COVID-19 Control Research Articles

A review: Data visualization for COVID-19

As COVID-19 raged across the globe, it seriously disrupted social health security, daily work, and the rest of the people, which aroused great panic among all classes. These facts extensively affected the regional circulation and economic growth of the epidemic area. Data visualization, an advanced technology, can help humans understand epidemic transmission trends, identify high-risk areas of outbreak, and evaluate prevention and control policies. Previous essays immediately established databases to organize and build datasets. Other researchers built new visualization models to analyze the causes of virus transmission and pointed out the low efficiency of the existing COVID-19 system response. Although various research and data visualization methods have been used on COVID-19, there has not been a comprehensive, systematic essay that covers the entire span of COVID-19 and its data visualization usage. Therefore, this paper will provide a new systematic and comprehensive perspective to explore the analysis of data visualization to solve COVID-19 data challenges and provide research methods and applications for COVID-19. To be specific, this paper first introduces the characteristics and challenges of COVID-19 epidemic data people may face during the data visualization process, which includes data complexity problems, data timeliness problems, data regional problems, and data quality problems. Then, this paper discusses data visualization methods used by predecessors in previous research. After that, this paper describes the urgent data visualization analysis requirements of COVID-19, including regional differences in virus spread, the influence of temperature on the virus, transmission trends, and death rates for different genders and ages, etc. Finally, this paper reviews applications of data visualization in COVID-19 analysis, followed by earlier-stage prevention, mid-term containment, and later-term reduction of impact. This paper provides an important reference for further research and application of data visualization technology in COVID-19 prevention and control, which brings new ideas for strengthening future epidemic surveillance and data visualization for global epidemic prevention and control.

Influenza A, Influenza B, human respiratory syncytial virus and SARSCoV-2 molecular diagnostics and epidemiology in the post COVID-19 era

BackgroundThe concurrent circulation of SARS-CoV-2 with other respiratory viruses is unstoppable and represents a new diagnostic reality for clinicians and clinical microbiology laboratories. Multiplexed molecular testing on automated platforms that focus on the simultaneous detection of multiple respiratory viruses in a single tube is a useful approach for current and future diagnosis of respiratory infections in the clinical setting.MethodsTwo time periods were included in the study: from February to April 2022, an early 2022 period, during the gradual lifting of COVID-19 prevention measures in the country, and from October 2022 to April 2023, the 2022/23 respiratory infections season. We analysed a total of 1,918 samples in the first period and 18,131 respiratory samples in the second period using a multiplex molecular assay for the simultaneous detection of Influenza A (Flu-A), Influenza B (Flu-B), Human Respiratory Syncytial Virus (HRSV) and SARS-CoV-2.ResultsThe results from early 2022 showed a strong dominance of SARS-CoV-2 infections with 1,267/1,918 (66.1%) cases. Flu-A was detected in 30/1,918 (1.6%) samples, HRSV in 14/1,918 (0.7%) samples, and Flu-B in 2/1,918 (0.1%) samples. Flu-A/SARS-CoV-2 co-detections were observed in 11/1,267 (0.9%) samples, and HRSV/SARS-CoV-2 co-detection in 5/1,267 (0.4%) samples. During the 2022/23 winter respiratory season, SARS-CoV-2 was detected in 1,738/18,131 (9.6%), Flu-A in 628/18,131 (3.5%), Flu-B in 106/18,131 (0.6%), and HRSV in 505/18,131 (2.8%) samples. Interestingly, co-detections were present to a similar extent as in early 2022.ConclusionThe results show that the multiplex molecular approach is a valuable tool for the simultaneous laboratory diagnosis of SARS-CoV-2, Flu-A/B, and HRSV in hospitalized and outpatients. Infections with Flu-A/B, and HRSV occurred shortly after the COVID-19 control measures were lifted, so a strong reoccurrence of various respiratory infections and co-detections in the post COVID-19 period was to be expected.

Core health system measures response to COVID-19 among East Asian countries.

The purpose of this study is to summarize the health system response to COVID-19 in four East Asian countries, analyze the effectiveness of their health system response, and provide lessons for other countries to control the epidemic and optimize their health system response. This study investigated and summarized COVID-19 data and health system response in four East Asian countries, China, Japan, Mongolia, and South Korea from national governments and ministries of health, WHO country offices, and official websites of international organizations, to assess the effectiveness of health system measures. As of June 30, 2022, all four countries are in a declining portion of COVID-19. China has two waves, and new cases increased slowly, with the total cases per million remaining within 4, indicating a low level. Japan has experienced six waves, with case growth at an all-time high, total cases per million of 250.994. Mongolia started the epidemic later, but also experienced four waves, with total cases per million of 632.658, the highest of the four countries. South Korea has seen an increasing number of new cases per wave, with a total case per million of 473.759. In containment strategies adopted by China and Mongolia, and mitigation strategies adopted by Japan and South Korea, health systems have played important roles in COVID-19 prevention and control. While promoting vaccination, countries should pay attention to non-pharmaceutical health system measures, as evidenced by: focusing on public information campaigns to lead public minds; strengthening detection capabilities for early detection and identification; using technical ways to participate in contact tracing, and promoting precise judging isolation.

Research on the Forecast of Emergency Supplies for Major Public Health Emergencies - An Empirical Study Based on the Distribution of Donated Facial Masks by the Wuhan COVID-19 Epidemic Prevention and Control Headquarters

Research on the Forecast of Emergency Supplies for Major Public Health Emergencies - An Empirical Study Based on the Distribution of Donated Facial Masks by the Wuhan COVID-19 Epidemic Prevention and Control Headquarters

A novel collocation method with a coronavirus optimization algorithm for the optimal control of COVID-19: A case study of Wuhan, China

In this study, we develop a numerical optimization approach to address the challenge of optimal control in the spread of COVID-19. We evaluate the impact of various control strategies aimed at reducing the number of exposed and infectious individuals. Our novel approach employs Legendre wavelets, their derivative operational matrix, and a collocation method to transform the COVID-19 transmission optimal control model into a nonlinear programming (NLP) problem. To solve this problem, we employ a coronavirus optimization algorithm (COVIDOA) to determine the optimal control, state variables, and objective value. We investigate three control plans for this highly contagious disease, focusing on individual protection, rapid detection and treatment, detection with delay in treatment, and environmental viral dispersion as time-based control functions. These strategies are applied within an SEIR-type control model specific to COVID-19 in China, designed to mitigate disease spread. Lastly, we analyze the effects of various parameters within the COVID-19 spread model. Our numerical results highlight the significant impact of strategies that minimize the number of exposed and infectious individuals, particularly those related to rapid detection, detection delay, and environmental viral dispersion, in controlling and preventing the transmission of the COVID-19 virus.

The Impact of COVID-19 during Pregnancy on Maternal Hemodynamic Function, Angiogenic Markers and Neonatal Outcome.

Infections with severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) in pregnancy are associated with the development of preeclampsia and fetal growth restriction (FGR). Recently, preeclampsia was linked to impaired maternal hemodynamic function. This retrospective study evaluated singleton pregnancies with COVID-19 during pregnancy and healthy pregnant controls matched for gestational age from November 2020 to March 2022. Non-invasive assessment of maternal hemodynamics by continuous wave Doppler ultrasound measurements (USCOM-1A® Monitor) and oscillometric arterial stiffness (Arteriograph) was performed. Overall, 69 pregnant women were included-23 women after COVID-19 during pregnancy and 46 healthy controls. While two women (8.7%) were admitted to the hospital due to COVID-19-related symptoms, none required intensive care unit admission or non-invasive/invasive ventilation. There were no statistically significant differences in the majority of hemodynamic parameters between the two cohorts. The prevalence of FGR was significantly higher in the COVID-19 during pregnancy group (9.5% vs. healthy controls: 0.0%; p = 0.036), especially in nulliparous women. No difference in angiogenic markers and neonatal outcomes were observed between pregnant women after COVID-19 and healthy controls. In conclusion, no significant differences in hemodynamic parameters or neonatal outcome were observed in women with COVID-19 during pregnancy. However, an increased prevalence of FGR could be described.

Utilizing disease transmission and response capacities to optimize covid-19 control in Malaysia

ObjectivesPublic Health Social Measures (PHSM) such as movement restriction movement needed to be adjusted accordingly during the COVID-19 pandemic to ensure low disease transmission alongside adequate health system capacities based on the COVID-19 situational matrix proposed by the World Health Organization (WHO). This paper aims to develop a mechanism to determine the COVID-19 situational matrix to adjust movement restriction intensity for the control of COVID-19 in Malaysia.MethodsSeveral epidemiological indicators were selected based on the WHO PHSM interim guidance report and validated individually and in several combinations to estimate the community transmission level (CT) and health system response capacity (RC) variables. Correlation analysis between CT and RC with COVID-19 cases was performed to determine the most appropriate CT and RC variables. Subsequently, the CT and RC variables were combined to form a composite COVID-19 situational matrix (SL). The SL matrix was validated using correlation analysis with COVID-19 case trends. Subsequently, an automated web-based system that generated daily CT, RC, and SL was developed.ResultsCT and RC variables were estimated using case incidence and hospitalization rate; Hospital bed capacity and COVID-19 ICU occupancy respectively. The estimated CT and RC were strongly correlated [ρ = 0.806 (95% CI 0.752, 0.848); and ρ = 0.814 (95% CI 0.778, 0.839), p < 0.001] with the COVID-19 cases. The estimated SL was strongly correlated with COVID-19 cases (ρ = 0.845, p < 0.001) and responded well to the various COVID-19 case trends during the pandemic. SL changes occurred earlier during the increase of cases but slower during the decrease, indicating a conservative response. The automated web-based system developed produced daily real-time CT, RC, and SL for the COVID-19 pandemic.ConclusionsThe indicators selected and combinations formed were able to generate validated daily CT and RC levels for Malaysia. Subsequently, the CT and RC levels were able to provide accurate and sensitive information for the estimation of SL which provided valuable evidence on the progression of the pandemic and movement restriction adjustment for the control of Malaysia.

Discussion and Countermeasures on the Application of Health Code in the Routine Prevention and Control of COVID-19

From the previous SARS to the current novel coronavirus, major public health emergencies have occurred in China one after another. With the development of The Times and the progress of society and science and technology, people are more and more aware of the importance of effective prevention and control of such incidents, and what means to adopt effective prevention and control has gradually attracted global attention. In the context of the new coronavirus epidemic, the health code, an innovative young measure, can be said to have opened up a precedent and played an irreplaceable role in China's epidemic prevention and control. In the three years since the outbreak of COVID-19 from the beginning of 2020 to the end of 2022, health codes have been widely used and become an important means of epidemic prevention, but some problems have inevitably been exposed, especially in the period of normal epidemic prevention and control, such as: The problems of digital divide, information island, and abnormal color of health code have impacted the effective prevention and control of the epidemic in this period. After fully considering and demonstrating the application scenarios and promotion conditions of health code, combine and utilize existing technologies, such as: Bluetooth or GPS positioning, digital contact tracking technology, automatic identification technology, remote technology, etc., put forward the innovative concept of "health code chip", which can not only solve such problems, improve the technical level and practical application range of health code, so that health code has become an important tool and effective means to deal with major public health emergencies. Moreover, it can provide valuable reference opinions and experience for the handling of major public health emergencies in the world.

Public perspectives on COVID-19 public health and social measures in Japan and the United Kingdom: a qualitative study

BackgroundThe COVID-19 pandemic, caused by SARS-CoV-2, was one of the greatest modern public health crises that the world has faced. Countries undertook sweeping public health and social measures (PHSM); including environmental actions such as disinfection and ventilation; surveillance and response, such as contact tracing and quarantine; physical, such as crowd control; and restrictions on travel. This study focuses on the public perceptions of PHSM in two countries, Japan and the United Kingdom (UK) as examples of high-income countries that adopted different measures over the course of the pandemic.MethodsThis study was conducted between November 2021 and February 2022, a period in which the Omicron variant of SARS-CoV-2 was predominant. Fourteen online focus group discussions were conducted in each country. Overall, 106 total participants (50 from the UK and 56 from Japan) participated in 23 focus groups (11 in the UK and 12 in Japan) with an average of three to six participants per group. Both countries were compared using a thematic analysis method.ResultsBoth countries’ participants agreed that vaccination was an effective measure. However, they did not favor mandatory vaccination policies. Working from home was well accepted by both sides, but they reported that schools should have continued to be opened as before COVID-19. Both sides of participants expressed that temperature testing alone in indoor facilities was ineffective as a COVID-19 control measure. There were contrasting views on face covering rules in public spaces, international and domestic movement restrictions. High acceptance of mask-wearing was reflective of Japanese customs, while it was accepted as a strong recommendation for participants in the UK. Japanese participants favored quarantine for international travel, while the UK participants supported banning non-essential travel.ConclusionSimilar and contrasting views on PHSM against COVID-19 between Japan and the UK demonstrated how policies in controlling an epidemic should be tailored by country with respect to its norms, cultures, economic and disease burden. Our findings may guide how policy makers can engage with the public through effective health communication and consider regulations that are aligned with the public’s views and capacities in changing their behavior for future pandemic preparedness.

A Prospective Study Investigating Immune Checkpoint Molecule and CD39 Expression on Peripheral Blood Cells for the Prognostication of COVID-19 Severity and Mortality.

In patients with COVID-19, broad panels of immune checkpoint molecules (ICPMs) and the purinergic signaling have not been studied in parallel. We aimed to perform in-depth immunophenotyping of major cell subsets present in human peripheral blood of COVID-19 patients and controls using PD1, TIM3, LAG3, TIGIT, and CD200R, as well as CD39, as markers for the purinergic signaling pathway. We studied 76 COVID-19 patients and 12 healthy controls using peripheral blood mononuclear cells on flow cytometry. Univariable and multivariable statistics were performed. All ICPMs studied were significantly overexpressed on different cell subsets of COVID-19 patients when compared with healthy controls. Elevated lactate dehydrogenase; C-reactive protein; age; and high expression of CD45+, CD39+CD45+, TIM3+CD39+CD4+CD45+, and TIM3+CD39+CD8+CD3+CD4+ cells were significantly associated with severe COVID-19. On multivariable analysis, however, only high expression of CD39+CD45+ (OR 51.4, 95% CI 1.5 to 1763) and TIM3+CD39+CD4+CD3+CD45+ (OR 22.6, 95% CI 1.8 to 277) cells was an independent predictor for severe COVID-19. In conclusion, numerous ICPMs are overexpressed in COVID-19 patients when compared with healthy controls, suggesting a pathophysiological role of these molecules in SARS-CoV-2 infection. However, only TIM3 in co-expression with CD39 remained as a significant independent prognostic ICPM on multivariable analysis. The flow cytometric evaluation of TIM3+CD39+CD4+CD3+CD45+, as well as CD39+CD45+, is a powerful tool for the prognostication of COVID-19 patients on hospital admission.

Changes in International Migration to and from Australia During the COVID-19 Pandemic

The COVID-19 pandemic slowed down international migration around the world, with many countries closing their international borders for a prolonged period of time. Although there are studies emerging that analyse the impact of COVID-19 and border control measures, more detailed migration flow data have been largely absent. In this research note, we examine changes to the patterns of immigration and emigration in Australia during the pandemic to further our understanding of the differing impacts of the pandemic on population groups. Foreign-born populations with large shares of international students recorded the highest declines in immigration, especially those from China, Malaysia, and South America. Immigration of seasonal workers from the Pacific Islands, on the other hand, exhibited increased levels. There were also unexpected situations where residents who made temporary visits outside Australia were unable to return, or persons who were visiting on short-term visas prolonged their stay. Results reveal how responsive migration can be to policies in a time of a population health crisis. The nuance and complexity of these patterns underscore the importance of migration dynamics, adding to our knowledge of the changing international migration profiles during the recent pandemic.

Mathematical Model for COVID-19

Since the end of 2019, novel coronavirus has started to spread around the world and continue to mutate. From the initial Alpha to Delta and Omicron, it continues to affect our economic, social and spiritual life. In the process of prevention and control of COVID-19, many people are constantly questioning the prevention and control measures taken in China, such as wearing masks when going in and out of public places, washing hands frequently when going out and back home, regular disinfection in public places, the necessity of building large-scale shelter hospitals, fixed-point isolation of close contacts and infected persons, and universal vaccination. In this paper, the mathematical models, Si, Sir, SEIR, SEIRD, are used to scientifically reveal the transmission link and future development trend of novel coronavirus; At the same time, through mathematical analysis, the necessity of the above new crown epidemic prevention measures is explained in detail.

The Multi-discourse Fight of COVID-19 Vaccine in the World of Digital Platforms: Rethinking Popularity of Anti-intellectualism

Abstract This study explored how government institutions used digital platforms to enhance knowledge and share scientific information regarding the development and distribution of COVID-19 vaccines by drawing samples from official Twitter accounts in five different countries that were front-runners in vaccine manufacturing. Through content analysis, we selected a total of 243 tweets with 4,678 comments from the five Twitter accounts, and data were categorized into two sets for analysis, the first stage being to assign sentiment scores to all the collected comments from tweets to determine their positivity, negativity, and neutrality. Secondly, we analyzed themes derived from comments and established through the themes that geopolitics has exacerbated the anti-intellectualist logic of viewing science as impractical for the control and prevention of the pandemic leading to the domination of irrational thinking towards vaccine efficacy, the origin of COVID-19, and the undermining of the global health governance on COVID-19 control and management.

Difference in Rumor Dissemination and Debunking Before and After the Relaxation of COVID-19 Prevention and Control Measures in China: Infodemiology Study.

The information epidemic emerged along with the COVID-19 pandemic. While controlling the spread of COVID-19, the secondary harm of epidemic rumors to social order cannot be ignored. The objective of this paper was to understand the characteristics of rumor dissemination before and after the pandemic and the corresponding rumor management and debunking mechanisms. This study aimed to provide a theoretical basis and effective methods for relevant departments to establish a sound mechanism for managing network rumors related to public health emergencies such as COVID-19. This study collected data sets of epidemic rumors before and after the relaxation of the epidemic prevention and control measures, focusing on large-scale network rumors. Starting from 3 dimensions of rumor content construction, rumor propagation, and rumor-refuting response, the epidemic rumors were subdivided into 7 categories, namely, involved subjects, communication content, emotional expression, communication channels, communication forms, rumor-refuting subjects, and verification sources. Based on this framework, content coding and statistical analysis of epidemic rumors were carried out. The study found that the rumor information was primarily directed at a clear target audience. The main themes of rumor dissemination were related to the public's immediate interests in the COVID-19 field, with significant differences in emotional expression and mostly negative emotions. Rumors mostly spread through social media interactions, community dissemination, and circle dissemination, with text content as the main form, but they lack factual evidence. The preferences of debunking subjects showed differences, and the frequent occurrence of rumors reflected the unsmooth channels of debunking. The χ2 test of data before and after the pandemic showed that the P value was less than .05, indicating that the difference in rumor content before and after the pandemic had statistical significance. This study's results showed that the themes of rumors during the pandemic are closely related to the immediate interests of the public, and the emotions of the public accelerate the spread of these rumors, which are mostly disseminated through social networks. Therefore, to more effectively prevent and control the spread of rumors during the pandemic and to enhance the capability to respond to public health crises, relevant authorities should strengthen communication with the public, conduct emotional risk assessments, and establish a joint mechanism for debunking rumors.

Changing risk factors for developing SARS-CoV-2 infection from Delta to Omicron.

One of the few studies to estimate infection risk with SARS-CoV-2 in the general population was the UK Office of National Statistics Infection Survey. This survey provided data that allowed us to describe and interpret apparent risk factors for testing positive for SARS-CoV-2 in a period when variants and COVID-19 controls experienced large changes. The ONS published estimates of likelihood of individuals testing positive in two week monitoring periods between 21st November 2021 and 7th May 2022, relating this positivity to social and behavioural factors. We applied meta-regression to these estimates of likelihood of testing positive to determine whether the monitored potential risk factors remained constant during the pandemic. Some risk factors had consistent relationship with risk of infection (always protective or always linked to higher risk, throughout monitoring period). Other risk factors had variable relationship with risk of infection, with changes seeming to especially correlate with the emergence of Omicron BA.2 dominance. These variable factors were mask-wearing habits, history of foreign travel, household size, working status (retired or not) and contact with children or persons age over 70. Relevance of some risk factors to likelihood of testing positive for SARS-CoV-2 may relate to reinfection risk, variant infectiousness and status of social distancing regulations.

Public attitudes toward COVID-19 prevention and control in China.

Based on the data of the Chinese General Social Survey (CGSS) in 2021, this study aims to investigate the public attitudes toward COVID-19 prevention and control in China. The household survey CGSS 2021 contains 8,148 valid samples gathered from 320 communities across 19 provinces in China. The logistic regression model is adopted to examine the relationship between public attitudes and influencing factors. The results show that the vast majority of respondents firmly believe that the government has the authority to implement strict measures; their confidence in the government and in the healthcare system has increased; and they willingly choose to be vaccinated. The regression results suggest that gender, age, health condition, political affiliation, source of information, sense of fairness, socio-economic status, and place of residence are significantly associated with individuals' attitudes toward COVID-19 prevention and control. These findings highlight the importance for the government to design epidemic or pandemic policies based on data and to tailor them toward specific demographics.

Optimal control analysis of COVID-19 stochastic model with comprehensive strategies

In this paper, we construct a stochastic SVEAIR (Susceptible-Vaccinated-Exposed -Asymptomatic-Infected-Removed) epidemic model. It aimed to investigate COVID-19 control strategies through four different control methods, which consist of prophylaxis, vaccination control, rapid screening of people in exposure categories, and people identified as infected without screening. Firstly, we study the optimal control model and obtain the optimal control strategy using stochastic control theory. Secondly, the optimal control model with control term or without control term is numerically analyzed by using the implicit Runge-Kutta approximation method. At last, The numerical simulations verify the theoretical results and it show that control could help reduce infection and improve population health.

Small fibre neuropathy frequently underlies the painful long-COVID syndrome

Abstract Approximately 10% to 20% of individuals with previous SARS-CoV-2 infection may develop long-COVID syndrome, characterized by various physical and mental health issues, including pain. Previous studies suggested an association between small fibre neuropathy and pain in long-COVID cases. In this case–control study, our aim was to identify small fibre neuropathy in patients experiencing painful long-COVID syndrome. Clinical data, quantitative sensory testing, and skin biopsies were collected from 26 selected patients with painful long-COVID syndrome. We also examined 100 individuals with past COVID-19 infection, selecting 33 patients with painless long-COVID syndrome, characterized mainly by symptoms such as brain fog and fatigue, and 30 asymptomatic post–COVID-19 controls. Demographic and clinical variables were compared among these groups. Among the 26 patients with painful long-COVID syndrome, 12 had skin biopsy and/or quantitative sensory testing abnormalities compatible with small fibre neuropathy. Demographic and clinical data did not differ across patients with small fibre neuropathy, patients with painless long-COVID syndrome, and asymptomatic post–COVID-19 controls. This case–control study showed that approximately 50% of patients experiencing painful long-COVID syndrome had small fibre neuropathy. However, in our patient cohort, this specific post–COVID-19 complication was unrelated to demographic and COVID-19 clinical variables. Approximately half of our sample of patients with painful long-COVID symptoms met diagnostic criteria for small fibre neuropathy.

Estimating disease transmission in a closed population under repeated testing

Abstract The article presents a novel statistical framework for COVID-19 transmission monitoring and control, which was developed and deployed at The Ohio State University main campus in Columbus during the Autumn term of 2020. Our approach effectively handles prevalence data with interval censoring and explicitly incorporates changes in transmission dynamics and human behaviour. To illustrate the methodology’s usefulness, we apply it to both synthetic and actual student SARS-CoV-2 testing data collected at the OSU Columbus campus in late 2020.

Assessment of the liver with two-dimensional shear wave elastography following COVID-19 infection: A pilot study.

The coronavirus disease (COVID-19) is a widely spread viral infectious disease, which can impact multiple organs, including the liver. Elevated liver enzymes have been reported in COVID-19 patients; however, potential changes in liver stiffness following the viral infection remain uncertain. The main aim of this pilot study was to determine if there is a significant difference in liver stiffness between individuals who have never been infected with COVID-19 and those who had been infected with COVID-19 <6 months, experiencing only mild symptoms. The secondary aim was to compare the liver stiffness between participants infected with COVID-19 depending on the elapsed time since infection. Two-dimensional shear wave elastography (2D-SWE) was performed prospectively on 68 participants. Thirty-four participants had been infected with COVID-19 (all for <6 months) (COVID-19 group), and another 34 had never been infected with COVID-19 (control group). The mean 2D-SWE measurements of both the COVID-19 group and the control group werecompared using an independent t-test. The mean 2D-SWE measurements of the COVID-19 subgroups A (<2 months), B (2 to <4 months) and C (4 to <6 months) were compared using a one-way ANOVA test (P < 0.05). The (mean ± standard deviation) liver stiffness (kPa) of the COVID-19 group (5.26 ± 1.63 kPa) was significantly higher than the control group (4.30 ± 0.96 kPa) (P = 0.005). There was no significant difference in liver stiffness among subgroups A (5.20 ± 1.79 kPa), B (4.70 ± 1.53 kPa) and C (5.96 ± 1.48 kPa) (P = 0.143) respectively. The mean liver stiffness of 4.30 ± 0.96k Pa in the control group showed a high probability of being normal as per guidelines. Conversely, the mean liver stiffness of 5.26 ± 1.63 kPa in the COVID-19 group exhibited a statistically significant increase compared to the control group. However, compensated advanced chronic liver disease was ruled out without other known clinical signs, as per guidelines. A statistically significant increase in liver stiffness value was observed in the post-COVID-19 infection groupcompared to the group who had never been infected. This highlights the potential for short-term impact on liver stiffness associated with COVID-19 infection. However, it is unclear if these changes in liver stiffness are associated with liver injury. Further study is warranted to investigate the effects of COVID-19 infection and its long-term impact on the liver.