{"doi":"10.1101/2021.08.26.21262579","title":"Population impact of SARS-CoV-2 variants with enhanced transmissibility and/or partial immune escape","abstract":"<jats:title>Summary</jats:title>\n                <jats:p>SARS-CoV-2 variants of concern exhibit varying degrees of transmissibility and, in some cases, escape from infection- and vaccine-induced immunity. Much effort has been devoted to measuring these phenotypes, but predicting their impact on the course of the pandemic – especially that of immune escape – remains a challenge. Here, we use a mathematical model to simulate the dynamics of wildtype and variant strains of SARS-CoV-2 in the context of vaccine rollout and nonpharmaceutical interventions. We show that variants with enhanced transmissibility easily rise to high frequency, whereas partial immune escape, on its own, often fails to do so. However, when these phenotypes are combined, enhanced transmissibility can carry the variant to high frequency, at which point partial immune escape may limit the ability of vaccination to control the epidemic. Our findings suggest that moderate immune escape poses a low risk unless combined with a substantial increase in transmissibility.</jats:p>","journal":null,"year":null,"id":628706,"datarank":0.29188652235829704,"base_score":1.9459101490553132,"endowment":1.9459101490553132,"self_citation_contribution":0.29188652235829704,"citation_network_contribution":0.0,"self_endowment_contribution":0.29188652235829704,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":6,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":109901,"name":"Rebecca Kahn","orcid":"0000-0001-9511-6142","position":1,"is_corresponding":false},{"id":669759,"name":"Bradford P. Taylor","orcid":"0000-0001-7808-955X","position":2,"is_corresponding":false},{"id":106022,"name":"Marc Lipsitch","orcid":"0000-0003-1504-9213","position":3,"is_corresponding":false},{"id":276821,"name":"William P. Hanage","orcid":"0000-0002-6319-7336","position":4,"is_corresponding":false},{"id":106018,"name":"Mary Bushman","orcid":"0000-0003-0933-5053","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Population impact of SARS-CoV-2 variants with enhanced transmissibility and/or partial immune escape","abstract":"<jats:title>Summary</jats:title>\n                <jats:p>SARS-CoV-2 variants of concern exhibit varying degrees of transmissibility and, in some cases, escape from infection- and vaccine-induced immunity. Much effort has been devoted to measuring these phenotypes, but predicting their impact on the course of the pandemic – especially that of immune escape – remains a challenge. Here, we use a mathematical model to simulate the dynamics of wildtype and variant strains of SARS-CoV-2 in the context of vaccine rollout and nonpharmaceutical interventions. We show that variants with enhanced transmissibility easily rise to high frequency, whereas partial immune escape, on its own, often fails to do so. However, when these phenotypes are combined, enhanced transmissibility can carry the variant to high frequency, at which point partial immune escape may limit the ability of vaccination to control the epidemic. Our findings suggest that moderate immune escape poses a low risk unless combined with a substantial increase in transmissibility.</jats:p>","is_dataset_classified":null,"base_score":1.9459101490553132,"endowment":1.9459101490553132,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"19910364","pmcid":null,"openalex_id":"https://openalex.org/W3214252701","authors":[],"funders":[{"funder_name":"National Institutes of Health","grant_id":"5R01AI128344-05","title":"Deep sequencing of pathogens to precisely define transmission networks using rare variants"},{"funder_name":"National Institutes of Health","grant_id":"1U01CA261277-01","title":"Casual, Statistical and Mathematical Modeling with Serologic Data"}],"total_grants":2,"fwci":null,"citation_percentile":null,"influential_citations":0,"citation_trend":[{"year":2021,"count":3},{"year":2022,"count":3}],"oa_status":"green","license":"cc-by-nc-nd","oa_locations":[{"url":"https://www.medrxiv.org/content/medrxiv/early/2021/08/29/2021.08.26.21262579.full.pdf","host_type":"repository"},{"url":"https://www.medrxiv.org/content/medrxiv/early/2021/08/29/2021.08.26.21262579.full.pdf","host_type":"repository"},{"url":"https://syndication.highwire.org/content/doi/10.1101/2021.08.26.21262579","host_type":"publisher"},{"url":"https://doi.org/10.1101/2021.08.26.21262579","host_type":"repository"},{"url":"https://europepmc.org/article/PPR/PPR388404","host_type":"Europe_PMC"},{"url":"https://europepmc.org/api/fulltextRepo?pprId=PPR388404&type=FILE&fileName=EMS134494-pdf.pdf&mimeType=application/pdf","host_type":"Europe_PMC"},{"url":"https://doi.org/10.1016/j.cell.2021.11.026","host_type":""},{"url":"http://www.cell.com/article/S009286742101374X/pdf","host_type":""},{"url":"https://doi.org/10.2139/ssrn.3924614","host_type":""},{"url":"https://pubmed.ncbi.nlm.nih.gov/34910927","host_type":""},{"url":"http://dx.doi.org/10.1016/j.cell.2021.11.026","host_type":""},{"url":"https://dx.doi.org/10.1016/j.cell.2021.11.026","host_type":""},{"url":"https://dx.doi.org/10.1101/2021.08.26.21262579","host_type":""},{"url":"https://dx.doi.org/10.2139/ssrn.3924614","host_type":""}],"fields_of_study":["SARS-CoV-2 and COVID-19 Research","COVID-19 epidemiological studies","Evolution and Genetic Dynamics","0303 health sciences","03 medical and health sciences"],"mesh_terms":[],"keywords":["Transmissibility (structural dynamics)","Immune system","Context (archaeology)","Immune escape","Population","Immunity","Biology","Phenotype","Pandemic","Immunology","Virology","Vaccination","Coronavirus disease 2019 (COVID-19)","Medicine","Disease","Genetics","Environmental health","Gene","Physics","SARS-CoV-2","Reinfection","COVID-19","Humans","Computer Simulation","Models, Biological","Article","Immune Evasion"],"sdg_mappings":[{"sdg_number":3,"sdg_label":"3. Good health"},{"sdg_number":0,"sdg_label":"Good health and well-being"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-05T14:43:30.318419Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}