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TransCode:Uncovering COVID-19 transmission patterns via deep learning

Infectious Diseases of Poverty 2023年第1期12卷 82-101页

作者： Jinfu Ren Mutong liu Yang liu Jiming Liu Department of Computer Science Hong Kong Baptist UniversityHong Kong SARChina

Background The heterogeneity of COVID-19 spread dynamics is determined by complex spatiotemporal transmission patterns at a fine scale,especially in densely populated regions.In this study,we aim to discover such fine-scale transmission patterns via deep learning.Methods We introduce the notion of TransCode to characterize fine-scale spatiotemporal transmission patterns of COVID-19 caused by metapopulation mobility and contact behaviors.First,in Hong Kong,China,we construct the mobility trajectories of confirmed cases using their visiting records.Then we estimate the transmissibility of individual cases in different locations based on their temporal infectiousness distribution.Integrating the spatial and temporal information,we represent the TransCode via spatiotemporal transmission networks.Further,we propose a deep transfer learning model to adapt the TransCode of Hong Kong,China to achieve fine-scale transmission characterization and risk prediction in six densely populated metropolises:New York City,San Francisco,Toronto,London,Berlin,and Tokyo,where fine-scale data are limited.All the data used in this study are publicly available.Results The TransCode of Hong Kong,China derived from the spatial transmission information and temporal infectiousness distribution of individual cases reveals the transmission patterns(e.g.,the imported and exported transmission intensities)at the district and constituency levels during different COVID-19 outbreaks waves.By adapting the TransCode of Hong Kong,China to other data-limited densely populated metropolises,the proposed method outperforms other representative methods by more than 10%in terms of the prediction accuracy of the disease dynamics(i.e.,the trend of case numbers),and the fine-scale spatiotemporal transmission patterns in these metropolises could also be well captured due to some shared intrinsically common patterns of human mobility and contact behaviors at the metapopulation level.Conclusions The fine-scale transmission patterns due to the metapopulation level

关键词： COVID-19 Densely populated regions Spatiotemporal transmission dynamics and heterogeneity Meta-population Human mobility and contact behaviors TransCode Deep transfer learning

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Optimal resource allocation with spatiotemporal transmission discovery for efective disease control

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Infectious Diseases of Poverty 2022年第2期11卷 102-103页

作者： Jinfu Ren Mutong liu Yang liu Jiming Liu Department of Computer Science Hong Kong Baptist UniversityKowloonHong Kong Special Administrative RegionPeople’s Republic of China

Background:The new waves of COVID-19 outbreaks caused by the SARS-CoV-2 Omicron variant are developing rapidly and getting out of control around the world,especially in highly populated regions.The healthcare capacity(especially the testing resources,vaccination coverage,and hospital capacity)is becoming extremely insufcient as the demand will far exceed the supply.To address this time-critical issue,we need to answer a key question:How can we efectively infer the daily transmission risks in diferent districts using machine learning methods and thus lay out the corresponding resource prioritization strategies,so as to alleviate the impact of the Omicron outbreaks?Methods:We propose a computational method for future risk mapping and optimal resource allocation based on the quantitative characterization of spatiotemporal transmission patterns of the Omicron variant.We collect the publicly available data from the ofcial website of the Hong Kong Special Administrative Region(HKSAR)Government and the study period in this paper is from December 27,2021 to July 17,2022(including a period for future prediction).First,we construct the spatiotemporal transmission intensity matrices across diferent districts based on infection case records.With the constructed cross-district transmission matrices,we forecast the future risks of various locations daily by means of the Gaussian process.Finally,we develop a transmission-guided resource prioritization strategy that enables efective control of Omicron outbreaks under limited capacity.Results:We conduct a comprehensive investigation of risk mapping and resource allocation in Hong Kong,China.The maps of the district-level transmission risks clearly demonstrate the irregular and spatiotemporal varying patterns of the risks,making it difcult for the public health authority to foresee the outbreaks and plan the responses accordingly.With the guidance of the inferred transmission risks,the developed prioritization strategy enables the optimal testing resource allocation for integrativ

关键词： COVID-19 Omicron outbreak Densely populated regions Spatiotemporal transmission risk Optimal resource allocation Integrative case management Efective disease control

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Systems thinking in combating infectious diseases

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Infectious Diseases of Poverty 2017年第1期6卷 1282-1288页

作者： Shang Xia Xiao-Nong Zhou Jiming Liu National Institute of Parasitic Diseases Chinese Center for Disease Control and PreventionShanghai 200025People’s Republic of China Key Laboratory of Parasite and Vector Biology National Health and Family Planning CommissionShanghai 200025People’s Republic of China WHO Collaborating Centre for Tropical Diseases Shanghai 200025People’s Republic of China Department of Computer Science Hong Kong Baptist UniversityKowloon TongHong Kong CDC-NIPD&HKBU-CSD Joint Research Laboratory for Intelligent Disease Surveillance and Control Shanghai 200025People’s Republic of China

The transmission of infectious diseases is a dynamic process determined by multiple factors originating from disease pathogens and/or parasites,vector species,and human populations.These factors interact with each other and demonstrate the intrinsic mechanisms of the disease transmission temporally,spatially,and socially.In this article,we provide a comprehensive perspective,named as systems thinking,for investigating disease dynamics and associated impact factors,by means of emphasizing the entirety of a system’s components and the complexity of their interrelated behaviors.We further develop the general steps for performing systems approach to tackling infectious diseases in the real-world settings,so as to expand our abilities to understand,predict,and mitigate infectious diseases.

关键词： Systems thinking Complex systems approach Infectious disease control

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Research on calculation method of text similarity based on smooth inverse frequency

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The Journal of China Universities of Posts and Telecommunications 2020年第2期27卷 56-64页

作者： Yuan Ye Yu Minmin liu jiming Key Laboratory of E-commerce and Modem Logistics Chongqing University of Posts and TelecommunicationsChongqing 400065China

In order to improve the accuracy of text similarity calculation,this paper presents a text similarity function part of speech and word order-smooth inverse frequency(PO-SIF)based on sentence vector,which optimizes the classical SIF calculation method in two aspects:part of speech and word order.The classical SIF algorithm is to calculate sentence similarity by getting a sentence vector through weighting and reducing noise.However,the different methods of weighting or reducing noise would affect the efficiency and the accuracy of similarity calculation.In our proposed PO-SIF,the weight parameters of the SIF sentence vector are first updated by the part of speech subtraction factor,to determine the most crucial words.Furthermore,PO-SIF calculates the sentence vector similarity taking into the account of word order,which overcomes the drawback of similarity analysis that is mostly based on the word frequency.The experimental results validate the performance of our proposed PO-SIF on improving the accuracy of text similarity calculation.

关键词： word2vec SIF part-of-speech word order similarity

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Accessing the syndemic of COVID-19 and malaria in tervention in Africa

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Infectious Diseases of Poverty 2021年第1期10卷 14-25页

作者： Benyun Shi Jinxin Zheng Shang Xia Shan Lin Xinyi Wang Yang liu Xiao-Nong Zhou Jiming Liu School of Computer Science and Technology Nanjing Tech UniversityNanjing 211800JiangsuChina National Institute of Parasitic Diseases Chinese Center for Disease Control and PreventionShanghai 200025China Key Laboratory of Parasite and Vector Biology Ministry of HealthShanghai 200025China Chinese Center for Tropical Diseases Research Shanghai 200025China WHO Collaborating Centre for Tropical Diseases Shanghai 200025China National Center for International Research on Tropical Diseases Ministry of Science and TechnologyShanghai 200025China School of Global Health Chinese Center for Tropical Diseases ResearchShanghai Jiao Tong University School of MedicineShanghai 200025China College of Information Engineering Nanjing University of Finance EconomicsNanjing 210003JiangsuChina Department of Computer Science Hong Kong Baptist UniversityHong KongChina.

Background:The pandemic of the coronavirus disease 2019(COVID-19)has caused substantial disruptions to health services in the low and middle-income countries with a high burden of other diseases,such as malaria in sub-Saharan Africa.The aim of this study is to assess the impact of COVID-19 pandemic on malaria transmission potential in malaria-endemic countries in Africa.Methods:We present a data-driven method to quantify the extent to which the COVID-19 pandemic,as well as various non-pharmaceutical interventions(NPIs),could lead to the change of malaria transmission potential in 2020.First,we adopt a particle Markov Chain Monte Carlo method to estimate epidemiological parameters in each country by fitting the time series of the cumulative number of reported COVID-19 cases.Then,we simulate the epidemic dynamics of COVID-19 under two groups of NPIs:(1)contact restriction and social distanci ng,and(2)early ide ratification and isolation of cases.Based on the simulated epidemic curves,we quantify the impact of COVID-19 epidemic and NPIs on the distribution of insecticide-treated nets(ITNs).Finally,by treating the total number of ITNs available in each country in 2020,we evaluate the negative effects of COVID-19 pandemic on malaria transmission potential based on the notion of vectorial capacity.Results:We con duct case studies in four malaria-endemic coun tries,Ethiopia,Nigeria,Tanza nia,and Zambia,in Africa.The epidemiological parameters(i.e.;the basic reproduction number R°and the duration of infection D1)of COVID-19 in each country are estimated as follows:Ethiopia(Rq=1.57,D1=5.32),Nigeria(Ro=2.18,D1=6.58),Tanzania(Ro=2.47,D1=6.01),and Zambia(R0=2.12,D1=6.96).Based on the estimated epidemiological parameters,the epidemic curves simulated under various NPIs indicated that the earlier the interventions are implemented,the better the epidemic is controlled.Moreover,the effect of combined NPIs is better than contact restriction and social di st a ncing only.By treating the total number of ITNs available in each count

关键词： COVID-19 pandemic Non-pharmaceutical interventions Particle Markov chain Monte Carlo Insecticidetreated nets Vectorial capacity Malaria transmission potential

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Optimization of the separation unit of methanol to propylene(MTP)process and its application

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Chinese Journal of Chemical Engineering 2019年第5期27卷 1089-1093页

作者： Zizong Wang Hongqian liu jiming Wang East China University of Science and Technology Shanghai 200237China China Petrochemical Corporation Beijing 100029China SINOPEC Engineering Incorporation Beijing 100101China

Based on a typical gas composition from a methanol-to-propylene (MTP) reactor, and guided by a requirement to recover both propylene and ethylene, three separation strategies are studied and simulated by using PROI1 package. These strategies are sequential separation, front-end dethanization, and front-end depropanization. The process does not involve an ethylene refrigeration system, using the separated stream as absorbent, and absorbing further the medium-pressure demethanization, and a proprietary technology by combining intercooling oil absorption and throttle expansio n. In fluences of different process streams as absorbent are studied on energy consumptions, propylene and ethylene recovery percentages, and other key-performance indicators of the separation strategies. Based on a commercial MTP plant with a methanol capacity of 1700 kt·a^-1, the simulated results show that the front-end dethanization using the C4 mixture as absorbent is the optimal separation strategy, in which the standard fuel oil consumption (a key-performance in dicator of energy con sumption) is 18.97 kt·h^-1, the total power consumption of two compressors is 22.4 MW, the propylene recovery percentage is 99.70%, and the ethylene recovery percentage is 99.70%. For a further improvement, the pre-dethanization and thermal coupling methods are applied. By using front-end pre-dethanization (partial cutting) with debutanizeroverhead, i.e. the C4 mixture, as absorbent, the power consumption of the compressors decreases to 19.9 MW, an 11% reduction compared with the clear-cutting method. The energy consumption for the dual compressors for crude gaseous product mixture and main product propylene refrigeration is 16.69 MW, 16.55% lower than that of the present MTP industrial plant with the same scale, and a total energy consumption of 20 MW for the triple compressors including product gas mixture compression, and ethylene and propylene refrigeration.

关键词： Heat integration distillation Methanol to propylene Ethylene Propylene

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Assessing the spatiotemporal malaria transmission intensity with heterogeneous risk factors:A modeling study in Cambodia

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Infectious Disease Modelling 2023年第1期8卷 253-269页

作者： Mutong liu Yang liu Ly Po Shang Xia Rekol Huy Xiao-Nong Zhou Jiming Liu Department of Computer Science Hong Kong Baptist UniversityHong Kong Special administrative region of China HKBU-CSD&NIPD Joint Research Laboratory for Intelligent Disease Surveillance and Control China National Center for Parasitology Entomology&Malaria Control(CNM)Ministry of HealthPhnom PenhCambodia National Institute of Parasitic Diseases Chinese Center for Disease Control and PreventionShanghaiChina Key Laboratory of Parasite and Vector Biology National Health and Commission of the People's Republic of ChinaShanghaiChina WHO Collaborating Center for Tropical Diseases ShanghaiChina

Malaria control can significantly benefit from a holistic and precise way of quantitatively measuring the transmission intensity,which needs to incorporate spatiotemporally varying risk factors.In this study,we conduct a systematic investigation to characterize malaria transmission intensity by taking a spatiotemporal network perspective,where nodes capture the local transmission intensities resulting from dominant vector species,the population density,and land cover,and edges describe the cross-region human mobility patterns.The inferred network enables us to accurately assess the transmission intensity over time and space from available empirical observations.Our study focuses on malaria-severe districts in Cambodia.The malaria transmission intensities determined using our transmission network reveal both qualitatively and quantitatively their seasonal and geographical characteristics:the risks increase in the rainy season and decrease in the dry season;remote and sparsely populated areas generally show higher transmission intensities than other areas.Our findings suggest that:the human mobility(e.g.,in planting/harvest seasons),environment(e.g.,temperature),and contact risk(coexistences of human and vector occurrence)contribute to malaria transmission in spatiotemporally varying degrees;quantitative relationships between these influential factors and the resulting malaria transmission risk can inform evidence-based tailor-made responses at the right locations and times.

关键词： Malaria Transmission intensity assessment Spatiotemporal network Computational approach Heterogeneous risk factors

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Insight into the triggering effect of(Al,Mg,Ca,Mn)-oxy-sulfide inclusions on localized corrosion of weathering steel

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Journal of Materials Science & Technology 2021年第5期64卷 99-113页

作者： Pan liu Qinhao Zhang Xinran Li jiming Hu Fahe Cao Department of Chemistry Zhejiang UniversityHangzhou310027China School of Materials Sun Yat-sen UniversityGuangzhou510006China

The surface properties of weathering steel(WS)is very important for its service performance and safety,and the localized corrosion induced by inclusions is closely related to the surface properties of WS and its application.In the current work,a common spherical(Al,Mg,Ca,Mn)-oxy-sulfide inclusion was selected to investigate the corrosion evolution of complex inclusion and its effect on localized corrosion on WS surface.The results indicate the inclusion in WS consists of(Ca,Mn)sulfides part and(Ca,Al,Mg)oxides part with complex core-shell structure.Locally preferential dissolution occurs in(Ca,Mn)sulfides part as well as metal matrix around the inclusions.Furthermore,both parts of the inclusions with poor conductivity and high-density dislocation at metal matrix around the inclusions was found,which suggests that traditional micro-galvanic corrosion cell may not be the cause of inclusion-induced localized corrosion on WS surface at initial stage of corrosion.The variation in maximum and average depth around the inclusion or selected region with immersion time indicates that localized corrosion induced by inclusions is overwhelmed by uniform corrosion of WS in the latter stage of immersion,then the rust formed on WS surface consists of two layers.

关键词： Weathering steel Inclusions Marine environment Localized corrosion Rust

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Seasonal variation in particle contribution and aerosol types in Shanghai based on satellite data from MODIS and CALIOP

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Particuology 2020年第4期18卷 18-25页

作者： Qiong liu Xin liu Tongqiang liu Yanming Kang Yonghang Chen jiming Li Hua Zhang College of Environmental Science and Engineering Donghua UniversityShanghaiChina College of Information Science and Technology Donghua UniversityShanghaiChina Key Laboratory for Semi-Arid Climate Change of the Ministry of Education College of Atmospheric Sciences Lanzhou UniversityLanzhouChina State Key Laboratory of Severe Weather Chinese Academy of Meteorological SciencesBeijingChina

Although the concentration of atmospheric particulate matter in Shanghai has declined in recent years,aerosols remain one of the major pollutants affecting air quality.Herein,spatio-seasonal variation in aerosol optical properties and aerosol types were studied overa 10-year period(2006-2015)in Shanghai,China,using satellite data from Moderate Resolution Imaging Spectroradiometer(MODIS)and CloudAerosol Lidar with Orthogonal Polarization(CALIOP).The average aerosol optical depth values for central urban and suburban areas of Shanghai were between 0.9 and 1.0.Clear seasonal variation in aerosol concentrations occurred,causing strongest attenuation in summer and weakest attenuation in autumn.Polluted dust,polluted continental(urban/industrial)and smoke aerosols were the main aerosol types.Desert dust aerosols occurred in the Shanghai area at higher altitudes(greater than 3 km)in spring,related to dusty weather in the north;while in winter,smoke aerosols occurred at high altitudes,related to haze pollution in the north.The aerosols detected in autumn were mainly from local sources,comprising polluted dust,polluted continental,and smoke aerosols.Aerosols in Shanghai clearly reflect both local and regional sources at different times.

关键词： Aerosol optical depth(AOD) Aerosol type Attenuation Seasonal variation Vertical distribution

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The Environmental Impact of Plastic Waste

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Journal of Environmental & Earth Sciences 2020年第2期2卷 26-35页

作者： Boyu Jiang jiming Yu Yihang liu Public health and Preventive Medicine Health Inspection and QuarantineNorth China University of Science and T echnologyTangshanHebei063210China Process Equipment and Control Engineering University of Science and Technology LiaoNingAnshanLiaoning114051China Preventive medicine Public health and Preventive MedicineNorth China University of Science and TechnologyTangshanHebei063210China

The pollution caused by disposable plastic products is becoming moreand more serious, and “plastic limit” has become a global consensus. Thisarticle mainly discusses the pollution problem from the following aspects:Integrate all relevant important indicators to establish a multiple regressionmodel of the maximum amount of disposable plastic waste to estimatethe maximum amount of disposable waste in the future without causingfurther damage to the environment;Establish an environmental safety levelevaluation model and analyze the impact of plastic waste on environmentalsafety;Try to set the lowest level target that can be achieved by globalwaste at this stage, and conduct correlation analysis on the impact ofhumans, enterprises, and the environment;Select several countries basedon their comprehensive strengths, conduct a comparative analysis of theirplastic production, economic strength, and environment, and try to exploretheir responsibilities.

关键词： Multiple egression Fuzzy hierarchy Plastic waste Environmental safety

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