Department of Mathematics, Simon Fraser University, Burnaby, BC V5A 1S6, Canada.
Department of Mathematics, Simon Fraser University, Burnaby, BC V5A 1S6, Canada.
J Theor Biol. 2023 Feb 21;559:111368. doi: 10.1016/j.jtbi.2022.111368. Epub 2022 Nov 24.
COVID-19 remains a major public health concern, with large resurgences even where there has been widespread uptake of vaccines. Waning immunity and the emergence of new variants will shape the long-term burden and dynamics of COVID-19. We explore the transition to the endemic state, and the endemic incidence in British Columbia (BC), Canada and South Africa (SA), to compare low and high vaccination coverage settings with differing public health policies, using a combination of modelling approaches. We compare reopening (relaxation of public health measures) gradually and rapidly as well as at different vaccination levels. We examine how the eventual endemic state depends on the duration of immunity, the rate of importations, the efficacy of vaccines and the transmissibility. These depend on the evolution of the virus, which continues to undergo selection. Slower reopening leads to a lower peak level of incidence and fewer overall infections in the wave following reopening: as much as a 60% lower peak and a 10% lower total in some illustrative simulations; under realistic parameters, reopening when 70% of the population is vaccinated leads to a large resurgence in cases. The long-term endemic behaviour may stabilize as late as January 2023, with further waves of high incidence occurring depending on the transmissibility of the prevalent variant, duration of immunity, and antigenic drift. We find that long term endemic levels are not necessarily lower than current pandemic levels: in a population of 100,000 with representative parameter settings (Reproduction number 5, 1-year duration of immunity, vaccine efficacy at 80% and importations at 3 cases per 100K per day) there are over 100 daily incident cases in the model. Predicted prevalence at endemicity has increased more than twofold after the emergence and spread of Omicron. The consequent burden on health care systems depends on the severity of infection in immunized or previously infected individuals.
COVID-19 仍然是一个主要的公共卫生关注点,即使在疫苗广泛接种的地方,也会出现大规模反弹。免疫减弱和新变种的出现将影响 COVID-19 的长期负担和动态。我们探讨了向地方病状态的转变,以及加拿大不列颠哥伦比亚省(BC)和南非(SA)的地方病发病率,使用多种建模方法比较了疫苗接种率低和高的环境中的情况以及不同的公共卫生政策。我们比较了逐渐和快速以及在不同疫苗接种水平下的重新开放(放松公共卫生措施)。我们研究了最终的地方病状态如何取决于免疫持续时间、输入率、疫苗的有效性和传染性。这些取决于病毒的演变,病毒仍在不断发生选择。较慢的重新开放导致重新开放后疫情高峰期的发病率和总感染人数减少:在一些说明性模拟中,高峰期减少了 60%,总感染人数减少了 10%;在现实参数下,当 70%的人口接种疫苗时,重新开放会导致病例大量反弹。随着时间的推移,长期地方病行为可能会在 2023 年 1 月稳定下来,由于流行变种的传染性、免疫持续时间和抗原漂移,还会出现高发病率的进一步波次。我们发现,长期地方病水平不一定低于当前的大流行水平:在一个有代表性参数设置(繁殖数 5,免疫持续时间 1 年,疫苗效力 80%,输入率为每天每 10 万人 3 例)的 10 万人的人群中,模型中每天有超过 100 例的病例。在奥密克戎出现和传播后,预计地方病时的患病率增加了两倍多。随后对医疗保健系统的负担取决于免疫或以前感染过的个体的感染严重程度。