Journal
JOURNAL OF INFECTIOUS DISEASES
Volume 212, Issue 9, Pages 1420-1428Publisher
OXFORD UNIV PRESS INC
DOI: 10.1093/infdis/jiv225
Keywords
influenza; infectiousness; public health; isolation
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Funding
- National Institute of Allergy and Infectious Diseases (NIAID) [HHSN266200700005C]
- NIAID Centers for Excellence in Influenza Research and Surveillance [N01-AI-70005]
- Government of the Hong Kong Special Administrative Region (Health and Medical Research Fund) [HK-10-04-02]
- National Institute of General Medical Sciences [U54 GM088558, 1U01GM110721-01]
- Area of Excellence Scheme of the University Grants Committee of Hong Kong [AoE/M-12/06]
- L'Oreal Hong Kong
- Laboratory of Excellence Integrative Biology of Emerging Infectious Diseases
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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 specimens 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 V-gamma, with estimates of gamma = 0.136 and gamma = 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.
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