[情報] COVID-19 死亡率

看板nCoV2019作者 (pura vita!)時間4年前 (2020/02/22 10:59), 編輯推噓8(9133)
留言43則, 17人參與, 4年前最新討論串1/2 (看更多)
發稿單位:worldometer 發稿時間:Feb.18, 2020 撰 稿 者:worldometer 原文連結:https://www.worldometers.info/coronavirus/coronavirus-death-rate/ 摘譯: 死亡率 (CFR, case fatality rate) 通常是以疫情結束後死亡數/總確診數來計算。但在疫情進行中,使用這個公式來計算,有時可能產生誤導。 以 Feb.8 全球累計 37,552 確診, 813 死亡計算。 deaths/cases = 813/37,552 = 2.2% CFR (有瑕疵的公式) (註: 以這個公式計算目前中國以外共 1,523 確診, 15死亡, CFR = 0.98%) 另一種方式是以平均確診到死亡日數 T 來估計,假設 T=7,則 Feb.1 的累計確診數為 14,381,可算出: Feb.8 deaths/Feb.1 cases = 813/14,381 = 5.7% CFR (正確的公式,假設T=7時) 在估計 T 時也可以用 (總死亡數+總治癒數) 的數目回推到與累計確診數相近的日期,使用這一公式,推出來的日期約 Jan.26/27 之間,相當於 T=12~13天。如果用這種方式推估T,因為使用相同的邏輯所以得出的結果會與第三種算法相同。即, CFR = 死亡數/(死亡+治癒數) 使用 Feb.22 的數字時,該公式算出來的死亡率為: 2,360 / (2,360 + 20,949) = 10% CFR (worldwide) 排除中國的病例後為: 15 / (15 + 236) = 6.0% CFR (outside of China) 兩者的差異可能來自於中國以外的樣本數較小以及 (輕症與無症狀) 確診比例較高。 另外一個可能影響估計的是未被通報的病例,未通報病例會使 CFR 的估計高於實際的數值。例如若武漢有 10,000 名未通報病例,CFR 就會從 10% 降到 7.1%。英國公衛專家在武漢病例只有2,000時,估計有10,000人已遭感染。 最後可以參考的是,在 2003 年 SARS 疫情進行中,WHO 當時報告的死亡率為 4% (最低為 3%),但當疫情結束後,死亡率上升到 9.6%。 原文: How to calculate the mortality rate during an outbreak The case fatality rate (CFR) represents the proportion of cases who eventually die from a disease. Once an epidemic has ended, it is calculated with the formula: deaths / cases. But while an epidemic is still ongoing, as it is the case with the current novel coronavirus outbreak, this formula is, at the very least, "naïve" and can be "misleading if, at the time of analysis, the outcome is unknown for a non negligible proportion of patients." [8] (Methods for Estimating the Case Fatality Ratio for a Novel, Emerging Infectious Disease - Ghani et al, American Journal of Epidemiology). In other words, current deaths belong to a total case figure of the past, not to the current case figure in which the outcome (recovery or death) of a proportion (the most recent cases) hasn't yet been determined. The correct formula, therefore, would appear to be: CFR = deaths at day.x / cases at day.x-{T} (where T = average time period from case confirmation to death) This would constitute a fair attempt to use values for cases and deaths belonging to the same group of patients. One issue can be that of determining whether there is enough data to estimate T with any precision, but it is certainly not T = 0 (what is implicitly used when applying the formula current deaths / current cases to determine CFR during an ongoing outbreak). Let's take, for example, the data at the end of February 8, 2020: 813 deaths (cumulative total) and 37,552 cases (cumulative total) worldwide. If we use the formula (deaths / cases) we get: 813 / 37,552 = 2.2% CFR (flawed formula). With a conservative estimate of T = 7 days as the average period from case confirmation to death, we would correct the above formula by using February 1 cumulative cases, which were 14,381, in the denominator: Feb. 8 deaths / Feb. 1 cases = 813 / 14,381 = 5.7% CFR (correct formula, and estimating T=7). T could be estimated by simply looking at the value of (current total deaths + current total recovered) and pair it with a case total in the past that has the same value. For the above formula, the matching dates would be January 26/27, providing an estimate for T of 12 to 13 days. This method of estimating T uses the same logic of the following method, and therefore will yield the same result. An alternative method, which has the advantage of not having to estimate a variable, and that is mentioned in the American Journal of Epidemiology study cited previously as a simple method that nevertheless could work reasonably well if the hazards of death and recovery at any time t measured from admission to the hospital, conditional on an event occurring at time t, are proportional, would be to use the formula: CFR = deaths / (deaths + recovered) which, with the latest data available, would be equal to: 2,360 / (2,360 + 20,949) = 10% CFR (worldwide) If we now exclude cases in mainland China, using current data on deaths and recovered cases, we get: 15 / (15 + 236) = 6.0% CFR (outside of mainland China) The sample size above is extremely limited, but this discrepancy in mortality rates, if confirmed as the sample grows in size, could be explained with a higher case detection rate outside of China especially with respect to Wuhan, where priority had to be initially placed on severe and critical cases, given the ongoing emergency. Unreported cases would have the effect of decreasing the denominator and inflating the CFR above its real value. For example, assuming 10,000 total unreported cases in Wuhan and adding them back to the formula, we would get a CFR of 7.1% (quite different from the CFR of 10% based strictly on confirmed cases). Neil Ferguson, a public health expert at Imperial College in the UK, said his “best guess” was that there were 100,000 affected by the virus even though there were only 2,000 confirmed cases at the time. [11] Without going that far, the possibility of a non negligible number of unreported cases in the initial stages of the crisis should be taken into account when trying to calculate the case fatally rate. As the days go by and the city organized its efforts and built the infrastructure, the ability to detect and confirm cases improved. As of February 3, for example, the novel coronavirus nucleic acid testing capability of Wuhan had increased to 4,196 samples per day from an initial 200 samples.[10] A significant discrepancy in case mortality rate can also be observed when comparing mortality rates as calculated and reported by China NHC: a CFR of 3.1% in the Hubei province (where Wuhan, with the vast majority of deaths is situated), and a CFR of 0.16% in other provinces (19 times less). Finally, we shall remember that while the 2003 SARS epidemic was still ongoing, the World Health Organization (WHO) reported a fatality rate of 4% (or as low as 3%), whereas the final case fatality rate ended up being 9.6%. -- ※ 發信站: 批踢踢實業坊(ptt.cc), 來自: 36.226.178.1 (臺灣) ※ 文章網址: https://www.ptt.cc/bbs/nCoV2019/M.1582340382.A.E44.html

02/22 11:01, 4年前 , 1F
有趣
02/22 11:01, 1F

02/22 11:03, 4年前 , 2F
一堆假設根本無意義
02/22 11:03, 2F

02/22 11:03, 4年前 , 3F
統計武漢封城前跟解封後的人口差
02/22 11:03, 3F

02/22 11:04, 4年前 , 4F
這個先擱置好了,最大基數的中國數字並
02/22 11:04, 4F

02/22 11:04, 4年前 , 5F
不受信任,目前開始爆發的各國,還在醫
02/22 11:04, 5F

02/22 11:04, 4年前 , 6F
治階段,然後又還有其他完全沒在檢測可
02/22 11:04, 6F

02/22 11:04, 4年前 , 7F
能患者的國家,目前要從數字取出結論還
02/22 11:04, 7F

02/22 11:04, 4年前 , 8F
太早
02/22 11:04, 8F

02/22 11:09, 4年前 , 9F
其實一大堆輕症的都不在統計數據內....
02/22 11:09, 9F

02/22 11:10, 4年前 , 10F
要探究真實的死亡率非常困難
02/22 11:10, 10F

02/22 11:11, 4年前 , 11F
頂多就是分析重症死亡率 才比較有意義
02/22 11:11, 11F

02/22 11:13, 4年前 , 12F
這個時間一堆還沒出院,死亡率參考而已
02/22 11:13, 12F

02/22 11:14, 4年前 , 13F
garbage in, garbage out
02/22 11:14, 13F

02/22 11:14, 4年前 , 14F
無參考價值
02/22 11:14, 14F

02/22 11:19, 4年前 , 15F
SARS的死亡率還是高多了,SARS當時沒有出
02/22 11:19, 15F

02/22 11:19, 4年前 , 16F
現像武漢這樣醫療體系崩壞的情況,但死亡
02/22 11:19, 16F

02/22 11:19, 4年前 , 17F
率還遠超過這次,跟這次死亡數大多集中在
02/22 11:19, 17F

02/22 11:19, 4年前 , 18F
武漢拉高平均數不一樣
02/22 11:19, 18F

02/22 11:45, 4年前 , 19F
以中國以外的地區看來之前2%嚴重低估
02/22 11:45, 19F

02/22 12:11, 4年前 , 20F
武漢的死亡是沒計算間接影響
02/22 12:11, 20F

02/22 12:12, 4年前 , 21F
如果算進去應該會海放SARS
02/22 12:12, 21F

02/22 12:13, 4年前 , 22F
因為洗腎病患也因肺炎導致醫療崩潰而
02/22 12:13, 22F

02/22 12:13, 4年前 , 23F
死,等於間接致死
02/22 12:13, 23F

02/22 12:13, 4年前 , 24F
這才是武漢肺炎可怕的地方
02/22 12:13, 24F

02/22 12:13, 4年前 , 25F
它不全靠致死率殺人
02/22 12:13, 25F

02/22 12:14, 4年前 , 26F
塞爆醫院後 連普通肺炎流感都能殺人
02/22 12:14, 26F

02/22 12:15, 4年前 , 27F
它癱瘓醫療後 所有病毒細菌聯手進攻
02/22 12:15, 27F

02/22 12:16, 4年前 , 28F
它致死率1%還是5%也就不重要了
02/22 12:16, 28F

02/22 12:16, 4年前 , 29F
細菌病毒的“國家隊”總和致死率暴增
02/22 12:16, 29F

02/22 12:17, 4年前 , 30F
還有病程長,二月初爆發中的,可能三月
02/22 12:17, 30F

02/22 12:17, 4年前 , 31F
中以後數據才有意義
02/22 12:17, 31F

02/22 12:19, 4年前 , 32F
SARS是單人球星 我自幹模式
02/22 12:19, 32F

02/22 12:20, 4年前 , 33F
武漢肺炎有靈氣開群體Buff打組織戰
02/22 12:20, 33F

02/22 14:22, 4年前 , 34F
感謝分享
02/22 14:22, 34F

02/22 14:58, 4年前 , 35F
這個死亡率的也要灰色吧,還是說官方出
02/22 14:58, 35F

02/22 14:59, 4年前 , 36F
的就不用?????
02/22 14:59, 36F

02/22 14:59, 4年前 , 37F
輕症無症狀那麼多
02/22 14:59, 37F

02/22 15:13, 4年前 , 38F
Pubmed 上有關於之前致死率的研究分析,
02/22 15:13, 38F

02/22 15:13, 4年前 , 39F
大家都可以去看一下
02/22 15:13, 39F

02/22 15:50, 4年前 , 40F
中國的算法有問題
02/22 15:50, 40F

02/22 16:18, 4年前 , 41F
02/22 16:18, 41F

02/22 16:19, 4年前 , 42F
武漢一條街可以數到20具屍
02/22 16:19, 42F

02/22 16:19, 4年前 , 43F
這些都不算在確診病例
02/22 16:19, 43F
文章代碼(AID): #1UK9aUv4 (nCoV2019)
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文章代碼(AID): #1UK9aUv4 (nCoV2019)