Mathematical model of SARS-CoV-2 transmission tailored to the unique situation of China

In a recent study posted to the Research Square* preprint server, researchers designed a dynamic mathematical model to simulate the transmission of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant in China and project its associated burden on healthcare facilities, should the zero-coronavirus disease 2019 (COVID-19) policy be lifted.

Study: Projecting the impact of the introduction of SARS-CoV-2 Omicron variant in China in the context of waning immunity after vaccination. Image Credit: Artreef/Shutterstock
Study: Projecting the impact of the introduction of SARS-CoV-2 Omicron variant in China in the context of waning immunity after vaccination. Image Credit: Artreef/Shutterstock

This news article was a review of a preliminary scientific report that had not undergone peer-review at the time of publication. Since its initial publication, the scientific report has now been peer reviewed and accepted for publication in a Scientific Journal. Links to the preliminary and peer-reviewed reports are available in the Sources section at the bottom of this article. View Sources

Background

The unprecedented impact of COVID-19 is mainly due to the constant emergence of multiple SARS-CoV-2 variants across the globe. The Omicron variant has recently outcompeted other variants and gained dominance due to its enhanced immune evasion and transmissibility properties. However, the severity of Omicron infection is reportedly lower than that of the other variants. 

China adopted the zero-COVID-19 dynamic policy in mid-2020 to transition from the pandemic to the endemic phase. However, the efficacy and durability of this policy are unknown. This warrants the need for other strategies to mitigate COVID-19.

About the study

In the present study, researchers developed a susceptible-latent-infectious-removed-susceptible (SLIRS) model to evaluate the SARS-CoV-2-infection burden, should an Omicron outbreak be let to unfold.

The baseline scenario assumed the following: 20 Omicron infections were imported on March 1, 2022; basic reproduction number (R0) was 7.2, and the generation time was 4.6 days without non-pharmaceutical infections (NPI); five million homologous inactivated vaccine booster doses were rolled out daily; 90% of individuals primary vaccinated at least six months prior would be booster vaccinated; good vaccine effectiveness (VE) / low Omicron immune escape scenario, without the use of antiviral drugs such as the homegrown BRII-196/BRII-198 monoclonal antibody or the imported Paxlovid drug.

The other scenarios considered the high and low Omicron immune escape, 10 million vaccines rollout with and without a subunit vaccine booster, 50% and 100% vaccine uptake in symptomatic cases with the use of 80% efficacy BRII-196/BRII-198 and 89% efficacy Paxlovid, respectively, epidemic seeding on June 1, 2022, and September 1, 2022, and NPIs such as school and/or workplace closure.

The age-specific Omicron infection fatality risk (IFR), hospitalization fatality risk (HFR), and risk of hospital admissions for symptomatic cases (CHR) were determined. In addition, a sensitivity analysis was performed considering longer generation times (6.4 days), five and 10 imported infection seeds, 65% less infectiousness in asymptomatic individuals, two-four-fold higher vaccine rollout, and heterologous vaccine boosters.

The impact of NPIs was assessed by delaying Omicron infection seeding time, implementing national school and/or workplace closures, and decreasing contacts equally across all ages.

Results

The model simulations showed that the present vaccination campaign would be unable to prevent mortality and overwhelming the healthcare facilities. Instead, a synergetic policy would be required based on heterologous boosters, managing 50% of symptomatic cases with BRII-196/BRII-198, and adopting NPIs that can decrease Rt to ≤2.

Omicron infections seeded in March 2022 could generate a COVID-19 “tsunami” without NPIs in China, which would lead to 476 million, 32 million, 7.9 million, and three million symptomatic cases, hospitalizations, intensive care units (ICU) admissions, and deaths, respectively. 

Most (89%) symptomatic infections would occur in vaccinated individuals aged 18-59 years (64%), whereas most deaths (37%) would occur in individuals aged above 60 years, and vaccinating them would decrease mortality by 17%.

About 11 million and four million hospital and ICU beds, respectively, were estimated to be required at the Omicron infection peak, which is 2.4-fold and 61-fold higher than the existing hospital and ICU bed capacities, respectively.

The ICU and hospital bed shortages would last for 50 and 14 days, respectively. Even if all the hospital beds were reserved for SARS-CoV-2 infections, a 1.4 million bed shortage would persist in China, considering the baseline scenario. Moreover, the outcomes would be 22-32% more severe in the high immune escape scenario.

Only scenarios considering 100% vaccine uptake in symptomatic cases with Paxlovid use and Rt values 1.5 and 2 could prevent hospital bed shortage during the Omicron peak. However, there would be a 12–28-day ICU bed shortage even in the best-case scenario.

Importantly, implementing stringent NPIs to reduce Rt to 1.5 could prevent this shortage until mid-August 2022 and reduce mortality to lower than that of influenza, after which ICU overload would occur in light of waning immunity over time.

Conclusion

Overall, the study results showed that Omicron infections would cause a significant upsurge in the healthcare burden. According to the findings, either stringent NPIs or ramped-up vaccination with heterologous boost and antiviral drug use with relaxed NPIs would be needed, especially for elders aged above 60 years, to decrease the Omicron burden and mortality rates in China.

This news article was a review of a preliminary scientific report that had not undergone peer-review at the time of publication. Since its initial publication, the scientific report has now been peer reviewed and accepted for publication in a Scientific Journal. Links to the preliminary and peer-reviewed reports are available in the Sources section at the bottom of this article. View Sources

Journal references:

Article Revisions

  • May 13 2023 - The preprint preliminary research paper that this article was based upon was accepted for publication in a peer-reviewed Scientific Journal. This article was edited accordingly to include a link to the final peer-reviewed paper, now shown in the sources section.
Pooja Toshniwal Paharia

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Pooja Toshniwal Paharia

Pooja Toshniwal Paharia is an oral and maxillofacial physician and radiologist based in Pune, India. Her academic background is in Oral Medicine and Radiology. She has extensive experience in research and evidence-based clinical-radiological diagnosis and management of oral lesions and conditions and associated maxillofacial disorders.

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