School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, China.
The Interdisciplinary Research Center for Mathematics and Life Sciences, Xi'an Jiaotong University, Xi'an, China.
BMC Public Health. 2022 Jun 27;22(1):1258. doi: 10.1186/s12889-022-13429-w.
Mass immunization is a potentially effective approach to finally control the local outbreak and global spread of the COVID-19 pandemic. However, it can also lead to undesirable outcomes if mass vaccination results in increased transmission of effective contacts and relaxation of other public health interventions due to the perceived immunity from the vaccine.
We designed a mathematical model of COVID-19 transmission dynamics that takes into consideration the epidemiological status, public health intervention status (quarantined/isolated), immunity status of the population, and strain variations. Comparing the control reproduction numbers and the final epidemic sizes (attack rate) in the cases with and without vaccination, we quantified some key factors determining when vaccination in the population is beneficial for preventing and controlling future outbreaks.
Our analyses predicted that there is a critical (minimal) vaccine efficacy rate (or a critical quarantine rate) below which the control reproduction number with vaccination is higher than that without vaccination, and the final attack rate in the population is also higher with the vaccination. We also predicted the worst case scenario occurs when a high vaccine coverage rate is achieved for a vaccine with a lower efficacy rate and when the vaccines increase the transmission efficient contacts.
The analyses show that an immunization program with a vaccine efficacy rate below the predicted critical values will not be as effective as simply investing in the contact tracing/quarantine/isolation implementation. We reached similar conclusions by considering the final epidemic size (or attack rates). This research then highlights the importance of monitoring the impact on transmissibility and vaccine efficacy of emerging strains.
大规模免疫接种是最终控制 COVID-19 疫情在当地爆发和全球传播的一种潜在有效方法。然而,如果大规模疫苗接种导致有效接触者的传播增加,并且由于疫苗的感知免疫力而放松其他公共卫生干预措施,那么也可能会导致不理想的结果。
我们设计了一种 COVID-19 传播动力学的数学模型,该模型考虑了流行病学状况、公共卫生干预措施(隔离/隔离)、人口免疫状况和菌株变化。通过比较有疫苗接种和无疫苗接种情况下的控制繁殖数和最终的流行规模(发病率),我们量化了一些决定人群中何时进行疫苗接种对预防和控制未来疫情有益的关键因素。
我们的分析预测,存在一个临界(最小)疫苗效力率(或临界隔离率),低于该值时,接种疫苗的控制繁殖数高于不接种疫苗的繁殖数,并且接种疫苗的人群的最终发病率也更高。我们还预测了最坏的情况是,当疫苗接种率较高时,疫苗的效力较低,并且疫苗会增加传播有效接触者的效率。
分析表明,疫苗效力率低于预测临界值的免疫接种计划不会像单纯投资于接触者追踪/隔离/隔离实施那样有效。我们通过考虑最终的流行规模(或发病率)得出了类似的结论。这项研究突出了监测新兴菌株对传染性和疫苗效力的影响的重要性。