Laboratório Central de Saúde Pública Professor Gonçalo Muniz, Salvador 40295-010, Brazil.
Department of Zoology, University of Oxford, Oxford OX1 3SZ, UK.
Viruses. 2022 Jul 15;14(7):1549. doi: 10.3390/v14071549.
RT-PCR testing data provides opportunities to explore regional and individual determinants of test positivity and surveillance infrastructure. Using Generalized Additive Models, we explored 222,515 tests of a random sample of individuals with COVID-19 compatible symptoms in the Brazilian state of Bahia during 2020. We found that age and male gender were the most significant determinants of test positivity. There was evidence of an unequal impact among socio-demographic strata, with higher positivity among those living in areas with low education levels during the first epidemic wave, followed by those living in areas with higher education levels in the second wave. Our estimated probability of testing positive after symptom onset corroborates previous reports that the probability decreases with time, more than halving by about two weeks and converging to zero by three weeks. Test positivity rates generally followed state-level reported cases, and while a single laboratory performed ~90% of tests covering ~99% of the state's area, test turn-around time generally remained below four days. This testing effort is a testimony to the Bahian surveillance capacity during public health emergencies, as previously witnessed during the recent Zika and Yellow Fever outbreaks.
实时聚合酶链反应（RT-PCR）检测数据提供了探索区域和个体阳性检测决定因素以及监测基础设施的机会。本研究使用广义加性模型，对巴西巴伊亚州 2020 年期间 COVID-19 症状相符的随机个体样本的 222515 次检测进行了探索。结果发现，年龄和性别是阳性检测的最显著决定因素。社会人口统计学各阶层的影响存在不平等现象，在第一波疫情中，教育水平较低地区的阳性检出率较高，其次是第二波疫情中教育水平较高地区的阳性检出率。本研究估计的症状出现后阳性检测概率与先前的报告一致，即随着时间的推移概率降低，大约两周内降低一半，三周后趋近于零。阳性检测率总体上与州级报告病例相符，尽管有一个实验室进行了约 90%的检测，覆盖了全州约 99%的地区，但检测周转时间通常仍保持在四天以下。这一检测工作证明了巴伊亚州在公共卫生紧急情况下的监测能力，就像在最近的寨卡和黄热病爆发期间所见证的那样。
