Related Experiment Video
Updated: Jun 11, 2026
Development and Validation of a Quantitative PCR Method for Equid Herpesvirus-2 Diagnostics in Respiratory Fluids
Published on: March 17, 2016
Estimating pathogen-specific asymptomatic ratios
Te-En Wang1, Chien-Yu Lin, Chwan-Chuen King
1Graduate Institute of Epidemiology, College of Public Health, National Taiwan University, Taipei, Taiwan.
Abstract:
The asymptomatic ratio (the proportion of asymptomatic infected cases among the total infected cases) is an important indicator in public health. However, symptoms manifested by a case infected with a pathogen may result from infections other than the specific pathogen of interest. When a case is infected with multiple pathogens, it can be difficult to distinguish which pathogen is causing the symptoms. These conditions complicate the estimation of asymptomatic ratios. We used influenza serologic data from Taiwan to test a novel log-linear binomial regression model that estimates pathogen-specific asymptomatic ratios for influenza subtypes. We find that 75% of the H1N1 subtype and 65% of the H3N2 subtype were asymptomatic. Asymptomatic ratios help to quantify the magnitude of asymptomatic persons who may be capable of spreading pathogens to others.
Insights
Estimating asymptomatic ratios for influenza subtypes is challenging due to co-infections. A new model found 75% of H1N1 and 65% of H3N2 cases were asymptomatic, highlighting the spread potential of these influenza viruses.
Area of Science:
- Epidemiology
- Infectious Diseases
- Biostatistics
Background:
- The asymptomatic ratio is crucial for public health, but accurately estimating it is difficult when multiple pathogens cause symptoms.
- Distinguishing pathogen-specific symptoms complicates the calculation of asymptomatic proportions.
Purpose of the Study:
- To develop and validate a novel log-linear binomial regression model for estimating pathogen-specific asymptomatic ratios.
- To apply the model to influenza subtypes using serologic data from Taiwan.
Main Methods:
- Utilized a novel log-linear binomial regression model.
- Employed influenza serologic data from Taiwan for analysis.
- Focused on estimating asymptomatic ratios for specific influenza subtypes (H1N1 and H3N2).
Main Results:
- The model successfully estimated pathogen-specific asymptomatic ratios for influenza subtypes.
- Found that 75% of H1N1 influenza cases were asymptomatic.
- Determined that 65% of H3N2 influenza cases were asymptomatic.
Conclusions:
- The developed model effectively addresses challenges in estimating asymptomatic ratios in the presence of co-infections.
- The findings quantify the significant proportion of asymptomatic influenza cases, underscoring their potential role in pathogen transmission.
- Asymptomatic ratios are vital for understanding and managing infectious disease spread.
