About: Lockdown timing and efficacy in controlling COVID-19 using mobile phone tracking

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Lockdown timing and efficacy in controlling COVID-19 using mobile phone tracking
Creator	Ferrari, Fabrizio Filippini, Tommaso Goffi, Alessia Maffeis, Giuseppe Orsini, Nicola Rothman, Kenneth Vinceti, Marco
Source	Elsevier; Medline; PMC
abstract	BACKGROUND: Italy's severe COVID-19 outbreak was addressed by a lockdown that gradually increased in space, time and intensity. The effectiveness of the lockdown has not been precisely assessed with respect to the intensity of mobility restriction and the time until the outbreak receded. METHODS: We used processed mobile phone tracking data to measure mobility restriction, and related those data to the number of new SARS-CoV-2 positive cases detected on a daily base in the three most affected Italian regions, Lombardy, Veneto and Emilia-Romagna, from February 1 through April 6, 2020, when two subsequent lockdowns with increasing intensity were implemented by the Italian government. FINDINGS: During the study period, mobility restriction was inversely related to the daily number of newly diagnosed SARS-CoV-2 positive cases only after the second, more effective lockdown, with a peak in the curve of diagnosed cases of infection occurring 14 to 18 days from lockdown in the three regions and 9 to 25 days in the included provinces. An effective reduction in transmission must have occurred nearly immediately after the tighter lockdown, given the lag time of around 10 days from asymptomatic infection to diagnosis. The period from lockdown to peak was shorter in the areas with the highest prevalence of the infection. This effect was seen within slightly more than one week in the most severely affected areas. INTERPRETATION: It appears that the less rigid lockdown led to an insufficient decrease in mobility to reverse an outbreak such as COVID-19. With a tighter lockdown, mobility decreased enough to bring down transmission promptly below the level needed to sustain the epidemic. FUNDING: No funding sources have been used for this work.
has issue date	2020-07-13(xsd:dateTime)
bibo:doi	10.1016/j.eclinm.2020.100457
bibo:pmid	32838234
has license	no-cc
sha1sum (hex)	924d55f6d8212ff8c30d109f7b8ba7d40f67bfeb
schema:url	https://doi.org/10.1016/j.eclinm.2020.100457
resource representing a document's title	Lockdown timing and efficacy in controlling COVID-19 using mobile phone tracking
has PubMed Central identifier	PMC7355328
has PubMed identifier	32838234
schema:publication	EClinicalMedicine
resource representing a document's body	covid:924d55f6d8212ff8c30d109f7b8ba7d40f67bfeb#body_text
is schema:about of	named entity 'effective' named entity 'SARS-CoV-2' named entity 'April 6' named entity 'RTI' named entity 'MOBILE PHONE' named entity 'USED' named entity 'DAYS' named entity 'gradually' named entity 'study' named entity 'outbreak' named entity 'restriction' named entity 'days' named entity 'mobility' named entity 'Background' named entity 'data' named entity 'cases' named entity 'Lombardy' named entity 'Italian regions' named entity 'mobility' named entity 'data analysis' named entity 'Italy' named entity 'linear regression' named entity 'SARS-CoV-2' named entity 'dashed' named entity 'gray line' named entity 'April 6' named entity 'mobile phone tracking' named entity 'cell phone' named entity 'Italy' named entity 'cumulative incidence' named entity 'Italian regions' named entity '5.7' named entity 'individual mobility' named entity 'Lombardy' named entity 'SARS-CoV-2' named entity 'gray line' named entity 'Rome' named entity 'nationwide lockdown' named entity 'infection' named entity 'public transportation' named entity 'Veneto' named entity 'Northern Italy' named entity 'Piacenza' named entity 'infection' named entity 'Codogno' named entity 'COVID-19' named entity 'Italy' named entity 'air pollutants' named entity 'February 23' named entity 'SARS-CoV-2' named entity 'COVID-19 outbreak' named entity 'Bergamo' named entity 'Lombardy' named entity 'SARS-CoV-2' named entity 'Italian regions' named entity 'February 24' named entity 'mobile phone' named entity 'individual mobility' named entity 'Veneto' named entity 'Brescia' named entity 'Ferrara' named entity 'Stata' named entity 'Lombardy' named entity 'Lombardy' named entity 'gray line' named entity 'virus' named entity 'heteroskedasticity' named entity 'individual mobility' named entity 'February 23' named entity 'Pavia' named entity 'mobile phone' named entity 'cubic splines' named entity 'mobile phone tracking' named entity 'Italy' named entity 'Codogno'

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