Using the IPcase Index with Inflection Points and the Corresponding Case Numbers to Identify the Impact Hit by COVID-19 in China: An Observation Study

Abstract

Coronavirus disease 2019 (COVID-19) occurred in Wuhan and rapidly spread around the world. Assessing the impact of COVID-19 is the first and foremost concern. The inflection point (IP) and the corresponding cumulative number of infected cases (CNICs) are the two viewpoints that should be jointly considered to differentiate the impact of struggling to fight against COVID-19 (SACOVID). The CNIC data were downloaded from the GitHub website on 23 November 2020. The item response theory model (IRT) was proposed to draw the ogive curve for every province/metropolitan city/area in China. The ipcase-index was determined by multiplying the IP days with the corresponding CNICs. The IRT model was parameterized, and the IP days were determined using the absolute advantage coefficient (AAC). The difference in SACOVID was compared using a forest plot. In the observation study, the top three regions hit severely by COVID-19 were Hong Kong, Shanghai, and Hubei, with IPcase indices of 1744, 723, and 698, respectively, and the top three areas with the most aberrant patterns were Yunnan, Sichuan, and Tianjin, with IP days of 5, 51, and 119, respectively. The difference in IP days was determined (χ2 = 5065666, df = 32, p < 0.001) among areas in China. The IRT model with the AAC is recommended to determine the IP days during the COVID-19 pandemic.

Using the Angle Index to Assess COVID-19 Damage at the Early Stage and Throughout 2020 in Comparison of Mathematical Models

“…Traditionally, the mean number of confirmed cases across varying periods (number of days) yields significantly different IP days, even though the daily number of confirmed cases (computed based on the previous seven days) can be applied to estimate the "observed" IP days [8,9]. In this case, using a mathematical model to determine the "expected" IP days is more objective than referring to the IP days based on the mean number of confirmed cases, which is typically employed in practice [2].…”

“…Although many mathematical models [2,[10][11][12][13][14][15][16][17][18][19] have been proposed to predict the number of COVID-19 cases, none of those models-except one using item response theory (IRT)…”

“…As such, y1 denotes the corresponding number of cases on day 1 (i.e., x1 = 0), y2 corresponds to the CNCCs on the middle, and y3 corresponds to the CNCCs on the present day. The model parameters, which are similar to the EXPO and IRT models, can be estimated by minimizing the model residual using the Microsoft add-in tool [2]; details are given in Additional file 1 (e.g., executing the procedural, SolverSolve UserFinish: = True, ShowRef: = "ShowTrial", using visual basic for applications (VBA)).…”

“…In comparison, a "pandemic" is defined as a near-global disease outbreak in which multiple countries across the world are infected [1]. Using the cumulative numbers of the confirmed case (CNCCs) is a commonly used method in assessing the negative impacts of the COVID-19 outbreak (ImpactCOVID for short) [2][3][4][5]. However, its evaluation might be questionable due to the fact that it does not consider the length of infected days effectively under control (known as "LID").…”

Using the Absolute Advantage Coefficient(AAC) to Measure the Strength of Damage Hit by COVID-19 in India on a Growth-Share Matrix

“…However, those dashboards merely displayed basic information on the numbers of death and con rmed cases of COVID-19 on a world map [14]. None of those dashboards were equipped with more sophisticated knowledge to ful ll the public's interest and need of the COVID-19 situation, such as using (i) the growth/share matrix(GSM) coined by the Boston Consulting Group (BCG) in 1970 to classify countries/regions in feature (i.e., growth on the Y-axis and share on the X-axis) [15][16][17], and (ii) the absolute advantage coe cient(AAC) [18][19][20][21][22] to report the strength of damage hit by COIVD-19 when compared to the next two countries/regions(e.g., what are the situations in India using the GSM and the AAC when the deadly second wave of Covid-19 spreads from cities to small towns [23]. The GSM is the most famous and simple portfolio planning matrix suggested to organizations to achieve a balance between the four categories of products a company produces [24,25], and was established in1970 by Bruce Doolin Henderson for the BCG in Boston, Massachusetts, the USA.…”