Background: The outbreak of the COVID-19 epidemic has caused an unprecedented public health crisis and drastically impacted the economy. The relationship between different control measures and economic losses becomes a research hotspot.
Methods: In this study, the SEIR infectious disease model was revised and coupled with an economic model to quantify this nonlinear relationship in Wuhan. The control measures were parameterized into two factors: the effective number of daily contacts (people) (); the average waiting time for quarantined patients (day) ().
Results: The parameter has a threshold value that if r is less than 5 (people), the number of COVID-19 infected patients is very close to 0. A "central valley" around = 5~6 can be observed, indicating an optimal control measure to reduce economic losses. A lower value of parameter g is beneficial to stop COVID-19 spread with a lower economic cost.
Conclusion: The simulation results demonstrate that implementing strict control measures as early as possible can stop the spread of COVID-19 with a minimal economic impact. The quantitative assessment method in this study can be applied in other COVID-19 pandemic areas or countries.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8621982 | PMC |
| http://dx.doi.org/10.3390/ijerph182211753 | DOI Listing |
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