Background: During the coronavirus disease 2019 (COVID-19) pandemic, global influenza activity sharply declined due to extensive non-pharmaceutical interventions (NPIs). Understanding how influenza activity rebounded after these interventions were lifted is critical for informing future respiratory virus control strategies.

Methods: We conducted a descriptive analysis of the temporal characteristics of weekly number of influenza-like illness (ILI) cases, ILI%, influenza-positive cases, and influenza-positive rates. Poisson log-link regression models, incorporating meteorological factors using data from 2013 to 2019, were established to predict the weekly influenza-positive rate under a counterfactual scenario without COVID-19 interventions in 2022–2023.

Results: Our findings indicate that the cancellation of COVID-19-related NPIs had a notable impact on increasing influenza transmission. Children under 5 years old exhibited the highest ILI cases. The influenza positivity rate surged to 34.35% during the pandemic relaxation, surpassing pre-pandemic (24.53%) and pandemic (9.56%) rates. During the pre-COVID-19 period, various influenza virus subtypes were co-circulated, with the predominant subtype varying. However, during the COVID-19 pandemic period, the dominant strains were influenza A/H1N1 and influenza B/Victoria lineage, while influenza A/H3N2 predominated in the pandemic relaxation period.

Conclusion: The marked resurgence of influenza activity in Shenzhen following the lifting of COVID-19-related NPIs underscores the need for sustained surveillance and preparedness for concurrent or sequential respiratory virus outbreaks.

Background: Seasonal influenza is a recurrent respiratory infection, and timely detection is essential for public health. In Japan, surveillance is conducted through sentinel medical institutions under the National Epidemiological Surveillance of Infectious Diseases (NESID). Recently, access to large claims databases, such as the JMDC claims database (JMDCdb), has increased. While both are sample-based systems, JMDCdb covers a much larger population. We aimed to assess consistency between these sources in estimating influenza cases and the effective reproduction number (R_t) and to explore their utility in epidemic analysis.

Methods: We analyzed data from week 36 of 2016 to week 35 of 2019. Influenza cases were estimated from NESID (reported cases and cases per sentinel) and JMDCdb (cases with influenza-related diagnoses and antiviral prescriptions). Daily infection counts were derived to estimate R_t.

Results: Although minor differences appeared at epidemic peaks, estimates from NESID reports aligned well with JMDCdb. Estimates based on cases per sentinel were lower. R_t values were consistent across data sources. R_t exceeded 1.0 when cases per sentinel surpassed 0.2–0.3. Using a threshold of 0.25 cases per sentinel enabled detection of epidemic onset 4–5 weeks earlier than current standards.

Conclusion: Claims data, such as those from JMDCdb, may be useful for retrospective examination of influenza trends. Moreover, a detailed analysis of the number of cases reported per sentinel suggested the potential to propose threshold values that enable earlier prediction of epidemics than conventional criteria.

Background: Socioeconomic inequalities in disability-free life span have been widening. We evaluated the mediating role of multiple modifiable risk factors, including tooth loss, on socioeconomic inequalities in disability onset and mortality among Japanese older adults.

Methods: This prospective cohort study utilized data from the Japan Gerontological Evaluation Study, targeting adults aged ≥65 years. The 2013 baseline questionnaire survey participants were followed until 2022 (n = 48,474; median follow-up, 9.0 years). Time-varying mediators were also assessed in questionnaire surveys in 2016 and 2019. Discrete-time survival analysis estimated the association of socioeconomic status (SES)—a standardized principal component score incorporating household income, wealth, and years of education—with disability or mortality onset. The Karlson–Holm–Breen method decomposed total effects into pathways through 11 mediators, including tooth loss and major risk factors for disability and mortality.

Results: During the follow-up, 29.1% became disabled or died. Compared to the highest SES group, the lowest SES quartile group exhibited a hazard ratio of 1.26 (95% confidence interval [CI], 1.19–1.34) for disability or mortality. Tooth loss exhibited the second largest indirect effect (proportion mediated 12.4%; 95% CI, 8.0–17.2), following moderate depression (16.0%; 95% CI, 11.7–21.5). Tooth loss exhibited the strongest association with SES, attributing to the large indirect effect.

Conclusion: The findings suggest that tackling inequalities in tooth loss may be an effective way to reduce socioeconomic inequalities in a disability-free life span.