Research On Human Contact Pattern In The Domain Of Infectious Diseases

The mathematical model of infectious diseases,as an auxiliary means of public health decision-making,provides essential help in solving the challenges of infectious diseases.As the spread of most infectious diseases depends heavily on the human contact pattern,figuring out human contact patterns would be helpful in understanding the propagation of infectious diseases,predicting the outbreaks of infectious diseases,and controlling infectious diseases.This thesis mainly focuses on human contact pattern in the domain of infectious diseases,including pattern modeling,pattern inference,and pattern application.Pattern modeling is mainly used to construct a framework to characterize the contact behavior.Pattern inference can provide methods to infer the contact pattern.Pattern application can provide valuable services.In particular,we combine pattern modeling,pattern inference,and pattern application in a unified framework to conduct the research work concerning the following three issues:· Large-scale population contact pattern inference.The census data contained more comprehensive human social macro information.Using the census data,combining contact pattern modeling method and inference method,large-scale population contact pattern can be inferred.The inferred contact patterns can be used to predict the spread of infectious diseases and to guide the development of surveillance strategies in infectious diseases.· Large-scale population dynamic contact pattern inference.To understand the influence of contact pattern on the transmission of infectious diseases,besides the large-scale population contact pattern inference,another key issue is large-scale population dynamic contact pattern inference.This research line attempts to detect the times at which the contact pattern changes fundamentally and quantify how large it changes combined with the inferred contact patterns and the infectious disease measurement data.The research can be used to evaluate the effectiveness of control measures which be implemented during the spread of infectious diseases.Thus it can guide the public health decision-making in the face of emergencies.· Contact pattern application in early surveillance of infectious diseases.In the domain of infectious diseases,the contact pattern has many applications,such as the prediction of infectious disease transmission and the implementation of infectious disease control measures.Among them,early surveillance of infectious diseases as an important application,which can early detect and warn the infectious disease emergence.Thus it can provide the response time for public health institutions to respond to infectious diseases.Specifically,we have made the following contributions around the above research issues:1.Modelling and inferring large-scale population heterogeneous contact pattern.We introduce a heuristic method to infer heterogeneous contact pattern at an urban level in Hong Kong.Additionally,some outcome measures for Hong Kong will depend sensitively on the details of contact pattern.Some other outcome measures do not depend sensitively.So we analyze the similarity of different contact patterns and the sensitivities of incidence trends to these contact patterns.2.Modelling and inferring dynamic large-scale population heterogeneous contact patterns.Taking 2009 H1N1 in Hong Kong as an example,we propose a probabilistic framework to detect when the contact pattern changes and how it changes during the period of the infectious disease.This is accomplished by developing a model for integrating the inferred contact patterns and the infectious disease measurement data.The results can be assessed for the delay effect of control measures and give better advice to deal with infectious diseases.3.Optimizing sentinel surveillance in temporal network epidemiology.We introduce surveillance strategies which exploit dynamic contact network structure and learn from the vaccine strategies on dynamic contact network to early surveillance the emergence of infectious disease.Through the combination of the surveillance strategies on the dynamic network and on the static network,the result can be used to develop surveillance systems.