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Defining the population attributable fraction for infectious diseases
Ellen Brooks-Pollock1, Leon Danon2
1National Institute for Health Research Health Protection Research Unit (NIHR HPRU) in Evaluation of Interventions, School of Social and Community Medicine.
International Journal of Epidemiology
|May 5, 2017
Summary
Estimating the population attributable fraction (PAF) for infectious diseases is complex. A new method using the basic reproduction number provides a consistent approach, resolving discrepancies in existing methods for public health policy.
Area of Science:
- Epidemiology
- Mathematical Modeling
- Public Health
Background:
- The population attributable fraction (PAF) quantifies disease burden from risk groups.
- High-risk individuals can amplify infectious disease spread in the general population.
- Accurate PAF estimation is crucial for infectious disease control strategies.
Purpose of the Study:
- To compare existing methods for calculating PAF in infectious diseases.
- To develop a novel, consistent method for PAF estimation.
- To address limitations in current PAF calculation approaches.
Main Methods:
- Utilized a mathematical model of disease transmission with a high-risk group.
- Compared existing PAF calculation approaches.
- Developed a new PAF method based on the basic reproduction number.
Main Results:
- Existing PAF methods yield inconsistent estimates depending on transmission categorization.
- The new method, based on the basic reproduction number, bridges gaps and resolves discrepancies.
- Assortative mixing decreases PAF, while disassortative mixing increases it.
Conclusions:
- Current PAF methods for infectious diseases are inconsistent.
- A new, straightforward PAF calculation method is proposed.
- This approach offers a parsimonious solution for infectious disease epidemiology.
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