Supervisory team
LSHTM
Nagasaki University
Project
Background
Seasonal influenza remains a major public health concern, particularly in school settings where close contact and high population density facilitate transmission. While vaccination is the primary preventive strategy, its coverage and effectiveness vary annually. Non-pharmaceutical interventions (NPIs) - such as hand hygiene, mask use, ventilation improvements, and social distancing - offer complementary protection and can reduce transmission even when vaccine uptake is suboptimal. In Japan, additional measures such as "silent lunch" and special seating arrangements have also been used to prevent transmission, but for all interventions there is uncertainty around the effectiveness and feasibility. Additionally, there is opportunity to share practices between Japan and the UK and identify interventions that can be applied across settings. This project aims to examine the feasibility of implementing NPIs in school environments and how digital technology could improve adherence.
Objectives
The main objectives are:
- To review the evidence for NPIs to prevent seasonal influenza in school settings, and how they might compare between the UK and Japan.
- To assess the barriers and facilitators for NPIs in school settings, especially the use of digital technology.
- To explore using mathematical models the potential impact of NPIs in schools and the wider community.
Methodology
The study will employ:
- mixed-methods approach,
- development of mathematical modelling for seasonal influenza in schools.
A cross-sectional survey will be administered to school administrators, teachers, and parents to gauge perceptions, attitudes, and readiness toward NPIs such as hand hygiene promotion, classroom ventilation, surface disinfection, and temporary isolation policies. Focus group discussions will explore social, cultural, and logistical factors affecting feasibility and compliance.
Quantitative data on absenteeism and reported influenza-like illness (ILI) will be collected over one influenza season from participating schools. The data will be used to inform mathematical models for seasonal influenza and how NPIs may influence transmission. Previously collected data on social contacts are available for use in both Japan and the UK.
Expected Outcomes
The project will generate comprehensive insights into which NPIs are most feasible and acceptable in real-world school settings. It will identify practical constraints - such as cost, staff workload, and student cooperation - that affect sustainability. Depending on the interests and experience of the student, these studies will happen in Japan, the UK, or both. The modelling will help formulate new approaches to conceptualising transmission in schools and how NPIs are included.
Significance
Given the recurring burden of influenza on public health systems and school attendance, understanding the feasibility of NPIs is essential for developing resilient health strategies. This research will contribute to pandemic preparedness by demonstrating how schools can serve as effective sites for infection control without relying solely on pharmaceutical measures or school closures. The outcomes could also inform responses to future respiratory disease outbreaks.
The role of LSHTM and NU in this collaborative project
- LSHTM will provide primary supervision: development and planning of project proposal, expertise in epidemiology, modelling, and mixed-methods research.
- NU will support via informal network of schools and educational facilities in Japan, and development of models for infectious disease transmission.
Skills we expect a student to develop/acquire whilst pursuing this project
Engagement with schools regarding public health challenges. An improved understanding of the cultural similarities and differences between the UK and Japan.
Particular prior educational requirements for a student undertaking this project
- An understanding of Japanese culture and language would be advantageous in order to engage with schools in Japan.
- Prior experience with modelling of infectious diseases would be preferred but not essential.