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K. Deitsch, S. Lukehart, J. Stringer (2009)
Common strategies for antigenic variation by bacterial, fungal and protozoan pathogensNature Reviews Microbiology, 7
J.A.P. Heesterbeek (2002)
A Brief History of R0 and a Recipe for its CalculationActa Biotheoretica, 50
R. Anderson, R. May (1979)
Population biology of infectious diseases: Part INature, 280
Zhipeng Cai, Tong Zhang, X. Wan (2012)
Antigenic distance measurements for seasonal influenza vaccine selection.Vaccine, 30 2
U. Dieckmann (2002)
Adaptive Dynamics of Pathogen–Host Interactions
JAP Heesterbeek (2002)
A brief history of R 0 and a recipe for its calculationActa Biotheor, 50
Y. Haraguchi, Akira Sasaki (1996)
Host-parasite arms race in mutation modifications: indefinite escalation despite a heavy load?Journal of theoretical biology, 183 2
D. Heinzmann, A. Barbour, P. Torgerson (2011)
A MECHANISTIC INDIVIDUAL-BASED TWO-HOST INTERACTION MODEL FOR THE TRANSMISSION OF A PARASITIC DISEASEInternational Journal of Biomathematics, 04
P. Rohani, R. Breban, D. Stallknecht, J. Drake (2009)
Environmental transmission of low pathogenicity avian influenza viruses and its implications for pathogen invasionProceedings of the National Academy of Sciences, 106
Alexander Lange, N. Ferguson (2009)
Antigenic Diversity, Transmission Mechanisms, and the Evolution of PathogensPLoS Computational Biology, 5
O. Diekmann, J. Heesterbeek, J. Metz (1990)
On the definition and the computation of the basic reproduction ratio R0 in models for infectious diseases in heterogeneous populationsJournal of Mathematical Biology, 28
P. Driessche, James Watmough (2002)
Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission.Mathematical biosciences, 180
Thibault Nidelet, J. Koella, O. Kaltz (2009)
Effects of shortened host life span on the evolution of parasite life history and virulence in a microbial host-parasite systemBMC Evolutionary Biology, 9
J. Plotkin, J. Dushoff, S. Levin (2002)
Hemagglutinin sequence clusters and the antigenic evolution of influenza A virusProceedings of the National Academy of Sciences of the United States of America, 99
(WHO (2016) Life expectancy increased by 5 years since 2000, but health inequalities persist. In World Health Statistics: Monitoring Health for the SDG’s, p 7. ISBN 978-92-4-156526-4)
WHO (2016) Life expectancy increased by 5 years since 2000, but health inequalities persist. In World Health Statistics: Monitoring Health for the SDG’s, p 7. ISBN 978-92-4-156526-4WHO (2016) Life expectancy increased by 5 years since 2000, but health inequalities persist. In World Health Statistics: Monitoring Health for the SDG’s, p 7. ISBN 978-92-4-156526-4, WHO (2016) Life expectancy increased by 5 years since 2000, but health inequalities persist. In World Health Statistics: Monitoring Health for the SDG’s, p 7. ISBN 978-92-4-156526-4
(WHO (2017) Ebola virus disease. http://www.who.int/mediacentre/factsheets/fs103/en/. Accessed 31 Jan 2018)
WHO (2017) Ebola virus disease. http://www.who.int/mediacentre/factsheets/fs103/en/. Accessed 31 Jan 2018WHO (2017) Ebola virus disease. http://www.who.int/mediacentre/factsheets/fs103/en/. Accessed 31 Jan 2018, WHO (2017) Ebola virus disease. http://www.who.int/mediacentre/factsheets/fs103/en/. Accessed 31 Jan 2018
E. Brooks-Pollock, G. Roberts, M. Keeling (2014)
A dynamic model of bovine tuberculosis spread and control in Great BritainNature, 511
Souvik Bhattacharya, M. Martcheva, Xuezhi Li (2014)
A PREDATOR-PREY-DISEASE MODEL WITH IMMUNE RESPONSE IN INFECTED-PREY ∗Journal of Mathematical Analysis and Applications, 411
RM Anderson, RM May (1995)
Infectious diseases of humans
(2016)
Life expectancy increased by 5 years since 2000, but health inequalities persistSaudi Medical Journal, 37
M. Alexander, Sarah Dietrich, Yi Hua, S. Moghadas (2009)
A comparative evaluation of modelling strategies for the effect of treatment and host interactions on the spread of drug resistanceJournal of Theoretical Biology, 259
M. Baalen, M. Sabelis (1995)
The milker-killer dilemma in spatially structured predator-prey interactionsOikos, 74
(Sigmund K, Sabelis MW, Dieckmann U, Metz JAJ (2002) Adaptive dynamics of pathogen-host interactions. In: Dieckmann U, Metz JAJ, Sabelis MW, Sigmund K (eds) Adaptive dynamics of infectious diseases: in pursuit of virulence management. Cambridge University Press, International Institute for Applied Systems Analysis, Cambridge, Laxenburg, pp 39–59)
Sigmund K, Sabelis MW, Dieckmann U, Metz JAJ (2002) Adaptive dynamics of pathogen-host interactions. In: Dieckmann U, Metz JAJ, Sabelis MW, Sigmund K (eds) Adaptive dynamics of infectious diseases: in pursuit of virulence management. Cambridge University Press, International Institute for Applied Systems Analysis, Cambridge, Laxenburg, pp 39–59Sigmund K, Sabelis MW, Dieckmann U, Metz JAJ (2002) Adaptive dynamics of pathogen-host interactions. In: Dieckmann U, Metz JAJ, Sabelis MW, Sigmund K (eds) Adaptive dynamics of infectious diseases: in pursuit of virulence management. Cambridge University Press, International Institute for Applied Systems Analysis, Cambridge, Laxenburg, pp 39–59, Sigmund K, Sabelis MW, Dieckmann U, Metz JAJ (2002) Adaptive dynamics of pathogen-host interactions. In: Dieckmann U, Metz JAJ, Sabelis MW, Sigmund K (eds) Adaptive dynamics of infectious diseases: in pursuit of virulence management. Cambridge University Press, International Institute for Applied Systems Analysis, Cambridge, Laxenburg, pp 39–59
M. Keeling, B. Grenfell (2000)
Individual-based perspectives on R(0).Journal of theoretical biology, 203 1
O. Diekmann (1996)
Mathematical Epidemiology of Infectious Diseases
E. Numfor, Souvik Bhattacharya, S. Lenhart, M. Martcheva (2014)
Optimal Control in Coupled Within-host and Between-host ModelsMathematical Modelling of Natural Phenomena, 9
J. Heesterbeek, J. Metz (2009)
On the Definition and the Computation of the Basic Reproduction Ratio
M.C.M. Jong, A. Stegeman, J. Goot, Guus Koch (2009)
Intra- and interspecies transmission of H7N7 highly pathogenic avian influenza virus during the avian influenza epidemic in The Netherlands in 2003.Revue scientifique et technique, 28 1
R. Neher, T. Bedford, R. Daniels, C. Russell, B. Shraiman (2015)
Prediction, dynamics, and visualization of antigenic phenotypes of seasonal influenza virusesProceedings of the National Academy of Sciences, 113
J. Heffernan, R. Smith, L. Wahl (2005)
Perspectives on the basic reproductive ratioJournal of The Royal Society Interface, 2
M. Keeling (1999)
The effects of local spatial structure on epidemiological invasionsProceedings of the Royal Society of London. Series B: Biological Sciences, 266
P. Ewald (1983)
Host-Parasite Relations, Vectors, and the Evolution of Disease SeverityAnnual Review of Ecology, Evolution, and Systematics, 14
The basic reproduction ratio, R 0, is a fundamental concept in epidemiology. It is defined as the total number of secondary infections brought on by a single primary infection, in a totally susceptible population. The value of R 0 indicates whether a starting epidemic reaches a considerable part of the population and causes a lot of damage, or whether it remains restricted to a relatively small number of individuals. To calculate R 0 one has to evaluate an integral that ranges over the duration of the infection of the host. This duration is, of course, limited by remaining host longevity. So, R 0 depends on remaining host longevity and in this paper we show that for long-lived hosts this aspect may not be ignored for long-lasting infections. We investigate in particular how this epidemiological measure of pathogen fitness depends on host longevity. For our analyses we adopt and combine a generic within- and between-host model from the literature. To find the optimal strategy for a pathogen from an evolutionary point of view, we focus on the indicator $$R_0^{{opt}}$$ R 0 opt , i.e., the optimum of R 0 as a function of its replication and mutation rates. These are the within-host parameters that the pathogen has at its disposal to optimize its strategy. We show that $$R_0^{{opt}}$$ R 0 opt is highly influenced by remaining host longevity in combination with the contact rate between hosts in a susceptible population. In addition, these two parameters determine whether a killer-like or a milker-like strategy is optimal for a given pathogen. In the killer-like strategy the pathogen has a high rate of reproduction within the host in a short time span causing a relatively short disease, whereas in the milker-like strategy the pathogen multiplies relatively slowly, producing a continuous small amount of offspring over time with a small effect on host health. The present research allows for the determination of a bifurcation line in the plane of host longevity versus contact rate that forms the boundary between the milker-like and killer-like regions. This plot shows that for short remaining host longevities the killer-like strategy is optimal, whereas for very long remaining host longevities the milker-like strategy is advantageous. For in-between values of host longevity, the contact rate determines which of both strategies is optimal.
Acta Biotheoretica – Springer Journals
Published: Feb 19, 2018
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