As the COVID-19 outbreak is developing the two most frequently reported statistics seem to be the raw confirmed case and case fatalities counts. Focusing on Italy, one of the hardest hit countries, we look at how these two values could be put in perspective to reflect the dynamics of the virus spread. In particular, we find that merely considering the confirmed case counts would be very misleading. The number of daily tests grows, while the daily fraction of confirmed cases to total tests has a change point. It (depending on region) generally increases with strong fluctuations till (around, depending on region) 15–22 March and then decreases linearly after. Combined with the increasing trend of daily performed tests, the raw confirmed case counts are not representative of the situation and are confounded with the sampling effort. This we observe when regressing on time the logged fraction of positive tests and for comparison the logged raw confirmed count. Hence, calibrating model parameters for this virus’s dynamics should not be done based only on confirmed case counts (without rescaling by the number of tests), but take also fatalities and hospitalization count under consideration as variables not prone to be distorted by testing efforts. Furthermore, reporting statistics on the national level does not say much about the dynamics of the disease, which are taking place at the regional level. These findings are based on the official data of total death counts up to 15 April 2020 released by ISTAT and up to 10 May 2020 for the number of cases. In this work, we do not fit models but we rather investigate whether this task is possible at all. This work also informs about a new tool to collect and harmonize official statistics coming from different sources in the form of a package for the R statistical environment and presents the “COVID-19 Data Hub.”

随着 COVID-19 疫情的发展，最常报告的两个统计数据似乎是原始确诊病例和病死人数。着眼于受灾最严重的国家之一意大利，我们着眼于如何正确看待这两个价值观，以反映病毒传播的动态。特别是，我们发现仅考虑确诊病例数会非常具有误导性。每日检测数量增加，而每日确诊病例占总检测的比例有一个变化点。它（取决于地区）通常会随着强烈的波动而增加，直到 3 月 15 日至 22 日（大约，取决于地区），然后在之后线性下降。结合日常检测的增加趋势，原始确诊病例数不能代表情况，并且与抽样工作相混淆。当按时间回归记录的阳性测试分数并比较记录的原始确认计数时，我们会观察到这一点。因此，校准该病毒动态的模型参数不应仅基于确诊病例数（不根据测试数量重新调整），而应将死亡人数和住院人数作为不易被测试工作扭曲的变量考虑在内。此外，国家层面的报告统计数据并不能说明疾病的动态，而这种动态正在区域层面发生。这些调查结果基于 ISTAT 发布的截至 2020 年 4 月 15 日的总死亡人数和截至 2020 年 5 月 10 日的病例数的官方数据。在这项工作中，我们不拟合模型，而是调查这项任务是否可行。R统计环境并呈现“ COVID-19 数据中心”。