Influenza A Virus Shedding and Infectivity in Households

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

doi:10.1093/infdis/jiv225

Cited by 109 publications

(116 citation statements)

References 40 publications

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“…12 Together this supports our findings that the infectiousness profile may more closely resemble that of influenza than of SARS (Figure 1a), although we did not have data on viral shedding before symptom onset for COVID-19. 9,13 Our results are also supported by reports on asymptomatic and pre-symptomatic transmission. 14,15 For a reproductive number of 2.5, 2 contact tracing and isolation alone are less likely to be successful if more than 30% of transmission occurred before symptom onset, unless >90% of the contacts can be traced.…”

Section: Main Textsupporting

confidence: 90%

Temporal dynamics in viral shedding and transmissibility of COVID-19

Lau

et al. 2020

Preprint

1,235

1,665

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We report temporal patterns of viral shedding in 94 laboratory-confirmed COVID-19 patients and modelled COVID-19 infectiousness profile from a separate sample of 77 infector-infectee transmission pairs. We observed the highest viral load in throat swabs at the time of symptom onset, and inferred that infectiousness peaked on or before symptom onset. We estimated that 44% of transmission could occur before first symptoms of the index. Disease control measures should be adjusted to account for probable substantial pre-symptomatic transmission.

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Section: Main Textsupporting

confidence: 90%

Temporal dynamics in viral shedding and transmissibility of COVID-19

Lau

et al. 2020

Preprint

1,235

1,665

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“…The length of time the virus remains in the body is related to the viral load. This suggests that the viral nucleic acid shedding pattern of SARS-CoV-2 is similar to that of influenza, which differs from that of SARS-CoV (9,11). The median time that it took for the nucleic acid test to turn negative in patients with severe disease was significantly longer than it was in patients with mild symptoms, indicating that elimination of SARS-CoV-2 RNA in the nasopharynx may influence the disease severity of patients with COVID-19 (5).…”

Section: Discussionmentioning

confidence: 92%

Correlation Between Relative Nasopharyngeal Virus RNA Load and Lymphocyte Count Disease Severity in Patients with COVID-19

et al. 2021

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The aim of this study was to analyze the correlation between dynamic changes in the nasopharyngeal viral load of patients infected with the new coronavirus causing pneumonia and lymphocyte count disease severity. Cases newly diagnosed with COVID-19 at the First Affiliated Hospital of Nanchang University from January 2020 to February 2020 were analyzed retrospectively. Quantitative real-time polymerase chain reaction was used to determine severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from throat swab sample DCT values; lymphocyte and lymphocyte subset counts, coagulation system factor levels, myocardial injury indexes, and laboratory biochemical indicators were compared between the mild group and the severe group. The correlation between the relative load of nasopharyngeal SARS-CoV-2 RNA and severe disease symptoms was analyzed. Of the 76 patients, 49 were male and 27 were female. The lymphocyte, CD4 + T lymphocyte, and CD8 + T lymphocyte counts all differed significantly between the two groups ( p < 0.001), as did differences in interleukin (IL)-2R, IL-6, and IL-8 levels ( p = 0.022, 0.026, and 0.012, respectively). Moreover, there were significant differences in prothrombin time, D-dimer, and fibrinogen levels between the mild group and the severe group ( p = 0.029, 0.006, and <0.001, respectively), and in lactate dehydrogenase and troponin ( p < 0.001 and p = 0.007, respectively). SARS-CoV-2 RNA load and lymphocyte count, CD4 + T lymphocyte count, and CD8 + T lymphocyte count were linearly negatively correlated ( p < 0.001). SARS-CoV-2 RNA load was positively correlated with IL-2R, prothrombin time, lactate dehydrogenase, and hypersensitive troponin T ( p = 0.002, p = 0.009, and p < 0.001, respectively). In addition, the time that it took for the nucleic acid test to turn negative was significantly shorter for patients in the mild group than for those in the severe group (Z = -6.713, p < 0.001).In conclusion, relative SARS-CoV-2 RNA load in the nasopharynx is closely related to COVID-19 severity. If the relative RNA load was higher, the lymphocyte count was lower, organ damage was greater, and the time it took for the nucleic acid test to turn negative was longer.

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“…In agreement with the 2007-2008 data, we did not detect differences in copy number by vaccination group for the 2004-2005 and 2005-2006 seasons (Supplementary Figure 2). Since copy number is dependent on time from illness onset [42,43], we analyzed the data based on sample collection day (Figure 1B). Using days 2-4, for which there were at least 5 data points for each treatment group, we did not find any significant differences (p=0.24-0.57 for days 2-4, non-parametric one way ANOVA).…”

Section: Resultsmentioning

confidence: 99%

Vaccination has minimal impact on the intrahost diversity of H3N2 influenza viruses

Debbink

McCrone

Petrie

et al. 2016

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While influenza virus diversity and antigenic drift have been well characterized on a global scale, the factors that influence the virus' rapid evolution within and between human hosts are less clear. Given the modest effectiveness of seasonal vaccination, vaccine-induced antibody responses could serve as a potent selective pressure for novel influenza variants at the individual or community level. We used next generation sequencing of patient-derived viruses from a randomized, placebo-controlled trial of vaccine efficacy to characterize the diversity of influenza A virus and to define the impact of vaccine-induced immunity on withinhost populations. Importantly, this study design allowed us to isolate the impact of vaccination while still studying natural infection. We used pre-season hemagglutination inhibition and neuraminidase inhibition titers to quantify vaccine-induced immunity directly and to assess its impact on intrahost populations. We identified 166 cases of H3N2 influenza over 3 seasons and 5119 person-years. We obtained whole genome sequence data for 119 samples and used a stringent and empirically validated analysis pipeline to identify intrahost single nucleotide variants at !1% frequency. Phylogenetic analysis of consensus hemagglutinin and neuraminidase sequences showed no stratification by pre-season HAI and NAI titer, respectively. In our study population, we found that the vast majority of intrahost single nucleotide variants were rare and that very few were found in more than one individual. Most samples had fewer than 15 single nucleotide variants across the entire genome, and the level of diversity did not significantly vary with day of sampling, vaccination status, or pre-season antibody titer. Contrary to what has been suggested in experimental systems, our data indicate that seasonal influenza vaccination has little impact on intrahost diversity in natural infection and that vaccine-induced immunity may be only a minor contributor to antigenic drift at local scales. Author summaryInfluenza is a significant global health problem. Vaccination is the best way to prevent influenza virus infection, and seasonal influenza vaccines are considered for reformulation each year in order to keep up with the virus' evolution. Despite these efforts, vaccine recipients often develop an immune response that does not protect from infection. Given the current recommendation that all people over 6 months of age get vaccinated, it is important to understand how vaccination itself may impact viral evolution during natural human infection. We studied how vaccination may alter viral evolution within individuals, as each person harbors many highly-related influenza variants that differ in their ability to escape the immune response. We compared groups of people in a vaccine trial to determine the impact that vaccination has on viral diversity and variant selection within individuals. We did not detect significant differences in the number of variants detected or in the prevalence of mutations that co...

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Influenza A Virus Shedding and Infectivity in Households

Cited by 109 publications

References 40 publications

Temporal dynamics in viral shedding and transmissibility of COVID-19

Temporal dynamics in viral shedding and transmissibility of COVID-19

Correlation Between Relative Nasopharyngeal Virus RNA Load and Lymphocyte Count Disease Severity in Patients with COVID-19

Vaccination has minimal impact on the intrahost diversity of H3N2 influenza viruses

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