Excess mortality during the COVID-19 pandemic: a geospatial and statistical analysis in Aden governorate, Yemen

Background The burden of COVID-19 in low-income and conflict-affected countries remains 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 quan...

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Main Authors: Francesco Checchi, Emilie S Koum Besson, Andy Norris, Abdulla S Bin Ghouth, Terri Freemantle, Mervat Alhaffar, Yolanda Vazquez, Chris Reeve, Patrick J Curran
Format: Article
Language:English
Published: BMJ Publishing Group 2021-03-01
Series:BMJ Global Health
Online Access:https://gh.bmj.com/content/6/3/e004564.full
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spelling doaj-914e9c6f72f54ac6b711125b7ef7fbe32021-04-03T19:30:25ZengBMJ Publishing GroupBMJ Global Health2059-79082021-03-016310.1136/bmjgh-2020-004564Excess mortality during the COVID-19 pandemic: a geospatial and statistical analysis in Aden governorate, YemenFrancesco Checchi0Emilie S Koum Besson1Andy Norris2Abdulla S Bin Ghouth3Terri Freemantle4Mervat Alhaffar5Yolanda Vazquez6Chris Reeve7Patrick J Curran8Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UKDepartment of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UKEarth observation, Satellite Applications Catapult, Didcot, UKDepartment of Community Medicine, Hadhramout University, Mukalla, YemenEarth observation, Satellite Applications Catapult, Didcot, UKDepartment of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UKEarth observation, Satellite Applications Catapult, Didcot, UKEarth observation, Satellite Applications Catapult, Didcot, UKDepartment of Psychology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USABackground The burden of COVID-19 in low-income and conflict-affected countries remains 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 (population approximately 1 million) by analysing very high-resolution satellite imagery and compared estimates to Civil Registry office records.Methods After 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 over the same period.Results We collected 78 observations from 11 cemeteries. In all but one, a peak in daily burial rates was evident from April to July 2020. Interpolation and mixed model methods estimated ≈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.Discussion To 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.https://gh.bmj.com/content/6/3/e004564.full
collection DOAJ
language English
format Article
sources DOAJ
author Francesco Checchi
Emilie S Koum Besson
Andy Norris
Abdulla S Bin Ghouth
Terri Freemantle
Mervat Alhaffar
Yolanda Vazquez
Chris Reeve
Patrick J Curran
spellingShingle Francesco Checchi
Emilie S Koum Besson
Andy Norris
Abdulla S Bin Ghouth
Terri Freemantle
Mervat Alhaffar
Yolanda Vazquez
Chris Reeve
Patrick J Curran
Excess mortality during the COVID-19 pandemic: a geospatial and statistical analysis in Aden governorate, Yemen
BMJ Global Health
author_facet Francesco Checchi
Emilie S Koum Besson
Andy Norris
Abdulla S Bin Ghouth
Terri Freemantle
Mervat Alhaffar
Yolanda Vazquez
Chris Reeve
Patrick J Curran
author_sort Francesco Checchi
title Excess mortality during the COVID-19 pandemic: a geospatial and statistical analysis in Aden governorate, Yemen
title_short Excess mortality during the COVID-19 pandemic: a geospatial and statistical analysis in Aden governorate, Yemen
title_full Excess mortality during the COVID-19 pandemic: a geospatial and statistical analysis in Aden governorate, Yemen
title_fullStr Excess mortality during the COVID-19 pandemic: a geospatial and statistical analysis in Aden governorate, Yemen
title_full_unstemmed Excess mortality during the COVID-19 pandemic: a geospatial and statistical analysis in Aden governorate, Yemen
title_sort excess mortality during the covid-19 pandemic: a geospatial and statistical analysis in aden governorate, yemen
publisher BMJ Publishing Group
series BMJ Global Health
issn 2059-7908
publishDate 2021-03-01
description Background The burden of COVID-19 in low-income and conflict-affected countries remains 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 (population approximately 1 million) by analysing very high-resolution satellite imagery and compared estimates to Civil Registry office records.Methods After 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 over the same period.Results We collected 78 observations from 11 cemeteries. In all but one, a peak in daily burial rates was evident from April to July 2020. Interpolation and mixed model methods estimated ≈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.Discussion To 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.
url https://gh.bmj.com/content/6/3/e004564.full
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