PMID- 32664927 OWN - NLM STAT- MEDLINE DCOM- 20200721 LR - 20240329 IS - 1741-7015 (Electronic) IS - 1741-7015 (Linking) VI - 18 IP - 1 DP - 2020 Jul 15 TI - Projected geographic disparities in healthcare worker absenteeism from COVID-19 school closures and the economic feasibility of child care subsidies: a simulation study. PG - 218 LID - 10.1186/s12916-020-01692-w [doi] LID - 218 AB - 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. FAU - Chin, Elizabeth T AU - Chin ET AUID- ORCID: 0000-0001-5774-4236 AD - Department of Biomedical Data Science, Stanford University, Stanford, CA, USA. etchin@stanford.edu. FAU - Huynh, Benjamin Q AU - Huynh BQ AD - Department of Biomedical Data Science, Stanford University, Stanford, CA, USA. FAU - Lo, Nathan C AU - Lo NC AD - Department of Medicine, University of California San Francisco, San Francisco, CA, USA. FAU - Hastie, Trevor AU - Hastie T AD - Department of Biomedical Data Science, Stanford University, Stanford, CA, USA. AD - Department of Statistics, Stanford University, Stanford, CA, USA. FAU - Basu, Sanjay AU - Basu S AD - Center for Primary Care, Harvard Medical School, Boston, MA, USA. AD - Research and Public Health, Collective Health, San Francisco, CA, USA. AD - School of Public Health, Imperial College, London, UK. LA - eng GR - T15 LM007033/LM/NLM NIH HHS/United States PT - Journal Article PT - Research Support, N.I.H., Extramural PT - Research Support, Non-U.S. Gov't DEP - 20200715 PL - England TA - BMC Med JT - BMC medicine JID - 101190723 SB - IM UOF - medRxiv. 2020 Apr 16;:. PMID: 32511455 MH - *Absenteeism MH - Betacoronavirus MH - COVID-19 MH - Child MH - Child Care/*economics MH - Computer Simulation MH - Coronavirus Infections/*epidemiology MH - Feasibility Studies MH - Forecasting MH - Geography MH - Health Personnel/*statistics & numerical data MH - Health Workforce MH - Humans MH - Intensive Care Units MH - Needs Assessment MH - Pandemics MH - Pneumonia, Viral/*epidemiology MH - SARS-CoV-2 MH - *Schools MH - United States/epidemiology PMC - PMC7360472 OTO - NOTNLM OT - Absenteeism OT - COVID-19 OT - Child care OT - Geographic disparities OT - Geospatial OT - School closures OT - Simulation study COIS- The authors declare that they have no competing interests. EDAT- 2020/07/16 06:00 MHDA- 2020/07/22 06:00 PMCR- 2020/07/15 CRDT- 2020/07/16 06:00 PHST- 2020/04/08 00:00 [received] PHST- 2020/07/01 00:00 [accepted] PHST- 2020/07/16 06:00 [entrez] PHST- 2020/07/16 06:00 [pubmed] PHST- 2020/07/22 06:00 [medline] PHST- 2020/07/15 00:00 [pmc-release] AID - 10.1186/s12916-020-01692-w [pii] AID - 1692 [pii] AID - 10.1186/s12916-020-01692-w [doi] PST - epublish SO - BMC Med. 2020 Jul 15;18(1):218. doi: 10.1186/s12916-020-01692-w.