Department of Emergency Medicine, Chi-Mei Medical Center, Tainan, Taiwan.
Department of Medical Research, Chiali Chi-Mei Medical Center, Tainan, Taiwan.
Medicine (Baltimore). 2022 Feb 4;101(5):e28749. doi: 10.1097/MD.0000000000028749.
Exponential-like infection growth leading to peaks (denoted by inflection points [IP] or turning points) is usually the hallmark of infectious disease outbreaks, including coronaviruses. To determine the IPs of the novel coronavirus (COVID-19), we applied the item response theory model to detect phase transitions for each country/region and characterize the IP feature on the temporal bar graph (TBG).
The IP (using the item difficulty parameter to locate) was verified by the differential equation in calculus and interpreted by the TBG with 2 virtual and real empirical data (i.e., from Collatz conjecture and COVID-19 pandemic in 2020). Comparisons of IPs, R2, and burst strength [BS = ln() denoted by the infection number at IP(Nip) and the item slope parameter(a) in item response theory were made for countries/regions and continents on the choropleth map and the forest plot.
We found that the evolution of COVID-19 on the TBG makes the data clear and easy to understand, the shorter IP (=53.9) was in China and the longest (=247.3) was in Europe, and the highest R2 (as the variance explained by the model) was in the US, with a mean R2 of 0.98. We successfully estimated the IPs for countries/regions on COVID-19 in 2020 and presented them on the TBG.
Temporal visualization is recommended for researchers in future relevant studies (e.g., the evolution of keywords in a specific discipline) and is not merely limited to the IP search in COVID-19 pandemics as we did in this study.
呈指数增长的感染增长导致峰值（由拐点[IP]或转折点表示）通常是传染病爆发的标志，包括冠状病毒。为了确定新型冠状病毒（COVID-19）的 IP，我们应用项目反应理论模型来检测每个国家/地区的相变，并在时间条形图（TBG）上描述 IP 特征。
通过微积分中的微分方程验证 IP（使用项目难度参数定位），并通过具有 2 个虚拟和真实经验数据（即，来自 Collatz 猜想和 2020 年 COVID-19 大流行）的 TBG 进行解释。对国家/地区和大陆的 IP、R2 和爆发强度[BS=ln()]进行比较（以 IP 处的感染数量 Nip 和项目响应理论中的项目斜率参数(a)表示）在专题地图和森林图上。
我们发现，COVID-19 在 TBG 上的演变使数据清晰易懂，中国的 IP 最短（=53.9），欧洲的最长（=247.3），美国的 R2 最高（表示模型解释的方差），平均 R2 为 0.98。我们成功估计了 2020 年 COVID-19 国家/地区的 IP，并在 TBG 上呈现了这些 IP。
建议未来相关研究的研究人员进行时间可视化（例如，特定学科中关键词的演变），而不仅仅限于我们在这项研究中对 COVID-19 大流行中的 IP 搜索。
