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020 ▼a 9780438048225
035 ▼a (MiAaPQ)AAI10817243
035 ▼a (MiAaPQ)princeton:12545
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 247004
0820 ▼a 574.5
1001 ▼a Morris, Sinead Elizabeth.
24510 ▼a Heterogeneity across Scales: Modeling the Impact of Pathogen and Host Life Histories on the Dynamics of Acute Infections.
260 ▼a [S.l.]: ▼b Princeton University., ▼c 2018.
260 1 ▼a Ann Arbor: ▼b ProQuest Dissertations & Theses, ▼c 2018.
300 ▼a 249 p.
500 ▼a Source: Dissertation Abstracts International, Volume: 79-10(E), Section: B.
500 ▼a Adviser: Bryan T. Grenfell.
5021 ▼a Thesis (Ph.D.)--Princeton University, 2018.
520 ▼a Mathematical modeling is an essential tool in understanding and controlling the spread of infectious diseases. Although simple, ordinary differential equation models have provided many insights into dynamics at the population level, they are lim
520 ▼a First I consider host life history, in particular the impact of host dispersal on the spatial spread of disease. Mathematical models incorporating dispersal typically rely on highly resolved spatial data, which is challenging to obtain, particul
520 ▼a Next, I explore pathogen life history, and the impact of host-pathogen interactions on population dynamics. In Chapter 4 I show that incorporating heterogeneity in the strength of pathogen-conferred immunity can improve predictions of population
590 ▼a School code: 0181.
650 4 ▼a Ecology.
650 4 ▼a Applied mathematics.
650 4 ▼a Epidemiology.
690 ▼a 0329
690 ▼a 0364
690 ▼a 0766
71020 ▼a Princeton University. ▼b Ecology and Evolutionary Biology.
7730 ▼t Dissertation Abstracts International ▼g 79-10B(E).
773 ▼t Dissertation Abstract International
790 ▼a 0181
791 ▼a Ph.D.
792 ▼a 2018
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T14998343 ▼n KERIS ▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다.
980 ▼a 201812 ▼f 2019
990 ▼a ***1012033