如何最好地预测新冠肺炎每日新增感染人数
How to Best Predict the Daily Number of New Infections of Covid-19
摘要：
了解新冠肺炎每日新增感染人数非常重要，因为这是导致封锁和紧急医疗保健措施的政治决策的基础。我们以德国为例来说明官方数据的不足之处，至少在德国，官方数据的披露只有几天的延迟，并且在周末严重低估（超过40%）。这些缺陷表明迫切需要替代数据来源。约翰霍普金斯大学系统科学与工程中心（JHU）提供的另一个被广泛引用的来源也与德国的官方数据平均偏差79%。我们认为，谷歌搜索和Twitter数据应该补充官方数据。他们的预测甚至比约翰霍普金斯大学的原始值更好，而且提前了几天。这两个数据来源也可用于世界上没有官方数字或被认为不可靠的地方。
英文摘要：
Knowledge about the daily number of new infections of Covid-19 is important because it is the basis for political decisions resulting in lockdowns and urgent health care measures. We use Germany as an example to illustrate shortcomings of official numbers, which are, at least in Germany, disclosed only with several days of delay and severely underreported on weekends (more than 40%). These shortcomings outline an urgent need for alternative data sources. The other widely cited source provided by the Center for Systems Science and Engineering at Johns Hopkins University (JHU) also deviates for Germany on average by 79% from the official numbers. We argue that Google Search and Twitter data should complement official numbers. They predict even better than the original values from Johns Hopkins University and do so several days ahead. These two data sources could also be used in parts of the world where official numbers do not exist or are perceived to be unreliable.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
