vaccination
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A Mathematical Model Shows High Viral Transmissions Reduce the Progression Rates for Severe Covid-19
The model suggests a clue as to when a pandemic will turn into an endemic
A mathematical model demonstrated that high transmission rates among highly vaccinated populations of COVID-19 ultimately reduce the numbers of severe cases. This model suggests a clue as to when this pandemic will turn into an endemic.
With the future of the pandemic remaining uncertain, a research team of mathematicians and medical scientists analyzed a mathematical model that may predict how the changing transmission rate of COVID-19 would affect the settlement process of the virus as a mild respiratory virus.
The team led by Professor Jae Kyoung Kim from the Department of Mathematical Science and Professor Eui-Cheol Shin from the Graduate School of Medical Science and Engineering used a new approach by dividing the human immune responses to SARS-CoV-2 into a shorter-term neutralizing antibody response and a longer-term T-cell immune response, and applying them each to a mathematical model. Additionally, the analysis was based on the fact that although breakthrough infection may occur frequently, the immune response of the patient will be boosted after recovery from each breakthrough infection.
The results showed that in an environment with a high vaccination rate, although COVID-19 cases may rise temporarily when the transmission rate increases, the ratio of critical cases would ultimately decline, thereby decreasing the total number of critical cases and in fact settling COVID-19 as a mild respiratory disease more quickly.
Conditions in which the number of cases may spike include relaxing social distancing measures or the rise of variants with higher transmission rates like the Omicron variant. This research did not take the less virulent characteristic of the Omicron variant into account but focused on the results of its high transmission rate, thereby predicting what may happen in the process of the endemic transition of COVID-19.
The research team pointed out the limitations of their mathematical model, such as the lack of consideration for age or patients with underlying diseases, and explained that the results of this study must be applied with care when compared against high-risk groups. Additionally, as medical systems may collapse when the number of cases rises sharply, this study must be interpreted with prudence and applied accordingly. The research team therefore emphasized that for policies that encourage a step-wise return to normality to succeed, the sustainable maintenance of public health systems is indispensable.
Professor Kim said, “We have drawn a counter-intuitive conclusion amid the unpredictable pandemic through an adequate mathematical model,” asserting the importance of applying mathematical models to medical research.
Professor Shin said, “Although the Omicron variant has become the dominant strain and the number of cases is rising rapidly in South Korea, it is important to use scientific approaches to predict the future and apply them to policies rather than fearing the current situation.”
The results of the research were published on medRxiv.org on February 11, under the title “Increasing viral transmission paradoxically reduces progression rates to severe COVID-19 during endemic transition.”
This research was funded by the Institute of Basic Science, the Korea Health Industry Development Institute, and the National Research Foundation of Korea.
-PublicationHyukpyo Hong, Ji Yun Noh, Hyojung Lee, Sunhwa Choi, Boseung Choi, Jae Kyung Kim, Eui-Cheol Shin, “Increasing viral transmission paradoxically reduces progression rates to
severe COVID-19 during endemic transition,” medRxiv, February 9, 2022 (doi.org/10.1101/2022.02.09.22270633)
-ProfileProfessor Jae Kyung KimDepartment of Mathematical SciencesKAIST
Professor Eui-Cheol ShinGraduate School of Medical Science and EngineeringKAIST
2022.02.22 View 7740 -
Professor Ko Kyu Young Appointed as a Distinguished Professor at KAIST
Professor Ko Kyu Young of the Graduate School of Medical Sciences was appointed as the Distinguished Professor at KAIST.
Professor Ko is famous internationally for his work on the catalyst for blood vessel growth COMP-ANG1, and also for his research on blood vessel growth and lymph duct growth control.
Professor Ko developed the Double Anti-Angiogenic Protein (DAAP) which effectively restricts the blood vessels from growing, opening a new approach to curing caner. The paper was published in ‘Cancer Cell’ as the cover paper (2010 August 17th edition) and is widely recognized as the marker that sums up the new paradigm of cure for cancer.
In addition, his work on explaining how the new antigen interacts with the T-lymphocyte during a vaccination lead to the possibility of the increase of the efficiency of vaccination. The result of the research was published as the cover paper in ‘Immunity’ magazine.
As is obvious to see his work with blood vessel growth and lymph duct growth and control is being published in major scientific journals. In addition he is continuously invited to international conferences as guest speakers and leader, effectively leading the field. As a result, he was appointed as the editor of ‘Blood’ magazine, the world’s best journal in the field of hematology and received ‘2010 KAISTian of the Year’ Award.
The title Distinguished Professor is appointed to those who have made world-class research results and educational results and actively lead their respective field. They are provided with extra incentives and can even continue on with the professorship after retirement.
It is only limited to 3% of the professors at KAIST and has to be someone recommended by the President, Vice-President, and the Deans of department and their worthiness is scrutinized by a foreign expert.
2011.03.25 View 10382