restriction on international travel

- H1: Public information campaign

- H2: Testing policy

- H3: Contact tracing

- H4: Emergency investment in health care

- H5: Investment in vaccines

-E1: Income support policies

-E2: Debt/contract relief

-E3: Fiscal measures

-E4: International support

In our analysis we will use the stringency index which is computed in the OxCGRT database . This Index uses information from the 9 first indicators (C1-C8 and H1). This index allows for efficient cross-national comparisons of government interventions.

Detailed information about this database and the stringency index can be found here : https://www.bsg.ox.ac.uk/research/publications/variation-government-responses-covid-19 .

This database will also allow us to calculate the correlations between the social distancing measures and the measures in support to the economy (such as fiscal and monetary policies). It will also be useful to analyze the impact of post-lockdown policies such as general testing of the population and contact tracing.

3- Data on the number of test performed by countries

It is now common knowledge that the number of coronavirus cases is largely underestimated. The testing policy varies a lot amongst countries. For example, South-Korea performed a wide amount of test whereas countries such as Italy only test people coming in the hospitals. Therefore, in order to have a better understanding of the number of reported cases, it is crucial to have data on the number of tests performed by each country.

We rely on the SARS CoV-2 test tracker data base to collect this information: https://www.finddx.org/covid-19/test-tracker/

This database compiles all estimates furnished by countries and entities (such as the World Bank) on the number of test performed.

4- Google trends data on the media coverage and the public interest on COVID-19

In order to analyse the impact of news coverage and public interest on the governments' responses to COVID-19, we use data from google trends. The google trends data provides an index of the volume of Google queries by geographic location and category for a chosen time period.

It is worth to remark that Google trends search index is a relative value. Data are scaled using the average search volume over the time period selected. The maximum volume of queries is normalized to 100. Therefore, in order to use these data in a cross-country analysis, it is important to consider a common denominator. Since China is not included in the following analysis, its Google queries will be used as common denominator.

For each country, the search volume for the query Coronavirus will be compared with the same search query in China. Those trends data will be computed from the beginning of the year 2020.

Google trends data have been used in various research projects including in epidemiology to estimate in real time diseases outbreaks. It as also been used in economic studies concerning trading behavior or forecasting future consumption amongst other. It is a powerful tool in order to have a proxy of the public interest on a given subject.

Documentation and answers concerning google trends can be found here: https://support.google.com/trends/?hl=en#topic=6248052 , https://ahrefs.com/blog/how-to-use-google-trends-for-keyword-research/ .

A program written in Python to web scratch this information is available under request.

5- Google mobility report

In order to assess if the lock-down and movement restrictions policies where respected, we rely on data from Google mobility reports. Those data highlights the percent change in visits to the following places

• Grocery and pharmacies :

• Parks, public places, and beaches

• Transit stations : subway, bus and train station

• Retail and recreation : restaurants, cafés, shopping centers, ...

• Residential areas

• Workplaces

Changes for each day are compared to a baseline value for that day of the week. The baseline is the median value, for the corresponding day of the week, during the 5-week period from January 3 to February 6. We will use this data at a country level. This dataset can be found here.

6- Country specific data

We use different country specific variables in our analysis such as the median age, the density of population, the number of hospitals beds per 1,000 inhabitants, as well as the Gini index. All of those data can be found on the website of international organizations (mainly the World Bank). Those countries specific data will allow us to perform our analysis pooling similar countries together.

The Global Health Security (GHS) Index could also be used in order to pool countries regarding their estimated health system capability. The GHS Index is an assessment of global health security capabilities in 195 countries. It was prepared in 2019 by the Johns Hopkins Center for Health Security, the Nuclear Threat Initiative (NTI) and the Economist Intelligence Unit (EIU). This Index is made of 6 categories, with one concerning health systems. This category aggregates information such as the capacity in hospitals, the access to healthcare, the capacity to acquires medical countermeasures, etc.

Detailed information about this index can be found on their website: https://www.ghsindex.org/