About COVID-19 and AI Simulation Project
Simulation using AI and other technologies
The COVID-19 AI Simulation Project explores the potential use of technology to balance economic activities with measures to prevent the spread of COVID-19.
We collect and analyze data on the early detection of the spread of infection using AI and other technologies, conduct simulations, develop new technologies that contribute to infection prevention measures, and verify the results for social implementation.
Scientific approach from multiple perspectives:
Approaches from multiple perspectives are necessary to predict and respond to uncertain events such as the recent COVID-19 pandemic. It is important to discuss and examine the validity of various models and verification methods, and to encourage further refinement by exchanging opinions among teams and models adopting different approaches.
For example, in predicting infection, it is common to quantitatively grasp the infection situation using an infectious disease mathematical model called SEIR. On the other hand, in the actual world, various infection types can occur according to complex human movements. Thus, we consider the multi-agent model and complex network theory also useful, dynamically linking various elements in analyzing how infection spreads.
In addition, it is important as a basic scientific attitude to update hypotheses and simulation assumptions in accordance with the latest data and situations that are constantly updated. In this project, discussions are held as needed among teams that adopt multiple approaches, and the latest results are announced promptly based on analyses that are tailored to the strengths and characteristics of each model.
In this project, instead of coming to a simple prediction, we analyze various scenarios such as “What could happen if … takes place.” In situations where the prediction itself causes people’s behavioral changes, it is important to consider multiple policies that accommodate various possibilities under multiple scenarios, rather than providing a single-scenario solution to the uncertain situation.
The spread of COVID-19 is affected by a complex interplay of uncertain and diverse factors, such as the progress of vaccination, the amount of medical resources available, and the effects of declaring an emergency. The purpose of this project is to present materials for policy making assuming various scenarios using multiple analytical models.
Structure of this project:
There is a need for a system that promply provides scientific evidence in reponse to fast-changing situations. For this project, individual research and development teams and Open Collaboration Partners (OCP) (thereinafter, research team) are selected from among applicants from the public for each research area. In addition, to ensure the prompt publication of research results and scientific appropriateness, advisors provide advice on individual research and development themes from an expert perspective and announce the progress of research as needed.
In addition, the Expert Committee reports the progress and results of the project to the AI Advisory Board, which evaluates the project from a cross-project perspective.
Preparing for future pandemics:
Various measures are being taken to put an end to the novel coronavirus; however, the fight against the pandemic will not end with the novel coronavirus. To prepare for other pandemics in the future, it is important to accumulate and disclose analytical knowledge, leaving its traces in history.
We know that real-time access to a variety of data is necessary to accurately analyze infection conditions and make meaningful simulations. Data on highly granular human flow density, human flow movements, genome sequences, international immigration status, cluster analysis, and medical resources are some of these examples. Through this project, we work on the construction of system to access such data, and organize the knowledge that contributes to discussions on the ideal pandemic countermeasures for national security purposes.
General description of the development research question
Since the World Health Organization (WHO) declared a state of emergency on January 31, 2020, the new coronavirus infection (COVID-19) has spread worldwide. In Japan, although the third wave of infection has been reduced in some areas due to the declaration of a state of emergency since October 2020, it has not been completely contained, and there are fears that the infection will spread again due to rebound caused by the new normal lifestyle and mutated species.
To achieve the right balance to conduct economic activities and contain the spread of COVID-19, we will collect and analyze data related to the early detection of the spread of infection using AI, etc. at corporate and academic institutions, develop new technologies that contribute to infection prevention measures, and conduct surveys and research to verify the results for social implementation. The purpose of this simulation project is to carry out these activities to contribute to the resolution of social issues and the formulation and implementation of necessary policy recommendations and concrete measures based on the results of the project.
Description of research areas for FY2021
FY2021 Research Area 1: Early detection of the spread of infection
Research and development will be carried out for the purpose of realizing new technology to detect the spread of infectious diseases at an early stage by data analysis using AI, etc.
- Is it possible to propose measures to catch signs of the spread of infectious diseases by analyzing data using AI, etc. based on information on SNS/Websites?
- In order to prevent re-spread of infection in areas where the declaration of a state of emergency has been lifted, is it possible to detect changes in the situation at an early stage by monitoring the status of infection through extensive testing in downtown areas?
- Is it possible to verify the timing, subjects, and the extent of PCR, breath test, specimen test, etc. to be conducted on community infection rates, in order to accurately catch signs of the spread of infectious diseases? In that case, is it possible to present the best mix from the viewpoint of cost effectiveness?
- Is it possible to develop an application and an information processing system that grasps the health status of people while preserving anonymity, to be applied in preventive measures?
- Is it possible to grasp the risk in the community by developing sensing devices such as sensors to observe viruses and coughs and developing appropriate device distribution and installation strategies?
- Is it possible to detect the inflow from overseas and the spatiotemporal spread in Japan as early as possible by combining the base sequence data of the virus with the human flow data, in order to present specific countermeasures?
- Based on the status of vaccination and various monitoring data, is it possible to detect local spread of infection and spread of variants after the progress of vaccination at an early stage?
- Based on the knowledge and data obtained under the above themes, is it possible to propose measures for early detection and prediction of the spread of infection?
FY2021 Research Area 2: Simulations on infection prevention
We conduct research and development for the purpose of simulating and verifying the situation of virus dispersion and reflecting it in various guidelines.
- Is it possible to present measures to reduce the risk of infection in situations where the risk of infection is considered high by focusing on the occurrence status and location of cluster cases?
- For places and events involving many people, is it possible to conduct a risk assessment of these events from the perspective of improved infection prevention measures and event restrictions?
- Is it possible to conduct a rapid examination at the time of entry at events and large-scale facilities and to continuously monitor the community infection rate?
- The themes of the simulation will be reviewed and added as needed in consultation with experts according to the situation.
FY2021 Research Area 3: Simulation of infection spread and control
The objectives of this research and development is to build a simulator (software) that can estimate the infection status and determine the impact of infection on medical care and the economy.
- With regard to COVID-19 and infectious diseases that will occur in the future, is it possible to construct a highly versatile simulator (software) that can easily and quickly predict the spread of infection and estimate the effectiveness of infection control measures (business hours restrictions, travel restrictions, telework, inspection/priority inspection, quarantine, contact confirmation apps, etc.)? Is it possible to simulate not only the prediction of the number of infected people and the number of seriously ill people, but also the over- and under-availability of medical resources, the impact on the economy, vaccination strategies, etc.? Can the simulator be made into a platform to facilitate the addition of new functions, data linkage, and visualization? Furthermore, is it possible to open source simulators and analytical systems and promote their use and development within and outside Japan? Can the platform be used to monitor the outbreak not only during COVID-19 and future pandemics, but also during normal times? In addition, is it possible to implement a function that enables rapid simulation against possible mutants of SARA-CoV-2, as well as possible future outbreaks of unknown coronaviruses and flu viruses?
- In preparation for the Tokyo Olympic and Paralympic Games, is it possible to collect and analyze data on immigration inspections of foreign visitors to Japan? In expanding the acceptance of overseas travelers, is it possible to verify the impact on the spread of infection from the false-negative test results and compliance with quarantine measures? In addition, is it possible to predict when a player and/or a spectator will be accepted?
- Is it possible to predict the impact of expanding and resuming international business travel and tourism and to make predictions that contribute to the strategy formulation for these activities?
- Is it possible to verify the coverage of vaccination and the suppressive effect on the spread of infection? Can an effective vaccination strategy be developed? Can quantitative data on the effects of vaccination be collected and reflected in medium- to long-term vaccination strategies and future vaccine development?
- The themes of the simulation will be reviewed and added as needed in consultation with experts according to the situation.
FY2021 Research Area 4: Introduction of new technology
We conduct R&D to support the construction of “new daily life” through the development of new technologies that contribute to the prevention of the spread of infection.
- Conduct research on trends in new technologies such as photocatalysts and ultraviolet rays (where appropriate, including verification of effectiveness).
- Is it possible to collect data for machine learning and develop an AI algorithm, such as determining the risk of deterioration by medical image analysis using AI?
2020 Research Areas Description of research questions for the year 2020
FY2020 Research Area 1:Indoor airflow simulation and visualization of droplets, which are necessary for improving the COVID-19 Infection Prevention Guidelines for each industrial sector
Objectives: To develop and implement a series of research and development programs that enable the formulation of guidelines for infection prevention, simulation and verification of virus spread in office, commercial facilities and public spaces, and implementation of effective infection prevention measures.
FY2020 Research Area 2:Effective combination of PCR, antibody tests, and other tests necessary for improving test efficiency and reliability
Objectives: To develop and deploy a series of technologies that enable effective implementation and data-based verification of the effectiveness of measures to reduce high-risk contact in daily life, as well as immediate visualization and inactivation of virus dispersal.
FY2020 Research Area 3:Effective combination of PCR, antibody tests, and other tests necessary for improving test efficiency and reliability
Objectives: To understand the immune response of the host immune system to SARS-CoV-2 infection, to enable monitoring of the infection situation at home and abroad, to establish reliable standard testing procedures to enable comparison of the effectiveness of infection control measures and prediction and verification of the impact of international human mobility, and to enable the sharing of such data.
FY2020 Research Area 4:Simulation and designing countermeasures against possible COVID-19 resurgence: predicting spreading of infection, estimating and verifying the effectiveness of countermeasures, and predicting demands on medical resources and optimizing their allocations
Objectives: Modeling and simulation of spreading infection and suppression of SARS-CoV-2, economic impacts of countermeasures, estimation of burden on medical resources is an important policy decision support tool. This part of the research program aims to develop, deploy, and continuously improve a modeling and simulation system to simulate the spread and control of infection in response to the ever-changing dynamics of the situation, and establish methods and operations for systematic data acquisition to make the simulation meaningful.
FY2020 Research Area 5:BioMedical Counter-measures: Analysis of CT scans for early detection and avoidance of severe illness, monitoring of patients with mild illness, prediction of risk of severe illness, understanding of the effects of viral mutation, etc.*
*Drug discovery, drug repurposing, vaccine development are handled in a separate program.
Objectives: to accelerate the acquisition of biological knowledge necessary for the development of infection control, vaccine development, and therapeutics to end COVID-19 at an early stage, and to research and develop methods for the detection of infected patients who need to be identified rapidly and with emphasis on super-spreaders and patients at risk of severe disease. Furthermore, we will rapidly establish a systematic clinical research base for emerging infectious diseases that are expected to emerge in the future. In addition, we will promote understanding of the changes in infectivity and pathogenicity caused by SARS-CoV-2 mutations and their impact on the development of vaccines and therapeutics, thereby contributing to the development of prevention and treatment methods. In addition, we will establish methods that can be applied to emerging viruses that are expected to emerge in the future.
Please note that the materials presented on this website explain the results of simulations conducted by researchers in the COVID-19 AI/Simulation Project, which are under the guidance of the Cabinet Secretariat to analyze the effects of corona countermeasures.The results of the simulations described in this document do not represent the official views of the government.