Nichita Eleodor, Pietrusiak Mary-Anne, Xie Fangli, Schwanke Peter, Pandya Anjali
Ontario Tech University, Oshawa, ON.
Durham Region Health Department, Whitby, ON.
Can Commun Dis Rep. 2022 Oct 1;48(10):449-464.
The coronavirus disease 2019 (COVID-19) pandemic has placed unprecedented demands on local public health units in Ontario, Canada, one of which was the need for in-house epidemiological modelling capabilities. The objective of this study is to develop a native Windows desktop app for epidemiological modelling, to be used by public health unit epidemiologists to predict COVID-19 transmission in Durham Region.
The developed app is an implementation of a multi-stratified compartmental epidemiological model that can accommodate multiple virus variants and levels of vaccination, as well as public health measures such as physical distancing, contact tracing followed by quarantine and testing followed by isolation. It was used to investigate the effects of different factors on COVID-19 transmission, including vaccination coverage, vaccine effectiveness, waning of vaccine-induced immunity and the advent of the Omicron variant. The simulation start date was November 22, 2021.
For the Delta variant, at least 90% of the population would need to be vaccinated to achieve herd immunity. A Delta-variant-only epidemiological curve would be flattened from the start in the absence of immunity waning and within six months in the presence of immunity waning. The percentage of infections caused by the Omicron variant was forecast to increase from 1% to 97% in the first month of the simulation. Total Omicron infections were forecasted to be reduced, respectively, by 26% or 41% if 3,000 or 5,000 booster doses were administered per day.
For the Delta variant, both natural and vaccination-induced immunity are necessary to achieve herd immunity, and waning of vaccine-induced immunity lengthens the time necessary to reach herd immunity. In the absence of additional public health measures, a wave driven by the Omicron variant was predicted to pose significant public health challenges with infections predicted to peak in 2-3 months from the start of the simulation, depending on the rate of administration of booster doses.
2019年冠状病毒病（COVID-19）大流行对加拿大安大略省的地方公共卫生部门提出了前所未有的要求，其中之一是需要具备内部流行病学建模能力。本研究的目的是开发一款用于流行病学建模的原生Windows桌面应用程序，供公共卫生部门的流行病学家用于预测达勒姆地区的COVID-19传播情况。
开发的应用程序是一个多分层的隔间流行病学模型的实现，该模型可以容纳多种病毒变体和疫苗接种水平，以及诸如保持社交距离、接触者追踪后隔离和检测后隔离等公共卫生措施。它被用于研究不同因素对COVID-19传播的影响，包括疫苗接种覆盖率、疫苗有效性、疫苗诱导免疫力的减弱以及奥密克戎变体的出现。模拟开始日期为2021年11月22日。
对于德尔塔变体，至少90%的人口需要接种疫苗才能实现群体免疫。在没有免疫力减弱的情况下，仅德尔塔变体的流行病学曲线从一开始就会趋于平缓；在存在免疫力减弱的情况下，会在六个月内趋于平缓。预计在模拟的第一个月，奥密克戎变体引起的感染百分比将从1%增加到97%。如果每天接种3000剂或5000剂加强针，预计奥密克戎变体的总感染数将分别减少26%或41%。
对于德尔塔变体，自然免疫和疫苗诱导的免疫对于实现群体免疫都是必要的，并且疫苗诱导免疫力的减弱会延长达到群体免疫所需的时间。在没有额外公共卫生措施的情况下，预计由奥密克戎变体引发的疫情将带来重大公共卫生挑战，根据加强针的接种速度，预计感染将在模拟开始后的2至3个月达到峰值。
