Can Koreans be 'FREE' from mask wearing?: Advanced mathematical model can suggest the idea (preprint)

Background: It was found that 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. Discussions about easing the indoor mask mandate are ongoing. 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. Findings We found that the peak size of administered severe patients might not exceed 1,100 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 did not exceed 650. Moreover, if the new variant have both of higher transmissibility and immune reduction therefore the effective reproductive number of the new variant is approximately 3 times higher than the current variant, additional interventions may be needed to keep the administered severe patients from exceeding 2,000, which is the critical level we set. Interpretation Our findings showed that the lifting of the mask mandate, except in hospitals, would be applicable more manageable if it is 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.

Multi-faceted analysis of COVID-19 epidemic in the Republic of Korea considering Omicron variant: Mathematical modeling-based study (preprint)

Background The most recent variant of concern, Omicron (B.1.1.529), has caused numerous cases worldwide including the Republic of Korea due to its fast transmission and reduced vaccine effectiveness. Methods A mathematical model considering age-structure, vaccine, antiviral treatment, and influx of the Omicron variant was developed. We estimated transmission rates among age groups using maximum likelihood estimation for the age-structured model. The impact of nonpharmaceutical interventions (in community and border), quantified by a parameter μ in the force of infection, and vaccination were examined through a multi-faceted analysis. A theory-based endemic equilibrium study was performed to find the manageable number of cases according to Omicron-and healthcare-related factors. Results By fitting the model to the available data, the estimated values of μ ranged from 0.31 to 0.73, representing the intensity of nonpharmaceutical interventions such as social distancing level. If μ < 0.55 and 300,000 booster shots were administered daily from February 3, 2022, the number of severe cases was forecasted to exceed the severe bed capacity. Moreover, the number of daily cases is reduced as the timing of screening measures is delayed. If screening measure was intensified as early as November 24, 2021 and the number of overseas entrant cases was contained to 1 case per 10 days, simulations showed that the daily incidence by February 3, 2022 could have been reduced by 87%. Furthermore, we found that the incidence number in mid-December 2021 exceeded the theory-driven manageable number of daily cases. Conclusion Nonpharmaceutical interventions, vaccination, and antiviral therapy influence the spread of Omicron and number of severe cases in the Republic of Korea. Intensive and early screening measures during the emergence of a new variant is key in controlling the epidemic size. Using the endemic equilibrium of the model, a formula for the manageable daily cases depending on the severity rate and average length of hospital stay was derived so that the number of severe cases does not surpass the severe bed capacity.

Optimal Selection of COVID-19 Vaccination Sites at the Municipal Level (preprint)

ABSTRACT In this work, we present an approach to determine the optimal location of coronavirus disease (COVID-19) vaccination sites at the municipal level. We assume that each municipality or town is subdivided into smaller administrative units, which we refer to as villages or barangays. The proposed method solves a minimization problem arising from a facility location problem, which is formulated based on the proximity of the vaccination sites to the villages, number of COVID-19 cases, and population densities of the villages. We present a numerical scheme to solve the optimization problem and give a detailed description of the algorithm, which is coded in Python. To make the results reproducible, the codes used in this study are uploaded to a public repository, which also contains complete instructions on how to use them. As an illustration, we apply our method in determining the optimal location of vaccination sites in San Juan, a town in the province of Batangas, in the Philippines. We hope that this study may guide the local government units in coming up with strategic plans for the COVID-19 vaccine rollout.