自2020年3月新冠疫情被宣布構(gòu)成全球大流行以來,有一個(gè)話題不斷引起爭論,那就是美國官方公布的新冠死亡人數(shù)統(tǒng)計(jì)數(shù)據(jù),是否準(zhǔn)確體現(xiàn)了與引發(fā)新冠的SARS-CoV-2病毒有關(guān)的死亡人數(shù)。
有些政客和許多公共衛(wèi)生從業(yè)者認(rèn)為,新冠死亡人數(shù)被高估。例如,2023年1月,《華盛頓郵報(bào)》發(fā)表的一篇評論文章稱,新冠死亡人數(shù)不僅包括死于新冠的人數(shù),還包括死于其他原因但恰好感染新冠的人數(shù)。
但大多數(shù)科學(xué)家認(rèn)為,新冠死亡人數(shù)被低估,因?yàn)檫@些數(shù)據(jù)沒有包含被錯(cuò)誤分類為其他死因的新冠死亡人數(shù)。
我們是由波士頓大學(xué)(Boston University)、明尼蘇達(dá)大學(xué)(University of Minnesota)、加州大學(xué)舊金山分校(University of California San Francisco)等機(jī)構(gòu)組成的研究團(tuán)隊(duì)的成員,自疫情爆發(fā)以來持續(xù)跟蹤新冠死亡人數(shù)。團(tuán)隊(duì)的主要目標(biāo)是評估美國新冠死亡人數(shù)是否被低估,以及哪些地區(qū)的死亡人數(shù)被低估。
研究超額死亡人數(shù)
研究這個(gè)問題的途徑之一是分析人口健康研究人員所說的超額死亡率。這個(gè)指標(biāo)將疫情期間的死亡人數(shù)與根據(jù)疫情之前的趨勢預(yù)測的死亡人數(shù)進(jìn)行對比。
超額死亡率評估了直接死于新冠的人數(shù),或通過間接途徑死亡的人數(shù),例如在新冠高峰期間避免前往醫(yī)院的患者。確定死因是一個(gè)復(fù)雜的過程,而記錄是否死亡卻非常直接。因此,計(jì)算超額死亡人數(shù)被認(rèn)為是對疫情死亡人數(shù)偏差最小的估算。
一般而言,如果新冠死亡人數(shù)超過超額死亡人數(shù),這意味著新冠死亡人數(shù)可能被高估,當(dāng)然有一些重要的說明,會在下文一一解釋。如果超額死亡人數(shù)超過新冠死亡人數(shù),后者可能被低估。
在最近發(fā)布的一項(xiàng)尚未經(jīng)過同行審議的研究中,我們的團(tuán)隊(duì)發(fā)現(xiàn),在2020年3月至2022年2月疫情的前兩年,美國超額死亡人數(shù)為996,869至1,278,540人。其中866,187人的死亡證明中確認(rèn)的死因?yàn)樾鹿凇_@意味著超額死亡人數(shù)比新冠死亡人數(shù)多130,682至412,353人。疫情第一年和第二年,兩者之間存在巨大差距。這意味著即使在經(jīng)過疫情最初幾個(gè)月的混亂之后,新冠疫情死亡人數(shù)依舊被低估。
多項(xiàng)重要研究也認(rèn)為,在新冠疫情前兩年,全美超額死亡人數(shù)超過了新冠死亡人數(shù)。我們的團(tuán)隊(duì)開展的初步分析發(fā)現(xiàn),超額死亡人數(shù)和新冠死亡人數(shù)的差距延續(xù)到了疫情第三年。這表明,新冠死亡人數(shù)現(xiàn)在依舊被低估。
理解數(shù)據(jù)差異
解釋超額死亡人數(shù)與公布的新冠死亡人數(shù)之間的差異是一項(xiàng)更具有挑戰(zhàn)性的任務(wù)。但有許多證據(jù)證明,數(shù)據(jù)的差異基本代表未被統(tǒng)計(jì)的新冠死亡人數(shù)。
我們在最近的一項(xiàng)研究中發(fā)現(xiàn),超額死亡人數(shù)在官方公布的新冠死亡人數(shù)之前達(dá)到最高峰。即使與阿爾茲海默癥等死因有關(guān)的超額死亡人數(shù)也是如此,因?yàn)樵谝咔槠陂g,由于患者避免去醫(yī)院或其他行為變化,這類超額死亡人數(shù)不太可能快速發(fā)生變化。
這一研究結(jié)果與我們的觀察結(jié)果一致。我們發(fā)現(xiàn),在新冠高峰開始時(shí),新冠死亡病例可能未被確認(rèn)或被錯(cuò)誤劃分為其他死因。目前,醫(yī)療提供商和死亡調(diào)查員在社區(qū)中進(jìn)行新冠檢測的頻率可能降低。如果超額死亡的死因并非新冠疫情,則在新冠疫情高峰時(shí)期,超額死亡人數(shù)應(yīng)該維持相對穩(wěn)定,或者在疫情高峰過后,由于醫(yī)院人滿為患和醫(yī)療中斷導(dǎo)致死亡,從而使超額死亡人數(shù)達(dá)到最高峰。
疫情期間,與服藥過量等外部死因有關(guān)的超額死亡人數(shù)同樣增多。然而,一項(xiàng)初步研究發(fā)現(xiàn),與超額死亡人數(shù)的整體增長幅度相比,這類死亡人數(shù)的增長幅度相對較小。因此,外因死亡人數(shù)也不能解釋超額死亡人數(shù)和新冠死亡人數(shù)之間的差異。
鑒于前文提到的《華盛頓郵報(bào)》發(fā)表的那篇重要的評論文章,這個(gè)證據(jù)值得考慮。文章提出,美國的新冠死亡人數(shù)被嚴(yán)重高估。作者主張,在某些醫(yī)院,大范圍新冠檢測導(dǎo)致感染新冠但死于其他病因的患者,在死亡證明中依舊將新冠作為死因之一。然而,這是一種根本性的誤解,將院內(nèi)死亡人數(shù)泛化到全國。
這種過度泛化存在缺陷的一個(gè)原因是,院內(nèi)死亡不同于院外死亡。在醫(yī)院以外,通常沒有新冠檢測,死亡調(diào)查人員沒有接受充分培訓(xùn),而且對死者不夠了解。事實(shí)上,我們的研究表明,在醫(yī)院外,新冠死亡人數(shù)被嚴(yán)重低估。
農(nóng)村地區(qū)的驗(yàn)尸官調(diào)查報(bào)告也顯示,在院外死因確認(rèn)方面存在巨大差異。如果與驗(yàn)尸官自己的政治理念不一致,或者死者家屬希望不要提及新冠,有些驗(yàn)尸官甚至?xí)谒劳鲇涗浿姓f明死者未感染新冠。
過度泛化的另外一個(gè)問題是地理差異。初步研究表明,美國絕大多數(shù)縣的超額死亡人數(shù)超過新冠死亡人數(shù)。尤其是在南方各縣、落基山脈各州和農(nóng)村地區(qū),超額死亡人數(shù)超過新冠死亡人數(shù)的比例更高。這表明,在這些地區(qū)新冠死亡人數(shù)可能被低估。
我們的分析結(jié)果,至少在非常有限的程度上,可以支持新冠死亡人數(shù)有時(shí)候被高估的觀點(diǎn)。在新英格蘭和大西洋中部各州的多個(gè)大中型城區(qū),新冠死亡人數(shù)超過了超額死亡人數(shù)。但美國大多數(shù)地區(qū)并沒有遵循少數(shù)幾個(gè)縣的模式。
在新英格蘭和大西洋中部各州,將新冠劃定為死因的部分死亡人數(shù)可能實(shí)際上并非死于新冠,對于這種情況可能有其他解釋。首先,在這些地區(qū),新冠疫情防控措施,通過與新冠無關(guān)的途徑,可能防止了死亡,減少了超額死亡人數(shù)。例如,在富裕的城市縣域內(nèi)生活的居民擁有居家辦公和避免家庭擁擠的特權(quán),這可能降低他們死于流感的風(fēng)險(xiǎn)。流感每年通常會造成50,000人死亡。
事實(shí)上,2020至2021年流感季非常輕微,原因可能是社交隔離。另外一種可能的解釋是,在疫情前兩年后期,某些地區(qū)的死亡人數(shù)少于預(yù)期,原因是在這些地區(qū)健康狀況最差的居民已經(jīng)死于新冠。這些解釋表明,即使在新英格蘭和大西洋中部各縣,雖然官方記錄的新冠死亡人數(shù)高于預(yù)估超額死亡人數(shù),在其他死亡人數(shù)減少時(shí),許多新冠死亡人數(shù)依舊有可能發(fā)生。
明確死亡人數(shù)為什么重要
最后,確定有多少人死于新冠疫情,是一項(xiàng)重要的科學(xué)事業(yè),會產(chǎn)生重大政治影響。明確新冠死亡人數(shù)和死亡地點(diǎn)具有廣泛的意義,能夠知道目前對疫情響應(yīng)資源的分配方式,并為未來的公共衛(wèi)生緊急事件做好準(zhǔn)備。
因此,我們認(rèn)為,科學(xué)界應(yīng)該仔細(xì)審查統(tǒng)計(jì)新冠死亡人數(shù)背后的科學(xué)嚴(yán)謹(jǐn)性。由于疫情被嚴(yán)重政治化,在發(fā)表新冠死亡人數(shù)被高估或低估的言論時(shí),都應(yīng)該慎之又慎。
最后,我們的團(tuán)隊(duì)進(jìn)行的研究以及我們參與開展的調(diào)查報(bào)告發(fā)現(xiàn),新冠死亡人數(shù)被低估的情況在黑人、拉丁裔和美洲原住民社區(qū)以及低收入地區(qū)明顯更為普遍。主張新冠死亡人數(shù)被高估的說法,破壞了為核對這些社區(qū)被低估的死亡人數(shù)和保證向受影響最嚴(yán)重的地區(qū)分配資源所做的努力。例如,如果一個(gè)人的死亡證明上未注明死因?yàn)樾鹿?,他們的家人就不具備參加疫情社會保障?xiàng)目的資格,例如美國聯(lián)邦應(yīng)急管理署(FEMA)的葬禮援助項(xiàng)目。
為了了解在疫情期間,美國公共衛(wèi)生制度的成功和不足之處,充分統(tǒng)計(jì)新冠導(dǎo)致的死亡人數(shù)必不可少。除此之外,死者的親友和愛人,也應(yīng)當(dāng)知道新冠造成的真正損失。
安德魯·斯托克斯現(xiàn)任波士頓大學(xué)全球健康系助理教授;迪耶萊·倫德伯格現(xiàn)任波士頓大學(xué)全球健康系助理研究員;伊麗莎白·里格利-菲爾德現(xiàn)任明尼蘇達(dá)大學(xué)社會學(xué)助理教授;陳毅恒(音譯)現(xiàn)任加州大學(xué)舊金山分校流行病學(xué)和生物統(tǒng)計(jì)學(xué)研究數(shù)據(jù)專家。(財(cái)富中文網(wǎng))
本文根據(jù)知識共享許可轉(zhuǎn)載自The Conversation。
翻譯:劉進(jìn)龍
審校:汪皓
自2020年3月新冠疫情被宣布構(gòu)成全球大流行以來,有一個(gè)話題不斷引起爭論,那就是美國官方公布的新冠死亡人數(shù)統(tǒng)計(jì)數(shù)據(jù),是否準(zhǔn)確體現(xiàn)了與引發(fā)新冠的SARS-CoV-2病毒有關(guān)的死亡人數(shù)。
有些政客和許多公共衛(wèi)生從業(yè)者認(rèn)為,新冠死亡人數(shù)被高估。例如,2023年1月,《華盛頓郵報(bào)》發(fā)表的一篇評論文章稱,新冠死亡人數(shù)不僅包括死于新冠的人數(shù),還包括死于其他原因但恰好感染新冠的人數(shù)。
但大多數(shù)科學(xué)家認(rèn)為,新冠死亡人數(shù)被低估,因?yàn)檫@些數(shù)據(jù)沒有包含被錯(cuò)誤分類為其他死因的新冠死亡人數(shù)。
我們是由波士頓大學(xué)(Boston University)、明尼蘇達(dá)大學(xué)(University of Minnesota)、加州大學(xué)舊金山分校(University of California San Francisco)等機(jī)構(gòu)組成的研究團(tuán)隊(duì)的成員,自疫情爆發(fā)以來持續(xù)跟蹤新冠死亡人數(shù)。團(tuán)隊(duì)的主要目標(biāo)是評估美國新冠死亡人數(shù)是否被低估,以及哪些地區(qū)的死亡人數(shù)被低估。
研究超額死亡人數(shù)
研究這個(gè)問題的途徑之一是分析人口健康研究人員所說的超額死亡率。這個(gè)指標(biāo)將疫情期間的死亡人數(shù)與根據(jù)疫情之前的趨勢預(yù)測的死亡人數(shù)進(jìn)行對比。
超額死亡率評估了直接死于新冠的人數(shù),或通過間接途徑死亡的人數(shù),例如在新冠高峰期間避免前往醫(yī)院的患者。確定死因是一個(gè)復(fù)雜的過程,而記錄是否死亡卻非常直接。因此,計(jì)算超額死亡人數(shù)被認(rèn)為是對疫情死亡人數(shù)偏差最小的估算。
一般而言,如果新冠死亡人數(shù)超過超額死亡人數(shù),這意味著新冠死亡人數(shù)可能被高估,當(dāng)然有一些重要的說明,會在下文一一解釋。如果超額死亡人數(shù)超過新冠死亡人數(shù),后者可能被低估。
在最近發(fā)布的一項(xiàng)尚未經(jīng)過同行審議的研究中,我們的團(tuán)隊(duì)發(fā)現(xiàn),在2020年3月至2022年2月疫情的前兩年,美國超額死亡人數(shù)為996,869至1,278,540人。其中866,187人的死亡證明中確認(rèn)的死因?yàn)樾鹿?。這意味著超額死亡人數(shù)比新冠死亡人數(shù)多130,682至412,353人。疫情第一年和第二年,兩者之間存在巨大差距。這意味著即使在經(jīng)過疫情最初幾個(gè)月的混亂之后,新冠疫情死亡人數(shù)依舊被低估。
多項(xiàng)重要研究也認(rèn)為,在新冠疫情前兩年,全美超額死亡人數(shù)超過了新冠死亡人數(shù)。我們的團(tuán)隊(duì)開展的初步分析發(fā)現(xiàn),超額死亡人數(shù)和新冠死亡人數(shù)的差距延續(xù)到了疫情第三年。這表明,新冠死亡人數(shù)現(xiàn)在依舊被低估。
理解數(shù)據(jù)差異
解釋超額死亡人數(shù)與公布的新冠死亡人數(shù)之間的差異是一項(xiàng)更具有挑戰(zhàn)性的任務(wù)。但有許多證據(jù)證明,數(shù)據(jù)的差異基本代表未被統(tǒng)計(jì)的新冠死亡人數(shù)。
我們在最近的一項(xiàng)研究中發(fā)現(xiàn),超額死亡人數(shù)在官方公布的新冠死亡人數(shù)之前達(dá)到最高峰。即使與阿爾茲海默癥等死因有關(guān)的超額死亡人數(shù)也是如此,因?yàn)樵谝咔槠陂g,由于患者避免去醫(yī)院或其他行為變化,這類超額死亡人數(shù)不太可能快速發(fā)生變化。
這一研究結(jié)果與我們的觀察結(jié)果一致。我們發(fā)現(xiàn),在新冠高峰開始時(shí),新冠死亡病例可能未被確認(rèn)或被錯(cuò)誤劃分為其他死因。目前,醫(yī)療提供商和死亡調(diào)查員在社區(qū)中進(jìn)行新冠檢測的頻率可能降低。如果超額死亡的死因并非新冠疫情,則在新冠疫情高峰時(shí)期,超額死亡人數(shù)應(yīng)該維持相對穩(wěn)定,或者在疫情高峰過后,由于醫(yī)院人滿為患和醫(yī)療中斷導(dǎo)致死亡,從而使超額死亡人數(shù)達(dá)到最高峰。
疫情期間,與服藥過量等外部死因有關(guān)的超額死亡人數(shù)同樣增多。然而,一項(xiàng)初步研究發(fā)現(xiàn),與超額死亡人數(shù)的整體增長幅度相比,這類死亡人數(shù)的增長幅度相對較小。因此,外因死亡人數(shù)也不能解釋超額死亡人數(shù)和新冠死亡人數(shù)之間的差異。
鑒于前文提到的《華盛頓郵報(bào)》發(fā)表的那篇重要的評論文章,這個(gè)證據(jù)值得考慮。文章提出,美國的新冠死亡人數(shù)被嚴(yán)重高估。作者主張,在某些醫(yī)院,大范圍新冠檢測導(dǎo)致感染新冠但死于其他病因的患者,在死亡證明中依舊將新冠作為死因之一。然而,這是一種根本性的誤解,將院內(nèi)死亡人數(shù)泛化到全國。
這種過度泛化存在缺陷的一個(gè)原因是,院內(nèi)死亡不同于院外死亡。在醫(yī)院以外,通常沒有新冠檢測,死亡調(diào)查人員沒有接受充分培訓(xùn),而且對死者不夠了解。事實(shí)上,我們的研究表明,在醫(yī)院外,新冠死亡人數(shù)被嚴(yán)重低估。
農(nóng)村地區(qū)的驗(yàn)尸官調(diào)查報(bào)告也顯示,在院外死因確認(rèn)方面存在巨大差異。如果與驗(yàn)尸官自己的政治理念不一致,或者死者家屬希望不要提及新冠,有些驗(yàn)尸官甚至?xí)谒劳鲇涗浿姓f明死者未感染新冠。
過度泛化的另外一個(gè)問題是地理差異。初步研究表明,美國絕大多數(shù)縣的超額死亡人數(shù)超過新冠死亡人數(shù)。尤其是在南方各縣、落基山脈各州和農(nóng)村地區(qū),超額死亡人數(shù)超過新冠死亡人數(shù)的比例更高。這表明,在這些地區(qū)新冠死亡人數(shù)可能被低估。
我們的分析結(jié)果,至少在非常有限的程度上,可以支持新冠死亡人數(shù)有時(shí)候被高估的觀點(diǎn)。在新英格蘭和大西洋中部各州的多個(gè)大中型城區(qū),新冠死亡人數(shù)超過了超額死亡人數(shù)。但美國大多數(shù)地區(qū)并沒有遵循少數(shù)幾個(gè)縣的模式。
在新英格蘭和大西洋中部各州,將新冠劃定為死因的部分死亡人數(shù)可能實(shí)際上并非死于新冠,對于這種情況可能有其他解釋。首先,在這些地區(qū),新冠疫情防控措施,通過與新冠無關(guān)的途徑,可能防止了死亡,減少了超額死亡人數(shù)。例如,在富裕的城市縣域內(nèi)生活的居民擁有居家辦公和避免家庭擁擠的特權(quán),這可能降低他們死于流感的風(fēng)險(xiǎn)。流感每年通常會造成50,000人死亡。
事實(shí)上,2020至2021年流感季非常輕微,原因可能是社交隔離。另外一種可能的解釋是,在疫情前兩年后期,某些地區(qū)的死亡人數(shù)少于預(yù)期,原因是在這些地區(qū)健康狀況最差的居民已經(jīng)死于新冠。這些解釋表明,即使在新英格蘭和大西洋中部各縣,雖然官方記錄的新冠死亡人數(shù)高于預(yù)估超額死亡人數(shù),在其他死亡人數(shù)減少時(shí),許多新冠死亡人數(shù)依舊有可能發(fā)生。
明確死亡人數(shù)為什么重要
最后,確定有多少人死于新冠疫情,是一項(xiàng)重要的科學(xué)事業(yè),會產(chǎn)生重大政治影響。明確新冠死亡人數(shù)和死亡地點(diǎn)具有廣泛的意義,能夠知道目前對疫情響應(yīng)資源的分配方式,并為未來的公共衛(wèi)生緊急事件做好準(zhǔn)備。
因此,我們認(rèn)為,科學(xué)界應(yīng)該仔細(xì)審查統(tǒng)計(jì)新冠死亡人數(shù)背后的科學(xué)嚴(yán)謹(jǐn)性。由于疫情被嚴(yán)重政治化,在發(fā)表新冠死亡人數(shù)被高估或低估的言論時(shí),都應(yīng)該慎之又慎。
最后,我們的團(tuán)隊(duì)進(jìn)行的研究以及我們參與開展的調(diào)查報(bào)告發(fā)現(xiàn),新冠死亡人數(shù)被低估的情況在黑人、拉丁裔和美洲原住民社區(qū)以及低收入地區(qū)明顯更為普遍。主張新冠死亡人數(shù)被高估的說法,破壞了為核對這些社區(qū)被低估的死亡人數(shù)和保證向受影響最嚴(yán)重的地區(qū)分配資源所做的努力。例如,如果一個(gè)人的死亡證明上未注明死因?yàn)樾鹿冢麄兊募胰司筒痪邆鋮⒓右咔樯鐣U享?xiàng)目的資格,例如美國聯(lián)邦應(yīng)急管理署(FEMA)的葬禮援助項(xiàng)目。
為了了解在疫情期間,美國公共衛(wèi)生制度的成功和不足之處,充分統(tǒng)計(jì)新冠導(dǎo)致的死亡人數(shù)必不可少。除此之外,死者的親友和愛人,也應(yīng)當(dāng)知道新冠造成的真正損失。
安德魯·斯托克斯現(xiàn)任波士頓大學(xué)全球健康系助理教授;迪耶萊·倫德伯格現(xiàn)任波士頓大學(xué)全球健康系助理研究員;伊麗莎白·里格利-菲爾德現(xiàn)任明尼蘇達(dá)大學(xué)社會學(xué)助理教授;陳毅恒(音譯)現(xiàn)任加州大學(xué)舊金山分校流行病學(xué)和生物統(tǒng)計(jì)學(xué)研究數(shù)據(jù)專家。(財(cái)富中文網(wǎng))
本文根據(jù)知識共享許可轉(zhuǎn)載自The Conversation。
翻譯:劉進(jìn)龍
審校:汪皓
Since the COVID-19 pandemic was declared in March 2020, a recurring topic of debate has been whether official COVID-19 death statistics in the U.S. accurately capture the fatalities associated with SARS-CoV-2, the virus that causes COVID-19.
Some politicians and a few public health practitioners have argued that COVID-19 deaths are overcounted. For instance, a January 2023 opinion piece in The Washington Post claims that COVID-19 death tallies include not only those who died from COVID-19 but those who died from other causes but happened to have COVID-19.
Most scientists, however, have suggested that COVID-19 death tallies represent underestimates because they fail to capture COVID-19 deaths that were misclassified to other causes of death.
We are part of a team of researchers at Boston University, University of Minnesota, University of California San Francisco and other institutions who have been tracking COVID-19 deaths since the beginning of the pandemic. A major goal for our team has been to assess whether the undercounting of COVID-19 deaths has occurred, and if so in which parts of the country.
Examining excess deaths
One way to examine the issue is to look at what population health researchers call excess mortality. It’s a measure which, in this case, compares the number of deaths that occurred during the pandemic to the number of deaths that would have been expected based on pre-pandemic trends.
Excess mortality captures deaths that arose from COVID-19 directly or through indirect pathways such as patients avoiding hospitals during COVID-19 surges. While determining a cause of death can be a complex process, recording whether or not someone died is more straightforward. For this reason, calculations of excess deaths are viewed as the least biased estimate of the pandemic’s death toll.
As a general rule of thumb – with some important caveats that we explain below – if there are more COVID-19 deaths than excess deaths, COVID-19 deaths were likely overestimated. If there are more excess deaths than COVID-19 deaths, COVID-19 deaths were likely underestimated.
In a newly released study that has not yet been peer-reviewed, our team found that during the first two years of the pandemic – from March 2020 to February 2022 – there were between 996,869 and 1,278,540 excess deaths in the U.S. Among these, 866,187 were recognized as COVID-19 on death certificates. This means that there were between 130,682 and 412,353 more excess deaths than COVID-19 deaths. The gap between excess deaths and COVID-19 deaths was large in both the first and second years of the pandemic. This suggests that COVID-19 deaths were undercounted even after the pandemic’s chaotic early months.
Major studies have also concluded that excess deaths exceeded COVID-19 deaths at the national level during the first two years of the pandemic. And preliminary analyses by our team have found that the gap between excess deaths and COVID-19 deaths has persisted into the third year of the pandemic. This suggests that COVID-19 deaths are still being undercounted.
Making sense of the discrepancy
Explaining the discrepancy between excess deaths and reported COVID-19 deaths is a more challenging task. But several threads of evidence support the idea that the difference largely reflects uncounted COVID-19 deaths.
In a recent study, we found that excess deaths peaked immediately before spikes in reported COVID-19 deaths. This was the case even for excess deaths associated with causes like Alzheimer’s disease that are unlikely to rapidly change due to patients avoiding hospitals or other changes in behavior during the pandemic.
This finding aligns with the observation that COVID-19 deaths may go unrecognized – and be misclassified to other causes of death – at the beginning of COVID-19 surges. At this time, COVID-19 testing may be less frequent in the community, among medical providers and among death investigators. If excess deaths were not caused by COVID-19, they would instead either remain relatively constant during COVID-19 surges or they would peak afterwards when hospitals were overcrowded and deaths may have resulted from health care interruptions.
Excess deaths related to external causes of death such as drug overdose also increased during the pandemic. However, a preliminary study found that the scale of this increase was small relative to the overall increase in excess deaths. So deaths from external factors alone cannot explain the gap between excess and COVID-19 deaths.
This evidence is worth considering in light of the prominent opinion piece in the Washington Post mentioned earlier, which suggests that the U.S.‘s tally of COVID-19 deaths is a substantial overcount. The author argues that in some hospitals, widespread COVID-19 testing has led patients with COVID-19 who died of other causes to still have COVID-19 included as a cause on their death certificate. There is a fundamental misunderstanding, however, in generalizing these hospital deaths to the entire country.
One reason this overgeneralization is flawed is because hospital deaths are distinct from out-of-hospital deaths. In out-of-hospital settings, COVID-19 testing is often lacking and death investigators have less training and less information about the deceased. In fact, our research suggests that COVID-19 deaths are largely undercounted in out-of-hospital settings.
Investigative reporting among coroners in rural areas has also revealed significant variability in out-of-hospital cause of death assignment. Some coroners have even gone on record to state that they do not include COVID-19 on death records if it contradicts their own political beliefs or if families wish for it to be omitted.
The other problem with the overgeneralization is geographic. Our preliminary study demonstrates that excess deaths exceeded COVID-19 deaths in the vast majority of counties across the U.S. In particular, counties in the South, the Rocky Mountain states and rural areas had many more excess deaths than COVID-19 deaths. This suggests that COVID-19 deaths were likely undercounted in these areas.
The idea that COVID-19 deaths are sometimes overreported is, to a very limited extent, supported by our analyses. A select number of large and medium-sized metro areas in New England and the mid-Atlantic states have had more COVID-19 deaths than excess deaths. But most of the country has not followed the patterns of this small group of counties.
While it is possible that some deaths assigned to COVID-19 in New England and the mid-Atlantic states were not actually caused by COVID-19, other explanations are also possible. First, COVID-19 mitigation efforts could have prevented deaths in these areas via pathways unrelated to COVID-19, reducing excess deaths. For example, some people living in wealthy, urban counties had the privilege to work from home and avoid household crowding, which may have reduced their risk of dying from flu. Flu is typically responsible for as many as 50,000 deaths each year.
In fact, the 2020-2021 flu season was minimal, likely because of social distancing. Another possible explanation is that later in the first two years of the pandemic, there may have also been fewer deaths than expected in some areas because some of the least healthy people in the area had already died of COVID-19. These alternative explanations imply that, even in those New England and mid-Atlantic counties where more COVID-19 deaths were recorded than estimated excess deaths, many COVID-19 deaths may still have occurred even as other kinds of deaths decreased.
Why it matters
Ultimately, figuring out how many people have died as a result of the COVID-19 pandemic is a major scientific undertaking that has significant political importance. Knowing how many people died and where these deaths occurred has widespread implications for informing how current pandemic response resources are allocated and for preparing for future public health emergencies.
As a result, in our view, it is critical that the scientific community carefully reviews the rigor of the science behind the counting of COVID-19 deaths. Given the intense politicization of the pandemic, claims of overcounting or undercounting need to be made cautiously.
Finally, research by our team and investigative reporting conducted in partnership with our team has found that the undercounting of COVID-19 deaths is significantly more common in Black, Hispanic and Native American communities as well as low-income areas. Claims that COVID-19 deaths have been overcounted undermine efforts to reconcile the undercounts in these communities and to ensure resources are being allocated to those most affected. For example, if a person does not have COVID-19 assigned as a cause on their death certificate, their family is ineligible for pandemic social programs such as the FEMA funeral assistance program.
To understand where the U.S. public health system has succeeded and fallen short during the pandemic, a full accounting of deaths caused by COVID-19 is needed. More than that, families, friends and loved ones of those who have died so far also deserve to know the true toll that COVID-19 has taken.
Andrew Stokes is Assistant Professor of Global Health, Boston University; Dielle Lundberg is Research Assistant in the Department of Global Health, Boston University; Elizabeth Wrigley-Field is Assistant Professor of Sociology, University of Minnesota, and Yea-Hung Chen is Research Data Specialist in Epidemiology and Biostatistics, University of California, San Francisco.
This article is republished from The Conversation under a Creative Commons license.