基于联邦学习的新冠肺炎疫情跨区域智慧防控技术——以上海市实践为例  

Cross-region smart COVID-19 pandemic management and control based on federated learning:With Shanghai as an example

作　　者：钱学胜 吴寰宇[4] 陈诚[5] 黄晓燕[4] 童庆[5] 戴伟辉[1,2] QIAN Xuesheng;WU Huanyu;CHEN Cheng;HUANG Xiaoyan;TONG Qing;DAI Weihui(Smart City Research Center,Fudan University,Shanghai 200433,China;School of Management,Fudan University,Shanghai 200433,China;Macao Institute of System Engineering,Macao University of Science and Technology,Macao 999078,China;Shanghai Center for Disease Control and Prevention,Shanghai 200336,China;Wonders Information Co.,Ltd.,Shanghai 201112,China)

机构地区：[1]复旦大学智慧城市研究中心,上海200433 [2]复旦大学管理学院,上海200433 [3]澳门系统工程研究所,中国澳门999078 [4]上海市疾病预防控制中心,上海200336 [5]万达信息股份有限公司,上海201112

出　　处：《科技导报》2021年第24期96-107,共12页Science & Technology Review

基　　金：国家重点研发计划项目(2018YFB2101100);教育部哲学社会科学研究重大课题攻关项目(19JZD010);国家自然科学基金面上项目(71971066);教育部人文社会科学研究规划基金项目(18YJA630019);上海市科技创新行动计划项目(20492420102);上海市哲学社会科学规划课题(2019BGL031)。

摘　　要：新冠肺炎病毒不断变异的毒株的系列新特征,给传统的传染病防控方法与公共卫生防控体系带来了巨大的挑战。充分发挥数字技术在抗疫过程中的关键赋能价值,全面构建精准的常态化监测预警及智慧防控体系,系应对上述挑战的有效途径。通过对疫情智慧防控体系构成要素的剖析,揭示联邦学习对建立跨区域、跨部门的智慧疫情防控体系的关键路径作用。并基于跨区域涉疫数据分类及防控工作要点,研究设计了基于联邦学习的跨区域疫情智慧防控技术及其平台应用。该应用已在上海市以及长三角区域的抗疫实践中取得了显著成效。SARS-CoV-2 and its variants,the viruses that cause the COVID-19 pandemic,have some new characteristics,such as the high transmissibility,the long incubation period,the sweeping susceptible population,and the high environmental endurance,so a key question of the pandemic management and control is monitoring the asymptomatic transmission in daily life and socioeconomic activities,especially,the wide-range of cross-region spread.These features pose a great challenge to the traditional pandemic management and control methods and the global public health surveillance and control system.An effective way to tackle this challenge is making full use of the digital technology in the pandemic management and control,and building an accurate regular epidemiological surveillance and smart pandemic management and control system.By analyzing the essential factors of a smart pandemic management and control system,the critical role of the federated learning in the practice of the cross-region and cross-department smart pandemic management and control is shown.According to the classifications of the cross-region pandemic-related data and the pandemic management and control requirements,the technology and the application of the cross-region smart pandemic management and control based on the federated learning are explored.This method is successfully applied in the COVID-19 pandemic management and control in Shanghai and Yangtze River Delta,providing a new pathway for the integrated decision-making and targeted pandemic management and control in China.This method is also instrumental for other countries in the pandemic management and control.

关 键 词：疫情联防联控 智慧防控 智慧城市 城市数字化转型 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程] R184[自动化与计算机技术—控制科学与工程]