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Epidemic Surveillance of Influenza Infections:A Network-Free Strategy—Hong Kong Special Administrative Region,China,2008–2011

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China CDC weekly 2022年第46期4卷 1025-1031,I0002-I0005页

作者： Zhanwei Du Qi Tan Yuan Bai Lin Wang Benjamin J.Cowling Petter Holme WHO Collaborating Centre for Infectious Disease Epidemiology and Control School of Public HealthLi Ka Shing Faculty of MedicineThe University of Hong KongHong Kong SARChina Laboratory of Data Discovery for Health Limited(D24H) Hong Kong Science and Technology ParkHong Kong SARChina Department of Genetics University of CambridgeCambridgeUK Department of Computer Science Aalto UniversityEspooFinland

Introduction:The ease of coronavirus disease 2019(COVID-19)non-pharmacological interventions and the increased susceptibility during the past COVID-19 pandemic could be a precursor for the resurgence of influenza,potentially leading to a severe outbreak in the winter of 2022 and future seasons.The recent increased availability of data on Electronic Health Records(EHR)in public health systems,offers new opportunities to monitor individuals to mitigate outbreaks.Methods:We introduced a new methodology to rank individuals for surveillance in temporal networks,which was more practical than the static networks.By targeting previously infected nodes,this method used readily available EHR data instead of the contactnetwork structure.Results:We validated this method qualitatively in a real-world cohort study and evaluated our approach quantitatively by comparing it to other surveillance methods on three temporal and empirical networks.We found that,despite not explicitly exploiting the contacts’network structure,it remained the best or close to the best strategy.We related the performance of the method to the public health goals,the reproduction number of the disease,and the underlying temporal-network structure(e.g.,burstiness).Discussion:The proposed strategy of using historical records for sentinel surveillance selection can be taken as a practical and robust alternative without the knowledge of individual contact behaviors for public health policymakers.

关键词： network policy networks

Model Versions and Fast Algorithms for Network Epidemiology

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后勤工程学院学报 2014年第3期30卷 1-7页

作者： Petter Holme Dept.of Energy Science Sungkyunkwan University Dept.of Physics IceLab Ume University Dept.of Sociology Stockholm University

Network epidemiology has become a core framework for investigating the role of human contact patterns in the spreadingof infectious diseases.In network epidemiology,one represents the contact structure as a network of nodes(individuals)connected bylinks(sometimes as a temporal network where the links are not continuously active)and the disease as a compartmental model(whereindividuals are assigned states with respect to the disease and follow certain transition rules between the states).In this paper,we discussfast algorithms for such simulations and also compare two commonly used versions,one where there is a constant recovery rate(the numberof individuals that stop being infectious per time is proportional to the number of such people);the other where the duration of the diseaseis constant.The results show that,for most practical purposes,these versions are qualitatively the same.

关键词： network theory algorithm stochastic simulation infectious disease

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China CDC weekly 2022年第40期4卷 885-889,I0002-I0005页

作者： Yuan Bai Mingda Xu Caifen Liu Mingwang Shen Lin Wang Linwei Tian Suoyi Tan Lei Zhang Petter Holme Xin Lu Eric H.Y.Lau Benjamin J.Cowling Zhanwei Du WHO Collaborating Centre for Infectious Disease Epidemiology and Control School of Public HealthLi Ka Shing Faculty of MedicineThe University of Hong KongHong Kong Special Administrative RegionChina Laboratory of Data Discovery for Health Limited(D24H) Hong Kong Science ParkHong Kong Special Administrative RegionChina China-Australia Joint Research Center for Infectious Diseases School of Public HealthXi’an Jiaotong University Health Science CenterXi’an CityShaanxi ProvinceChina Department of Genetics University of CambridgeCambridge CB23EHUK College of Systems Engineering National University of Defense TechnologyChangsha CityHunan ProvinceChina Department of Computer Science Aalto UniversityEspooFinland Center for Computational Social Science Kobe UniversityKobeJapan

Introduction:Minimizing the importation and exportation risks of coronavirus disease 2019(COVID-19)is a primary concern for sustaining the“Dynamic COVID-zero”strategy in China.Risk estimation is essential for cities to conduct before relaxing border control measures.Methods:Informed by the daily number of passengers traveling between 367 prefectures(cities)in China,this study used a stochastic metapopulation model parameterized with COVID-19 epidemic characteristics to estimate the importation and exportation risks.Results:Under the transmission scenario(R0=5.49),this study estimated the cumulative case incidence of Changchun City,Jilin Province as 3,233(95%confidence interval:1,480,4,986)before a lockdown on March 14,2022,which is close to the 3,168 cases reported in real life by March 16,2022.In a total of 367 prefectures(cities),127(35%)had high exportation risks according to the simulation and could transmit the disease to 50%of all other regions within a period from 17 to 94 days.The average time until a new infection arrives in a location in 1 of the 367 prefectures(cities)ranged from 26 to 101 days.Conclusions:Estimating COVID-19 importation and exportation risks is necessary for preparedness,prevention,and control measures of COVID-19—especially when new variants emerge.

关键词： Export Changchun prevention

Substance graphs are optimal simple-graph representations of metabolism

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Chinese Science Bulletin 2010年第27期55卷 3161-3168页

作者： holme petter HUSS Mikael Department of Physics Ume University Department of Energy Science Sungkyunkwan University Science for Life Laboratory Stockholm Box 1031 171 21 SolnaSweden Computational and Systems Biology Genome Institute of Singapore

One approach to study the system-wide organization of biochemistry is to use statistical graph theory.In such heavily simplified methods,which disregard most of the dynamic aspects of biochemistry,one is faced with fundamental questions.One such question is how the chemical reaction systems should be reduced to a graph retaining as much functional information as possible from the original reaction system.In these graph representations,should the edges go between substrates and products,or substrates and substrates,or both?Should vertices represent substances or reactions?Different representations encode different information about the reaction system and affect network measures in different ways.This paper investigates which representation reflects the functional organization of the metabolic system in the best way,according to the defined criteria.Four different graph representations of metabolism(three where the vertices are metabolites,one where the vertices are reactions)are evaluated using data from different organisms and databases.The graph representations are evaluated by comparing the overlap between clusters(network modules)and annotated functions,and also by comparing the set of identified currency metabolites with those that other authors have identified using qualitative biological arguments.It is found that a"substance network",where all metabolites participating in a reaction are connected,is better than others,evaluated with respect to both the functional overlap between modules and functions and to the number and identity of the identified currency metabolites.

关键词：图形表示代谢物物质生物数据库反应体系化学反应系统顶点表示代谢产物

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Mobility in China, 2020: a tale of four phases

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National Science Review 2021年第11期8卷 110-120页

作者： Suoyi Tan Shengjie Lai Fan Fang Ziqiang Cao Bin Sai Bing Song Bitao Dai Shuhui Guo Chuchu Liu Mengsi Cai Tong Wang Mengning Wang Jiaxu Li Saran Chen Shuo Qin Jessica R.Floyd Zhidong Cao Jing Tan Xin Sun Tao Zhou Wei Zhang Andrew J.Tatem Petter Holme Xiaohong Chen Xin Lu School of Business Central South University Institute of Big Data and Internet Innovations Hunan University of Technology and Business College of Systems Engineering National University of Defense Technology WorldPop School of Geography and Environmental ScienceUniversity of Southampton School of Mathematics and Big Data Foshan University State Key Laboratory on Blind Signal Processing State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences Chinese Evidence-Based Medicine Center National Clinical Research Center for Geriatrics West China Hospital Sichuan University Big Data Research Center University of Electronic Science and Technology of China West China Biomedical Big Data Center West China Hospital Sichuan University Tokyo Tech World Hub Research Initiative Institute of Innovative Research Tokyo Institute of Technology

2020 was an unprecedented year,with rapid and drastic changes in human mobility due to the COVID-19 pandemic.To understand the variation in commuting patterns among the Chinese population across stable and unstable periods,we used nationwide mobility data from 318 million mobile phone users in China to examine the extreme fluctuations of population movements in 2020,ranging from the Lunar New Year travel season(chunyun), to the exceptional calm of COVID-19 lockdown,and then to the recovery period.We observed that cross-city movements,which increased substantially in chunyun and then dropped sharply during the lockdown,are primarily dependent on travel distance and the socio-economic development of cities.Following the Lunar New Year holiday,national mobility remained low until mid-February,and COVID-19 interventions delayed more than 72.89 million people returning to large cities.Mobility network analysis revealed clusters of highly connected cities,conforming to the social-economic division of urban agglomerations in China.While the mass migration back to large cities was delayed,smaller cities connected more densely to form new clusters.During the recovery period after travel restrictions were lifted,the netflows of over 55% city pairs reversed in direction compared to before the lockdown.These findings offer the most comprehensive picture of Chinese mobility at fine resolution across various scenarios in China and are of critical importance for decision making regarding future public-health-emergency response,transportation planning and regional economic development,among others.

关键词： human mobility travel restrictions COVID-19 mobile phone data behavioral response