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Real-time estimation and prediction of mortality caused by COVID-19 with patient information based algorithm.
Wang, Lishi; Li, Jing; Guo, Sumin; Xie, Ning; Yao, Lan; Cao, Yanhong; Day, Sara W; Howard, Scott C; Graff, J Carolyn; Gu, Tianshu; Ji, Jiafu; Gu, Weikuan; Sun, Dianjun.
Afiliação
  • Wang L; Department of Basic Medicine, Inner Mongolia Medical University, Inner Mongolia 010110, PR China; Department of Orthopedic Surgery and BME-Campbell Clinic, University of Tennessee Health Science Center, Memphis, TN 38163, USA.
  • Li J; Department of Orthopedic Surgery and BME-Campbell Clinic, University of Tennessee Health Science Center, Memphis, TN 38163, USA.
  • Guo S; Department of Oncology, Hebei Chest Hospital, Lung Cancer Control and Prevention Center of Hebei Province, Shijiazhuang, Hebei 050041, PR China.
  • Xie N; College of Business, University of Louisville, Louisville, KY 40292, USA.
  • Yao L; Health Outcomes and Policy Research, College of Graduate Health Sciences, University of Tennessee Health Science Center, Memphis, TN 38103, USA; Center for Endemic Disease Control, Chinese Center for Disease Control and Prevention, Harbin Medical University, 157 Baojian Road, Harbin, Heilongjiang 15
  • Cao Y; Center for Endemic Disease Control, Chinese Center for Disease Control and Prevention, Harbin Medical University, 157 Baojian Road, Harbin, Heilongjiang 150081, PR China; Key Laboratory of Etiologic Epidemiology, Education Bureau of Heilongjiang Province & Ministry of Health (23618104), Harbin,
  • Day SW; College of Nursing, University of Tennessee Health Science Center, Memphis, TN 38105, USA.
  • Howard SC; College of Nursing, University of Tennessee Health Science Center, Memphis, TN 38105, USA.
  • Graff JC; College of Nursing, University of Tennessee Health Science Center, Memphis, TN 38105, USA.
  • Gu T; Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100050, PR China.
  • Ji J; Beijing Cancer Hospital and Key Laboratory of Carcinogenesis and Translational Research, Department of Gastrointestinal Surgery, Peking University Cancer Hospital and Institute, Beijing 100142, PR China.
  • Gu W; Department of Orthopedic Surgery and BME-Campbell Clinic, University of Tennessee Health Science Center, Memphis, TN 38163, USA; Research Service, Memphis VA Medical Center, 1030 Jefferson Avenue, Memphis, TN 38104, USA. Electronic address: wgu@uthsc.edu.
  • Sun D; Center for Endemic Disease Control, Chinese Center for Disease Control and Prevention, Harbin Medical University, 157 Baojian Road, Harbin, Heilongjiang 150081, PR China. Electronic address: hrbmusdj@163.com.
Sci Total Environ ; 727: 138394, 2020 Jul 20.
Article em En | MEDLINE | ID: mdl-32334207
The global COVID-19 outbreak is worrisome both for its high rate of spread, and the high case fatality rate reported by early studies and now in Italy. We report a new methodology, the Patient Information Based Algorithm (PIBA), for estimating the death rate of a disease in real-time using publicly available data collected during an outbreak. PIBA estimated the death rate based on data of the patients in Wuhan and then in other cities throughout China. The estimated days from hospital admission to death was 13 (standard deviation (SD), 6 days). The death rates based on PIBA were used to predict the daily numbers of deaths since the week of February 25, 2020, in China overall, Hubei province, Wuhan city, and the rest of the country except Hubei province. The death rate of COVID-19 ranges from 0.75% to 3% and may decrease in the future. The results showed that the real death numbers had fallen into the predicted ranges. In addition, using the preliminary data from China, the PIBA method was successfully used to estimate the death rate and predict the death numbers of the Korean population. In conclusion, PIBA can be used to efficiently estimate the death rate of a new infectious disease in real-time and to predict future deaths. The spread of 2019-nCoV and its case fatality rate may vary in regions with different climates and temperatures from Hubei and Wuhan. PIBA model can be built based on known information of early patients in different countries.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Pneumonia Viral / Algoritmos / Infecções por Coronavirus / Pandemias / Betacoronavirus Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans País como assunto: Asia / Europa Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Pneumonia Viral / Algoritmos / Infecções por Coronavirus / Pandemias / Betacoronavirus Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans País como assunto: Asia / Europa Idioma: En Ano de publicação: 2020 Tipo de documento: Article