SARS-CoV-2の年齢特有の死亡率と免疫パターン
Megan O'Driscoll1,2, Gabriel Ribeiro Dos Santos3,4, Lin Wang3,4
1Department of Genetics, University of Cambridge, Cambridge, UK. mo487@cam.ac.uk.
Nature
|November 2, 2020
まとめ
COVID-19 パンデミックの真の規模を推定することは,不一致なデータのために困難です. この研究では,45か国における感染率と感染による死亡率を推定するために,年齢別死亡データと血清発生率を使用しています.
科学分野:
- 流行病学について
- 感染症モデリング
- 公衆衛生
背景:
- COVID-19 パンデミックの規模とSARS-CoV-2 感染の重度の推定は,データの不一致により困難です.
- 観察されたCOVID-19の死亡は感染のほんの一部であり,報告の違い,特に高齢者および介護施設での死亡は,比較を複雑にする.
- 死亡率と伝染率の直接的な比較は,長期介護施設の不均一な負担と変動する報告慣行によって妨げられています.
研究 の 目的:
- 年齢別COVID-19死亡データと血清発生率の研究を用いて,複数の国における感染および死亡率の一貫性を調査する.
- 人口感染率と感染死亡率 (IFR) の堅実な推定を,一貫した年齢別死亡率データを活用して開発する.
- 人口の年齢構造と介護施設の負担が,各国間のIFRの異質性に与える影響を評価する.
主な方法:
- 45カ国の年齢別COVID-19関連死亡データを活用した.
- 22件の血清流行研究の結果を併用して,結果のクロス検証を行いました.
- 感染率とIFRを推定するモデルフレームワークを開発し,年齢分布と人口構造を分析した.
主要な成果:
- 65歳未満の個体における死亡の年齢分布は,環境全体で一貫しており,人口の感染割合を信頼できる見積もりを可能にしました.
- 感染による死亡率は30歳以降の年齢とともにログ線形で増加し,5歳から9歳までの子供では最も低い.
- 対象となった45カ国の人口の約5%が2020年9月1日までに感染したと推定され,一部のラテンアメリカの国ではより高い感染率が示唆されている.
結論:
- 年齢別死亡データは,特に若い年齢層では,パンデミック進行と人口の感染率を推定するための堅実な方法を提供します.
- 人口の年齢構造と介護施設の動態は,各国間のIFRの変動を部分的に説明しますが,他の要因が寄与している可能性があります.
- 開発されたモデリング・フレームワークは,各国が容易に入手可能な年齢別死亡データを用いて,自国のパンデミック状態を評価するための貴重なツールを提供します.
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