Who can go back to work when the COVID-19 pandemic remits?
PLoS One
; 15(8): e0238299, 2020.
Article
in English
| MEDLINE | ID: covidwho-732996
Preprint
This scientific journal article is probably based on a previously available preprint. It has been identified through a machine matching algorithm, human confirmation is still pending.
See preprint
This scientific journal article is probably based on a previously available preprint. It has been identified through a machine matching algorithm, human confirmation is still pending.
See preprint
ABSTRACT
This paper seeks to determine which workers affected by lockdown measures can return to work when a government decides to apply lockdown exit strategies. This system, which we call Sequential Selective Multidimensional Decision (SSMD), involves deciding sequentially, by geographical areas, sectors of activity, age groups and immunity, which workers can return to work at a given time according to the epidemiological criteria of the country as well as that of a group of reference countries, used as a benchmark, that have suffered a lower level of lockdown de-escalation strategies. We apply SSMD to Spain, based on affiliation to the Social Security system prior to the COVID-19 pandemic, and conclude that 98.37% of the population could be affected. The proposed system makes it possible to accurately identify the target population for serological IgG antibody tests in the work field, as well as those affected by special income replacement measures due to lockdown being maintained over a longer period.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Pneumonia, Viral
/
Coronavirus Infections
/
Return to Work
Type of study:
Experimental Studies
/
Observational study
/
Prognostic study
/
Randomized controlled trials
Limits:
Adolescent
/
Adult
/
Aged
/
Child
/
Child, preschool
/
Humans
/
Infant
/
Middle aged
/
Infant, Newborn
/
Young adult
Country/Region as subject:
Europa
Language:
English
Journal:
PLoS One
Journal subject:
Science
/
Medicine
Year:
2020
Document Type:
Article
Affiliation country:
Journal.pone.0238299
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