Population dynamics and diseases

Research output: Book/ReportPh.D. thesisResearch

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Population dynamics and diseases. / Eilersen, Andreas Thomas.

Niels Bohr Institute, Faculty of Science, University of Copenhagen, 2022. 133 p.

Research output: Book/ReportPh.D. thesisResearch

Harvard

Eilersen, AT 2022, Population dynamics and diseases. Niels Bohr Institute, Faculty of Science, University of Copenhagen.

APA

Eilersen, A. T. (2022). Population dynamics and diseases. Niels Bohr Institute, Faculty of Science, University of Copenhagen.

Vancouver

Eilersen AT. Population dynamics and diseases. Niels Bohr Institute, Faculty of Science, University of Copenhagen, 2022. 133 p.

Author

Eilersen, Andreas Thomas. / Population dynamics and diseases. Niels Bohr Institute, Faculty of Science, University of Copenhagen, 2022. 133 p.

Bibtex

@phdthesis{e85ef1a745d447f4a67664fe15f8d2f4,
title = "Population dynamics and diseases",
abstract = "Wherever multiple organisms coexist, there are population dynamics. This thesis set out to explore the previously less well-described dynamics that arise when a population of pathogenic organisms interact with populations of prey animals and their predators. The main question to be answered was whether prey species can use the pathogens they carry as weapons against their predators, makingsusceptibility to diseases not exclusively a problem from an evolutionary standpoint. It turned out that this was indeed the case. We subsequently quantified when this effect would be important.Finally, we discovered that ecosystems with multiple prey species exhibit chaotic behaviour when affected by an enzootic disease.The mathematical study of disease dynamics turned out to be highly relevant for the real world after the outbreak of the COVID-19 pandemic. Some of the complexities of disease spread are missed by traditional differential equation models of epidemics. Therefore, we produced several individualbased models for testing and quarantine strategies to mitigate COVID-19. Our models allowed us to investigate the impact of individual differences on epidemics. Under this headline, we examined the interaction between inhomogeneous disease spreading - or superspreading - and population density.We found that individual differences such as a tendency towards superspreading or inhomogeneous networks may explain some unforeseen dynamics of COVID-19. Finally, we developed evolutionary models that enabled us to guess at how SARS-CoV-2 may evolve in the future. The results of this second section point to a new understanding of epidemic diseases and particularly how to describe them mathematically",
author = "Eilersen, {Andreas Thomas}",
year = "2022",
language = "English",
publisher = "Niels Bohr Institute, Faculty of Science, University of Copenhagen",

}

RIS

TY - BOOK

T1 - Population dynamics and diseases

AU - Eilersen, Andreas Thomas

PY - 2022

Y1 - 2022

N2 - Wherever multiple organisms coexist, there are population dynamics. This thesis set out to explore the previously less well-described dynamics that arise when a population of pathogenic organisms interact with populations of prey animals and their predators. The main question to be answered was whether prey species can use the pathogens they carry as weapons against their predators, makingsusceptibility to diseases not exclusively a problem from an evolutionary standpoint. It turned out that this was indeed the case. We subsequently quantified when this effect would be important.Finally, we discovered that ecosystems with multiple prey species exhibit chaotic behaviour when affected by an enzootic disease.The mathematical study of disease dynamics turned out to be highly relevant for the real world after the outbreak of the COVID-19 pandemic. Some of the complexities of disease spread are missed by traditional differential equation models of epidemics. Therefore, we produced several individualbased models for testing and quarantine strategies to mitigate COVID-19. Our models allowed us to investigate the impact of individual differences on epidemics. Under this headline, we examined the interaction between inhomogeneous disease spreading - or superspreading - and population density.We found that individual differences such as a tendency towards superspreading or inhomogeneous networks may explain some unforeseen dynamics of COVID-19. Finally, we developed evolutionary models that enabled us to guess at how SARS-CoV-2 may evolve in the future. The results of this second section point to a new understanding of epidemic diseases and particularly how to describe them mathematically

AB - Wherever multiple organisms coexist, there are population dynamics. This thesis set out to explore the previously less well-described dynamics that arise when a population of pathogenic organisms interact with populations of prey animals and their predators. The main question to be answered was whether prey species can use the pathogens they carry as weapons against their predators, makingsusceptibility to diseases not exclusively a problem from an evolutionary standpoint. It turned out that this was indeed the case. We subsequently quantified when this effect would be important.Finally, we discovered that ecosystems with multiple prey species exhibit chaotic behaviour when affected by an enzootic disease.The mathematical study of disease dynamics turned out to be highly relevant for the real world after the outbreak of the COVID-19 pandemic. Some of the complexities of disease spread are missed by traditional differential equation models of epidemics. Therefore, we produced several individualbased models for testing and quarantine strategies to mitigate COVID-19. Our models allowed us to investigate the impact of individual differences on epidemics. Under this headline, we examined the interaction between inhomogeneous disease spreading - or superspreading - and population density.We found that individual differences such as a tendency towards superspreading or inhomogeneous networks may explain some unforeseen dynamics of COVID-19. Finally, we developed evolutionary models that enabled us to guess at how SARS-CoV-2 may evolve in the future. The results of this second section point to a new understanding of epidemic diseases and particularly how to describe them mathematically

M3 - Ph.D. thesis

BT - Population dynamics and diseases

PB - Niels Bohr Institute, Faculty of Science, University of Copenhagen

ER -

ID: 310504341