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myEpi. Epidemiology of One.

Bobashev G - Front Public Health (2014)

Bottom Line: Traditional epidemiology requires that results be generalizable to a predefined population.The key component of myEpi is that a single individual may be viewed as an entire population of events and thus, the analysis should be generalizable to this population.These data can include physiological measures and records of healthy and risky behaviors (e.g., exercise, sleep, smoking, food consumption, alcohol, and drug use).

View Article: PubMed Central - PubMed

Affiliation: RTI International , Durham, NC , USA.

ABSTRACT
A new concept of within-individual epidemiology termed "myEpi" is introduced. It is argued that traditional epidemiological methods, which are usually applied to populations of humans, can be applicable to a single individual and thus used for self-monitoring and forecasting of "epidemic" outbreaks within an individual. Traditional epidemiology requires that results be generalizable to a predefined population. The key component of myEpi is that a single individual may be viewed as an entire population of events and thus, the analysis should be generalizable to this population. Applications of myEpi are aimed for, but not limited to, the analysis of data collected by individuals with the help of wearable sensors and digital diaries. These data can include physiological measures and records of healthy and risky behaviors (e.g., exercise, sleep, smoking, food consumption, alcohol, and drug use). Although many examples of within-individual epidemiology exist, there is a pressing need for systematic guidance to the analysis and interpretation of intensive individual-level data. myEpi serves this need by adapting statistical methods (e.g., regressions, hierarchical models, survival analysis, agent-based models) to individual-level data.

No MeSH data available.


Related in: MedlinePlus

An illustration of inferring to an individual form the population-level and individual-level data. The green “myEpi” oval denotes within-person data which could be also combined with information about blood relatives, social networks, as well as the entire population and the environment. The purpose of the analysis, however, is the individual-level inference.
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Related In: Results  -  Collection

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Figure 1: An illustration of inferring to an individual form the population-level and individual-level data. The green “myEpi” oval denotes within-person data which could be also combined with information about blood relatives, social networks, as well as the entire population and the environment. The purpose of the analysis, however, is the individual-level inference.

Mentions: In this article, I introduce the concept of individual epidemiology (myEpi), which aims to provide individual-level inference. By definition, myEpi considers an individual as a population of person-level events and behaviors (Figure 1) and thus inferences about an individual can be obtained from within-person data.


myEpi. Epidemiology of One.

Bobashev G - Front Public Health (2014)

An illustration of inferring to an individual form the population-level and individual-level data. The green “myEpi” oval denotes within-person data which could be also combined with information about blood relatives, social networks, as well as the entire population and the environment. The purpose of the analysis, however, is the individual-level inference.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4129497&req=5

Figure 1: An illustration of inferring to an individual form the population-level and individual-level data. The green “myEpi” oval denotes within-person data which could be also combined with information about blood relatives, social networks, as well as the entire population and the environment. The purpose of the analysis, however, is the individual-level inference.
Mentions: In this article, I introduce the concept of individual epidemiology (myEpi), which aims to provide individual-level inference. By definition, myEpi considers an individual as a population of person-level events and behaviors (Figure 1) and thus inferences about an individual can be obtained from within-person data.

Bottom Line: Traditional epidemiology requires that results be generalizable to a predefined population.The key component of myEpi is that a single individual may be viewed as an entire population of events and thus, the analysis should be generalizable to this population.These data can include physiological measures and records of healthy and risky behaviors (e.g., exercise, sleep, smoking, food consumption, alcohol, and drug use).

View Article: PubMed Central - PubMed

Affiliation: RTI International , Durham, NC , USA.

ABSTRACT
A new concept of within-individual epidemiology termed "myEpi" is introduced. It is argued that traditional epidemiological methods, which are usually applied to populations of humans, can be applicable to a single individual and thus used for self-monitoring and forecasting of "epidemic" outbreaks within an individual. Traditional epidemiology requires that results be generalizable to a predefined population. The key component of myEpi is that a single individual may be viewed as an entire population of events and thus, the analysis should be generalizable to this population. Applications of myEpi are aimed for, but not limited to, the analysis of data collected by individuals with the help of wearable sensors and digital diaries. These data can include physiological measures and records of healthy and risky behaviors (e.g., exercise, sleep, smoking, food consumption, alcohol, and drug use). Although many examples of within-individual epidemiology exist, there is a pressing need for systematic guidance to the analysis and interpretation of intensive individual-level data. myEpi serves this need by adapting statistical methods (e.g., regressions, hierarchical models, survival analysis, agent-based models) to individual-level data.

No MeSH data available.


Related in: MedlinePlus