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Rhinovirus prevalence as indicator for efficacy of measures against SARS-CoV-2.
Kitanovski, Simo; Horemheb-Rubio, Gibran; Adams, Ortwin; Gärtner, Barbara; Lengauer, Thomas; Hoffmann, Daniel; Kaiser, Rolf.
  • Kitanovski S; Bioinformatics and Computational Biophysics, Faculty of Biology and Centre for Medical Biotechnology (ZMB), University of Duisburg-Essen, Essen, 45141, Germany.
  • Horemheb-Rubio G; Institute of Virology, University of Cologne, Faculty of Medicine and University Hospital of Cologne, Cologne, 50935, Germany.
  • Adams O; Department of Infectious Diseases, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, 14080, Mexico.
  • Gärtner B; Institute of Virology, University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, 40225, Germany.
  • Lengauer T; Institute of Medical Microbiology and Hygiene, Saarland University Medical Center, Homburg, 66421, Germany.
  • Hoffmann D; Computational Biology, Max Planck Institute for Informatics, Saarland Informatics Campus, Saarbrücken, 66123, Germany.
  • Kaiser R; Bioinformatics and Computational Biophysics, Faculty of Biology and Centre for Medical Biotechnology (ZMB), University of Duisburg-Essen, Essen, 45141, Germany. daniel.hoffmann@uni-due.de.
BMC Public Health ; 21(1): 1178, 2021 06 21.
Article in English | MEDLINE | ID: covidwho-1277928
ABSTRACT

BACKGROUND:

Non-pharmaceutical measures to control the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) should be carefully tuned as they can impose a heavy social and economic burden. To quantify and possibly tune the efficacy of these anti-SARS-CoV-2 measures, we have devised indicators based on the abundant historic and current prevalence data from other respiratory viruses.

METHODS:

We obtained incidence data of 17 respiratory viruses from hospitalized patients and outpatients collected by 37 clinics and laboratories between 2010-2020 in Germany. With a probabilistic model for Bayes inference we quantified prevalence changes of the different viruses between months in the pre-pandemic period 2010-2019 and the corresponding months in 2020, the year of the pandemic with noninvasive measures of various degrees of stringency.

RESULTS:

We discovered remarkable reductions δ in rhinovirus (RV) prevalence by about 25% (95% highest density interval (HDI) [-0.35,-0.15]) in the months after the measures against SARS-CoV-2 were introduced in Germany. In the months after the measures began to ease, RV prevalence increased to low pre-pandemic levels, e.g. in August 2020 δ=-0.14 (95% HDI [-0.28,0.12]).

CONCLUSIONS:

RV prevalence is negatively correlated with the stringency of anti-SARS-CoV-2 measures with only a short time delay. This result suggests that RV prevalence could possibly be an indicator for the efficiency for these measures. As RV is ubiquitous at higher prevalence than SARS-CoV-2 or other emerging respiratory viruses, it could reflect the efficacy of noninvasive measures better than such emerging viruses themselves with their unevenly spreading clusters.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Rhinovirus / COVID-19 Type of study: Observational study / Prognostic study Limits: Humans Country/Region as subject: Europa Language: English Journal: BMC Public Health Journal subject: Public Health Year: 2021 Document Type: Article Affiliation country: S12889-021-11178-w

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Rhinovirus / COVID-19 Type of study: Observational study / Prognostic study Limits: Humans Country/Region as subject: Europa Language: English Journal: BMC Public Health Journal subject: Public Health Year: 2021 Document Type: Article Affiliation country: S12889-021-11178-w