The U.S. left behind 6 million coronavirus cases


Cell phone location data can be useful when it comes to predicting future trends in comidd-19 cases, according to new research published Monday in the journal JMI Internal Medicine.

“Perhaps the most important observation of this study was that a decrease in activity in the workplace, transport stations and retail spaces and an increase in activity at the place of residence are associated with a significant reduction in Covid-19 cases at 5, 10. And 1 day is a day, ”said the researchers, led by Dr. Shiv Sehra of Harvard Medical School.

For example, counties with the highest use of cell phones in residential locations have a 19% lower growth rate in new cases at 15-day levels, with the lowest levels of home use in the counties.

Researchers have also found that grocery stores and areas that are classified as parks are not strongly associated with growth rates of activity. However, it is difficult to assess the direct impact of individual activities, they said.

Researchers have been using publicly available cell phone location data and new U.S. data. The county used daily new reported cases on a specific day, in different locations, and to evaluate the connection between cell phone activity between growth rates in the new Covid-1. Case five, 10 and 15 days later.

They found that there had been a significant change in activities shortly before the stay-at-home order was issued in individual states, including less activity outside the home.

Researchers have found that the use of cell phones in urban counties has increased further after the stay-at-home order, with population levels and in more cases per capita.

However, as the time for stay-home orders increased, cell phones were also used in non-residential locations. For example, at the time of the initial stay-at-home order, retail locations saw an average daily increase of 0.5%, suggesting that “orders should be complied with over time,” the researchers said.

Keep in mind: The study had some limitations, including the likelihood of selection bias. There may also be other differences at the county level, such as the mask command during the study period.

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