Background Influenza is a public health issue that needs to be addressed strategically. The assessment of detailed infectious profiles is an important part of this effort. Household transmission data play a key role in estimating such profiles. We used diagnostic and questionnaire-based data on influenza patients at a Japanese clinic to estimate the detailed infectious period (as well as incubation period, symptomatic and infectious periods, and extended infectious period after recovery) and the secondary attack ratio (SAR) of influenza for households of various sizes based on a modified Cauchemez-type model. Results The data were from enrolled patients with confirmed influenza who were treated at the Hirotsu Clinic (Kawasaki, Japan) with a neuraminidase inhibitor (NAI) during six northern hemisphere influenza seasons between 2010 and 2016. A total of 2342 outpatients, representing 1807 households, were included. For influenza type A, the average incubation period was 1.43 days (95% probability interval, 0.03–5.32 days). The estimated average symptomatic and infective period was 1.76 days (0.33–4.62 days); the extended infective period after recovery was 0.25 days. The estimated SAR rose from 20 to 32% as household size increased from 3 to 5. For influenza type B, the average incubation period, average symptomatic and infective period, and extended infective period were estimated as 1.66 days (0.21–4.61), 2.62 days (0.54–5.75) and 1.00 days, respectively. The SAR increased from 12 to 21% as household size increased from 3 to 5. Conclusion All estimated periods of influenza type B were longer than the corresponding periods for type A. However, the SAR for type B was less than that for type A. These results may reflect Japanese demographics and treatment policy. Understanding the infectious profiles of influenza is necessary for assessing public health measures.

The challenge for medical schools in Japan is to develop research activities for innovation. This study aimed at analyzing the connection between the research output of “promising researchers” (next-generation leaders in terms of research activity) and their supervisors' past research activities to identify those factors that impact researchers' performance. Activity was analyzed from the viewpoints of productivity, coauthorship networks, and research impact using a novel index called the Research Diversity Index (REDi) that quantifies crossdisciplinarity. Research funding, which has not yet been fully utilized in correlation studies of the characteristics of authors, was also considered in this study. For the promising researchers extracted using betweenness centrality scores within coauthorship networks, there were diachronic correlations between the records of the promising researchers and those of their supervisors. Supervisor leadership as measured by the number of last-authored publications and extent of networking had a positive effect on the promising researchers productivity. Supervisors' research style of integrating knowledge from multiple fields, as measured by REDi, was negatively correlated with the publication impact of promising researchers, suggesting that REDi is useful as a novel indicator of research quality not being captured by existing indices. It was also noted that establishing an academic presence through extensive collaborations could be advantageous for obtaining research funding, especially from top-down government programs. The possible implications of this study for promoting research activities are the importance of incorporating new doctorates into research groups at an early stage and that of promoting interinstitutional, crossdisciplinary collaborations.Classification codeMSC: 62P10 Applications of statistics to biology and medical sciences; meta-analysis.JEL: Z1Z10 Cultural Economics • Economic Sociology • Economic Anthropology- General.

BackgroundInfluenza is a public health issue that needs to be addressed strategically. The assessment of detailed infectious profiles is an important part of this effort. Household transmission data play a key role in estimating such profiles. We used diagnostic and questionnaire-based data on influenza patients at a Japanese clinic to estimate the detailed infectious period (as well as incubation period, symptomatic and infectious periods, and extended infectious period after recovery) and the secondary attack ratio (SAR) of influenza for households of various sizes based on a modified Cauchemez-type model.ResultsThe data were from enrolled patients with confirmed influenza who were treated at the Hirotsu Clinic (Kawasaki, Japan) with a neuraminidase inhibitor (NAI) during six northern hemisphere influenza seasons between 2010 and 2016. A total of 2,342 outpatients, representing 1,807 households, were included. For influenza type A, the average incubation period was 1.43 days (95% probability interval: 0.03-5.32 days). The estimated average symptomatic and infective period was 1.76 days (0.33-4.62 days); the extended infective period after recovery was 0.25 days. The estimated SAR rose from 20% to 32% as household size increased from 3 to 5. For influenza type B, the average incubation period, average symptomatic and infective period, and extended infective period were estimated as 1.66 days (0.21-4.61), 2.62 days (0.54-5.75) and 1.00 days, respectively. The SAR increased from 12% to 21% as household size increased from 3 to 5.ConclusionAll estimated periods of influenza type B were longer than the corresponding periods for type A. However, the SAR for type B was less than that for type A. These results may reflect Japanese demographics and treatment policy. Understanding the infectious profiles of influenza is necessary for assessing public health measures.

Abstract Background Influenza is a public health issue that needs to be addressed strategically and assessment of detailed infectious profiles is important for that. Household transmission data have played a key role for estimating these profiles. From one clinic’s influenza diagnostic and questionnaire-based data, we aimed to estimate the detailed infectious period (incubation, symptomatic and infective, and extended infective after recovery) and secondary attack ratio (SAR) for each household size of influenza by using modified Cauchemez-type model.Results The data source was derived from enrolled patients with confirmed influenza who were treated at the Hirotsu Clinic (Kawasaki, Japan) with a neuraminidase inhibitor (NAI) during the 6 Northern Hemisphere influenza seasons between 2010 and 2016. A total of 2,342 outpatients representing 1,807 households were included. For influenza type A, average incubation period and its 95% probability interval was 1.43 (0.03-5.32) days. Estimated average symptomatic and infective period was 1.76 (0.33-4.62) days and point estimated extended infective period after recovery was 0.25 days. Estimated SAR elevated from 20% to 32% as household size increases from 3 to 5. For influenza type B, average incubation period, average symptomatic and infective period, and extended infective period were estimated 1.66 (0.21-4.61) days, 2.62 (0.54-5.75) days and 1.00 days, respectively. SAR was increased 12% to 21% as household size increases from 3 to 5.Conclusion All estimated periods of influenza type B were longer than those of influenza type A. On the other hands, SAR of type B was less than that of type A. These results may reflect Japanese demographics and treatment policy. It is useful to understand the infectious profiles of influenza for examining public health measures.