CovidPublicV1, Main, Exploration, bibRecord, 000133

Influenza-negative influenza-like illness (fnILI) Z-score as a proxy for incidence and mortality of COVID-19.

Identifieur interne : 000133 ( Main/Exploration ); précédent : 000132; suivant : 000134

Influenza-negative influenza-like illness (fnILI) Z-score as a proxy for incidence and mortality of COVID-19.

Auteurs : Fatima N. Mirza [États-Unis] ; Amyn A. Malik [États-Unis] ; Chandra Couzens [États-Unis] ; Saad B. Omer [États-Unis]

Source :

The Journal of infection [ 1532-2742 ] ; 2020.

RBID : pubmed:32888977

Descripteurs français

KwdFr :
- Bases de données factuelles (MeSH), Betacoronavirus (MeSH), Grippe humaine (virologie), Grippe humaine (épidémiologie), Humains (MeSH), Incidence (MeSH), Infections à coronavirus (mortalité), Infections à coronavirus (virologie), Infections à coronavirus (épidémiologie), Orthomyxoviridae (MeSH), Pandémies (MeSH), Pneumopathie virale (mortalité), Pneumopathie virale (virologie), Pneumopathie virale (épidémiologie), Saisons (MeSH), États-Unis (épidémiologie).
MESH :
- mortalité : Infections à coronavirus, Pneumopathie virale.
- virologie : Grippe humaine, Infections à coronavirus, Pneumopathie virale.
- épidémiologie : Grippe humaine, Infections à coronavirus, Pneumopathie virale, États-Unis.
- Bases de données factuelles, Betacoronavirus, Humains, Incidence, Orthomyxoviridae, Pandémies, Saisons.
Wicri :
- geographic : États-Unis.

English descriptors

KwdEn :
- Betacoronavirus (MeSH), COVID-19 (MeSH), Centers for Disease Control and Prevention, U.S. (MeSH), Coronavirus Infections (epidemiology), Coronavirus Infections (mortality), Coronavirus Infections (virology), Databases, Factual (MeSH), Humans (MeSH), Incidence (MeSH), Influenza, Human (epidemiology), Influenza, Human (virology), Orthomyxoviridae (MeSH), Pandemics (MeSH), Pneumonia, Viral (epidemiology), Pneumonia, Viral (mortality), Pneumonia, Viral (virology), SARS-CoV-2 (MeSH), Seasons (MeSH), United States (epidemiology).
MESH :
- geographic , epidemiology : United States.
- epidemiology : Coronavirus Infections, Influenza, Human, Pneumonia, Viral.
- mortality : Coronavirus Infections, Pneumonia, Viral.
- virology : Coronavirus Infections, Influenza, Human, Pneumonia, Viral.
- Betacoronavirus, COVID-19, Centers for Disease Control and Prevention, U.S., Databases, Factual, Humans, Incidence, Orthomyxoviridae, Pandemics, SARS-CoV-2, Seasons.

Abstract

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.

DOI: 10.1016/j.jinf.2020.08.046
PubMed: 32888977
PubMed Central: PMC7462572

Affiliations:

Links toward previous steps (curation, corpus...)

to stream Main, to step Corpus: 000126
to stream Main, to step Curation: 000126

Le document en format XML

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<front><div type="abstract" xml:lang="en">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.</div>
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<Abstract><AbstractText>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.</AbstractText>
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Influenza-negative influenza-like illness (fnILI) Z-score as a proxy for incidence and mortality of COVID-19.

Influenza-negative influenza-like illness (fnILI) Z-score as a proxy for incidence and mortality of COVID-19.

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