Modelling the Effect of the Interaction between Vaccination and Nonpharmaceutical Measures on COVID-19 Incidence.

IF 1.1 Q4 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH Global Health Epidemiology and Genomics Pub Date : 2022-03-31 eCollection Date: 2022-01-01 DOI:10.1155/2022/9244953
Atsegine Canga, Gorka Bidegain
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Abstract

Since December 2019, the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread rapidly from Wuhan (China) across the globe, affecting more than 200 countries by mid-2021, with over 190 M reported cases and around 4 M fatalities. During the first year of the pandemic, affected countries implemented a variety of nonpharmaceutical interventions to control virus transmission. In December 2020, countries started administering several authorised vaccines under a limited supply scenario. In this context, the aim of this study was to develop a SEIR-type continuous-time deterministic disease model, to determine the impact of interaction between different vaccination scenarios and levels of protection measures on disease incidence. For this, the model incorporates (i) a protection measure including low (self-protection), medium (mobility limitation), high (closure of indoor facilities), and very high (lockdown) protection levels, (ii) quarantine for confirmed cases, and (iii) vaccination rate and efficacy of four types of vaccines (Pfizer, Moderna, Astra Zeneca, and Janssen). The model was verified and evaluated using the response timeline and vaccination strategies and rates in the Basque Country (N. Spain). Once the model performance was validated, different initial phase (when 30% of the population is vaccinated) vaccination scenarios were simulated, including (i) a realistic vaccine limited supply scenario and (ii) four potential full vaccine supply scenarios where a unique vaccine type is administered. Significant differences in disease prevalence and cumulative mortality were found between vaccination scenarios for low and medium-level protection measures. For high-level protection measures, any vaccine scenario is effective at limiting the virus transmission and disease mortality. The results obtained here may vary in further studies since there may be some unpredictable factors/covariates. With this in mind, the model here could be easily applied to other regions or countries, modifying the strategies implemented and initial conditions.

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模拟疫苗接种与非药物措施之间的相互作用对 COVID-19 发病率的影响。
自 2019 年 12 月以来,新型严重急性呼吸系统综合征冠状病毒 2(SARS-CoV-2)从中国武汉迅速蔓延至全球,到 2021 年年中已影响 200 多个国家,报告病例超过 1.9 亿例,约 400 万人死亡。在大流行的第一年,受影响国家采取了各种非药物干预措施来控制病毒传播。2020 年 12 月,各国开始在供应有限的情况下接种几种授权疫苗。在此背景下,本研究旨在开发一个 SEIR 型连续时间确定性疾病模型,以确定不同疫苗接种方案和保护措施水平之间的相互作用对疾病发病率的影响。为此,模型纳入了(i) 保护措施,包括低(自我保护)、中(限制行动)、高(关闭室内设施)和极高(封锁)保护水平,(ii) 确诊病例的隔离,以及(iii) 四种疫苗(辉瑞、Moderna、阿斯利康和杨森)的接种率和效力。该模型使用巴斯克地区(西班牙北部)的响应时间表、疫苗接种策略和接种率进行了验证和评估。模型性能得到验证后,对不同的初始阶段(30% 的人口接种疫苗)疫苗接种情景进行了模拟,包括 (i) 现实的疫苗有限供应情景和 (ii) 四种潜在的全面疫苗供应情景,即接种一种独特的疫苗类型。在低级和中级保护措施的不同疫苗接种方案中,疾病流行率和累积死亡率存在显著差异。对于高级别保护措施,任何疫苗方案都能有效限制病毒传播和疾病死亡率。由于可能存在一些不可预测的因素/变量,进一步研究得出的结果可能会有所不同。有鉴于此,此处的模型可以很容易地应用于其他地区或国家,只需修改所实施的策略和初始条件即可。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Global Health Epidemiology and Genomics
Global Health Epidemiology and Genomics PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH-
CiteScore
1.40
自引率
0.00%
发文量
10
审稿时长
20 weeks
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