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SARS-CoV-2 Surveillance System in Canada: Longitudinal Trend Analysis

机译：加拿大SARS-COV-2监控系统：纵向趋势分析

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BACKGROUND:The COVID-19 global pandemic has disrupted structures and communities across the globe. Numerous regions of the world have had varying responses in their attempts to contain the spread of the virus. Factors such as public health policies, governance, and sociopolitical climate, have led to differential levels of success at controlling the spread of SARS-CoV-2. Ultimately, a more advanced surveillance metric for COVID-19 transmission is necessary to help government systems and national leaders understand which responses have been effective and gauge where outbreaks occur.OBJECTIVE:The goal of this study is to provide advanced COVID-19 surveillance metrics for Canada at the country, province, and territory level that account for shifts in the pandemic including speed, acceleration, jerk and persistence. Enhanced surveillance identifies risks for explosive growth and regions that have tamped out outbreaks successfully.METHODS:Using a longitudinal trend analysis study design, we extracted 62 days of COVID data from Canadian public health registries for 13 provinces and territories. We used an empirical difference equation to measure the daily number of cases in Canada as a function of the prior number of cases, the level of testing, and weekly shift variables based on a dynamic panel model that was estimated using the generalized method of moments (GMM) approach by implementing the Arellano-Bond estimator in R.RESULTS:We compare the week of February 7-13, 2021 with the week of February 14-20, 2021. Canada, as a whole, had a decrease in speed from 8.4 daily new cases per 100,000 population to 7.5 daily new cases per 100,000 population. The persistence of new cases during the week of February 14-20 reported 7.5 cases that are a result of COVID transmissions 7 days earlier. The two most populous provinces of Ontario and Quebec both experienced decreases in speed from 7.9 and 11.5, respectively, for the week of February 7-13 to speeds of 6.9 and 9.3 daily new cases per 100,000 population, respectively, the week of February 14-20. Nunavut experienced a significant increase in speed during this time from 3.3 daily new cases per 100,000 population to 10.9 daily new cases per 100,000 population.CONCLUSIONS:Canada excelled at COVID control early on in the pandemic, especially during the Great COVID Shutdown. The second wave at the end of 2020 resulted in a resurgence of the outbreak which has since been controlled. Enhanced surveillance identifies outbreaks and where there is the potential for explosive growth which informs proactive health policy.
机译：背景：Covid-19 Global Pandemic在全球扰乱了地球结构和社区。众多世界各地在遏制病毒的蔓延的尝试中具有不同的反应。公共卫生政策，治理和社会政治气候等因素导致控制SARS-COV-2传播的差异程度。最终，需要一个更先进的Covid-19传输监视度量，以帮助政府系统和国家领导人了解哪些反应是有效的，并且衡量爆发的爆发。目的：本研究的目标是提供先进的Covid-19监视指标加拿大在乡村，省和领土层面，占大流行的转变，包括速度，加速，混蛋和持久性。增强监督识别出于成功爆发爆发的爆炸性增长和地区的风险。我们使用了实证差分方程来测量加拿大的每日案件数量，作为先前的情况，测试水平和基于使用普通时刻方法估计的动态面板模型（ GMM）通过实施R.Results的阿勒拉诺键估计人员：我们比较2月7日至33日的一周，2021年2月14日至2010年2月14日，加拿大总的来说，加拿大速度从8.4减少每10万人每10万人的新案例为每10万人每日7.5人口。新案件的持续存在于2月14日 - 20日，报告7.5案件，这是Covid传输7天早些时候的结果。 2010年2月7日至13日的7.9和11.5分别在7.9和11.5周内分别经历了两大的速度下降了7.9和11.5的速度，分别为每10万人每10万人的每日新案件的速度为6.9％和9.3季度。 20。 Nunavut在这段时间内从3.3每10万人的新案例到10.9每10万人的新案件的速度显着增加。结论：加拿大在大流行早期的COVID控制，特别是在大型Covid关闭期间。 2020年底的第二波导致自控制的爆发的重新恢复。增强监督识别爆发，爆发性增长潜力，可通知积极的健康政策。

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