Multi-Faceted Analysis of COVID-19 Epidemic in Korea Considering Omicron Variant: Mathematical Modeling-Based Study

Social contact patterns in South Korea: an analysis of a survey conducted in 2023-2024

BACKGROUND

Understanding social contact patterns is fundamental to the study of infectious disease transmission. However, in South Korea, detailed social contact data have not been publicly available. While global research on social contact patterns has expanded, there remains a critical need for more context-specific data in South Korea.

METHODS

We conducted a social contact survey over two distinct weeks covering various time periods, including school vacations and national holidays. Participants provided details such as the location, duration, frequency, and type of close contact, as well as information on the contact person's age, sex, residential area and relationship with the participant. We analyzed the data using summary statistics and the Bayesian linear mixed model.

RESULTS

A total of 1,987 participants recorded 133,776 contacts over two weeks, averaging 4.81 contacts per participant per day. The average number of contacts per day varied by age, household size, and time period. Contacts were highest in the age group 5-19, lowest in the age group 20-29, and then gradually increased up to the age group 70+. Contacts also increased with household size. Weekdays during the school semester showed the highest number of contacts, followed by weekdays during vacations, the Lunar New Year holidays, and weekends. Contact patterns differed notably by period; during the Lunar New Year holidays, closed contacts with extended family members and, therefore, subnational social mixing were enhanced.

CONCLUSION

Our analyses across different time periods revealed significant and some unique variations of social contact patterns in South Korea. These findings can improve our understanding of infectious disease transmission in South Korea and will be useful for tailoring regional epidemiological models.

Risk of Severe Acute Respiratory Syndrome Coronavirus 2 Transmission in Seoul, Korea

BACKGROUND

The risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission during the endemic phase may vary from that during the previous pandemic phase. We evaluated the risk of infection in a general population with laboratory-confirmed coronavirus disease 2019 (COVID-19) in a community setting in Korea.

MATERIALS AND METHODS

This study included 1,286 individuals who had been in contact with an index COVID-19 case between January 24, 2020, and June 30, 2022. Variables such as age, sex, nationality, place of contact, level of contact, the status of exposed cases, period, and level of mask-wearing were assessed.

RESULTS

Among 1,286 participants, 132 (10.30%) were confirmed to have COVID-19. With increasing age, the risk of the exposed persons contracting COVID-19 from index cases tended to increase (P <0.001), especially for people in their 70s (odds ratio, 1.24; 95% confidence interval, 1.11-1.40; P <0.001). We found an increasing trend in the risk of a COVID-19 exposed case becoming a secondary infection case (P <0.001) in long-term care facilities where the attack rate was high.

CONCLUSION

The risk of COVID-19 transmission is high in long-term care facilities where many older adults reside. Intensive management of facilities at risk of infection and strict mask-wearing of confirmed COVID-19 cases are necessary to prevent the risk of COVID-19 infection.

Cost-effectiveness analysis of COVID-19 variants effects in an age-structured model

This study analyzes the impact of COVID-19 variants on cost-effectiveness across age groups, considering vaccination efforts and nonpharmaceutical interventions in Republic of Korea. We aim to assess the costs needed to reduce COVID-19 cases and deaths using age-structured model. The proposed age-structured model analyzes COVID-19 transmission dynamics, evaluates vaccination effectiveness, and assesses the impact of the Delta and Omicron variants. The model is fitted using data from the Republic of Korea between February 2021 and November 2022. The cost-effectiveness of interventions, medical costs, and the cost of death for different age groups are evaluated through analysis. The impact of different variants on cases and deaths is also analyzed, with the Omicron variant increasing transmission rates and decreasing case-fatality rates compared to the Delta variant. The cost of interventions and deaths is higher for older age groups during both outbreaks, with the Omicron outbreak resulting in a higher overall cost due to increased medical costs and interventions. This analysis shows that the daily cost per person for both the Delta and Omicron variants falls within a similar range of approximately $10-$35. This highlights the importance of conducting cost-effect analyses when evaluating the impact of COVID-19 variants.

Risk estimation of lifted mask mandates and emerging variants using mathematical model

Background

More than half of the population in Korea had a prior COVID-19 infection. In 2022, most nonpharmaceutical interventions, except mask-wearing indoors, had been lifted. And in 2023, the indoor mask mandates were eased.

Methods

We developed an age-structured compartmental model that distinguishes vaccination history, prior infection, and medical staff from the rest of the population. Contact patterns among hosts were separated based on age and location. We simulated scenarios with the lifting of the mask mandate all at once or sequentially according to the locations. Furthermore, we investigated the impact of a new variant assuming that it has higher transmissibility and risk of breakthrough infection.

Results

We found that the peak size of administered severe patients may not exceed 1100 when the mask mandate is lifted everywhere, and 800 if the mask mandate only remains in the hospital. If the mask mandate is lifted in a sequence (except hospital), then the peak size of administered severe patients may not exceed 650. Moreover, if the new variant has both higher transmissibility and immune reduction, the effective reproductive number of the new variant is approximately 3 times higher than that of the current variant, and additional interventions may be needed to keep the administered severe patients from exceeding 2,000, which is the critical level we set.

Conclusion

Our findings showed that the lifting of the mask mandate, except in hospitals, would be more manageable if implemented sequentially. Considering a new variant, we found that depending on the population immunity and transmissibility of the variant, wearing masks and other interventions may be necessary for controlling the disease.

Mathematical Modeling of SARS-CoV-2 Omicron Wave under Vaccination Effects

Over the course of the COVID-19 pandemic millions of deaths and hospitalizations have been reported. Different SARS-CoV-2 variants of concern have been recognized during this pandemic and some of these variants of concern have caused uncertainty and changes in the dynamics. The Omicron variant has caused a large amount of infected cases in the US and worldwide. The average number of deaths during the Omicron wave toll increased in comparison with previous SARS-CoV-2 waves. We studied the Omicron wave by using a highly nonlinear mathematical model for the COVID-19 pandemic. The novel model includes individuals who are vaccinated and asymptomatic, which influences the dynamics of SARS-CoV-2. Moreover, the model considers the waning of the immunity and efficacy of the vaccine against the Omicron strain. This study uses the facts that the Omicron strain has a higher transmissibility than the previous circulating SARS-CoV-2 strain but is less deadly. Preliminary studies have found that Omicron has a lower case fatality rate compared to previous circulating SARS-CoV-2 strains. The simulation results show that even if the Omicron strain is less deadly it might cause more deaths, hospitalizations and infections. We provide a variety of scenarios that help to obtain insight about the Omicron wave and its consequences. The proposed mathematical model, in conjunction with the simulations, provides an explanation for a large Omicron wave under various conditions related to vaccines and transmissibility. These results provide an awareness that new SARS-CoV-2 variants can cause more deaths even if their fatality rate is lower.

Modelling the end of a Zero-COVID strategy using nirmatrelvir/ritonavir, vaccination and NPIs in Wallis and Futuna

Background

Ending Zero-COVID is challenging, particularly when vaccine coverage is low. Considering Wallis and Futuna, a French Zero-COVID territory affected by reluctance to vaccination, low immunity and high levels of comorbidities, we investigate how targeted use of nirmatrelvir/ritonavir (brand name Paxlovid) can complement vaccination and non-pharmaceutical interventions (NPIs), and mitigate the epidemic rebound expected when Zero-COVID ends.

Methods

We developed a discrete age-stratified compartmental model describing SARS-CoV-2 spread and healthcare impact once Wallis and Futuna reopens. It accounts for comorbidity risk groups (CRG), vaccine coverage (2 doses, 3 doses), the effectiveness of vaccines (recent or old injection), treatments and NPIs. In our baseline scenario, cases aged 65+ in intermediate/high CRG and 40+ in high CRG are eligible for treatment.

Findings

The epidemic is expected to start 13-20 days after reopening with a doubling time of 1.6-3.7 days. For medium transmission intensity (R0 = 5), 134 (115-156) hospital admissions are expected within 3 months, with no pharmaceutical measures. In our baseline scenario, admissions are reduced by 11%-21% if 50% of the target group receive treatment, with maximum impact when combined with NPIs and vaccination. The number of hospitalisations averted (HA) per patient treated (PT) is maximum when 65+ in high CRG are targeted (0.124 HA/PT), quickly followed by 65+ in intermediate/high CRG (0.097 HA/PT), and any 65+ (0.093 HA/PT). Expanding the target group increases both PT and HA, but marginal gains diminish.

Interpretation

Modelling suggests that test and treat may contribute to the mitigation of epidemic rebounds at the end of Zero-COVID, particularly in populations with low immunity and high levels of comorbidities.

Funding

RECOVER, VEO, AXA, Groupama, SpF, IBEID, INCEPTION, EMERGEN.

Mathematical Modeling of COVID-19 Transmission and Intervention in South Korea: A Review of Literature

South Korea implemented interventions to curb the spread of the novel coronavirus disease 2019 (COVID-19) pandemic with discovery of the first case in early 2020. Mathematical modeling designed to reflect the dynamics of disease transmission has been shown to be an important tool for responding to COVID-19. This study aimed to review publications on the structure, method, and role of mathematical models focusing on COVID-19 transmission dynamics in Korea. In total, 42 papers published between August 7, 2020 and August 21, 2022 were studied and reviewed. This study highlights the construction and utilization of mathematical models to help craft strategies for predicting the course of an epidemic and evaluating the effectiveness of control strategies. Despite the limitations caused by a lack of available epidemiological and surveillance data, modeling studies could contribute to providing scientific evidence for policymaking by simulating various scenarios.

Fractal-fractional age-structure study of omicron SARS-CoV-2 variant transmission dynamics

This paper proposes a new fractal-fractional age-structure model for the omicron SARS-CoV-2 variant under the Caputo-Fabrizio fractional order derivative. Caputo-Fabrizio fractal-fractional order is particularly successful in modelling real-world phenomena due to its repeated memory effect and ability to capture the exponentially decreasing impact of disease transmission dynamics. We consider two age groups, the first of which has a population under 50 and the second of a population beyond 50. Our results show that at a population dynamics level, there is a high infection and recovery of omicron SARS-CoV-2 variant infection among the population under 50 (Group-1), while a high infection rate and low recovery of omicron SARS-CoV-2 variant infection among the population beyond 50 (Group-2) when the fractal-fractional order is varied.