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10.1017/dmp.2020.353 http://scihub22266oqcxt.onion/10.1017/dmp.2020.353 32907678!7591754!32907678     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=32907678&cmd=llinks): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 215       Disaster+Med+Public+Health+Prep 2021 ; 15 (4): e10-e11 Nephropedia Template TP {{tp|p=32907678|t=2021. Current Data Gaps in Modeling Essential Worker Absenteeism Due to COVID-19 |pdf=|usr=}}{{32907678}} gab.com Text Current Data Gaps in Modeling Essential Worker Absenteeism Due to COVID-19 JO: Disaster Med Public Health Prep http://www.kidney.de/pget.php?&tw=1&pmid=32907678 #FOAvip With the uncertain physical and mental health implications of COVID-19 infection, companies have taken a myriad of actions that aim to reduce the risk of employees contracting the virus, with most grounded in reducing or eliminating in-person interactions. Our preliminary analysis indicates that while there is some data to support modelling absenteeism, there are gaps in the available evidence, requiring the use of assumptions that limit precision and efficacy for decision support. Improved data on time-to-recovery after hospitalization, absenteeism due to family or other household member illness, and mental health's impact on returning to work will support the development of more robust absenteeism models and analytical approaches. Twit Text FOAVip Current Data Gaps in Modeling Essential Worker Absenteeism Due to COVID-19 ????Disaster Med Public Health Prep http://www.kidney.de/pget.php?&tw=1&pmid=32907678 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32907678 #FOAvip English Wikipedia <ref>{{Cite pmid|32907678}}</ref> Current Data Gaps in Modeling Essential Worker Absenteeism Due to COVID-19 #MMPMID32907678 White Z; Schlegelmilch J; Ratner J; Saxena G; Wongsodirdjo K; Aguilar S; Kushner D; Ortega J; Paaso A; Bahramirad S Disaster Med Public Health Prep 2021[Aug]; 15 (4): e10-e11 PMID32907678show ga With the uncertain physical and mental health implications of COVID-19 infection, companies have taken a myriad of actions that aim to reduce the risk of employees contracting the virus, with most grounded in reducing or eliminating in-person interactions. Our preliminary analysis indicates that while there is some data to support modelling absenteeism, there are gaps in the available evidence, requiring the use of assumptions that limit precision and efficacy for decision support. Improved data on time-to-recovery after hospitalization, absenteeism due to family or other household member illness, and mental health's impact on returning to work will support the development of more robust absenteeism models and analytical approaches. |*Absenteeism[MESH] |*COVID-19/epidemiology/therapy[MESH] |*Data Collection/standards[MESH] |*Employment/statistics & numerical data[MESH] |Hospitalization[MESH] |Humans[MESH]Current Data Gaps in Modeling Essential Worker Absenteeism Due to COVI(epmc).pdf DeepDyve Pubget Overpricing