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1000 Titel
  • Estimation of country-level basic reproductive ratios for novel Coronavirus (SARS-CoV-2/COVID-19) using synthetic contact matrices
1000 Autor/in
  1. Hilton, Joe |
  2. Keeling, Matt |
1000 Erscheinungsjahr 2020
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2020-07-02
1000 Erschienen in
1000 Quellenangabe
  • 16(7):e1008031
1000 Copyrightjahr
  • 2020
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1371/journal.pcbi.1008031 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7363110/ |
1000 Ergänzendes Material
  • https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1008031#sec005 |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • The 2019-2020 pandemic of atypical pneumonia (COVID-19) caused by the virus SARS-CoV-2 has spread globally and has the potential to infect large numbers of people in every country. Estimating the country-specific basic reproductive ratio is a vital first step in public-health planning. The basic reproductive ratio (R0) is determined by both the nature of pathogen and the network of human contacts through which the disease can spread, which is itself dependent on population age structure and household composition. Here we introduce a transmission model combining age-stratified contact frequencies with age-dependent susceptibility, probability of clinical symptoms, and transmission from asymptomatic (or mild) cases, which we use to estimate the country-specific basic reproductive ratio of COVID-19 for 152 countries. Using early outbreak data from China and a synthetic contact matrix, we estimate an age-stratified transmission structure which can then be extrapolated to 151 other countries for which synthetic contact matrices also exist. This defines a set of country-specific transmission structures from which we can calculate the basic reproductive ratio for each country. Our predicted R0 is critically sensitive to the intensity of transmission from asymptomatic cases; with low asymptomatic transmission the highest values are predicted across Eastern Europe and Japan and the lowest across Africa, Central America and South-Western Asia. This pattern is largely driven by the ratio of children to older adults in each country and the observed propensity of clinical cases in the elderly. If asymptomatic cases have comparable transmission to detected cases, the pattern is reversed. Our results demonstrate the importance of age-specific heterogeneities going beyond contact structure to the spread of COVID-19. These heterogeneities give COVID-19 the capacity to spread particularly quickly in countries with older populations, and that intensive control measures are likely to be necessary to impede its progress in these countries. AUTHOR SUMMARY: Over 100 countries have reported laboratory-confirmed cases of atypical pneumonia caused by 2019 novel coronavirus (COVID-19). Cases are largely reported in older age groups, suggesting a strong age-dependent component to either transmission or the probability of developing symptoms and thus being detected. We introduce a mathematical model for COVID-19 transmission in which contact behaviour, susceptibility, detection probability, and transmission from undetected cases all vary with age. We fit our model to epidemiological data from the outbreak in China for the special case where asymptomatic transmission is negligible, and compare it to a null model where only contact behaviour varies with age. Our fitted model suggests that contacts involving older individuals are particularly likely to generate new detected cases, intensifying the spread of infection in countries with older populations. We estimate the basic reproductive ratio (a measure of a pathogen’s capacity for spread) of COVID-19 in 152 countries under both models, and find that estimates of the basic reproductive ratio are highly dependent on the assumed underlying transmission structure; our more complex model predicts higher values in Japan and much of Europe and lower values in much of Africa, in comparison to the contact frequency-based model where this pattern is reversed.
1000 Sacherschließung
lokal Epidemiology
gnd 1206347392 COVID-19
lokal Infectious disease epidemiology
lokal Italy
lokal China
lokal Japan
lokal Mathematical models
lokal Europe
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. https://orcid.org/0000-0002-2787-3827|https://orcid.org/0000-0003-4639-4765
1000 Label
1000 Förderer
  1. National Institute for Health Research |
  2. Government of the United Kingdom |
  3. Engineering and Physical Sciences Research Council |
  4. Health Data Research UK (HDR UK) |
1000 Fördernummer
  1. 17/63/82
  2. -
  3. EP/S022244/1
  4. -
1000 Förderprogramm
  1. -
  2. -
  3. -
  4. -
1000 Dateien
1000 Förderung
  1. 1000 joinedFunding-child
    1000 Förderer National Institute for Health Research |
    1000 Förderprogramm -
    1000 Fördernummer 17/63/82
  2. 1000 joinedFunding-child
    1000 Förderer Government of the United Kingdom |
    1000 Förderprogramm -
    1000 Fördernummer -
  3. 1000 joinedFunding-child
    1000 Förderer Engineering and Physical Sciences Research Council |
    1000 Förderprogramm -
    1000 Fördernummer EP/S022244/1
  4. 1000 joinedFunding-child
    1000 Förderer Health Data Research UK (HDR UK) |
    1000 Förderprogramm -
    1000 Fördernummer -
1000 Objektart article
1000 Beschrieben durch
1000 @id frl:6422741.rdf
1000 Erstellt am 2020-08-25T12:27:09.721+0200
1000 Erstellt von 122
1000 beschreibt frl:6422741
1000 Bearbeitet von 122
1000 Zuletzt bearbeitet 2020-08-25T12:29:57.935+0200
1000 Objekt bearb. Tue Aug 25 12:29:36 CEST 2020
1000 Vgl. frl:6422741
1000 Oai Id
  1. oai:frl.publisso.de:frl:6422741 |
1000 Sichtbarkeit Metadaten public
1000 Sichtbarkeit Daten public
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