Testing behaviour and positivity for SARS-CoV-2 infection: insights from web-based participatory surveillance in the Netherlands.

OBJECTIVES: We aimed to identify populations at a high risk for SARS-CoV-2 infection but who are less likely to present for testing, by determining which sociodemographic and household factors are associated with a lower propensity to be tested and, if tested, with a higher risk of a positive test result. DESIGN AND SETTING: Internet-based participatory surveillance data from the general population of the Netherlands. PARTICIPANTS: Weekly survey data collected over a 5-month period (17 November 2020 to 18 April 2021) from a total of 12 026 participants who had contributed at least 2 weekly surveys was analysed. METHODS: Multivariable analyses using generalised estimating equations for binomial outcomes were conducted to estimate the adjusted ORs of testing and of test positivity associated with participant and household characteristics. RESULTS: Male sex (adjusted OR for testing (ORt): 0.92; adjusted OR for positivity (ORp): 1.30, age groups<20 (ORt: 0.89; ORp: 1.27), 50-64 years (ORt: 0.94; ORp: 1.06) and 65+ years (ORt: 0.78; ORp: 1.24), diabetics (ORt: 0.97; ORp: 1.06) and sales/administrative employees (ORt: 0.93; ORp: 1.90) were distinguished as lower test propensity/higher test positivity factors. CONCLUSIONS: The factors identified using this approach can help identify potential target groups for improving communication and encouraging testing among those with symptoms, and thus increase the effectiveness of testing, which is essential for the response to the COVID-19 pandemic and for public health strategies in the longer term.

Contribution of seasonality in transmission of Mycobacterium tuberculosis to seasonality in tuberculosis disease: a simulation study.

A seasonal rise in tuberculosis (TB) notifications has been confirmed in several studies. Here, we examined one hypothesis for its cause: increased transmission of TB during wintertime due to crowding. Seasonality analysis was performed on actual and simulated notifications of clustered TB cases, which are considered to be representative of recent transmission, diagnosed from 1993 to 2004 in the Netherlands (n = 4,746). To test the hypothesis of winter crowding, notifications were simulated by adding patient delay and incubation period to an infection date randomly taken to be in winter in 80% of cases. The incubation periods were derived from frequency distributions for different TB disease localizations drawn from the literature. Seasonality analysis was performed using autocorrelation function plots and spectral analysis. Actual notifications showed strong seasonality in clustered TB and clustered extrapulmonary TB cases but not in clustered pulmonary TB cases. Analysis of simulated notifications revealed barely significant seasonality only in extrapulmonary TB cases. Our results suggest that increased transmission of TB during wintertime is unlikely to be the only cause of the seasonal peak in TB notifications. A factor closer to the notification date probably contributes to the seasonality observed in TB notifications.