Population Health Laboratory (#PopHealthLab), University of Fribourg, Fribourg, Switzerland; Swiss School of Public Health (SSPH+), Zurich, Switzerland.
Population Health Laboratory (#PopHealthLab), University of Fribourg, Fribourg, Switzerland; Swiss School of Public Health (SSPH+), Zurich, Switzerland; Quality of Care Service, University Hospitals of Geneva, Geneva, Switzerland.
Public Health. 2024 Sep;234:98-104. doi: 10.1016/j.puhe.2024.06.006. Epub 2024 Jul 6.
To estimate the size of COVID-19 waves using four indicators across three pandemic periods and assess potential surveillance bias.
Case study using data from one region of Switzerland.
We compared cases, hospitalizations, deaths, and seroprevalence during three periods including the first three pandemic waves (period 1: Feb-Oct 2020; period 2: Oct 2020-Feb 2021; period 3: Feb-Aug 2021). Data were retrieved from the Federal Office of Public Health or estimated from population-based studies. To assess potential surveillance bias, indicators were compared to a reference indicator, i.e. seroprevalence during periods 1 and 2 and hospitalizations during the period 3. Timeliness of indicators (the duration from data generation to the availability of the information to decision-makers) was also evaluated.
Using seroprevalence (our reference indicator for period 1 and 2), the 2nd wave size was slightly larger (by a ratio of 1.4) than the 1st wave. Compared to seroprevalence, cases largely overestimated the 2nd wave size (2nd vs 1st wave ratio: 6.5), while hospitalizations (ratio: 2.2) and deaths (ratio: 2.9) were more suitable to compare the size of these waves. Using hospitalizations as a reference, the 3rd wave size was slightly smaller (by a ratio of 0.7) than the 2nd wave. Cases or deaths slightly underestimated the 3rd wave size (3rd vs 2nd wave ratio for cases: 0.5; for deaths: 0.4). The seroprevalence was not useful to compare the size of these waves due to high vaccination rates. Across all waves, timeliness for cases and hospitalizations was better than for deaths or seroprevalence.
The usefulness of indicators for assessing the size of pandemic waves depends on the type of indicator and the period of the pandemic.
使用四个指标在三个大流行期间评估 COVID-19 波的规模，并评估潜在的监测偏差。
使用瑞士一个地区的数据进行病例研究。
我们比较了三个时期的病例、住院、死亡和血清流行率，包括前三个大流行波（第 1 期：2020 年 2 月至 10 月；第 2 期：2020 年 10 月至 2021 年 2 月；第 3 期：2021 年 2 月至 8 月）。数据来自联邦公共卫生局或从基于人群的研究中估计。为了评估潜在的监测偏差，将指标与参考指标（即第 1 期和第 2 期的血清流行率和第 3 期的住院率）进行了比较。还评估了指标的及时性（从数据生成到决策者获得信息的持续时间）。
使用血清流行率（我们第 1 期和第 2 期的参考指标），第 2 波的规模略大于第 1 波（比值为 1.4）。与血清流行率相比，病例大大高估了第 2 波的规模（第 2 波与第 1 波的比值：6.5），而住院（比值：2.2）和死亡（比值：2.9）更适合比较这些波的规模。使用住院作为参考，第 3 波的规模略小于第 2 波（比值为 0.7）。病例或死亡略低估了第 3 波的规模（病例的第 3 波与第 2 波的比值：0.5；死亡的比值：0.4）。由于高疫苗接种率，血清流行率无法用于比较这些波的规模。在所有波中，病例和住院的及时性都优于死亡或血清流行率。
评估大流行波规模的指标的有用性取决于指标的类型和大流行的时期。
