Publicação
Individual variation in susceptibility or exposure to SARS-CoV-2 lowers the herd immunity threshold
| Resumo: | Individual variation in susceptibility and exposure is subject to selection by natural infection, accelerating the acquisition of immunity, and reducing herd immunity thresholds and epidemic final sizes. This is a manifestation of a wider population phenomenon known as “frailty variation”. Despite theoretical understanding, public health policies continue to be guided by mathematical models that leave out considerable variation and as a result inflate projected disease burdens and overestimate the impact of interventions. Here we focus on trajectories of the coronavirus disease (COVID-19) pandemic in England and Scotland until November 2021. We fit models to series of daily deaths and infer relevant epidemiological parameters, including coefficients of variation and effects of non-pharmaceutical interventions which we find in agreement with independent empirical estimates based on contact surveys. Our estimates are robust to whether the analysed data series encompass one or two pandemic waves and enable projections compatible with subsequent dynamics. We conclude that vaccination programmes may have contributed modestly to the acquisition of herd immunity in populations with high levels of pre-existing naturally acquired immunity, while being crucial to protect vulnerable individuals from severe outcomes as the virus becomes endemic. |
|---|---|
| Autores principais: | Gomes, M. Gabriela M. |
| Outros Autores: | Ferreira, Marcelo Urbano; Corder, Rodrigo M.; King, Jessica G.; Souto-Maior, Caetano; Penha-Gonçalves, Carlos; Gonçalves, Guilherme; Chikina, Maria; Pegden, Wesley; Aguas, Ricardo |
| Assunto: | COVID-19 Epidemic model Frailty variation Herd immunity threshold Individual variation Selection within cohorts Statistics and Probability Modelling and Simulation General Biochemistry,Genetics and Molecular Biology General Immunology and Microbiology General Agricultural and Biological Sciences Applied Mathematics SDG 3 - Good Health and Well-being |
| Ano: | 2022 |
| País: | Portugal |
| Tipo de documento: | artigo |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade Nova de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório Institucional da UNL |
| _version_ | 1868982785057751040 |
|---|---|
| author | Gomes, M. Gabriela M. |
| author2 | Ferreira, Marcelo Urbano Corder, Rodrigo M. King, Jessica G. Souto-Maior, Caetano Penha-Gonçalves, Carlos Gonçalves, Guilherme Chikina, Maria Pegden, Wesley Aguas, Ricardo |
| author2_role | author author author author author author author author author |
| author_facet | Gomes, M. Gabriela M. Ferreira, Marcelo Urbano Corder, Rodrigo M. King, Jessica G. Souto-Maior, Caetano Penha-Gonçalves, Carlos Gonçalves, Guilherme Chikina, Maria Pegden, Wesley Aguas, Ricardo |
| author_role | author |
| contributor_name_str_mv | CMA - Centro de Matemática e Aplicações Individual Health Care (IHC) Global Health and Tropical Medicine (GHTM) Instituto de Higiene e Medicina Tropical (IHMT) Elsevier Science B.V., Amsterdam. RUN |
| country_str | PT |
| creators_json_txt | [{\"Person.name\":\"Gomes, M. Gabriela M.\"},{\"Person.name\":\"Ferreira, Marcelo Urbano\"},{\"Person.name\":\"Corder, Rodrigo M.\"},{\"Person.name\":\"King, Jessica G.\"},{\"Person.name\":\"Souto-Maior, Caetano\"},{\"Person.name\":\"Penha-Gonçalves, Carlos\"},{\"Person.name\":\"Gonçalves, Guilherme\"},{\"Person.name\":\"Chikina, Maria\"},{\"Person.name\":\"Pegden, Wesley\"},{\"Person.name\":\"Aguas, Ricardo\"}] |
| datacite.contributors.contributor.contributorName.fl_str_mv | CMA - Centro de Matemática e Aplicações Individual Health Care (IHC) Global Health and Tropical Medicine (GHTM) Instituto de Higiene e Medicina Tropical (IHMT) Elsevier Science B.V., Amsterdam. RUN |
| datacite.creators.creator.creatorName.fl_str_mv | Gomes, M. Gabriela M. Ferreira, Marcelo Urbano Corder, Rodrigo M. King, Jessica G. Souto-Maior, Caetano Penha-Gonçalves, Carlos Gonçalves, Guilherme Chikina, Maria Pegden, Wesley Aguas, Ricardo |
| datacite.date.Accepted.fl_str_mv | 2022-05-07T00:00:00Z |
| datacite.date.available.fl_str_mv | 2022-09-14T22:21:49Z |
| datacite.date.embargoed.fl_str_mv | 2022-09-14T22:21:49Z |
| datacite.rights.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| datacite.subjects.subject.fl_str_mv | COVID-19 Epidemic model Frailty variation Herd immunity threshold Individual variation Selection within cohorts Statistics and Probability Modelling and Simulation General Biochemistry,Genetics and Molecular Biology General Immunology and Microbiology General Agricultural and Biological Sciences Applied Mathematics SDG 3 - Good Health and Well-being |
| datacite.titles.title.fl_str_mv | Individual variation in susceptibility or exposure to SARS-CoV-2 lowers the herd immunity threshold |
| dc.contributor.none.fl_str_mv | CMA - Centro de Matemática e Aplicações Individual Health Care (IHC) Global Health and Tropical Medicine (GHTM) Instituto de Higiene e Medicina Tropical (IHMT) Elsevier Science B.V., Amsterdam. RUN |
| dc.creator.none.fl_str_mv | Gomes, M. Gabriela M. Ferreira, Marcelo Urbano Corder, Rodrigo M. King, Jessica G. Souto-Maior, Caetano Penha-Gonçalves, Carlos Gonçalves, Guilherme Chikina, Maria Pegden, Wesley Aguas, Ricardo |
| dc.date.Accepted.fl_str_mv | 2022-05-07T00:00:00Z |
| dc.date.available.fl_str_mv | 2022-09-14T22:21:49Z |
| dc.date.embargoed.fl_str_mv | 2022-09-14T22:21:49Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | http://hdl.handle.net/10362/143733 |
| dc.language.none.fl_str_mv | eng |
| dc.rights.none.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| dc.subject.none.fl_str_mv | COVID-19 Epidemic model Frailty variation Herd immunity threshold Individual variation Selection within cohorts Statistics and Probability Modelling and Simulation General Biochemistry,Genetics and Molecular Biology General Immunology and Microbiology General Agricultural and Biological Sciences Applied Mathematics SDG 3 - Good Health and Well-being |
| dc.title.fl_str_mv | Individual variation in susceptibility or exposure to SARS-CoV-2 lowers the herd immunity threshold |
| dc.type.none.fl_str_mv | http://purl.org/coar/resource_type/c_6501 |
| description | Individual variation in susceptibility and exposure is subject to selection by natural infection, accelerating the acquisition of immunity, and reducing herd immunity thresholds and epidemic final sizes. This is a manifestation of a wider population phenomenon known as “frailty variation”. Despite theoretical understanding, public health policies continue to be guided by mathematical models that leave out considerable variation and as a result inflate projected disease burdens and overestimate the impact of interventions. Here we focus on trajectories of the coronavirus disease (COVID-19) pandemic in England and Scotland until November 2021. We fit models to series of daily deaths and infer relevant epidemiological parameters, including coefficients of variation and effects of non-pharmaceutical interventions which we find in agreement with independent empirical estimates based on contact surveys. Our estimates are robust to whether the analysed data series encompass one or two pandemic waves and enable projections compatible with subsequent dynamics. We conclude that vaccination programmes may have contributed modestly to the acquisition of herd immunity in populations with high levels of pre-existing naturally acquired immunity, while being crucial to protect vulnerable individuals from severe outcomes as the virus becomes endemic. |
| dirty | 0 |
| eu_rights_str_mv | openAccess |
| format | article |
| fulltext.url.fl_str_mv | https://run.unl.pt/bitstreams/1c851be2-4a69-47e4-b09c-9b722c60611d/download |
| id | run_2e4dfa5ea02fd3ea8cb0fe81064589db |
| identifier.url.fl_str_mv | http://hdl.handle.net/10362/143733 |
| inst_facet_str | urn:organizationAcronym:unl{{{_:::_}}}Universidade Nova de Lisboa |
| instacron_str | unl |
| institution | Universidade Nova de Lisboa |
| instname_str | Universidade Nova de Lisboa |
| language | eng |
| network_acronym_str | run |
| network_name_str | Repositório Institucional da UNL |
| oai_identifier_str | oai:run.unl.pt:10362/143733 |
| organization_str_mv | urn:organizationAcronym:unl |
| person_str_mv | Gomes, M. Gabriela M. Ferreira, Marcelo Urbano Corder, Rodrigo M. King, Jessica G. Souto-Maior, Caetano Penha-Gonçalves, Carlos Gonçalves, Guilherme Chikina, Maria Pegden, Wesley Aguas, Ricardo |
| publishDate | 2022 |
| repo_facet_str | urn:repositoryAcronym:run{{{_:::_}}}Repositório Institucional da UNL |
| reponame_str | Repositório Institucional da UNL |
| repository_id_str | urn:repositoryAcronym:run |
| service_str_mv | urn:repositoryAcronym:run |
| spelling | engenIndividual variation in susceptibility and exposure is subject to selection by natural infection, accelerating the acquisition of immunity, and reducing herd immunity thresholds and epidemic final sizes. This is a manifestation of a wider population phenomenon known as “frailty variation”. Despite theoretical understanding, public health policies continue to be guided by mathematical models that leave out considerable variation and as a result inflate projected disease burdens and overestimate the impact of interventions. Here we focus on trajectories of the coronavirus disease (COVID-19) pandemic in England and Scotland until November 2021. We fit models to series of daily deaths and infer relevant epidemiological parameters, including coefficients of variation and effects of non-pharmaceutical interventions which we find in agreement with independent empirical estimates based on contact surveys. Our estimates are robust to whether the analysed data series encompass one or two pandemic waves and enable projections compatible with subsequent dynamics. We conclude that vaccination programmes may have contributed modestly to the acquisition of herd immunity in populations with high levels of pre-existing naturally acquired immunity, while being crucial to protect vulnerable individuals from severe outcomes as the virus becomes endemic.application/pdfenIndividual variation in susceptibility or exposure to SARS-CoV-2 lowers the herd immunity thresholdGomes, M. Gabriela M.Ferreira, Marcelo UrbanoCorder, Rodrigo M.King, Jessica G.Souto-Maior, CaetanoPenha-Gonçalves, CarlosGonçalves, GuilhermeChikina, MariaPegden, WesleyAguas, RicardoCMA - Centro de Matemática e AplicaçõesIndividual Health Care (IHC)Global Health and Tropical Medicine (GHTM)Instituto de Higiene e Medicina Tropical (IHMT)Elsevier Science B.V., Amsterdam.HostingInstitutionOrganizationalRUNe-mailmailto:run@unl.ptrun@unl.ptISSNIsPartOf0022-5193URNIsPartOfPURE: 46297383URNIsPartOfPURE UUID: 8e4eb7bf-0f3e-4775-a2f5-901a507e3b9aURNIsPartOfScopus: 85125527948URNIsPartOfPubMed: 35189135URNIsPartOfPubMedCentral: PMC8855661URNIsPartOfWOS: 000774219500004URNIsPartOfORCID: /0000-0002-5293-9090/work/119032013DOIIsPartOf10.1016/j.jtbi.2022.1110632022-09-14T22:21:49Z2022-05-072022-05-07T00:00:00ZHandlehttp://hdl.handle.net/10362/143733http://purl.org/coar/access_right/c_abf2open accessCOVID-19Epidemic modelFrailty variationHerd immunity thresholdIndividual variationSelection within cohortsStatistics and ProbabilityModelling and SimulationGeneral Biochemistry,Genetics and Molecular BiologyGeneral Immunology and MicrobiologyGeneral Agricultural and Biological SciencesApplied MathematicsSDG 3 - Good Health and Well-being4908733 bytesliteraturehttp://purl.org/coar/resource_type/c_6501journal articlehttp://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://run.unl.pt/bitstreams/1c851be2-4a69-47e4-b09c-9b722c60611d/download |
| spellingShingle | Individual variation in susceptibility or exposure to SARS-CoV-2 lowers the herd immunity threshold Gomes, M. Gabriela M. COVID-19 Epidemic model Frailty variation Herd immunity threshold Individual variation Selection within cohorts Statistics and Probability Modelling and Simulation General Biochemistry,Genetics and Molecular Biology General Immunology and Microbiology General Agricultural and Biological Sciences Applied Mathematics SDG 3 - Good Health and Well-being |
| status | SINGLETON |
| subject.fl_str_mv | COVID-19 Epidemic model Frailty variation Herd immunity threshold Individual variation Selection within cohorts Statistics and Probability Modelling and Simulation General Biochemistry,Genetics and Molecular Biology General Immunology and Microbiology General Agricultural and Biological Sciences Applied Mathematics SDG 3 - Good Health and Well-being |
| title | Individual variation in susceptibility or exposure to SARS-CoV-2 lowers the herd immunity threshold |
| title_full | Individual variation in susceptibility or exposure to SARS-CoV-2 lowers the herd immunity threshold |
| title_fullStr | Individual variation in susceptibility or exposure to SARS-CoV-2 lowers the herd immunity threshold |
| title_full_unstemmed | Individual variation in susceptibility or exposure to SARS-CoV-2 lowers the herd immunity threshold |
| title_short | Individual variation in susceptibility or exposure to SARS-CoV-2 lowers the herd immunity threshold |
| title_sort | Individual variation in susceptibility or exposure to SARS-CoV-2 lowers the herd immunity threshold |
| topic | COVID-19 Epidemic model Frailty variation Herd immunity threshold Individual variation Selection within cohorts Statistics and Probability Modelling and Simulation General Biochemistry,Genetics and Molecular Biology General Immunology and Microbiology General Agricultural and Biological Sciences Applied Mathematics SDG 3 - Good Health and Well-being |
| topic_facet | COVID-19 Epidemic model Frailty variation Herd immunity threshold Individual variation Selection within cohorts Statistics and Probability Modelling and Simulation General Biochemistry,Genetics and Molecular Biology General Immunology and Microbiology General Agricultural and Biological Sciences Applied Mathematics SDG 3 - Good Health and Well-being |
| url | http://hdl.handle.net/10362/143733 |
| visible | 1 |