Evidence map›Paper›PMID 33758012›Full record

ArticleBMJ global health2021

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

Emilie S Koum Besson, Andy Norris, Abdulla S Bin Ghouth, Terri Freemantle, Mervat Alhaffar, Yolanda Vazquez, Chris Reeve, Patrick J Curran, Francesco Checchi

Abstract read
In one paragraph

Article in BMJ global health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

41 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  11. Mortality among populations affected by armed conflict in northeast Nigeria, 2016 to 2019.Proceedings of the National Academy of Sciences of the United States of America · 2023
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  18. The role of remote sensing during a global disaster: COVID-19 pandemic as case study.Remote sensing applications : society and environment · 2022
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Emilie S Koum BessonDepartment of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK emilie.koum-besson@lshtm.ac.uk.
Andy NorrisEarth observation, Satellite Applications Catapult, Didcot, UK.
Abdulla S Bin GhouthDepartment of Community Medicine, Hadhramout University, Mukalla, Yemen.
Terri FreemantleEarth observation, Satellite Applications Catapult, Didcot, UK.
Mervat AlhaffarDepartment of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK.
Yolanda VazquezEarth observation, Satellite Applications Catapult, Didcot, UK.
Chris ReeveEarth observation, Satellite Applications Catapult, Didcot, UK.
Patrick J CurranDepartment of Psychology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Francesco ChecchiDepartment of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe 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.

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 over the same period.

resultsWe 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.

Indexed as

CemeteriesSatellite ImageryCOVID-19HumansPandemicsPneumonia, ViralRegistriesRisk FactorsSARS-CoV-2YemenCOVID-19epidemiologygeographic information systemspublic Health

Identifiers

PMID33758012
PMCPMC7992372

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.