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Time-analysis of COVID-19 dispersion among health care workers and the general population
Patricia A. F. Leme; Mehrsa Jalalizadeh; Franciele A. V. Dionato; Keini Buosi; Luciana S.B. Dal Col; Cristiane F. Giacomelli; Karen L. Ferrari; Ana Carolina Pagliarone; Lucas M. Gon; Cristiane L. Maia; Akbar A. Esfahani; Leonardo Oliveira Reis.
Afiliação
  • Patricia A. F. Leme; University of Campinas, Unicamp
  • Mehrsa Jalalizadeh; University of Campinas, Unicamp
  • Franciele A. V. Dionato; University of Campinas, Unicamp
  • Keini Buosi; University of Campinas, Unicamp
  • Luciana S.B. Dal Col; University of Campinas, Unicamp
  • Cristiane F. Giacomelli; University of Campinas, Unicamp
  • Karen L. Ferrari; University of Campinas, Unicamp
  • Ana Carolina Pagliarone; University of Campinas, Unicamp
  • Lucas M. Gon; University of Campinas, Unicamp
  • Cristiane L. Maia; University of Campinas, Unicamp
  • Akbar A. Esfahani; University of Campinas, Unicamp
  • Leonardo Oliveira Reis; UroScience, School of Medical Sciences, University of Campinas, UNICAMP and Pontifical Catholic University of Campinas, PUC-Campinas, Brazil.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-21261433
ABSTRACT
IntroductionHeath care workers with direct (HCW-D) or indirect (HCW-A) patient contact represent 4.2% to 17.8% of COVID-19 cases. We evaluate the temporal COVID-19 infection behavior among HCW-D, HCW-A, and non-HCW. MethodsFrom February 2020 to April 2021, trained nurses recorded age, gender, occupation, and symptoms in a COVID-19 testing outpatient health center. We allocated data into weekly time fractals and calculated the proportion of COVID-19 positive among HCW vs. non-HCW and incorporated an ARFIMA model (traditionally used in weather forecast) to predict future cases of COVID-19. ResultsAmong 8,998 COVID-19 RT-PCR tests, 3,462 (42%) patients were HCW-D, and 933 (11%) were HCW-A. Overall, 1,914 (21.3%) returned positive, representing 27%, 25% and 19% of HCW-D, HCW-A and non-HCW, respectively. HCW-D or HCW-A were significantly more likely to test positive for COVID-19 than non-HCW (OR=1.5, p<0.0001). The percentage of positive to negative test results remained steady over time. In the positive cases, the percentage of HCW to non-HCW declined significantly over time (Mann-Kendal trend test tau=-0.58, p<0.0001). Our ARFIMA model showed a long-memory infection pattern in the occurrence of new COVID-19 cases lasting for months. Average error was 1.9 cases per week comparing predicted to actual values three months later (May-July 2021). ConclusionHCW have a sustained 50% higher risk of COVID-19 positivity in the pandemic. Time-series analysis showed a long-memory infection pattern with virus spread mainly among HCWs before the general population. The tool http//wdchealth.covid-map.com/shiny/covid-map/ will be updated according to population previous infection and vaccination impact.
Licença
cc_by_nc_nd
Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Experimental_studies / Estudo prognóstico Idioma: Inglês Ano de publicação: 2021 Tipo de documento: Preprint
Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Experimental_studies / Estudo prognóstico Idioma: Inglês Ano de publicação: 2021 Tipo de documento: Preprint
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