With the persistent outbreak of the COVID-19 pandemic, researchers from the Chinese Academy of Sciences and The City University of Hong Kong, working together closely under the Alliance of International Science Organizations (ANSO), developed the ANSO-PFIP (ANSO Pandemic Forecast Information Platform). The platform aims to significantly improve the predictability of COVID-19, publish information on the development trend of COVID-19 to ANSO member institutions and countries, and enrich the forecast information about COVID-19. The main functions of the platform are as follows:
1. Short-term prediction of COVID-19 pandemic
The method of model-data fusion significantly improves the accuracy of short-term epidemic forecast and quickly perceives the latest epidemic trend, which not only helps policymakers to quantify the effectiveness of public health and epidemic prevention policies but also helps the public to promptly understand the instant status about the epidemic.
2. Medium- and long-term prediction of COVID-19
The platform shows the COVID-19 in mild, mitigate, and suppressed interventions in three kinds of prevention and control scenarios, to reveal the development of pandemic in the long-term scale under the current outbreak's stage. The platform provides data of possible future infection, prompts the risk of epidemic rebound and assesses the impact on important events (such as the Winter Olympic Games), provides a scientific reference for long-term and epidemic prevention policy of fighting against the disease.
3. The temporal and spatial display of epidemic data
Based on the big data, cloud storage, distributed high-performance computing, and WebGIS technologies, we built the spatio-temporal data analysis module of the epidemic. The platform automatically analyzes the real-time change and spatio-temporal development trend of the epidemic to provide strong support for public decision-making. It is a beneficial exploration of international cooperation in controlling the pandemic.
4. Multi-model fusion
Through the academic cooperation between Mainland China and Hong Kong China, the platform can integrate data from different models and multi-sources to improve the accuracy and efficiency of epidemic prediction using machine learning, and plays an exemplary role in the scientific cooperation mechanism of controlling the epidemic under the framework of ANSO.
5. Automatic release of daily briefings and weekly reports
The automatic release of daily and weekly reports on COVID-19 has been provided. Comprehensible short-term and future trend assessments of COVID-19 are provided to the corresponding countries. An intelligent "data→knowledge→decision" epidemic information extraction system is initially formed, which has significantly improved the intelligence level of the epidemic forecast.
The ANSO-PFIP was jointly developed by the Chinese Academy of Sciences and the City University of Hong Kong. It is a complete, accurate, rapid, and scientific prediction platform for studying the dynamic development of COVID-19, so that the public can quickly percept the epidemic trend and take appropriate epidemic prevention measures to cooperate with the fighting against the epidemic. The platform meets the requirements of assessing the current quarantine policy, tracking management, developing a plan for future health demands, assisting enterprises in policy development, and conducting domestic and foreign aids. The platform provides accurate and effective scientific references for public health and socio-economic policies at regional and global levels.
Based on Bayesian estimation theory and ComDA, which is a data assimilation software package independently developed by the Chinese Academy of Sciences, the ANSO-PFIP adopted the Markov chain-Monte Carlo parameter estimation algorithm and ensembled Kalman filter data assimilation algorithm to perform short-term numerical predictions and error analyses of the future confirmed infected population. At the same time, a hybrid simulation of the SIR model and a simplified model of the City University of Hong Kong, which took the vaccination and human intervention measures into account, was used to publish the future long-term trend forecast of the epidemic. Predictions for countries in three kinds of prevention and control scenarios (the government and the management of epidemic suppressed intervention, mitigate intervention, and mild intervention) present the development trends of the epidemic (epidemic under suppressed interference scenario will be eased, while mild intervention may lead to severe outbreaks of the epidemic), then provide the references for the corresponding prevention and control measures. The platform introduces a data assimilation methodology, which is well applied in earth sciences, to balance the uncertainties and harmonize infectious disease model simulation and published data, thus to achieve high accurate COVID-19 forecast.
The ANSO-PFIP has been serving the COVID-19 control measures in countries and regions along the Belt and Road. Based on the ANSO-PFIP, two reports on the Belt and Road, i.e., "Suggestions on Epidemic Forecasting services for Global Response to COVID-19" and "Strategic Suggestions on China's Reopening under the Current Situation of COVID-19 Pandemic", have been reported by many media.
Trailer of World Internet Conference
Copyright © World Internet Conference. All rights Reserved
Presented by China Daily. 京ICP备13028878号-23
Copyright © World Internet Conference. All rights Reserved Presented by China Daily. 京ICP备13028878号-23