RESUMEN
The seasonalities of influenza-like illnesses (ILIs) and invasive pneumococcal diseases (IPDs) remain incompletely understood. Experimental evidence indicates that influenza-virus infection predisposes to pneumococcal disease, so that a correspondence in the seasonal patterns of ILIs and IPDs might exist at the population level. We developed a method to characterize seasonality by means of easily interpretable summary statistics of seasonal shape-or seasonal waveforms. Nonlinear mixed-effects models were used to estimate those waveforms based on weekly case reports of ILIs and IPDs in 5 regions spanning continental France from July 2000 to June 2014. We found high variability of ILI seasonality, with marked fluctuations of peak amplitudes and peak times, but a more conserved epidemic duration. In contrast, IPD seasonality was best modeled by a markedly regular seasonal baseline, punctuated by 2 winter peaks in late December to early January and January to February. Comparing ILI and IPD seasonal waveforms, we found indication of a small, positive correlation. Direct models regressing IPDs on ILIs provided comparable results, even though they estimated moderately larger associations. The method proposed is broadly applicable to diseases with unambiguous seasonality and is well-suited to analyze spatially or temporally grouped data, which are common in epidemiology.
Asunto(s)
Gripe Humana/epidemiología , Dinámicas no Lineales , Infecciones Neumocócicas/epidemiología , Estaciones del Año , Francia/epidemiología , Humanos , Análisis de RegresiónRESUMEN
International case definitions recommended by the Centers for Disease Control and Prevention (CDC), the European Centre for Disease Prevention and Control (ECDC), and the World Health Organization (WHO) are commonly used for influenza surveillance. We evaluated clinical factors associated with the laboratory-confirmed diagnosis of influenza and the performance of these influenza case definitions by using a complete dataset of 14,994 patients with acute respiratory infection (ARI) from whom a specimen was collected between August 2009 and April 2014 by the Groupes Régionaux d'Observation de la Grippe (GROG), a French national influenza surveillance network. Cough and fever ≥ 39 °C most accurately predicted an influenza infection in all age groups. Several other symptoms were associated with an increased risk of influenza (headache, weakness, myalgia, coryza) or decreased risk (adenopathy, pharyngitis, shortness of breath, otitis/otalgia, bronchitis/ bronchiolitis), but not throughout all age groups. The WHO case definition for influenza-like illness (ILI) had the highest specificity with 21.4%, while the ECDC ILI case definition had the highest sensitivity with 96.1%. The diagnosis among children younger than 5 years remains challenging. The study compared the performance of clinical influenza definitions based on outpatient surveillance and will contribute to improving the comparability of data shared at international level.