Department of Internal Medicine, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán (INCMyNSZ), Mexico City, Mexico
National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, USA
Rev Invest Clin. 2020 Dec 4;73(2):120-6. doi: 10.24875/RIC.20000587.
Underestimation of the number of cases during the coronavirus disease 2019 (COVID-19) pandemic has been a constant concern worldwide. Detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA using realtime reverse-transcription polymerase chain reaction (RT-PCR) is the most common method to confirm a case. However, these tests have suboptimal sensitivity.
The objective of the study was to estimate the number of COVID-19 confirmed cases, intensive care unit (ICU) admissions and deaths in Mexico, accounting for the probabilities of false-negative tests.
We used publicly available, national databases of all SARS-CoV-2 tests performed at public laboratories in Mexico between February 27 and October 31, 2020. We used the estimated probabilities of false-negative tests based on the day of clinical sample collection after symptom initiation calculated previously. With the resulting model, we estimated the corrected daily number of cases, ICU admissions, and deaths.
Among 2,024,822 people tested in Mexico between February 27 and October 31 with an available result, we estimated 1,248,583 (95% confidence interval 1,094,850-1,572,818) cases, compared to 902,343 cases reported with positive tests. ICU admissions and deaths were 15% and 8% higher than reported, respectively.
Accounting for SARS-CoV-2 RT-PCR-based diagnostic tests’ precision is a simple way to improve estimations for the true number of COVID-19 cases among tested persons.
在 2019 年冠状病毒病（COVID-19）大流行期间，低估病例数量一直是全球关注的问题。使用实时逆转录聚合酶链反应（RT-PCR）检测严重急性呼吸综合征冠状病毒 2（SARS-CoV-2）RNA 是确认病例的最常见方法。然而，这些测试的敏感性并不理想。
本研究的目的是估计墨西哥 COVID-19 确诊病例、重症监护病房（ICU）入院和死亡人数，同时考虑到假阴性测试的概率。
我们使用了墨西哥公共实验室在 2020 年 2 月 27 日至 10 月 31 日期间进行的所有 SARS-CoV-2 检测的公开可用的国家数据库。我们使用了之前根据症状发作后临床样本采集日计算的估计假阴性测试概率。利用得到的模型，我们估计了校正后的每日病例、ICU 入院和死亡人数。
在 2020 年 2 月 27 日至 10 月 31 日期间接受检测的 2024822 人中，我们估计有 1248583 例（95%置信区间 1094850-1572818）病例，而阳性检测报告的病例数为 902343 例。ICU 入院和死亡人数分别比报告的数字高出 15%和 8%。
考虑到基于 SARS-CoV-2 RT-PCR 的诊断测试的精度，是提高对检测人群中 COVID-19 真实病例数量估计的一种简单方法。
