A newly-released COVID-19 community mobility reports by Google has shown that traffic to transit, retail and recreation locations in Nigeria has reduced in the wake of the coronavirus movement restrictions.


The report, which shows data from March 29, examined how citizens visited transit stations, work places, retail and recreation centers, parks, grocery stores and residentials across the country.

It revealed that traffic to transit locations reduced by 34% while that of retail and recreation centers also reduced by 39% compared to baseline levels measured in January and February.

According to Google, the first ever COVID-19 community mobility reports cut across 131 countries.


The search giant added that the reports help to provide countries with insights on the percentage increase or decrease of movement across different high-level categories of places.

Jen Fitzpatrick, Google’s senior vice-president, Geo, in a statement, said the initiative would enable people to understand relevant information to the community response to social distancing.

“Just like how people can use Google Maps to identify when a local business tends to be the most crowded, we’re using the same aggregated, anonymized data to provide high-level insights into what has changed. We think these reports could support decisions about how to manage the COVID-19 pandemic while adhering to our stringent privacy protocols and policies,” the statement said.


“Ultimately, understanding not only whether people are traveling, but also trends in destinations, can help officials design guidance to protect public health and essential needs of communities and we will continue to evaluate these reports as we get feedback from public health officials, civil society groups, local governments and the community at large during these unprecedented times.”

Fitzpatrick said, in addition to the community mobility reports, Google is collaborating with selected epidemiologists working on COVID-19 with updates to an existing aggregate, anonymized dataset that can be used to better understand and forecast the pandemic.

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