LEADER 03791nam 2200505 450 001 996465345003316 005 20210217080723.0 010 $a3-030-52109-5 024 7 $a10.1007/978-3-030-52109-7 035 $a(CKB)4100000011457754 035 $a(DE-He213)978-3-030-52109-7 035 $a(MiAaPQ)EBC6353496 035 $a(PPN)250222124 035 $a(EXLCZ)994100000011457754 100 $a20210217d2020 uy 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aComputational epidemiology $efrom disease transmission modeling to vaccination decision making /$fJiming Liu, Shang Xia 205 $a1st ed. 2020. 210 1$aCham, Switzerland :$cSpringer,$d[2020] 210 4$dİ2020 215 $a1 online resource (XVIII, 113 p. 50 illus., 20 illus. in color.) 225 1 $aHealth information science 311 $a3-030-52107-9 320 $aIncludes bibliographical references and index. 327 $aParadigms in Epidemiology -- Computational Modeling in a Nutshell -- Developing Strategies for Vaccine Allocation -- Explaining Individuals? Vaccination Decisions -- Characterizing Socially-Influenced Vaccination Decisions -- Understanding the Impact of Social Media -- Welcome to the Era of Systems Epidemiology. 330 $aThis book provides a comprehensive introduction to computational epidemiology, highlighting its major methodological paradigms throughout the development of the field while emphasizing the needs for a new paradigm shift in order to most effectively address the increasingly complex real-world challenges in disease control and prevention. Specifically, the book presents the basic concepts, related computational models, and tools that are useful for characterizing disease transmission dynamics with respect to a heterogeneous host population. In addition, it shows how to develop and apply computational methods to tackle the challenges involved in population-level intervention, such as prioritized vaccine allocation. A unique feature of this book is that its examination on the issues of vaccination decision-making is not confined only to the question of how to develop strategic policies on prioritized interventions, as it further approaches the issues from the perspective of individuals, offering a well integrated cost-benefit and social-influence account for voluntary vaccination decisions. One of the most important contributions of this book lies in it offers a blueprint on a novel methodological paradigm in epidemiology, namely, systems epidemiology, with detailed systems modeling principles, as well as practical steps and real-world examples, which can readily be applied in addressing future systems epidemiological challenges. The book is intended to serve as a reference book for researchers and practitioners in the fields of computer science and epidemiology. Together with the provided references on the key concepts, methods, and examples being introduced, the book can also readily be adopted as an introductory text for undergraduate and graduate courses in computational epidemiology as well as systems epidemiology, and as training materials for practitioners and field workers. 410 0$aHealth information science. 606 $aEpidemiology$xData processing 606 $aEpidemiology$xComputer simulation 615 0$aEpidemiology$xData processing. 615 0$aEpidemiology$xComputer simulation. 676 $a614.40285 700 $aLiu$b Jiming$f1962-$0771474 702 $aXia$b Shang 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996465345003316 996 $aComputational epidemiology$91997597 997 $aUNISA