Jumpei Ito

Forecasting SARS-CoV-2 epidemic surges by an ultra-early detection of the next variants

Researcher

Jumpei Ito

Outline

The epidemic surge of SARS-CoV-2 is caused by the emergence of variants with higher transmissibility. In this study, I will develop an AI identifying novel variants, predicting the next predominant variant, and forecasting the epidemic surge. Furthermore, I will elucidate the characteristics of the next variant by collaborating with researchers in fundamental virology. I would like to contribute to establishing a society robust to the emergence and epidemic of SARS-CoV-2 variants.

Yoshifumi Uwamino

The research for constructing sustainable clinical laboratory systems under the pandemic

Researcher

Yoshifumi Uwamino

Outline

In this project, the reason why Japanese clinical laboratories were not able to fully respond to the demands of society and healthcare in the early stages of the COVID-19 pandemic will be seeked. Thus, a model of robust clinical laboratory system that can function stably and contribute to society in the event of another pandemic will be proposed by strengthening the self-help functions of individual laboratories through digitalization and automation, and by building a mutual aid system among laboratories using networks.

Akira Endo

Integrating decision science and infectious disease modelling for pandemic control

Researcher

Akira Endo

Outline

This project aims to propose a new approach that integrates decision science and infectious disease modelling, which allows quantitative assessment of control policies to optimise individual- and population-level risks and benefits during an outbreak. During an outbreak, individuals adjust their behaviour considering the community transmission level to maximise their utility; those behaviours then shape the progression of the outbreak to modify the risk-benefit balance for individiuals. Using vaccination and stay-at-home behaviours as key decision making processes in pandemics, optimal pandemic management strategies will be explored using model-based inference and simulation.

Yusuke Okubo

Building a Pandemic-Resilient Children’s Medical, Health, and Educational Collaboration Model

Researcher

Yusuke Okubo

Outline

Under the pandemic of COVID-19, I observed an inefficient medical care delivery system for children and poor coordination between medical care and education and between medical care and community health. Using large administrative data, I will analyze how the COVID-19 pandemic affected the healthcare system delivered to children and how the newly introduced healthcare policy had effects on it using causal inference and machine learning methods. I will investigate the regional medical network and conduct simulations using mathematical models to seek a sustainable children’s medical care system.

Akihisa Kato

Development of a technology platform that can respond rapidly to the next pandemic created by comprehensive knowledge

Researcher

Akihisa Kato

Outline

Accurate analysis of viruses, which are microparticles composed of nucleic acids and proteins, is the foundation of infectious disease control. However, viral genomes encode a large amount of non-calorical genetic information, and it is not easy to decode their entire contents. This research aims to create innovative technology to decode the non-standard genetic information of viruses, thereby establishing a social and technological framework for pandemic resilience.

Hideyuki Shimizu

Next-generation infectious disease control by integrating microbiology knowledge and AI

Researcher

Hideyuki Shimizu

Outline

Rapid drug discovery is critical as a social infrastructure against the next pandemic. By teaching artificial intelligence (AI) the properties of microorganisms, this study aims to achieve rapid and accurate drug discovery using AI for infectious diseases. Specifically, I will use deep learning to decipher the relationship between microbial proteins and compound affinity while simultaneously developing an AI that can efficiently identify antimicrobial peptides encoded in the microbe’s genome.

Eri Nakamura

Regional Control and Coordination between Residents and Firms Led by Public Utilities in Pandemics and Emergency Situations

Researcher

Eri Nakamura

Outline

The purpose of this study is to establish the method of constructing an optimal sustainable platform for control and coordination among residents and firms led by public utilities in emergency situations such as pandemics. Especially, the urban transport business is examined as a case of public utilities that have close contact with residents and customers through service providing process, and the water supply business is examined as a case that have close contact with the government and regulators through production process. This study aims to construct control and coordination network including these public utilities to integrate the regional society.

Shuhei Nomura

Empirical analyses of disease burden for building new health systems

Researcher

Shuhei Nomura

Outline

Burden of disease, a comprehensive and comparable health indicator, is important information for prioritizing health policy, but its use in Japan has been limited compared to other countries. This study aims to establish a foundation for the use of burden of disease to build new health systems at both national and global levels that are equitable, resilient, and sustainable beyond the COVID-19 crisis, while maintaining socioeconomic activity, and to generate evidence that will contribute to the discussion of Japan’s domestic and global health policies.

Takahiro Yamamoto

Historicizing personal identification and its implication for pandemic response: a case study of ID photographs in twentieth-century Japan

Researcher

Takahiro Yamamoto

Outline

Secure and precise personal identification is essential for the continuation of socioeconomic activities under a pandemic. This study will carry out historical analysis of policy discussions and public discourses over the spread of personal identification technologies, with a case study of ID photographs in twentieth-century Japan. Through the examination of its emergence, public responses, and format standardization, the project aims to better understand the background of its social acceptance and its relationship with privacy concerns. The research findings will contribute to a better implementation of pandemic response measures relating to personal identification in the future.