3.2 Rapid influenza diagnostic test performance
Overall sensitivity and specificity of Sofia® were 76.1% (95% CI: 72.8—79.1) and 97.2% (96.2—97.9), respectively, with slightly higher sensitivity for influenza A than for influenza B (Table 2). Factors associated with sensitivity in the adjusted model were runny nose (OR=3.0, p<0.001), nasal congestion (1.59, p=0.045), days from symptom onset (per day; 0.75; p<0.001), myalgia (0.60; p=0.014), age (per 5 years; 0.55; p<0.001), and detection of another virus (0.50; p=0.043) (Figure 1). Fever was excluded from the adjusted analysis because the variance inflation factor was 18.09, meaning it was highly collinear with other variables. None of the factors explored in the adjusted model were associated with specificity.
DISCUSSION
Among a population of K-12 students evaluated in a community-based setting, Sofia® demonstrated high specificity and moderately high sensitivity. In an adjusted analysis, we found that older age, increased days from illness onset, the presence of additional viruses, and the presence of myalgia could result in lower sensitivity. Alternatively, the presence of runny nose and nasal congestion could improve sensitivity.
The effect of age on RIDT sensitivity is well documented, and our results demonstrate this holds true even among children in a community setting.3 Previous studies have also noted the importance of the duration between when symptoms started and when the test was performed.11 The effect of individual symptoms on test sensitivity is not well understood, but our previous clinic-based study also showed that the presence of a runny nose improves sensitivity.10 One explanation for this could be that having a runny nose or nasal congestion is correlated with a greater quantity of viral antigen within the sample collected. Absence of these symptoms may help to guide interpretation of negative results.
Our study benefited from a large sample recruited from a community setting over six influenza seasons, which is underrepresented in the literature where studies often rely on recruiting medically attended cases in health care facilities over fewer influenza seasons.10-12 Despite the strengths of the study design, our results should be considered in the context of at least two limitations. First, our analysis is based on the performance of one RIDT and results may vary based on the type of test. Second, our study is limited to Southcentral Wisconsin. Other studies have shown that sensitivity improves when prevalence is high, but local influenza seasonality is not well defined in the literature, so we defined it based on the general influenza season in the region.12
Our results suggest that routine use of RIDT in schools and other community congregate settings (e.g., select workplaces) could assist with early identification of increasing influenza activity, and thereby help with timely implementation of targeted countermeasures. This in turn could help reduce virus transmission and related disruptions caused by widespread transmission, including increased student and staff absenteeism. Some real-world experience of using RIDT to keep schools open already exists from the context of the still-ongoing COVID-19 pandemic. For example, in one study, continuous rapid testing after a known exposure performed as well as quarantine in preventing the spread of SARS-CoV-2.13 Future studies are needed to explore feasibility of RIDT-supported prevention programs to reduce the impact of influenza and other respiratory infections in other congregate community settings and in different populations.
Table 1: Demographics and distribution of sample characteristics for K-12 students.