Shioda Kayoko, Lau Max Sy, Kraay Alicia Nm, Nelson Kristin N, Siegler Aaron J, Sullivan Patrick S, Collins Matthew H, Weitz Joshua S, Lopman Benjamin A
Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA.
Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, USA.
medRxiv. 2020 Nov 16:2020.11.13.20231266. doi: 10.1101/2020.11.13.20231266.
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 serological assays. 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 (NYC) and Connecticut.
We estimated time from seroconversion to seroreversion and infection fatality ratio (IFR) using mortality data from March-October 2020 and population-level cross-sectional seroprevalence data from April-August 2020 in NYC 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 NYC 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%) and 8.8% (7.1-11.3%) at the end of September in NYC and 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.
This study was supported by the US National Science Foundation and the National Institute of Allergy and Infectious Diseases.
血清学检测可识别既往感染情况，并有助于估计总感染人数。然而，据报道，针对严重急性呼吸综合征冠状病毒2（SARS-CoV-2）的免疫球蛋白会降至血清学检测的可检测水平以下。我们通过血清学研究估计SARS-CoV-2感染的累积发病率，同时考虑抗体获得（血清转化）和衰减（血清逆转）的预期水平，并使用来自纽约市（NYC）和康涅狄格州的数据应用此框架。
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月纽约市和康涅狄格州的人群水平横断面血清阳性率数据，估计从血清转化到血清逆转的时间以及感染死亡率（IFR）。然后，我们估计了SARS-CoV-2感染的每日血清阳性率和累积发病率。
从血清转化到血清逆转的估计平均时间为3至4个月。纽约市的估计感染死亡率为1.1%（95%可信区间：1.0 - 1.2%），康涅狄格州为1.4%（1.1 - 1.7%）。估计的每日血清阳性率在春季达到峰值后下降。到9月底，纽约市和康涅狄格州的估计累积发病率分别达到26.8%（24.2 - 29.7%）和8.8%（7.1 - 11.3%），高于最高血清阳性率测量值（分别为22.1%和6.1%）。
使用未经抗体衰减调整的横断面血清学数据会低估SARS-CoV-2感染的累积发病率。我们的方法有助于量化低估的程度，并对抗体衰减进行估计调整。
本研究由美国国家科学基金会和国家过敏与传染病研究所资助。
