A Google aid for public health agents to combat Covid-19

In the universe of big private organizations, there is an exponential growth trend in the use of Big Data and Data Analytics to aid decision making, especially as a means of prospecting and planning, but also in times of crisis. The practice is generalized and is shared by the different areas organizations – credit risk rating agency, insurance brokers, companies streaming and sports teams, each one to his own way.

In summary, Big Data is a large amount of data, usually collected passively, which may or may not be structured, stored on large hard disks or even in memory clouds, which can be easily processed, manipulated and later analyzed for the generation of data insights, outlining scenarios and forecasting results for certain decisions. Specifically, Data Analisys is the process by which happens the organization and management of data in the desired way to obtain useful answers from the bank provided by the Big Data.

Large organizations have been using these resources to the identification of new consumer markets, potential projects or delimitation strategies.

The novelty now is that governments can also use these technologies in the fight against COVID-19, to obtain information to support decisions in order to assist in the crisis management. The Google released reports obtained through Big Data on the mobility of citizens in over 130 countries (enter here). Data are aggregated – such as those used in Google Maps – showing how and when certain types of places are occupied, generating data on the dynamics of movement, which can be useful to inform public health policy dependent of the social dynamics.

The data collected begin on February 15th and classify the mobility in six categories:

a) Shopping, general trade and entertainment.     

b) Food and pharmacy     

c) Parks and gardens     

d) Public transport    

e) Work     

f) Residential      

The graphs that will be presented refer to the degree of mobility during this period of crisis, compared to the same period of previous years.


The quarantine in the Brazilian states did not start on February 15th, the date that Google assumed as the beginning for its international data analysis. In the State of Santa Catarina, taken as an example of celerity in public decision-making in relation to COVID-19, quarantine was only officially enacted on March 18th, the same day as the approval of the public calamity decree requested by the federal government. Despite the disparity regarding the dates of the beginning of the quarantine between Brazil and other countries, there is no significant loss for the analysis.

It is also worth checking the timeline provided by the book publisher Sanar (access here).

In terms of shopping in malls, food and entertainment services, there is a sharp drop compared to the same date in previous years, of about 40%, probably this occurred by a reckless reaction of the population due to the first suspicion of contamination, in the state of São Paulo.

As this first suspicion was discarded and the new disease took another five days to confirm the first suspect, activity in this sector returned to normal, dropping vertiginously (almost 80%) only from the second half of March, when most Brazilian states had already decreed quarantine.

The sector that considers parks, beaches and public squares, one sees a large increase in the last week of February, but it is extremely unlikely that this result hold any kind of relationship with the COVID-19, the more likely it is that this movement be the result of the carnival party, which in 2020 took place between February 21th and 25th, unlike previous years, when the party extended until March. The small drop in mobility in early March can be explained by the same reason.

However, as of the second half of March the fall becomes more striking, until reaching its peak on the 29th, which also occurs at around 80%, but occurs more gradually.

The movement in the region of the residence itself has steadily increased since the second half of March, reaching around 25%, which can be explained by the fact that citizens prefer to shop in small shops on their streets instead of taking chances in large supermarket chains and also the fact of many Brazilians living in conditions that prevent total containment inside the house, especially the children and underage teenagers, as unsanitary conditions or many individuals sharing few rooms.

Food and pharmacy purchases showed a small increase from the end of February until the beginning of the quarantine, which may indicate that the population was willing to stock up on food and reduce visits to the supermarket. From the beginning of the quarantine it also felt but in a lower intensity, reaching a value close to 40%, as supermarkets and pharmacies are considered essential services and there is no legal requirement for its closure.

Public transport also suffered a fall in late February, which also can be explained by the carnival event, since most municipalities often adopt different bus schedules during the festivities. The sharp drop, which begins in the 2nd week of March, can be attributed to the decrees of state governments that banned everything from the use of public transportation to jobs considered “non-essential”.

In relation to mobility in the workplace, the sharp drop and rise in late February and early March, respectively, are also easily explained by the carnival holiday. The drop from the middle of March onwards is less evident probably due to the discrepancy between the beginning of the quarantine in different states. Santa Catarina and São Paulo and Rio de Janeiro, for example, had a difference of 6 days.

A comparison between the states

It is interesting to compare data on mobility between Brazilian states, because unlike countries with less territoriality, Brazil did not have the decree of quarantine in the national government, but state governments, which sometimes happened with a considerable time difference.

We will take the analysis of the state of Santa Catarina – taken as an example of speed in public decision-making in relation to the virus – and the states of São Paulo and Rio de Janeiro, criticized for the delay in making more energetic public decisions.

Based on the figures presented above, it is clear that – from the worsening of the pandemic in the country and from the point of view of assessing the effectiveness of the government measures adopted – the state of Santa Catarina had better results in the six categories of analysis and, with the exception of in the “workplace” category, falls in circulation were rapid and constant, showing that the measures had a considerable impact on the population’s behavior. The only increase was not the circulation of people in the region close to the residence, which can be a good sign, if we assume that this happened to favor local businesses instead of agglomerations in major markets. It is also relevant to point out that Santa Catarina presents, for the 6 analysis categories, results considerably better than the Brazilian average, while São Paulo presents similar results and Rio de Janeiro presents similar or worse results.

For complete data on all Brazilian states, access here .

Finally, it should be noted that this prior analysis concerns only the possible impact of state government measures on the behavior of the population, but does not assess whether these measures are effective in relation to the pandemic.

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