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.