Kazuhiko Ikeuchi

Surveillance and Development of Control Strategies for Sexually Transmitted Infections in the Era of COVID-19 Pandemic

Researcher

Kazuhiko Ikeuchi

Outline

Behavioral changes during the COVID-19 pandemic have led to a decrease in most infectious diseases, while sexually transmitted infections (STIs) such as syphilis and Mpox have increased. Using big data, I aim to reveal the incidence, prevalence, reinfection rates, and risks of STIs. Based on these findings, I intend to develop strategies for controlling STI outbreaks. Additionally, I aim to establish a system for the early detection of emerging STIs outbreaks in the future.

Kosuke Inoue

Precision Public Health for the Elderly in the Post-COVID Society.

Researcher

Kosuke Inoue

Outline

In this study, I apply cutting-edge causal inference and machine learning techniques to a nationwide elderly cohort, elucidating the characteristics of older adults who are vulnerable to pandemics (e.g., worsening depressive symptoms, cognitive decline). Additionally, I shed light on the characteristics of older adults who benefit significantly from physical activity and social participation during the COVID-19 crisis. By estimating individual vulnerabilities and intervention effects based on multifaceted attribute information, I pave the way for new horizons in personalized strategies, considering the societal context. Through this approach, I aim to catalyze a historical transformation in the role and practice of medicine and public health globally.

Keisuke Ejima

Development of a multifaceted pandemic response through IoT technology and the development of digital twin technology

Researcher

Keisuke Ejima

Outline

First, I will establish an efficient method for acquiring clinical data. I will connect a fully automated genetic testing system to a server using IoT technology to streamline the process from sample collection to data storage. Next, I will develop digital twins, which are computer-based patients that replicate real-world patients. I will create a system using data generated from these digital twins to formulate feasible strategies for infectious disease control. The digital twins will be made publicly available, encouraging further use in pandemic preparedness.

Junna Kawasaki

A technological framework to systematically assess the emerging risks of infectious diseases from zoonotic viruses.

Researcher

Junna Kawasaki

Outline

Numerous infectious diseases have emerged through viral transmissions from animals to humans. This study endeavors to identify viruses with pandemic potential and elucidate the early warning indicators and risk factors for zoonotic disease outbreaks by re-using public deep sequencing data and conducting large-scale virus genomic surveillance in humans and animals. This study will provide an essential scientific groundwork for pandemic preparedness, especially promoting a proactive approach and risk mitigation strategies in the pre-pandemic stage.

Toshikazu Kuniya

Mathematical analysis and implementation of multi-group structured epidemic models

Researcher

Toshikazu Kuniya

Outline

In this study, I focus on multi-group epidemic models in which the host population is divided into subgroups according to the heterogeneity of each individual. In particular, I construct multi-group structured epidemic models that enable us to consider multiple factors such as the variation of the immunity level and the people’s behavior change. I aim for development and implementation of mathematical theory of such multi-group structured models. Moreover, using the theory of type reproduction number, I analyze the effectiveness of policies targeted to specific groups, for instance, vaccination policies targeted to high risk groups.

Yoshiharu Kobayashi

The Politics of Pandemic Preparedness

Researcher

Yoshiharu Kobayashi

Outline

Effective pandemic preparedness relies on the active engagement of citizens and their willingness to support long-term investments in preparedness. While interest in preparedness may have surged in response to the COVID-19 pandemic, there is a serious concern that this enthusiasm may wane over time. Furthermore, our understanding of how pre-pandemic preparedness may influence the political dynamics during a pandemic and subsequent pandemic responses remains limited. Through a political science perspective, this project aims to identify political challenges in preparing for future pandemics and their implications for pandemic response.

Hiroki Saito

Establishing a platform of multi-platform trials for infectious diseases

Researcher

Hiroki Saito

Outline

This research aims not only to establish a Platform of Multi-platform Trials (PMPT), a new concept to connect multiple platform trials for infectious diseases, but also to address how to sustain and develop PMPT in the unique research environment in Japan, leading to the resilient society for infectious disease threats.

Shinya Tsuzuki

Optimization of infectious disease countermeasures by expanding the concept of willingness to pay

Researcher

Shinya Tsuzuki

Outline

The goal of this project is to determine the upper limit of “the cost that our society is willing to pay for infectious disease control” in order to prepare for a new pandemic that will eventually occur. The goal of this study is to optimize infectious disease countermeasures from both economic and health perspectives by determining the upper limit of the acceptable cost, or “willingness to pay”.

Miki Nagao

Research on Robust Elderly Welfare and Healthcare Systems Resilient to Infectious Diseases.

Researcher

Miki Nagao

Outline

In this research, I will analyze three key aspects using real-world data from the COVID-19 pandemic: 1. Analysis of cluster risk factors and visualization of outcomes in elderly-care facilities, 2. Assessment of the physical, mental, and economic impact on elderly welfare and healthcare stakeholders, and 3. Evaluation of time-sensitive initiatives implemented by local authorities. Furthermore, I will provide recommendations for building a resilient elderly welfare system that remains steadfast even during a pandemic, while also developing a seamless system to integrate welfare and healthcare.

Fuminari Miura

Infectious disease modelling for compressing large-scale data in society: theory and disease control

Researcher

Fuminari Miura

Outline

Mathematical modelling of infectious diseases is widely used as an important tool for policy making. This approach becomes more effective when combined with observational data on epidemic situations. In this project, I propose a modelling framework to integrate various data sources that reflect social activities of people and the spread of pathogens. By developing this framework, I aim to obtain more granular understanding of transmission dynamics among heterogeneous subgroups in a population and utilize such information to optimize the targeted interventions for disease control.