Mathematical modelling of COVID-19 vaccination strategies in Kyrgyzstan
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Le résumé fourni par la source
Abstract Objectives In December 2020, an unprecedented vaccination programme to deal with the COVID-19 pandemic was initiated worldwide. However, the vaccine provision is currently insufficient for most countries to vaccinate their entire eligible population, so it is essential to develop the most efficient vaccination strategies. COVID-19 disease severity and mortality vary by age, therefore age-dependent vaccination strategies must be developed. Study design/Methods Here, we use an age-dependent SIERS (susceptible–infected–exposed–recovered–susceptible) deterministic model to compare four hypothetical age-dependent vaccination strategies and their potential impact on the COVID-19 epidemic in Kyrgyzstan. Results Over the short-term (until March 2022), a vaccination rollout strategy focussed on high-risk groups (aged >50 years) with some vaccination among high-incidence groups (aged 20–49 years) may decrease symptomatic cases and COVID-19-attributable deaths. However, there will be limited impact on the estimated overall number of COVID-19 cases with the relatively low coverage of high-incidence groups (15–25% based on current vaccine availability). Vaccination plus non-pharmaceutical interventions (NPIs), such as mask wearing and social distancing, will further decrease COVID-19 incidence and mortality and may have an indirect impact on all-cause mortality. Conclusions Our results and other evidence suggest that vaccination is most effective in flattening the epidemic curve and reducing mortality if supported by NPIs. In the short-term, focussing on high-risk groups may reduce the burden on the health system and result in fewer deaths. However, the herd effect from delaying another peak may only be achieved by greater vaccination coverage in high-incidence groups.
Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.
Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Mathematical modelling of COVID-19 vaccination strategies in Kyrgyzstan
- Date Crossref
- 30/12/2021
- Éditeur
- openRxiv
- Type
- posted-content
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Où se fait cette recherche
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University of Oxford Nuffield Department of Medicine pays non établi dans la noticeUniversité ou école supérieure
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Development Fund pays non établi dans la noticeOrganisation à but non lucratif
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Stavros Niarchos Foundation pays non établi dans la noticeOrganisation à but non lucratif
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Kyrgyz State Medical Academy pays non établi dans la noticeÉtablissement de santé
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International COVID-19 Modelling Consortium pays non établi dans la noticeInstitution
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Public Fund “Institution of Social Development” in the Kyrgyz Republic pays non établi dans la noticeStructure de recherche
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Public Fund "Institution of Social Development" in the Kyrgyz Republic pays non établi dans la noticeStructure de recherche
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Soros Foundation in the Kyrgyz Republic pays non établi dans la noticeOrganisation à but non lucratif
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Ministry of Health of the Kyrgyz Republic pays non établi dans la noticeOrganisme public
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Medical Association in the Kyrgyz Republic pays non établi dans la noticeOrganisation à but non lucratif
Nuffield Department of Medicine — University of Oxford, Development Fund et Stavros Niarchos Foundation, avec 7 autres affiliations.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.