| Literature DB >> 32501803 |
Jean Louis Pépin1,2, Rosa Maria Bruno3,4, Rui-Yi Yang5, Vincent Vercamer5, Paul Jouhaud5, Pierre Escourrou6,7, Pierre Boutouyrie3,4.
Abstract
BACKGROUND: In the context of home confinement during the coronavirus disease (COVID-19) pandemic, objective, real-time data are needed to assess populations' adherence to home confinement to adapt policies and control measures accordingly.Entities:
Keywords: COVID-19; home confinement; lockdown; monitoring; pandemic; tracking; wearable activity trackers; wearables
Mesh:
Year: 2020 PMID: 32501803 PMCID: PMC7307323 DOI: 10.2196/19787
Source DB: PubMed Journal: J Med Internet Res ISSN: 1438-8871 Impact factor: 5.428
Characteristics of the studied population.
| Country | Province or | Size of user populationa | Proportion of women (%)a | Mean age (years) | Lockdown rules | Lockdown date | Baseline steps per | Lockdown steps per day | Decrease in steps | |
| Australia | N/Ab | 10,000 | 42 | 42 | Partial | 2020-03-23 | 5765 | 5302 | 8.0 | <.001 |
| Canada | N/A | 10,000 | 38 | 43 | None | N/A | 5049 | 4708 | 6.8 | <.001 |
| China | N/A | 10,000 | 19 | 36 | Total | 2020-01-23 | 4108 | 3034 | 26.1 | <.001 |
| China | Hubei | 100 | 14 | 35 | Total | 2020-01-23 | 4375 | 1943 | 55.6 | <.001 |
| France | N/A | 100,000 | 43 | 43 | Total | 2020-03-17 | 4604 | 3342 | 27.4 | <.001 |
| Germany | N/A | 100,000 | 37 | 46 | Partial | 2020-03-16 | 5349 | 5416 | –1.3 | <.001 |
| Ireland | N/A | 10,000 | 38 | 42 | Total | 2020-03-28 | 5326 | 5356 | –0.6 | <.001 |
| Italy | N/A | 10,000 | 31 | 45 | Total | 2020-03-10 | 5445 | 3918 | 28.0 | <.001 |
| Italy | Lodi | 100 | 29 | 45 | Total | 2020-02-21 | 5640 | 5035 | 10.7 | <.001 |
| Japan | N/A | 100,000 | 29 | 43 | Total | 2020-04-07 | 5460 | 4581 | 16.1 | <.001 |
| Netherlands | N/A | 10,000 | 38 | 44 | None | N/A | 5193 | 5180 | 0.3 | <.001 |
| Singapore | N/A | 1000 | 33 | 41 | None | N/A | 6127 | 5860 | 4.3 | <.001 |
| Spain | N/A | 10,000 | 36 | 46 | Total | 2020-03-15 | 6215 | 3638 | 41.5 | <.001 |
| Sweden | N/A | 10,000 | 34 | 44 | None | N/A | 5681 | 6004 | –5.7 | <.001 |
| Switzerland | N/A | 10,000 | 40 | 44 | Partial | 2020-03-16 | 5325 | 4947 | 7.1 | <.001 |
| United Kingdom | N/A | 100,000 | 39 | 43 | Total | 2020-03-23 | 5690 | 5249 | 7.8 | <.001 |
| United States | N/A | 100,000 | 43 | 43 | Partial | 2020-03-22 | 5287 | 4912 | 7.1 | <.001 |
| United States | California | 100,000 | 38 | 43 | Total | 2020-03-19 | 5508 | 5013 | 9.0 | <.001 |
| United States | Florida | 10,000 | 44 | 46 | Partial | 2020-03-17 | 5303 | 5225 | 1.5 | <.001 |
| United States | Illinois | 10,000 | 41 | 42 | Total | 2020-03-21 | 5415 | 4966 | 8.3 | <.001 |
| United States | New Jersey | 10,000 | 38 | 43 | Total | 2020-03-21 | 5297 | 4693 | 11.4 | <.001 |
| United States | Pennsylvania | 10,000 | 43 | 44 | Partial | 2020-03-19 | 5186 | 4974 | 4.1 | <.001 |
| United States | New York | 10,000 | 39 | 42 | Partial | 2020-03-22 | 5776 | 4499 | 22.1 | <.001 |
| United States | Nevada | 1000 | 42 | 45 | Partial | 2020-03-21 | 5391 | 4902 | 9.1 | <.001 |
aThe number of users having activity data on a given day is subject to variation; the numbers given in the table are representative orders of magnitude of the daily number of users having activity data.
bNot applicable.
Figure 1Trajectories of average daily number of steps recorded by activity trackers from January 13, 2020, to April 13, 2020, in a number of representative countries worldwide adopting total (A), partial (B), or no (C) lockdown. Solid lines indicate total lockdown periods, dashed lines indicate partial lockdown periods, and dotted lines indicate no lockdown. Crosses indicate the start and end dates of lockdown in the different countries.