Analysis of influenza viruses epidemiological properties based on experimental human infections
Date Issued
2010
Date
2010
Author(s)
Yang, Shu-Ching
Abstract
Influenza is currently the most frequent cause of acute respiratory illness, affecting all age groups. The severe morbidity and mortality worldwide were due to annual epidemic of influenza. It is substantially requiring control measures to reduce the spread of influenza. The purpose of this study was to estimate the natural history and transmission parameters estimations and to relate it to key epidemiological parameters for understanding influenza virus type and subtypes. The recent published experimental data of viral shedding and symptom score dynamics were reanalyzed. A simple statistical algorithm was developed for linking between experimental human influenza infection and epidemiological factors. This study calculated threshold-adjusted area under the viral shedding versus time curve (AUC) of the fitted viral shedding models to obtain the virus-specific transmission rate (β), recovery rate (γ), infectious rate (σ), and basic reproduction number (R0). We used the mapping technique on virus-specific R0 and vital shedding data to estimate the infectiousness. The asymptomatic probability based on temporal variation of symptom scores was constructed. Results indicate that A (H3N2) had the highest viral load AUC value (6.09) than those of type B (3.78) and A (H1N1) (2.81), leading to the corresponding recovery rates (γ) were estimated to be 0.17, 0.20, and 0.30 d-1 and infectious rate (σ) were 0.39, 0.42, and 0.40 d-1, respectively. Based on a reference value of β = 0.51 d-1 of A (H1N1), mean β and R0 for A (H3N2) were estimated to be 1.11 d-1 and 6.5, respectively, whereas β = 0.69 d-1 and R0 = 3.4 were estimated for type B. Results also indicate that the estimated R0 = 1.74 for A (H1N1) is consistent with published data ranged from 1.7 – 2.0. Finally, this study linked both the dose-response relationship between experimental symptom scores and viral titer and the relationship between symptom scores and contact rate to map contact rate to viral titer. This study could offer a useful analytical tool not only to link virus-specific experimental human influenza data to natural history and transmission parameter estimates but also to relate it to key epidemiological factors.
Subjects
Influenza
Virus shedding
Symptoms
Epidemiology
Basic reproduction number
Transmission
SDGs
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