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Excess mortality during the COVID-19 pandemic in Aden governorate, Yemen: a geospatial and statistical analysis
Emilie S. Koum Besson; Andy Norris; Abdulla S. Bin Ghouth; Terri Freemantle; Mervat Alhaffar; Yolanda Vazquez; Chris Reeve; Patrick J. Curran; Francesco Checchi.
Afiliação
  • Emilie S. Koum Besson; Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, Keppel St, London School of Hygiene and Tropical Medicine, London,
  • Andy Norris; Satellite Applications Catapult, Electron Building, Didcot, United Kingdom
  • Abdulla S. Bin Ghouth; Department of Community Medicine, Hadhramout University, Hadhramout, Yemen
  • Terri Freemantle; Satellite Applications Catapult, Electron Building, Didcot, United Kingdom
  • Mervat Alhaffar; Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, Keppel St, London School of Hygiene and Tropical Medicine, London,
  • Yolanda Vazquez; Satellite Applications Catapult, Electron Building, Didcot, United Kingdom
  • Chris Reeve; Satellite Applications Catapult, Electron Building, Didcot, United Kingdom
  • Patrick J. Curran; Department of Psychology, University of North Carolina, Chapel Hill, NC, United States of America
  • Francesco Checchi; Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, Keppel St, London School of Hygiene and Tropical Medicine, London,
Preprint em Inglês | medRxiv | ID: ppmedrxiv-20216366
ABSTRACT
BackgroundThe burden of COVID-19 in low-income and conflict-affected countries is still unclear, largely reflecting low testing rates. In parts of Yemen, reports indicated a peak in hospital admissions and burials during May-June 2020. To estimate excess mortality during the epidemic period, we quantified activity across all identifiable cemeteries within Aden governorate in Yemen (population approximately one million) by analysing very high-resolution satellite imagery, and compared estimates to Civil Registry office records from the city. MethodsAfter identifying active cemeteries through remote and ground information, we applied geospatial analysis techniques to manually identify new grave plots and measure changes in burial surface area over a period from July 2016 to September 2020. After imputing missing grave counts using surface area data, we used alternative approaches, including simple interpolation and a generalised additive mixed growth model, to predict both actual and counterfactual (no epidemic) burial rates by cemetery and across the governorate during the most likely period of COVID-19 excess mortality (from 1 April 2020), and thereby compute excess burials. We also analysed death notifications to the Civil Registry office during April-July 2020 and in previous years. ResultsWe collected 78 observations from 11 cemeteries, of which 10 required imputation from burial surface area. Cemeteries ranged in starting size from 0 to 6866 graves. In all but one a peak in daily burial rates was evident from April to July 2020. Interpolation and mixed model methods estimated {approx} 1500 excess burials up to 6 July, and 2120 up to 19 September, corresponding to a peak weekly increase of 230% from the counterfactual. Satellite imagery estimates were generally lower than Civil Registry data, which indicated a peak 1823 deaths in May alone. However, both sources suggested the epidemic had waned by September 2020. DiscussionTo our knowledge this is the first instance of satellite imagery being used for population mortality estimation. Findings suggest a substantial, under-ascertained impact of COVID-19 in this urban Yemeni governorate, and are broadly in line with previous mathematical modelling predictions, though our method cannot distinguish direct from indirect virus deaths. Satellite imagery burial analysis appears a promising novel approach for monitoring epidemics and other crisis impacts, particularly where ground data are difficult to collect.
Licença
cc_by_nc_nd
Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Estudo observacional / Estudo prognóstico Idioma: Inglês Ano de publicação: 2020 Tipo de documento: Preprint
Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Estudo observacional / Estudo prognóstico Idioma: Inglês Ano de publicação: 2020 Tipo de documento: Preprint
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