Google’s COVID-19 location data shows regions that violate lock orders.

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Reports are available to all users in 131 countries, and in some regions, you can search for regional data on states and counties. Once a region is selected, Google will generate the report in PDF format that is easy to share with field workers, the company said.

The reports cover six categories: retail and leisure (restaurants, museums, shopping centers, etc.), grocery and pharmacy, parks (including beaches, marinas, etc.), public transit stations, workplaces and residences .

Coronavirus infection curves
Statista

Here in France, as the top image shows, there has been a massive drop in movement to most categories – up to 88% – with a 56% drop in business travel and an 18% increase in people staying at home. This is due to a lock imposed by the government (delivery) which prohibits unnecessary travel, with penalties ranging from fines up to 1,500 euros and even prison terms for extreme repeat offenders.

In California, which has implemented some of the strictest containment rules in the United States, we see a drop of only 50% in the retail and entertainment areas. These rules are, however, essentially self-enforced, which could explain why France has started to flatten its infection curve, while the American curve is a rocket ship going straight up.

Other mobile advertising companies also share similar data with the Centers for Disease Control and Prevention (CDC), according to the WSJ. However, Google has access to huge amounts of anonymized location data and has reportedly created reports to help public health officials prioritize regions as needed.

Location tracking has been used by countries like Korea and Taiwan to track movements of quarantined and healthy citizens. However, such actions alone have limited utility. These countries also tested a high percentage of their population and implemented more stringent social distancing rules.

In addition to the reports, Google said it was also working with epidemiologists to create an updated dataset of anonymized aggregated data, “to better understand and predict the pandemic,” the company said.

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