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A framework for reconstructing SARS-CoV-2 transmission dynamics using excess mortality data

Author

Listed:
  • Mahan Ghafari

    (University of Oxford)

  • Oliver J. Watson

    (Imperial College London)

  • Ariel Karlinsky

    (Hebrew University of Jerusalem)

  • Luca Ferretti

    (University of Oxford)

  • Aris Katzourakis

    (University of Oxford)

Abstract

The transmission dynamics and burden of SARS-CoV-2 in many regions of the world is still largely unknown due to the scarcity of epidemiological analyses and lack of testing to assess the prevalence of disease. In this work, we develop a quantitative framework based on excess mortality data to reconstruct SARS-CoV-2 transmission dynamics and assess the level of underreporting in infections and deaths. Using weekly all-cause mortality data from Iran, we are able to show a strong agreement between our attack rate estimates and seroprevalence measurements in each province and find significant heterogeneity in the level of exposure across the country with 11 provinces reaching near 100% attack rates. Despite having a young population, our analysis reveals that incorporating limited access to medical services in our model, coupled with undercounting of COVID-19-related deaths, leads to estimates of infection fatality rate in most provinces of Iran that are comparable to high-income countries.

Suggested Citation

  • Mahan Ghafari & Oliver J. Watson & Ariel Karlinsky & Luca Ferretti & Aris Katzourakis, 2022. "A framework for reconstructing SARS-CoV-2 transmission dynamics using excess mortality data," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
  • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-30711-y
    DOI: 10.1038/s41467-022-30711-y
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    Cited by:

    1. Ariel Karlinsky & Orsola Torrisi, 2023. "The Casualties of War: An Excess Mortality Estimate of Lives Lost in the 2020 Nagorno-Karabakh Conflict," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 42(3), pages 1-24, June.

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