Influenza A Virus Shedding and Infectivity in Households

Background. Viral shedding is often considered to correlate with the infectivity of influenza, but the evidence for this is limited. Methods. In a detailed study of influenza virus transmission within households in 2008-2012, index case patients with confirmed influenza were identified in outpatient...

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Veröffentlicht in:The Journal of infectious diseases 2015-11, Vol.212 (9), p.1420-1428
Hauptverfasser: Tsang, Tim K., Cowling, Benjamin J., Fang, Vicky J., Chan, Kwok-Hung, Ip, Dennis K. M., Leung, Gabriel M., Peiris, J. S. Malik, Cauchemez, Simon
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Sprache:eng
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Zusammenfassung:Background. Viral shedding is often considered to correlate with the infectivity of influenza, but the evidence for this is limited. Methods. In a detailed study of influenza virus transmission within households in 2008-2012, index case patients with confirmed influenza were identified in outpatient clinics, and we collected nose and throat swab spec-, imens for testing by reverse-transcription polymerase chain reaction from all household members regardless of illness. We used individual-based hazard models to characterize the relationship between viral load (V) and infectivity. Results. Assuming that infectivity was proportional to viral load V gave the worst fit, because it strongly overestimated the proportion of transmission occurring at symptom onset. Alternative models assuming that infectivity was proportional to a various functions of V provided better fits, although they all overestimated the proportion of transmission occurring > 3 days after symptom onset. The best fitting model assumed that infectivity was proportion to Vγ, with estimates of γ = 0.136 and γ = 0.156 for seasonal influenza A(H1N1) and A(H3N2) respectively. Conclusions. All the models we considered that used viral loads to approximate infectivity of a case imperfectly explained the timing of influenza secondary infections in households. Identification of more accurate correlates of infectivity will be important to inform control policies and disease modeling.
ISSN:0022-1899
1537-6613
DOI:10.1093/infdis/jiv225