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Understanding the Necessity and Economic Benefits of Lockdown Measures to Contain COVID-19
IEEE Transactions on Computational Social Systems ; : 1-13, 2022.
Article in English | Scopus | ID: covidwho-1992675
ABSTRACT
Since the outbreak of the coronavirus disease 2019 (COVID-19), the issue of how to maintain economic development while containing the epidemic has become a significant concern for decision-makers. Though lockdown measures are verified to be very effective in containing the epidemic, its economic costs and other influences have not been fully explored. As a result, decision-makers in many countries are still hesitant to include the lockdown measure in an intervention strategy in response to COVID-19. To address this issue, we propose a universal computational experiment approach for policy evaluation and adjustment based on the Artificial societies, Computational experiments, Parallel execution (ACP) concept. First, we innovatively construct a model via observable CO<inline-formula> <tex-math notation="LaTeX">$_2$</tex-math> </inline-formula> emissions, which is able to estimate the economic costs affected by nonpharmaceutical interventions. Furthermore, based on the population movement data, a risk source model is proposed to estimate the local transmission risk for any prefectures outside the epicenter. Finally, we integrate the data models in a high-resolution agent-based artificial society and carry out large-scale computational experiments supported by the Tianhe supercomputer. Policy adjustments and evaluations are carried out in four cities Wenzhou, Guangzhou, Beijing, and Wuhan. Our research findings show important implications for policy-making 1) the local transmission of a city can be almost contained if lockdowns are adopted immediately when the risk index is larger than 1.645, 1.960, or 2.576 at the 90%, 95%, or 99% confidence interval, respectively;2) if lockdowns are required, in-advance lockdown measures facilitate mitigation efficacy and reduce economic loss;and 3) lockdowns lasting for 7–14 days in a prefecture would be effective in controlling the spread of the epidemic. The duration of the measure should be prolonged with the increment of the initial transmission risk. IEEE
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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: IEEE Transactions on Computational Social Systems Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: IEEE Transactions on Computational Social Systems Year: 2022 Document Type: Article