Comparison of Influenza Epidemic Trends Based on a Large-scale Claims Database and National Infectious Disease...

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.

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.

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.

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.