Research press release





今回、William Msemburiたちは、こうした人命の損失を世界規模で定量化するため、超過死亡者数を推定した。そのために、2020年と2021年の死亡データとCOVID-19パンデミックが発生しなかったという仮定に基づいた予想死亡者数との比較が行われた。そして、この予想死亡者数を導き出し、不完全な死亡データしかない国や死亡データがない国の2020~2021年の死亡者数を推定するために数学的モデルを用いて研究が行う必要があった。詳細で完全な死亡データを入手できたのは、世界で100か国(52%)だけだった。


There were approximately 14.83 million excess deaths associated with COVID-19 across the world from 2020 to 2021, according to estimates by the World Health Organization (WHO) reported in a paper in Nature. This estimate is nearly three times the number of deaths reported to have been caused by COVID-19 over the same period.

Factors such as variations in testing access, differing diagnostic capacity, varying reporting of cause of death and inconsistent certification of COVID-19 as cause of death have made it difficult to assess the total effect of COVID-19 on the global population. Beyond what is directly attributed to COVID-19, the pandemic has also caused extensive collateral damage that has led to profound losses of livelihoods and lives.

To quantify this loss of life on a global scale, William Msemburi and colleagues estimated excess deaths — the comparison between mortality data from 2020 and 2021 with the number of deaths that would have been expected had the pandemic not occurred. This requires mathematical modelling to predict expected deaths as well as to infer 2020–2021 mortality for those countries with incomplete or no data. Only 100 countries worldwide (52%) had granular, complete death data available.

On the basis of their analysis, the authors found that COVID-19 has been responsible for between 13.3 and 16.6 (most probably 14.83) million excess deaths across the world — 2.74 times as many deaths as the 5.42 million previously reported. Excess mortality was 4.47 million in 2020 and 10.36 million in 2021. Excess mortality accounts for both the total number of deaths directly attributed to the virus and the indirect impact, such as disruption of essential health services or travel disruptions. The WHO estimations are the most conservative among similar estimates. Owing to the statistical modelling required to draw these conclusions, the authors advise interpreting some of these estimates with caution.

doi: 10.1038/s41586-022-05522-2

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