Immunological characteristics govern the transition of COVID-19 to endemicity
Open accessPublished version of a preprint
Abstract
Taming a pandemic: One year after its emergence, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become so widespread that there is little hope of elimination. There are, however, several other human coronaviruses that are endemic and cause multiple reinfections that engender sufficient immunity to protect against severe adult disease. By making assumptions about acquired immunity from its already endemic relatives, Lavine et al. developed a model with which to analyze the trajectory of SARS-CoV-2 into endemicity. The model accounts for SARS-CoV-2's age-structured disease profile and assesses the impact of vaccination. The transition from epidemic to endemic dynamics is associated with a shift in the age distribution of primary infections to younger age groups, which in turn depends on how fast the virus spreads. Longer-lasting sterilizing immunity will slow the transition to endemicity. Depending on the type of immune response it engenders, a vaccine could accelerate establishment of a state of mild disease endemicity. Science , this issue p. 741
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If immunity is insufficient to block viral replication, ongoing transmission is expected to reboost immune responses, leading to a long-term equilibrium of transmission and immune boosting.
“If immunity is insufficient to block viral replication, then any ongoing transmission is expected to reboost immune responses, leading to a long-term equilibrium of transmission and immune boosting82.”
From Prospects for durable immune control of SARS-CoV-2 and prevention of reinfection (2021) · cites this paper as [82]
When immunity falls below the level needed to block infection yet still guards against severe disease, and when post-reinfection viral loads suffice for spread, endemic transmission might boost memory and keep protection up.
“Immunity may drop below the threshold required to prevent infection but still provide sufficient protection against severe illness. If viral levels after reinfection are high enough to enable transmission, the endemic spread of infection may boost memory responses to maintain immunity at protective levels82.”
From Prospects for durable immune control of SARS-CoV-2 and prevention of reinfection (2021) · cites this paper as [82]
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Cites
Structural basis for the recognition of SARS-CoV-2 by full-length human ACE2
Yan, R., Zhang, Y., Li, Y., Xia, L., Guo, Y., & Zhou, Q. (2020) · Science · doi:10.1126/science.abb2762 · Cited by 4,950 · see citing works
Voysey, M., Clemens, S. A. C., Madhi, S. A., Weckx, L. Y., Folegatti, P. M., Aley, P. K., Angus, B., Baillie, V. L., Barnabas, S. L., Bhorat, Q. E., et al. (2021) · The Lancet · doi:10.1016/s0140-6736(20)32661-1 · Cited by 4,616 · see citing works
Temporal dynamics in viral shedding and transmissibility of COVID-19
He, X., Lau, E. H. Y., Wu, P., Deng, X., Wang, J., Hao, X., Lau, Y. C., Wong, J. Y., Guan, Y., Tan, X., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-0869-5 · Cited by 4,242 · see citing works
Estimates of the severity of coronavirus disease 2019: a model-based analysis
Verity, R., Okell, L. C., Dorigatti, I., Winskill, P., Whittaker, C., Imai, N., Cuomo-Dannenburg, G., Thompson, H., Walker, P. G. T., Fu, H., et al. (2020) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(20)30243-7 · Cited by 3,660 · see citing works
A crucial role of angiotensin converting enzyme 2 (ACE2) in SARS coronavirus–induced lung injury
Kuba, K., Imai, Y., Rao, S., Gao, H., Guo, F., Guan, B., Huan, Y., Yang, P., Zhang, Y., Deng, W., et al. (2005) · Nature Medicine · doi:10.1038/nm1267 · Cited by 3,445 · see citing works
Epidemiology, Genetic Recombination, and Pathogenesis of Coronaviruses
Su, S., Wong, G., Shi, W., Liu, J., Lai, A. C.-K., Zhou, J., Liu, W., Bi, Y., & Gao, G. F. (2016) · Trends in Microbiology · doi:10.1016/j.tim.2016.03.003 · Cited by 2,956 · see citing works
Projecting the transmission dynamics of SARS-CoV-2 through the postpandemic period
Kissler, S. M., Tedijanto, C., Goldstein, E., Grad, Y. H., & Lipsitch, M. (2020) · Science · doi:10.1126/science.abb5793 · Cited by 2,611 · see citing works
Angiotensin-converting enzyme 2 protects from severe acute lung failure
Imai, Y., Kuba, K., Rao, S., Huan, Y., Guo, F., Guan, B., Yang, P., Sarao, R., Wada, T., Leong-Poi, H., et al. (2005) · Nature · doi:10.1038/nature03712 · Cited by 2,453 · see citing works
Structure and function of immunoglobulins
Schroeder, H. W., & Cavacini, L. A. (2010) · Journal of Allergy and Clinical Immunology · doi:10.1016/j.jaci.2009.09.046 · Cited by 1,923 · see citing works
SARS-CoV-2-specific T cell immunity in cases of COVID-19 and SARS, and uninfected controls
Le Bert, N., Tan, A. T., Kunasegaran, K., Tham, C. Y. L., Hafezi, M., Chia, A., Chng, M. H. Y., Lin, M., Tan, N., Linster, M., et al. (2020) · Nature · doi:10.1038/s41586-020-2550-z · Cited by 1,887 · see citing works
High Contagiousness and Rapid Spread of Severe Acute Respiratory Syndrome Coronavirus 2
Sanche, S., Lin, Y. T., Xu, C., Romero-Severson, E., Hengartner, N., & Ke, R. (2020) · Emerging Infectious Diseases · doi:10.3201/eid2607.200282 · Cited by 1,619 · see citing works
Factors that make an infectious disease outbreak controllable
Fraser, C., Riley, S., Anderson, R. M., & Ferguson, N. M. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0307506101 · Cited by 1,144 · see citing works
Herd Immunity: Understanding COVID-19
Randolph, H. E., & Barreiro, L. B. (2020) · Immunity · doi:10.1016/j.immuni.2020.04.012 · Cited by 1,138 · see citing works
Changes in contact patterns shape the dynamics of the COVID-19 outbreak in China
Zhang, J., Litvinova, M., Liang, Y., Wang, Y., Wang, W., Zhao, S., Wu, Q., Merler, S., Viboud, C., Vespignani, A., et al. (2020) · Science · doi:10.1126/science.abb8001 · Cited by 1,107 · see citing works
Huang, A. T., Garcia-Carreras, B., Hitchings, M. D. T., Yang, B., Katzelnick, L. C., Rattigan, S. M., Borgert, B. A., Moreno, C. A., Solomon, B. D., Trimmer-Smith, L., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-18450-4 · Cited by 1,026 · see citing works
Human Coronavirus: Host-Pathogen Interaction
Fung, T. S., & Liu, D. X. (2019) · Annual Review of Microbiology · doi:10.1146/annurev-micro-020518-115759 · Cited by 964 · see citing works
Seasonal coronavirus protective immunity is short-lasting
Edridge, A. W. D., Kaczorowska, J., Hoste, A. C. R., Bakker, M., Klein, M., Loens, K., Jebbink, M. F., Matser, A., Kinsella, C. M., Rueda, P., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-1083-1 · Cited by 767 · see citing works
Wallinga, J., Teunis, P. F. M., & Kretzschmar, M. (2006) · American Journal of Epidemiology · doi:10.1093/aje/kwj317 · Cited by 702 · see citing works
Chan‐Yeung, M., & Xu, R. (2003) · Respirology · doi:10.1046/j.1440-1843.2003.00518.x · Cited by 639 · see citing works
The time course of the immune response to experimental coronavirus infection of man
Callow, K. A., Parry, H. F., Sergeant, M., & Tyrrell, D. A. J. (1990) · Epidemiology and Infection · doi:10.1017/s0950268800048019 · Cited by 598 · see citing works
Weisberg, S. P., Connors, T. J., Zhu, Y., Baldwin, M. R., Lin, W.-H. W., Wontakal, S. N., Szabo, P. A., Wells, S. B., Dogra, P., Gray, J. I., et al. (2020) · Nature Immunology · doi:10.1038/s41590-020-00826-9 · Cited by 540 · see citing works
Tang, F., Quan, Y., Xin, Z.-T., Wrammert, J., Ma, M.-J., Lv, H., Wang, T.-B., Yang, H., Richardus, J. H., Liu, W., et al. (2011) · The Journal of Immunology · doi:10.4049/jimmunol.0903490 · Cited by 496 · see citing works
Duration of Antibody Responses after Severe Acute Respiratory Syndrome
Wu, L.-P., Wang, N.-C., Chang, Y.-H., Tian, X.-Y., Na, D.-Y., Zhang, L.-Y., Zheng, L., Lan, T., Wang, L.-F., & Liang, G.-D. (2007) · Emerging Infectious Diseases · doi:10.3201/eid1310.070576 · Cited by 426 · see citing works
Channappanavar, R., Fett, C., Zhao, J., Meyerholz, D. K., & Perlman, S. (2014) · Journal of Virology · doi:10.1128/jvi.01505-14 · Cited by 411 · see citing works
Design and Analysis of Vaccine Studies
Halloran, M. E., Longini, I. M., & Struchiner, C. J. (2009) · Statistics for biology and health · doi:10.1007/978-0-387-68636-3 · Cited by 332 · see citing works
Effects of a "new" human respiratory virus in volunteers.
Bradburne, A. F., Bynoe, M. L., & Tyrrell, D. A. J. (1967) · BMJ · doi:10.1136/bmj.3.5568.767 · Cited by 304 · see citing works
Immune life history, vaccination, and the dynamics of SARS-CoV-2 over the next 5 years
Saad-Roy, C. M., Wagner, C. E., Baker, R. E., Morris, S. E., Farrar, J., Graham, A. L., Levin, S. A., Mina, M. J., Metcalf, C. J. E., & Grenfell, B. T. (2020) · Science · doi:10.1126/science.abd7343 · Cited by 278 · see citing works
A human coronavirus evolves antigenically to escape antibody immunity
Eguia, R., Crawford, K. H. D., Stevens-Ayers, T., Kelnhofer-Millevolte, L., Greninger, A. L., Englund, J. A., Boeckh, M. J., & Bloom, J. D. (2020) · doi:10.1101/2020.12.17.423313 · Cited by 258 · see citing works
Likelihood of survival of coronavirus disease 2019
Ruan, S. (2020) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(20)30257-7 · Cited by 232 · see citing works
Modeling shield immunity to reduce COVID-19 epidemic spread
Weitz, J. S., Beckett, S. J., Coenen, A. R., Demory, D., Dominguez-Mirazo, M., Dushoff, J. G., Leung, C. Y., Li, G., Măgălie, A., Park, S. W., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-0895-3 · Cited by 232 · see citing works
Abu-Raddad, L. J., Chemaitelly, H. S., Malek, J. A., Ahmed, A. A., Mohamoud, Y. A., Younuskunju, S., Ayoub, H. H., Kanaani, Z. A., Al‐Khal, A., Al‐Kuwari, E., et al. (2020) · Clinical Infectious Diseases · doi:10.1093/cid/ciaa1846 · Cited by 176 · see citing works
Modeling infectious disease dynamics
Cobey, S. E. (2020) · Science · doi:10.1126/science.abb5659 · Cited by 163 · see citing works
Patrick, D. M., Petric, M., Skowronski, D. M., Guasparini, R., Booth, T. F., Krajden, M., McGeer, P. L., Bastien, N., Gustafson, L., Dubord, J., et al. (2006) · Canadian Journal of Infectious Diseases and Medical Microbiology · doi:10.1155/2006/152612 · Cited by 152 · see citing works
Direct Observation of Repeated Infections With Endemic Coronaviruses
Galanti, M., & Shaman, J. (2021) · The Journal of Infectious Diseases · doi:10.1093/infdis/jiaa392 · Cited by 149 · see citing works
Zhou, W., Wang, W., Wang, H., Lu, R., & Tan, W. (2013) · BMC Infectious Diseases · doi:10.1186/1471-2334-13-433 · Cited by 124 · see citing works
Heterogeneity and longevity of antibody memory to viruses and vaccines
Antia, A., Ahmed, H., Handel, A., Carlson, N. E., Amanna, I. J., Antia, R., & Slifka, M. (2018) · PLOS Biology · doi:10.1371/journal.pbio.2006601 · Cited by 123 · see citing works
Self-citationA Catalytic Model of Infection for Measles
Griffiths, D. (1974) · Journal of the Royal Statistical Society Series C (Applied Statistics) · doi:10.2307/2347126 · Cited by 107 · see citing works
Salamatbakhsh, M., Mobaraki, K., Sadeghimohammadi, S., et al. (2019) · BMC Public Health · doi:10.1186/s12889-019-7899-2 · Cited by 29 · see citing works
JennieLavine/covid-immunity-endemicity: First release of covid-immunity-endemicity
JennieLavine (2020) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.4390505 · Cited by 1 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- [40]National Center for Health Statistics, Mortality in the United States, 2018; www.cdc.gov/nchs/data/databriefs/db355_tables-508.pdf#page=3%202018%20data. 31944640
Cited by
Sorted by citations
Markov, P. V., Ghafari, M., Beer, M., Lythgoe, K., Simmonds, P., Stilianakis, N. I., & Katzourakis, A. (2023) · Nature Reviews Microbiology · doi:10.1038/s41579-023-00878-2 · Cited by 1,179 · see citing works
Cohen, K. W., Linderman, S. L., Moodie, Z., Czartoski, J., Lai, L., Mantus, G., Norwood, C., Nyhoff, L. E., Edara, V. V., Floyd, K., et al. (2021) · Cell Reports Medicine · doi:10.1016/j.xcrm.2021.100354 · Cited by 441 · see citing works
Self-citationProspects for durable immune control of SARS-CoV-2 and prevention of reinfection
Cromer, D., Juno, J. A., Khoury, D., Reynaldi, A., Wheatley, A. K., Kent, S. J., & Davenport, M. P. (2021) · Nature Reviews Immunology · doi:10.1038/s41577-021-00550-x · Cited by 265 · see citing works
Characterizing the spatiotemporal heterogeneity of the COVID-19 vaccination landscape
Tiu, A., Susswein, Z., Merritt, A., & Bansal, S. (2021) · doi:10.1101/2021.10.04.21263345 · Cited by 37 · see citing works
- Authors
- Lavine, J. S., Bjornstad, O. N., & Antia, R.
- Affiliations
- Emory University (US)
- Department of Biology and Center for Infectious Disease Dynamics, The Pennsylvania State University, University Park, PA 16802, USA.
- Corresponding author
- Lavine, Jennie S.
- Venue
- Science
- Published
- 2021-02-12
- Volume
- 371
- Issue
- 6530
- Pages
- 741-745
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC7932103
- OpenAlex
- W3119411150
- Cited by
- 416
- References
- 40
- Citations by year
- 2026: 9 · 2025: 29 · 2024: 62 · 2023: 62 · 2022: 99 · 2021: 155
- FWCI
- 29.93
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Science (publishedVersion, cc-by)
- medRxiv (acceptedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Informationszentrum Lebenswissenschaften (ZB MED) (submittedVersion, cc-by)
- Funders
- NIH Office of the Director (U01AI150747, U01 HL139483, U01 AI144616)
- Topics
- Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
- Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
- Health Sciences › Medicine › Infectious Diseases › Viral Infections and Outbreaks Research
- Keywords
- SARS-CoV-2, COVID-19 pandemic, endemicity, waning immunity, human coronaviruses, common cold, disease severity, vaccine rollout, vaccination strategies, mathematical model
- MeSH terms
- Reinfection, COVID-19, SARS-CoV-2, COVID-19 Vaccines, Adolescent, Adult, Antibodies, Viral, Child, Child, Preschool, Humans, Immunoglobulin G, Immunoglobulin M, Infant, Severity of Illness Index, Seroepidemiologic Studies, Age Distribution, Coronavirus, Coronavirus Infections, Endemic Diseases, Communicable Diseases, Emerging, Severe Acute Respiratory Syndrome, Adaptive Immunity, Epidemics
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