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10.1016/j.jinf.2020.08.046

http://scihub22266oqcxt.onion/10.1016/j.jinf.2020.08.046
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suck abstract from ncbi


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pmid32888977      J+Infect 2020 ; 81 (5): 793-796
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  • Influenza-negative influenza-like illness (fnILI) Z-score as a proxy for incidence and mortality of COVID-19 #MMPMID32888977
  • Mirza FN; Malik AA; Couzens C; Omer SB
  • J Infect 2020[Nov]; 81 (5): 793-796 PMID32888977show ga
  • Although direct detection of SARS-CoV2 in symptomatic or asymptomatic individuals is the ideal epidemiological tool for determining the burden of disease, the lack of availability of testing can preclude its wider implementation as a robust surveillance system. We correlated the use of the derivative influenza-negative influenza-like illness (fnILI) z-score from the US Centers for Disease Control and Prevention as a proxy for incident cases and disease-specific deaths. For every unit increase of fnILI z-score, the number of cases increased by 376.5 (95% CI [202.5, 550.5]) and number of deaths increased by 10.2 (95% CI [5.4, 15.0]). FnILI data may serve as an accurate outcome measurement to track the spread of COVID-19 infection and disease, and allow for informed and timely decision-making on public health interventions.
  • |*Betacoronavirus[MESH]
  • |*Orthomyxoviridae[MESH]
  • |COVID-19[MESH]
  • |Centers for Disease Control and Prevention, U.S.[MESH]
  • |Coronavirus Infections/*epidemiology/*mortality/virology[MESH]
  • |Databases, Factual[MESH]
  • |Humans[MESH]
  • |Incidence[MESH]
  • |Influenza, Human/*epidemiology/virology[MESH]
  • |Pandemics[MESH]
  • |Pneumonia, Viral/*epidemiology/*mortality/virology[MESH]
  • |SARS-CoV-2[MESH]
  • |Seasons[MESH]


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