From the Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA.
Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA.
Epidemiology. 2021 Jul 1;32(4):518-524. doi: 10.1097/EDE.0000000000001361.
Serology tests can identify previous infections and facilitate estimation of the number of total infections. However, immunoglobulins targeting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been reported to wane below the detectable level of serologic assays (which is not necessarily equivalent to the duration of protective immunity). We estimate the cumulative incidence of SARS-CoV-2 infection from serology studies, accounting for expected levels of antibody acquisition (seroconversion) and waning (seroreversion), and apply this framework using data from New York City and Connecticut.
We estimated time from seroconversion to seroreversion and infection fatality ratio (IFR) using mortality data from March to October 2020 and population-level cross-sectional seroprevalence data from April to August 2020 in New York City and Connecticut. We then estimated the daily seroprevalence and cumulative incidence of SARS-CoV-2 infection.
The estimated average time from seroconversion to seroreversion was 3-4 months. The estimated IFR was 1.1% (95% credible interval, 1.0%, 1.2%) in New York City and 1.4% (1.1, 1.7%) in Connecticut. The estimated daily seroprevalence declined after a peak in the spring. The estimated cumulative incidence reached 26.8% (24.2%, 29.7%) at the end of September in New York City and 8.8% (7.1%, 11.3%) in Connecticut, higher than maximum seroprevalence measures (22.1% and 6.1%), respectively.
The cumulative incidence of SARS-CoV-2 infection is underestimated using cross-sectional serology data without adjustment for waning antibodies. Our approach can help quantify the magnitude of underestimation and adjust estimates for waning antibodies.
血清学检测可识别既往感染,并有助于估算总感染人数。然而,针对严重急性呼吸综合征冠状病毒 2(SARS-CoV-2)的免疫球蛋白已被报道会降至血清学检测方法无法检测的水平(这并不一定等同于保护性免疫的持续时间)。我们通过血清学研究估计 SARS-CoV-2 感染的累积发病率,同时考虑到预期的抗体获得(血清转阳)和衰减(血清转阴)水平,并使用来自纽约市和康涅狄格州的数据应用这一框架。
我们利用 2020 年 3 月至 10 月的死亡率数据以及 2020 年 4 月至 8 月的纽约市和康涅狄格州人群横断面血清阳性率数据,估计从血清转阳到血清转阴的时间以及感染病死率(IFR)。然后,我们估计了 SARS-CoV-2 感染的日血清阳性率和累积发病率。
估计从血清转阳到血清转阴的平均时间为 3-4 个月。纽约市的估计 IFR 为 1.1%(95%可信区间,1.0%,1.2%),康涅狄格州为 1.4%(1.1%,1.7%)。春季达到峰值后,估计的日血清阳性率下降。9 月底,纽约市的估计累积发病率达到 26.8%(24.2%,29.7%),康涅狄格州为 8.8%(7.1%,11.3%),均高于最大血清阳性率测量值(分别为 22.1%和 6.1%)。
如果不调整抗体衰减,使用横断面血清学数据会低估 SARS-CoV-2 感染的累积发病率。我们的方法可以帮助量化这种低估的程度,并调整衰减抗体的估计值。