tetano
Editor, Senior Moderator
BMC Med
. 2020 Jul 15;18(1):218.
doi: 10.1186/s12916-020-01692-w.
Projected geographic disparities in healthcare worker absenteeism from COVID-19 school closures and the economic feasibility of child care subsidies: a simulation study
Elizabeth T Chin[SUP] 1 [/SUP], Benjamin Q Huynh[SUP] 2 [/SUP], Nathan C Lo[SUP] 3 [/SUP], Trevor Hastie[SUP] 2 4 [/SUP], Sanjay Basu[SUP] 5 6 7 [/SUP]
Affiliations
Abstract
Background: School closures have been enacted as a measure of mitigation during the ongoing coronavirus disease 2019 (COVID-19) pandemic. It has been shown that school closures could cause absenteeism among healthcare workers with dependent children, but there remains a need for spatially granular analyses of the relationship between school closures and healthcare worker absenteeism to inform local community preparedness.
Methods: We provide national- and county-level simulations of school closures and unmet child care needs across the USA. We develop individual simulations using county-level demographic and occupational data, and model school closure effectiveness with age-structured compartmental models. We perform multivariate quasi-Poisson ecological regressions to find associations between unmet child care needs and COVID-19 vulnerability factors.
Results: At the national level, we estimate the projected rate of unmet child care needs for healthcare worker households to range from 7.4 to 8.7%, and the effectiveness of school closures as a 7.6% and 8.4% reduction in fewer hospital and intensive care unit (ICU) beds, respectively, at peak demand when varying across initial reproduction number estimates by state. At the county level, we find substantial variations of projected unmet child care needs and school closure effects, 9.5% (interquartile range (IQR) 8.2-10.9%) of healthcare worker households and 5.2% (IQR 4.1-6.5%) and 6.8% (IQR 4.8-8.8%) reduction in fewer hospital and ICU beds, respectively, at peak demand. We find significant positive associations between estimated levels of unmet child care needs and diabetes prevalence, county rurality, and race (p<0.05). We estimate costs of absenteeism and child care and observe from our models that an estimated 76.3 to 96.8% of counties would find it less expensive to provide child care to all healthcare workers with children than to bear the costs of healthcare worker absenteeism during school closures.
Conclusions: School closures are projected to reduce peak ICU and hospital demand, but could disrupt healthcare systems through absenteeism, especially in counties that are already particularly vulnerable to COVID-19. Child care subsidies could help circumvent the ostensible trade-off between school closures and healthcare worker absenteeism.
Keywords: Absenteeism; COVID-19; Child care; Geographic disparities; Geospatial; School closures; Simulation study.
. 2020 Jul 15;18(1):218.
doi: 10.1186/s12916-020-01692-w.
Projected geographic disparities in healthcare worker absenteeism from COVID-19 school closures and the economic feasibility of child care subsidies: a simulation study
Elizabeth T Chin[SUP] 1 [/SUP], Benjamin Q Huynh[SUP] 2 [/SUP], Nathan C Lo[SUP] 3 [/SUP], Trevor Hastie[SUP] 2 4 [/SUP], Sanjay Basu[SUP] 5 6 7 [/SUP]
Affiliations
- PMID: 32664927
- DOI: 10.1186/s12916-020-01692-w
Abstract
Background: School closures have been enacted as a measure of mitigation during the ongoing coronavirus disease 2019 (COVID-19) pandemic. It has been shown that school closures could cause absenteeism among healthcare workers with dependent children, but there remains a need for spatially granular analyses of the relationship between school closures and healthcare worker absenteeism to inform local community preparedness.
Methods: We provide national- and county-level simulations of school closures and unmet child care needs across the USA. We develop individual simulations using county-level demographic and occupational data, and model school closure effectiveness with age-structured compartmental models. We perform multivariate quasi-Poisson ecological regressions to find associations between unmet child care needs and COVID-19 vulnerability factors.
Results: At the national level, we estimate the projected rate of unmet child care needs for healthcare worker households to range from 7.4 to 8.7%, and the effectiveness of school closures as a 7.6% and 8.4% reduction in fewer hospital and intensive care unit (ICU) beds, respectively, at peak demand when varying across initial reproduction number estimates by state. At the county level, we find substantial variations of projected unmet child care needs and school closure effects, 9.5% (interquartile range (IQR) 8.2-10.9%) of healthcare worker households and 5.2% (IQR 4.1-6.5%) and 6.8% (IQR 4.8-8.8%) reduction in fewer hospital and ICU beds, respectively, at peak demand. We find significant positive associations between estimated levels of unmet child care needs and diabetes prevalence, county rurality, and race (p<0.05). We estimate costs of absenteeism and child care and observe from our models that an estimated 76.3 to 96.8% of counties would find it less expensive to provide child care to all healthcare workers with children than to bear the costs of healthcare worker absenteeism during school closures.
Conclusions: School closures are projected to reduce peak ICU and hospital demand, but could disrupt healthcare systems through absenteeism, especially in counties that are already particularly vulnerable to COVID-19. Child care subsidies could help circumvent the ostensible trade-off between school closures and healthcare worker absenteeism.
Keywords: Absenteeism; COVID-19; Child care; Geographic disparities; Geospatial; School closures; Simulation study.