Department of Biology, University of Florida, Gainesville, Florida, United States of America.
Institute of Global Health and Department of Preventive Medicine, Northwestern University, Chicago, Illinois, United States of America.
PLoS One. 2024 Mar 28;19(3):e0299143. doi: 10.1371/journal.pone.0299143. eCollection 2024.
Epidemic data are often difficult to interpret due to inconsistent detection and reporting. As these data are critically relied upon to inform policy and epidemic projections, understanding reporting trends is similarly important. Early reporting of the COVID-19 pandemic in particular is complicated, due to changing diagnostic and testing protocols. An internal audit by the State of Florida, USA found numerous specific examples of irregularities in COVID-19 case and death reports. Using case, hospitalization, and death data from the the first year of the COVID-19 pandemic in Florida, we present approaches that can be used to identify the timing, direction, and magnitude of some reporting changes. Specifically, by establishing a baseline of detection probabilities from the first (spring) wave, we show that transmission trends among all age groups were similar, with the exception of the second summer wave, when younger people became infected earlier than seniors, by approximately 2 weeks. We also found a substantial drop in case-fatality risk (CFR) among all age groups over the three waves during the first year of the pandemic, with the most drastic changes seen in the 0 to 39 age group. The CFR trends provide useful insights into infection detection that would not be possible by relying on the number of tests alone. During the third wave, for which we have reliable hospitalization data, the CFR was remarkably stable across all age groups. In contrast, the hospitalization-to-case ratio varied inversely with cases while the death-to-hospitalization ratio varied proportionally. Although specific trends are likely to vary between locales, the approaches we present here offer a generic way to understand the substantial changes that occurred in the relationships among the key epidemic indicators.
由于检测和报告的不一致，疫情数据往往难以解释。由于这些数据对于制定政策和预测疫情至关重要，因此了解报告趋势同样重要。特别是 COVID-19 大流行的早期报告较为复杂，这是由于诊断和检测方案不断变化。美国佛罗里达州的一项内部审计发现了 COVID-19 病例和死亡报告中存在的许多具体异常情况。利用佛罗里达州 COVID-19 大流行第一年的病例、住院和死亡数据，我们提出了一些方法，可以用来识别一些报告变化的时间、方向和幅度。具体来说，通过从第一波（春季）建立检测概率的基线，我们表明，所有年龄段的传播趋势相似，除了第二波夏季，年轻人比老年人更早感染，大约早 2 周。我们还发现，在大流行第一年的三个波次中，所有年龄段的病例病死率（CFR）都大幅下降，0 至 39 岁年龄组的变化最为显著。CFR 趋势提供了有关感染检测的有用见解，如果仅依靠检测数量，则无法获得这些见解。在我们有可靠住院数据的第三波中，所有年龄段的 CFR 都非常稳定。相比之下，住院与病例的比例与病例呈反比，而死亡与住院的比例则成比例变化。尽管特定趋势可能因地点而异，但我们在这里提出的方法提供了一种通用的方法来理解关键疫情指标之间发生的重大变化。
