Li Chenyu, Romagnani Paola, Anders Hans-Joachim
Medizinische Klinik und Poliklinik IV, Klinikum der Universität, Ludwig-Maximilians-Universität München, Munich, Germany.
Excellence Centre for Research, Transfer and High Education for the Development of DE NOVO Therapies (M.E.M., P.R.), University of Florence, Florence, Italy.
Front Big Data. 2020 Jul 24;3:26. doi: 10.3389/fdata.2020.00026. eCollection 2020.
In the first month of 2020, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), a novel coronavirus spreading quickly via human-to-human transmission, caused the coronavirus disease 2019 (COVID-19) pandemic. Italy installed a successful nationwide lockdown to mitigate the exponential increase of case numbers, as the basic reproduction number R0 reached 1 within 4 weeks. But is R0 really the relevant criterion as to whether or not community spreading is under control? In most parts of the world, testing largely focused on symptomatic cases, and we thus hypothesized that the true number of infected cases and relative testing capacity are better determinants to guide lockdown exit strategies. We employed the SEIR model to estimate the numbers of undocumented cases. As expected, the estimated numbers of all cases largely exceeded the reported ones in all Italian regions. Next, we used the numbers of reported and estimated cases per million of population and compared it with the respective numbers of tests. In Lombardy, as the most affected region, testing capacity per reported new case seemed between two and eight most of the time, but testing capacity per estimated new cases never reached four up to April 30. In contrast, Veneto's testing capacity per reported and estimated new cases were much less discrepant and were between four and 16 most of the time. As per April 30 also Marche, Lazio and other Italian regions arrived close to 16 ratio of test capacity per new estimated infection. Thus, the criterion to exit a lockdown should be decided at the level of the regions, based on the local testing capacity that should reach 16 times the estimated true number of newly infected cases as predicted.
2020年1月,严重急性呼吸综合征冠状病毒2(SARS-CoV-2),一种通过人际传播迅速传播的新型冠状病毒,引发了2019冠状病毒病(COVID-19)大流行。意大利成功实施了全国范围的封锁措施,以缓解病例数的指数级增长,因为基本繁殖数R0在4周内降至1。但R0真的是社区传播是否得到控制的相关标准吗?在世界大部分地区,检测主要集中在有症状的病例上,因此我们假设,实际感染病例数和相对检测能力是指导解除封锁策略的更好决定因素。我们使用SEIR模型来估计未报告病例的数量。不出所料,意大利所有地区估计的病例总数大大超过了报告的病例数。接下来,我们使用每百万人口中报告和估计的病例数,并将其与各自的检测数进行比较。在受影响最严重的伦巴第大区,每报告一例新病例的检测能力在大多数时候似乎在2到8之间,但截至4月30日,每估计一例新病例的检测能力从未达到4。相比之下,威尼托大区每报告和估计一例新病例的检测能力差异要小得多,大多数时候在4到16之间。截至4月30日,马尔凯、拉齐奥和意大利其他地区每新估计一例感染病例的检测能力也接近16。因此,解除封锁的标准应该在地区层面上决定,基于当地的检测能力,该能力应达到预测的新感染病例估计真实数量的16倍。