Related Experiment Video
Updated: Oct 10, 2025

Author Spotlight: Advancements in Multiplex Detection of Respiratory Viruses
Published on: November 10, 2023
Panel Associations Between Newly Dead, Healed, Recovered, and Confirmed Cases During COVID-19 Pandemic
Ming Guan1,2,3
1International Issues Center, Xuchang University, No. 88 Road Bayi, Xuchang, Henan, China. gming0604@163.com.
Insights
This study confirms panel associations between newly dead, healed, and recovered cases with newly confirmed coronavirus disease 2019 (COVID-19) cases globally. These findings aid in evaluating and controlling the COVID-19 pandemic
Area of Science:
- Epidemiology
- Public Health
- Biostatistics
Background:
- Understanding the relationships between newly recovered (NR), newly healed (NH), newly confirmed (NC), and newly dead (ND) cases of COVID-19 is crucial for disease control.
- Existing knowledge gaps necessitate exploring the panel associations among these key COVID-19 metrics.
Purpose of the Study:
- To investigate the panel associations of newly dead (ND), newly healed (NH), and newly recovered (NR) cases with newly confirmed (NC) cases of COVID-19.
- To analyze these associations across different geographical regions including China, the USA, and globally.
Main Methods:
- Utilized panel data from China, the USA, and global sources spanning from January 2020 to April 2021.
- Employed various regression techniques including pooled regression, quantile regression, and random-effects models.
- Conducted event study analyses to assess the impact of key events on newly confirmed cases (NC).
Main Results:
- Descriptive analysis indicated higher ND/NC ratios in China compared to the USA and global averages.
- Confirmed significant panel associations among ND, NH, NR, and NC across China, the USA, and globally.
- Panel event studies revealed that key events had a greater influence on NC in the USA and globally than in China.
Conclusions:
- The study validates the panel associations between newly dead, healed, and recovered cases and newly confirmed COVID-19 cases.
- Regression outcomes provide insights for comparing the effectiveness of various COVID-19 control strategies worldwide.
- Future research should focus on elucidating the underlying mechanisms driving these observed panel associations.
Background:
Currently, the knowledge of associations among newly recovered cases (NR), newly healed cases (NH), newly confirmed cases (NC), and newly dead cases (ND) can help to monitor, evaluate, predict, control, and curb the spreading of coronavirus disease 2019 (COVID-19). This study aimed to explore the panel associations of ND, NH, and NR with NC.
Methods:
Data from China Data Lab in Harvard Dataverse with China (January 15, 2020 to January 14, 2021), the United States of America (the USA, January 21, 2020 to April 5, 2021), and the World (January 22, 2020 to March 20, 2021) had been analyzed. The main variables included in the present analysis were ND, NH, NR, and NC. Pooled regression, stacked within-transformed linear regression, quantile regression for panel data, random-effects negative binomial regression, and random-effects Poisson regression were conducted to reflect the associations of ND, NH, and NR with NC. Event study analyses were performed to explore how the key events influenced NC.
Results:
Descriptive analyses showed that mean value of ND/NC ratio regarding China was more than those regarding the USA and the World. The results from tentative analysis reported the significant relationships among ND, NH, NR, and NC regarding China, the USA, and the World. Panel regressions confirmed associations of ND, NH, and NR with NC regarding China, the USA, and the World. Panel event study showed that key events influenced NC regarding USA and the World more greatly than that regarding China.
Conclusion:
The findings in this study confirmed the panel associations of ND, NH, and NR with NC in the three datasets. The efficiencies of various control strategies of COVID-19 pandemic across the globe were compared by the regression outcomes. Future direction of research work could explore the influencing mechanisms of the panel associations.
Related Concept Videos
Contingency Table
Causality in Epidemiology
Steps in Outbreak Investigation
Principles of Disease Surveillance
Pareto Chart
The Pareto chart is named after the Italian economist Vilfredo Pareto, who described the Pareto...
Prevalence and Incidence
Prevalence indicates the proportion of individuals in a population who have a specific disease or health...

