Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
Earth observation, Satellite Applications Catapult, Didcot, UK.
BMJ Glob Health. 2021 Mar;6(3). doi: 10.1136/bmjgh-2020-004564.
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.
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.
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.
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.
在低收入和受冲突影响的国家,COVID-19 的负担仍不清楚,这主要反映了检测率低。在也门的一些地区,报告显示 2020 年 5 月至 6 月期间医院入院和埋葬人数达到高峰。为了估计疫情期间的超额死亡率,我们通过分析非常高分辨率的卫星图像,对亚丁省(人口约 100 万)内所有可识别的墓地的活动进行了量化,并将估计值与民事登记处的记录进行了比较。
通过远程和地面信息确定活跃的墓地后,我们应用地理空间分析技术手动识别新的墓地,并在 2016 年 7 月至 2020 年 9 月期间测量埋葬面积的变化。在使用表面积数据推断出缺失的坟墓数量后,我们使用替代方法,包括简单插值和广义加性混合增长模型,来预测每个墓地和整个省在 COVID-19 超额死亡率最有可能的时期(从 2020 年 4 月 1 日开始)的实际和虚拟(无疫情)埋葬率,从而计算超额埋葬。我们还分析了同期向民事登记处报告的死亡通知。
我们从 11 个墓地收集了 78 个观测值。在除一个墓地外的所有墓地中,从 2020 年 4 月到 7 月,每日埋葬率都达到了高峰。插值和混合模型方法估计截至 6 月 7 日有 1500 例超额埋葬,截至 9 月 19 日有 2120 例超额埋葬,这相当于从虚拟值每周增加 230%。卫星图像估计值通常低于民事登记处的数据,后者显示仅 5 月就有 1823 人死亡。然而,这两个来源都表明疫情到 2020 年 9 月已经消退。
据我们所知,这是首次使用卫星图像进行人口死亡率估计。研究结果表明,也门这个城市州的 COVID-19 造成了大量未被发现的严重影响,与之前的数学模型预测基本一致,尽管我们的方法无法区分直接和间接的病毒死亡。卫星图像埋葬分析似乎是一种很有前途的监测疫情和其他危机影响的新方法,特别是在难以收集地面数据的地方。