학술행사
- 발표자 심은하 교수 (숭실대학교)
- 개최일시 2022-05-26 14:00-16:00
1. 일시: 2022년 5월 26일(목), 14:00-16:00
2. 장소: 산업수학혁신센터 세미나실, 줌 화상 회의로 진행(비대면)
3. 발표자: 심은하 교수 (숭실대학교)
4. 주요내용: Computational model of COVID-19 transmission and control strategies
To control the transmission of coronavirus disease (COVID-19), numerous countries have implemented social distancing and testing policies with contact tracing as a measure to flatten the curve of the ongoing pandemic. Optimizing these control measures is urgent given the substantial societal and economic impacts associated with infection and interventions. To determine the optimal social distancing and testing strategies, we developed a mathematical model of COVID-19 transmission and applied optimal control theory, identifying the best approach to reduce the epidemiological burden of COVID-19 at a minimal cost. The results demonstrate that testing as a standalone optimal strategy does not have a significant effect on the final size of an epidemic, but it would delay the peak of the pandemic. If social distancing is the sole control strategy, it would be optimal to gradually increase the level of social distancing as the incidence curve of COVID- 19 grows, and relax the measures after the curve has reached its peak. Furthermore , our results show that testing should be maintained at a maximum level in the early phases and after the peak of the epidemic, whereas social distancing should be intensified when the prevalence of the disease is greater than 15%. Accordingly, public health agencies should implement early testing and switch to social distancing when the incidence level begins to increase. After the peak of the pandemic, it would be optimal to gradually relax social distancing and switch back to testing.
1. 일시: 2022년 5월 26일(목), 14:00-16:00
2. 장소: 산업수학혁신센터 세미나실, 줌 화상 회의로 진행(비대면)
3. 발표자: 심은하 교수 (숭실대학교)
4. 주요내용: Computational model of COVID-19 transmission and control strategies
To control the transmission of coronavirus disease (COVID-19), numerous countries have implemented social distancing and testing policies with contact tracing as a measure to flatten the curve of the ongoing pandemic. Optimizing these control measures is urgent given the substantial societal and economic impacts associated with infection and interventions. To determine the optimal social distancing and testing strategies, we developed a mathematical model of COVID-19 transmission and applied optimal control theory, identifying the best approach to reduce the epidemiological burden of COVID-19 at a minimal cost. The results demonstrate that testing as a standalone optimal strategy does not have a significant effect on the final size of an epidemic, but it would delay the peak of the pandemic. If social distancing is the sole control strategy, it would be optimal to gradually increase the level of social distancing as the incidence curve of COVID- 19 grows, and relax the measures after the curve has reached its peak. Furthermore , our results show that testing should be maintained at a maximum level in the early phases and after the peak of the epidemic, whereas social distancing should be intensified when the prevalence of the disease is greater than 15%. Accordingly, public health agencies should implement early testing and switch to social distancing when the incidence level begins to increase. After the peak of the pandemic, it would be optimal to gradually relax social distancing and switch back to testing.
