L-BioStat, KU Leuven, Leuven, Belgium.
I-BioStat, UHasselt, Diepenbeek, Belgium.
PLoS One. 2024 May 6;19(5):e0303254. doi: 10.1371/journal.pone.0303254. eCollection 2024.
One of the key tools to understand and reduce the spread of the SARS-CoV-2 virus is testing. The total number of tests, the number of positive tests, the number of negative tests, and the positivity rate are interconnected indicators and vary with time. To better understand the relationship between these indicators, against the background of an evolving pandemic, the association between the number of positive tests and the number of negative tests is studied using a joint modeling approach. All countries in the European Union, Switzerland, the United Kingdom, and Norway are included in the analysis. We propose a joint penalized spline model in which the penalized spline is reparameterized as a linear mixed model. The model allows for flexible trajectories by smoothing the country-specific deviations from the overall penalized spline and accounts for heteroscedasticity by allowing the autocorrelation parameters and residual variances to vary among countries. The association between the number of positive tests and the number of negative tests is derived from the joint distribution for the random intercepts and slopes. The correlation between the random intercepts and the correlation between the random slopes were both positive. This suggests that, when countries increase their testing capacity, both the number of positive tests and negative tests will increase. A significant correlation was found between the random intercepts, but the correlation between the random slopes was not significant due to a wide credible interval.
了解和减少 SARS-CoV-2 病毒传播的关键工具之一是检测。检测总数、阳性检测数、阴性检测数和阳性率是相互关联的指标，随时间而变化。为了更好地了解这些指标之间的关系，针对不断演变的大流行背景，使用联合建模方法研究了阳性检测数和阴性检测数之间的关系。分析中包括欧盟所有国家、瑞士、英国和挪威。我们提出了一个联合惩罚样条模型，其中惩罚样条被重新参数化为线性混合模型。该模型通过平滑国家特定的偏离整体惩罚样条来允许灵活的轨迹，并通过允许自相关参数和残差方差在国家之间变化来考虑异方差性。阳性检测数和阴性检测数之间的关联来自于随机截距和斜率的联合分布。随机截距之间的相关性和随机斜率之间的相关性均为正。这表明，当国家增加检测能力时，阳性检测和阴性检测的数量都会增加。随机截距之间存在显著相关性，但由于置信区间较宽，随机斜率之间的相关性不显著。
