The DOI matches its Crossref record; 63 of the 63 references it cites were found in a registry or an index.
Modeling transmission of SARS-CoV-2 Omicron in China
Open accessAbstract
Having adopted a dynamic zero-COVID strategy to respond to SARS-CoV-2 variants with higher transmissibility since August 2021, China is now considering whether, and for how long, this policy can remain in place. The debate has thus shifted towards the identification of mitigation strategies for minimizing disruption to the healthcare system in the case of a nationwide epidemic. To this aim, we developed an age-structured stochastic compartmental susceptible-latent-infectious-removed-susceptible model of SARS-CoV-2 transmission calibrated on the initial growth phase for the 2022 Omicron outbreak in Shanghai, to project COVID-19 burden (that is, number of cases, patients requiring hospitalization and intensive care, and deaths) under hypothetical mitigation scenarios. The model also considers age-specific vaccine coverage data, vaccine efficacy against different clinical endpoints, waning of immunity, different antiviral therapies and nonpharmaceutical interventions. We find that the level of immunity induced by the March 2022 vaccination campaign would be insufficient to prevent an Omicron wave that would result in exceeding critical care capacity with a projected intensive care unit peak demand of 15.6 times the existing capacity and causing approximately 1.55 million deaths. However, we also estimate that protecting vulnerable individuals by ensuring accessibility to vaccines and antiviral therapies, and maintaining implementation of nonpharmaceutical interventions could be sufficient to prevent overwhelming the healthcare system, suggesting that these factors should be points of emphasis in future mitigation policies.
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Clinical characteristics of coronavirus disease 2019 in China
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Self-citationImmunological memory to SARS-CoV-2 assessed for up to 8 months after infection.
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Age-dependent effects in the transmission and control of COVID-19 epidemics
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Waning Immune Humoral Response to BNT162b2 Covid-19 Vaccine over 6 Months
Levin, E. G., Lustig, Y., Cohen, C., Fluss, R., Indenbaum, V., Amit, S., Doolman, R., Asraf, K., Mendelson, E., Ziv, A., et al. (2021) · New England Journal of Medicine · doi:10.1056/nejmoa2114583 · Cited by 1,703
Rapid epidemic expansion of the SARS-CoV-2 Omicron variant in southern Africa
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Self-citationBroadly neutralizing antibodies overcome SARS-CoV-2 Omicron antigenic shift
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Cited by
SARS-CoV-2 IgG seropositivity after the severe Omicron wave of COVID-19 in Hong Kong
Poon, R. W.-S., Chan, B. P.-C., Chan, W.-M., Fong, C. H.-Y., Zhang, X., Lu, L., Chen, L.-L., Lam, J.-Y., Cheng, V. C.-C., Wong, S. S. Y., et al. (2022) · Emerging Microbes & Infections · doi:10.1080/22221751.2022.2106899 · Cited by 20
Metadata
- Authors
- Cai, J., Deng, X., Yang, J., Sun, K., Liu, H., Chen, Z., Peng, C., Chen, X., Wu, Q., Zou, J., Sun, R., Zheng, W., Zhao, Z., Lu, W., Liang, Y., Zhou, X., Ajelli, M., & Yu, H.
- Venue
- Nature Medicine
- Published
- 2022-05-10
- Volume
- 28
- Issue
- 7
- Pages
- 1468-1475
- ISSN
- 1078-8956 (ISSN-L)
- 1546-170X
- OpenAlex
- W4280581045
- Cited by
- 281
- References
- 63
- FWCI
- 39.01
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Cai, J., Deng, X., Yang, J., Sun, K., Liu, H., Chen, Z., Peng, C., Chen, X., Wu, Q., Zou, J., Sun, R., Zheng, W., Zhao, Z., Lu, W., Liang, Y., Zhou, X., Ajelli, M., & Yu, H. (2022). Modeling transmission of SARS-CoV-2 Omicron in China. Nature Medicine. https://doi.org/10.1038/s41591-022-01855-7
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