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. 2023 May 19;102(20):e33570.
doi: 10.1097/MD.0000000000033570.

The 95% control lines on both confirmed cases and days of infection with COVID-19 were applied to compare the impact on public health between 2020 and 2021 using the hT-index

Hua-Ying Chuang  1   2   3 , Wei-Chih Kan  4   5 , Tsair-Wei Chien  6 , Chia-Liang Tsai  2
Affiliations

The 95% control lines on both confirmed cases and days of infection with COVID-19 were applied to compare the impact on public health between 2020 and 2021 using the hT-index

Hua-Ying Chuang et al. Medicine (Baltimore). .

Abstract

Background: COVID-19, the disease caused by the novel coronavirus, is now a worldwide pandemic. The number of infected people has continually increased, and currently, this pandemic continues to present challenges to public health. Scatter plots are frequently used to interpret the impact in relation to confirmed cases. However, the 95% confidence intervals are rarely given to the scatter plot. The objective of this study was to; Develop 95% control lines on daily confirmed cases and infected days for countries/regions in COVID-19 (DCCIDC) and; Examine their impacts on public health (IPH) using the hT-index.

Methods: All relevant COVID-19 data were downloaded from GitHub. The hT-index, taking all DCCIDCs into account, was applied to measure the IPHs for counties/regions. The 95% control lines were proposed to highlight the outliers of entities in COVID-19. The hT-based IPHs were compared among counties/regions between 2020 and 2021 using the choropleth map and the forest plot. The features of the hT-index were explained using the line chart and the box plot.

Results: The top 2 countries measured by hT-based IPHs were India and Brazil in 2020 and 2021. The outliers beyond the 95% confidence intervals were Hubei (China), with a lower hT-index favoring 2021 ( = 6.4 in 2021 vs 15.55 in 2020) and higher hT indices favoring 2021 in Thailand (28.34 vs 14,77) and Vietnam (27.05 vs 10.88). Only 3 continents of Africa, Asia, and Europe had statistically and significantly fewer DCCIDCs (denoted by the hT-index) in 2021. The hT-index generalizes the h-index and overcomes the disadvantage without taking all elements (e.g., DCCIDCs) into account in features.

Conclusions: The scatter plot combined with the 95% control lines was applied to compare the IPHs hit by COVID-19 and suggested for use with the hT-index in future studies, not limited to the field of public health as we did in this research.

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Conflict of interest statement

The authors have no funding and conflicts of interest to disclose.

Figures

Figure 1.
Figure 1.
How to form 95% confidence interval lines when the SEs are known[33].
Figure 2.
Figure 2.
Study flow chart.
Figure 3.
Figure 3.
Comparison of top 3 countries/regions hit by COVID-19 using hT-index [top 4 in DCC were the US (19,899,082), India (10,266,674), Brazil (10,266,674), and Russia (7,675,973) in 2020 and the US (54,533,878), India (34,861,579), Brazil (22,291,839), and the UK (13,010,849) in 2021]. DCC = daily confirmed case.
Figure 4.
Figure 4.
Comparison of hT indices among countries/regions in 2020 and 2021.
Figure 5.
Figure 5.
Comparison of hT-/h-indices among countries/regions in 2020 and 2021 (each entity with h infected days has at least exp(h) daily confirmed cases).
Figure 6.
Figure 6.
How to calculate the hT-index (e.g., Huan with h infected days has at least exp (h) daily confirmed cases).
Figure 7.
Figure 7.
Comparison of h-/hT indices and the patterns of excess and tail parts.
Figure 8.
Figure 8.
Comparison of hT indices among continents/countries in 2020 and 2021 (note. Significant in Africa, Asia, and Europe in favor of 2021).
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