Modelling herd immunity requirements in Queensland: impact of vaccination effectiveness, hesitancy and variants of SARS-CoV-2.
Modelling herd immunity requirements in Queensland: impact of vaccination effectiveness, hesitancy and variants of SARS-CoV-2.
复制标题
建模昆士兰州的牛群免疫要求:SARS-COV-2的疫苗接种有效性,犹豫和变体的影响。
DOI:
10.1098/rsta.2021.0311
复制
发表时间:
2022-10-03
期刊:
影响因子:
5
通讯作者:
Roberts, James A.
中科院分区:
文献类型:
--
作者:
Sanz-Leon, Paula;Hamilton, Lachlan H. W.;Raison, Sebastian J.;Pan, Anna J. X.;Stevenson, Nathan J.;Stuart, Robyn M.;Abeysuriya, Romesh G.;Kerr, Cliff C.;Lambert, Stephen B.;Roberts, James A.
关键词:
Long-term control of SARS-CoV-2 outbreaks depends on the widespread coverage of effective vaccines. In Australia, two-dose vaccination coverage of above 90% of the adult population was achieved. However, between August 2020 and August 2021, hesitancy fluctuated dramatically. This raised the question of whether settings with low naturally derived immunity, such as Queensland where less than of the population is known to have been infected in 2020, could have achieved herd immunity against 2021’s variants of concern. To address this question, we used the agent-based model Covasim. We simulated outbreak scenarios (with the Alpha, Delta and Omicron variants) and assumed ongoing interventions (testing, tracing, isolation and quarantine). We modelled vaccination using two approaches with different levels of realism. Hesitancy was modelled using Australian survey data. We found that with a vaccine effectiveness against infection of 80%, it was possible to control outbreaks of Alpha, but not Delta or Omicron. With 90% effectiveness, Delta outbreaks may have been preventable, but not Omicron outbreaks. We also estimated that a decrease in hesitancy from 20% to 14% reduced the number of infections, hospitalizations and deaths by over 30%. Overall, we demonstrate that while herd immunity may not be attainable, modest reductions in hesitancy and increases in vaccine uptake may greatly improve health outcomes. This article is part of the theme issue ‘Technical challenges of modelling real-life epidemics and examples of overcoming these’.
登录
查看更多内容
影响因子:
2
作者:
Gomes MGM;Ferreira MU;Corder RM;King JG;Souto-Maior C;Penha-Gonçalves C;Gonçalves G;Chikina M;Pegden W;Aguas R
通讯作者:
Aguas R
影响因子:
82.9
作者:
Giordano G;Colaneri M;Di Filippo A;Blanchini F;Bolzern P;De Nicolao G;Sacchi P;Colaneri P;Bruno R
通讯作者:
Bruno R
影响因子:
56.9
作者:
Britton, Tom;Ball, Frank;Trapman, Pieter
通讯作者:
Trapman, Pieter
影响因子:
5.2
作者:
Chang SL;Cliff OM;Zachreson C;Prokopenko M
通讯作者:
Prokopenko M
DOI:
10.1056/nejmoa2035389
发表时间:
2021-02-04
期刊:
The New England journal of medicine
影响因子:
--
作者:
Baden LR;El Sahly HM;Essink B;Kotloff K;Frey S;Novak R;Diemert D;Spector SA;Rouphael N;Creech CB;McGettigan J;Khetan S;Segall N;Solis J;Brosz A;Fierro C;Schwartz H;Neuzil K;Corey L;Gilbert P;Janes H;Follmann D;Marovich M;Mascola J;Polakowski L;Ledgerwood J;Graham BS;Bennett H;Pajon R;Knightly C;Leav B;Deng W;Zhou H;Han S;Ivarsson M;Miller J;Zaks T;COVE Study Group
通讯作者:
COVE Study Group