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Leveraging community mortality indicators to infer COVID-19 mortality and transmission dynamics in Damascus, Syria

Author

Listed:
  • Oliver J. Watson

    (Imperial College London)

  • Mervat Alhaffar

    (London School of Hygiene and Tropical Medicine)

  • Zaki Mehchy

    (London Schools of Economics)

  • Charles Whittaker

    (Imperial College London)

  • Zack Akil

    (Google)

  • Nicholas F. Brazeau

    (Imperial College London)

  • Gina Cuomo-Dannenburg

    (Imperial College London)

  • Arran Hamlet

    (Imperial College London)

  • Hayley A. Thompson

    (Imperial College London)

  • Marc Baguelin

    (Imperial College London
    London School of Hygiene and Tropical Medicine)

  • Richard G. FitzJohn

    (Imperial College London)

  • Edward Knock

    (Imperial College London)

  • John A. Lees

    (Imperial College London)

  • Lilith K. Whittles

    (Imperial College London)

  • Thomas Mellan

    (Imperial College London)

  • Peter Winskill

    (Imperial College London)

  • Natasha Howard

    (London School of Hygiene and Tropical Medicine
    National University of Singapore and National University Health System)

  • Hannah Clapham

    (National University of Singapore and National University Health System)

  • Francesco Checchi

    (London School of Hygiene and Tropical Medicine)

  • Neil Ferguson

    (Imperial College London)

  • Azra Ghani

    (Imperial College London)

  • Emma Beals

    (European Institute of Peace
    Middle East Institute)

  • Patrick Walker

    (Imperial College London)

Abstract

The COVID-19 pandemic has resulted in substantial mortality worldwide. However, to date, countries in the Middle East and Africa have reported considerably lower mortality rates than in Europe and the Americas. Motivated by reports of an overwhelmed health system, we estimate the likely under-ascertainment of COVID-19 mortality in Damascus, Syria. Using all-cause mortality data, we fit a mathematical model of COVID-19 transmission to reported mortality, estimating that 1.25% of COVID-19 deaths (sensitivity range 1.00% – 3.00%) have been reported as of 2 September 2020. By 2 September, we estimate that 4,380 (95% CI: 3,250 – 5,550) COVID-19 deaths in Damascus may have been missed, with 39.0% (95% CI: 32.5% – 45.0%) of the population in Damascus estimated to have been infected. Accounting for under-ascertainment corroborates reports of exceeded hospital bed capacity and is validated by community-uploaded obituary notifications, which confirm extensive unreported mortality in Damascus.

Suggested Citation

  • Oliver J. Watson & Mervat Alhaffar & Zaki Mehchy & Charles Whittaker & Zack Akil & Nicholas F. Brazeau & Gina Cuomo-Dannenburg & Arran Hamlet & Hayley A. Thompson & Marc Baguelin & Richard G. FitzJohn, 2021. "Leveraging community mortality indicators to infer COVID-19 mortality and transmission dynamics in Damascus, Syria," Nature Communications, Nature, vol. 12(1), pages 1-10, December.
    • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-22474-9
    DOI: 10.1038/s41467-021-22474-9
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    Cited by:

    1. Richard J. Sheppard & Oliver J. Watson & Rachel Pieciak & James Lungu & Geoffrey Kwenda & Crispin Moyo & Stephen Longa Chanda & Gregory Barnsley & Nicholas F. Brazeau & Ines C. G. Gerard-Ursin & Danie, 2023. "Using mortuary and burial data to place COVID-19 in Lusaka, Zambia within a global context," Nature Communications, Nature, vol. 14(1), pages 1-15, December.

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