@article{siva-jothy_v_2020,
	title = {To {V}, {R0} to {V} ?},
	copyright = {All rights reserved},
	url = {https://era.ed.ac.uk/handle/1842/36740},
	doi = {10.7488/era/47},
	abstract = {Outbreaks of infectious disease can be caused by only a few highly infectious 
individuals. These individuals are produced by variation in traits affecting contact 
between infected and susceptible individuals, the likelihood that contact results in 
infection and the duration of infection. High-risk individuals are difficult to predict 
because traditional assessments of disease transmission, such as R0, rely on 
population averages that conceal the variation that produces high transmission-risk 
phenotypes. Contact rate between infected and susceptible individuals, is primarily 
determined by behaviour whereas physiological immunity is the main determinant 
of the likelihood that contact causes infection and infection duration. I characterise 
variation in traits affecting the determinants of disease transmission and use this to 
predict individual variation in disease transmission, V. Using the fruit fly, Drosophila 
melanogaster, and its viral pathogen Drosophila C Virus, I have found pervasive and 
complex effects of genetic and sex-specific variation, mating, and infection on suites 
of behaviours, physiological traits and outcomes of infection. Many of my results 
point to an individual’s disease transmission potential being determined by genetic 
background and sex. Males, for example, typically survive DCV infection longer than 
females, however the amount of virus they shed is also determined by their genetic 
background. To predict how this variation could affect disease transmission 
dynamics, I simulated outbreaks of DCV in theoretical populations. These 
populations exhibited genetic and sex-specific variation based on my experiments 
and significantly affected population-level outbreak dynamics. Differences in these 
dynamics highlight potentially high-risk transmission classes of individuals, defined 
by their genetic background and sex.},
	language = {en},
	urldate = {2020-02-12},
	journal = {University of Edinburgh},
	author = {Siva-Jothy, Jonathon Arumugam},
	month = jan,
	year = {2020},
}

{"_id":"BRKD65EjQxbugMmKW","bibbaseid":"sivajothy-tovr0tov-2020","author_short":["Siva-Jothy, J. A."],"bibdata":{"bibtype":"article","type":"article","title":"To V, R0 to V ?","copyright":"All rights reserved","url":"https://era.ed.ac.uk/handle/1842/36740","doi":"10.7488/era/47","abstract":"Outbreaks of infectious disease can be caused by only a few highly infectious individuals. These individuals are produced by variation in traits affecting contact between infected and susceptible individuals, the likelihood that contact results in infection and the duration of infection. High-risk individuals are difficult to predict because traditional assessments of disease transmission, such as R0, rely on population averages that conceal the variation that produces high transmission-risk phenotypes. Contact rate between infected and susceptible individuals, is primarily determined by behaviour whereas physiological immunity is the main determinant of the likelihood that contact causes infection and infection duration. I characterise variation in traits affecting the determinants of disease transmission and use this to predict individual variation in disease transmission, V. Using the fruit fly, Drosophila melanogaster, and its viral pathogen Drosophila C Virus, I have found pervasive and complex effects of genetic and sex-specific variation, mating, and infection on suites of behaviours, physiological traits and outcomes of infection. Many of my results point to an individual’s disease transmission potential being determined by genetic background and sex. Males, for example, typically survive DCV infection longer than females, however the amount of virus they shed is also determined by their genetic background. To predict how this variation could affect disease transmission dynamics, I simulated outbreaks of DCV in theoretical populations. These populations exhibited genetic and sex-specific variation based on my experiments and significantly affected population-level outbreak dynamics. Differences in these dynamics highlight potentially high-risk transmission classes of individuals, defined by their genetic background and sex.","language":"en","urldate":"2020-02-12","journal":"University of Edinburgh","author":[{"propositions":[],"lastnames":["Siva-Jothy"],"firstnames":["Jonathon","Arumugam"],"suffixes":[]}],"month":"January","year":"2020","bibtex":"@article{siva-jothy_v_2020,\n\ttitle = {To {V}, {R0} to {V} ?},\n\tcopyright = {All rights reserved},\n\turl = {https://era.ed.ac.uk/handle/1842/36740},\n\tdoi = {10.7488/era/47},\n\tabstract = {Outbreaks of infectious disease can be caused by only a few highly infectious \nindividuals. These individuals are produced by variation in traits affecting contact \nbetween infected and susceptible individuals, the likelihood that contact results in \ninfection and the duration of infection. High-risk individuals are difficult to predict \nbecause traditional assessments of disease transmission, such as R0, rely on \npopulation averages that conceal the variation that produces high transmission-risk \nphenotypes. Contact rate between infected and susceptible individuals, is primarily \ndetermined by behaviour whereas physiological immunity is the main determinant \nof the likelihood that contact causes infection and infection duration. I characterise \nvariation in traits affecting the determinants of disease transmission and use this to \npredict individual variation in disease transmission, V. Using the fruit fly, Drosophila \nmelanogaster, and its viral pathogen Drosophila C Virus, I have found pervasive and \ncomplex effects of genetic and sex-specific variation, mating, and infection on suites \nof behaviours, physiological traits and outcomes of infection. Many of my results \npoint to an individual’s disease transmission potential being determined by genetic \nbackground and sex. Males, for example, typically survive DCV infection longer than \nfemales, however the amount of virus they shed is also determined by their genetic \nbackground. To predict how this variation could affect disease transmission \ndynamics, I simulated outbreaks of DCV in theoretical populations. These \npopulations exhibited genetic and sex-specific variation based on my experiments \nand significantly affected population-level outbreak dynamics. Differences in these \ndynamics highlight potentially high-risk transmission classes of individuals, defined \nby their genetic background and sex.},\n\tlanguage = {en},\n\turldate = {2020-02-12},\n\tjournal = {University of Edinburgh},\n\tauthor = {Siva-Jothy, Jonathon Arumugam},\n\tmonth = jan,\n\tyear = {2020},\n}\n\n\n\n","author_short":["Siva-Jothy, J. A."],"key":"siva-jothy_v_2020","id":"siva-jothy_v_2020","bibbaseid":"sivajothy-tovr0tov-2020","role":"author","urls":{"Paper":"https://era.ed.ac.uk/handle/1842/36740"},"metadata":{"authorlinks":{}}},"bibtype":"article","biburl":"https://bibbase.org/zotero-mypublications/pfvale","dataSources":["Hmaj6fS6FKQuG3nSG","66wkvtmTF9APhQn6L","tWbkRzQp4qoRJ9g7W","WhdFcL9q2Loo6bDrg","rf5D6MWTahxXEXZ5P"],"keywords":[],"search_terms":["siva-jothy"],"title":"To V, R0 to V ?","year":2020}