In the face of the new coronavirus, why must we insist on dynamic zero-COVID?

Recently, the famous journal Nature Medicine published online a study by Professor Yu Hongjie's team from the School of Public Health of Fudan University.

The study modeled the COVID-19 epidemic in my country and pointed out that if the dynamic zero-clearing policy is cancelled, there may be 111.22 million infections and 1.55 million deaths, and the demand for ICUs will be 15.6 times the existing beds.

In the face of a COVID-19 pandemic that has caused huge losses and deaths, how can we formulate policies to avoid the consequences of the collapse of the medical system? Let’s talk about this today.

01. Omicron epidemic simulation

Researchers developed a model for the 2022 Omicron outbreak in Shanghai.

The model uses SLIRS, which stands for susceptible-latent-infectious-removed-susceptible.

The model is then used to estimate the medical burden of the COVID-19 pandemic, such as the number of people who get sick, the number of people who need hospitalization, the number of people in intensive care, and the number of deaths.

The model also takes into account age-specific vaccine coverage data, vaccine efficacy against different clinical endpoints, waning immunity, different antiviral therapies and non-drug interventions.

02. Simulation results

The model first simulated the short-term epidemic in Shanghai.

As shown in the figure above, the blue line is the reported number of infections and cases, while the orange line is the number predicted by the model. Overall, the fit is pretty good.

Next, a model prediction result

The following figure is a forecast result from March to September, with non-ICU patients on the left and ICU patients on the right. Including epidemiological conditions, age distribution, etc., according to the forecast, there will be 112.2 million infections, 5.1 million hospitalizations, 2.7 million ICU admissions, and 1.6 million deaths.

By age group, the situation in different regions is divided into the whole country and Shanghai, Shanxi and Shandong as examples. It can be seen that the elderly in different regions will be the hardest hit areas, especially the blue ones represent people over 60 years old. The ICU demand will reach 6.58-15.74 per thousand people, and the death rate will also be between 3.78-9377 per thousand people.

ICU is an important strategy for responding to the new coronavirus, especially for those with respiratory disorders and other people who urgently need treatment. It is predicted that 1 million ICU beds will be needed to cope with the peak of respiratory diseases. However, there are only about 64,000 ICU beds in my country at present, which means that the demand for ICUs is about 15.6 times the existing ICUs.

This shortage period will last 44 days.

Vaccination can effectively relieve the symptoms of COVID-19, so if the vaccine is injected, this situation will be alleviated.

Therefore, China's expected healthcare needs and number of deaths between March and September 2022 will vary under different vaccination rates.

If vaccination is ideal (including booster shots), it will reduce hospitalization rates by 33.8%, ICU rates by 54.1%, and mortality by 60.8%.

03. Conclusion

Conclusion: If the dynamic zero-clearing policy is abandoned, 5.1 million people will be hospitalized, 2.7 million people will be admitted to the ICU, and 1.55 million people will die in the six months from March to September.

For people over 60 years old, if they are not vaccinated, they may be the main group of deaths.

Note: Yu Hongjie, male, professor and doctoral supervisor at the School of Public Health, Fudan University, director of the Key Laboratory of Public Health Safety of the Ministry of Education, Fudan University, and vice president of the Shanghai Institute of Major Infectious Diseases and Biosafety. He is a recipient of the National Outstanding Young Scientist Fund, a leading talent in scientific and technological innovation of the "Ten Thousand Talents Plan" of the Organization Department of the CPC Central Committee, and a highly cited scientist in 2020 by Clarivate Analytics.

ref.

Cai, J., Deng, X., Yang, J. et al. Modeling transmission of SARS-CoV-2 Omicron in China. Nat Med (2022). https://doi.org/10.1038/s41591-022-01855-7