Epidemiological and virological differences in human clustered and sporadic infections with avian influenza A H7N9

Characterization of Unlinked Cases of COVID-19 and Implications for Contact Tracing Measures: Retrospective Analysis of Surveillance Data

BACKGROUND

Contact tracing and intensive testing programs are essential for controlling the spread of COVID-19. However, conventional contact tracing is resource intensive and may not result in the tracing of all cases due to recall bias and cases not knowing the identity of some close contacts. Few studies have reported the epidemiological features of cases not identified by contact tracing ("unlinked cases") or described their potential roles in seeding community outbreaks.

OBJECTIVE

For this study, we characterized the role of unlinked cases in the epidemic by comparing their epidemiological profile with the linked cases; we also estimated their transmission potential across different settings.

METHODS

We obtained rapid surveillance data from the government, which contained the line listing of COVID-19 confirmed cases during the first three waves in Hong Kong. We compared the demographics, history of chronic illnesses, epidemiological characteristics, clinical characteristics, and outcomes of linked and unlinked cases. Transmission potentials in different settings were assessed by fitting a negative binomial distribution to the observed offspring distribution.

RESULTS

Time interval from illness onset to hospital admission was longer among unlinked cases than linked cases (median 5.00 days versus 3.78 days; P<.001), with a higher proportion of cases whose condition was critical or serious (13.0% versus 8.2%; P<.001). The proportion of unlinked cases was associated with an increase in the weekly number of local cases (P=.049). Cluster transmissions from the unlinked cases were most frequently identified in household settings, followed by eateries and workplaces, with the estimated probability of cluster transmissions being around 0.4 for households and 0.1-0.3 for the latter two settings.

CONCLUSIONS

The unlinked cases were positively associated with time to hospital admission, severity of infection, and epidemic size-implying a need to design and implement digital tracing methods to complement current conventional testing and tracing. To minimize the risk of cluster transmissions from unlinked cases, digital tracing approaches should be effectively applied in high-risk socioeconomic settings, and risk assessments should be conducted to review and adjust the policies.

Spatial and temporal clusters of avian influenza a (H7N9) virus in humans across five epidemics in mainland China: an epidemiological study of laboratory-confirmed cases

Background

Avian influenza A (H7N9) virus was first reported in mainland China in 2013, and alarming in 2016–17 due to the surge across a wide geographic area. Our study aimed to identify and explore the spatial and temporal variation across five epidemics to reinforce the epidemic prevention and control.

Methods

We collected spatial and temporal information about all laboratory-confirmed human cases of A (H7N9) virus infection reported in mainland China covering 2013–17 from the open source. The autocorrelation analysis and intensity of cases were used to analyse the spatial cluster while circular distribution method was used to analyse the temporal cluster.

Results

Across the five epidemics, a total of 1553 laboratory-confirmed human cases with A (H7N9) virus were reported in mainland China. The global Moran’s I index values of five epidemic were 0.610, 0.132, 0.308, 0.306, 0.336 respectively, among which the differences were statistically significant. The highest intensity was present in the Yangtze River Delta region and the Pearl River Delta region, and the range enlarged from the east of China to inner provinces and even the west of China across the five epidemics. The temporal clusters of the five epidemics were statistically significant, and the peak period was from the end of January to April with the first and the fifth epidemic later than the mean peak period.

Conclusions

Spatial and temporal clusters of avian influenza A (H7N9) virus in humans are obvious, moreover the regions existing clusters may enlarge across the five epidemics. Yangtze River Delta region and the Pearl River Delta region have the spatial cluster and the peak period is from January to April. The government should facilitate the tangible improvement for the epidemic preparedness according to the characteristics of spatial and temporal clusters of patients with avian influenza A (H7N9) virus.

Importance of 1918 virus reconstruction to current assessments of pandemic risk

Reconstruction of the 1918 influenza virus has facilitated considerable advancements in our understanding of this extraordinary pandemic virus. However, the benefits of virus reconstruction are not limited to this one strain. Here, we provide an overview of laboratory studies which have evaluated the reconstructed 1918 virus, and highlight key discoveries about determinants of virulence and transmissibility associated with this virus in mammals. We further discuss recent and current pandemic threats from avian and swine reservoirs, and provide specific examples of how reconstruction of the 1918 pandemic virus has improved our ability to contextualize research employing novel and emerging strains. As influenza viruses continue to evolve and pose a threat to human health, studying past pandemic viruses is key to future preparedness efforts.

The temporal distribution of new H7N9 avian influenza infections based on laboratory-confirmed cases in Mainland China, 2013-2017

In this study, estimates of the growth rate of new infections, based on the growth rate of new laboratory-confirmed cases, were used to provide a statistical basis for in-depth research into the epidemiological patterns of H7N9 epidemics. The incubation period, interval from onset to laboratory confirmation, and confirmation time for all laboratory-confirmed cases of H7N9 avian influenza in Mainland China, occurring between January 2013 and June 2017, were used as the statistical data. Stochastic processes theory and maximum likelihood were used to calculate the growth rate of new infections. Time-series analysis was then performed to assess correlations between the time series of new infections and new laboratory-confirmed cases. The rate of new infections showed significant seasonal fluctuation. Laboratory confirmation was delayed by a period of time longer than that of the infection (average delay, 13 days; standard deviation, 6.8 days). At the lags of −7.5 and −15 days, respectively, the time-series of new infections and new confirmed cases were significantly correlated; the cross correlation coefficients (CCFs) were 0.61 and 0.16, respectively. The temporal distribution characteristics of new infections and new laboratory-confirmed cases were similar and strongly correlated.

Prevention of Influenza A(H7N9) and Bacterial Infections in Mice Using Intranasal Immunization With Live Influenza Vaccine and the Group B Streptococcus Recombinant Polypeptides

We investigate the protective effect of combined vaccination based on live attenuated influenza vaccine (LAIV) and group B streptococcus (GBS) recombinant polypeptides against potential pandemic H7N9 influenza infection followed by GBS burden. Mice were intranasally immunized using 107 50% egg infectious dose (EID₅₀) of H7N3 LAIV, the mix of the 4 GBS peptides (group B streptococcus vaccine [GBSV]), or combined LAIV + GBSV vaccine. The LAIV raised serum hemagglutination-inhibition antibodies against H7N9 in higher titers than against H7N3. Combined vaccination provided advantageous protection against infections with A/Shanghai/2/2013(H7N9)CDC-RG influenza and serotype II GBS. Combined vaccine significantly improved bacterial clearance from the lungs after infection compared with other vaccine groups. The smallest lung lesions due to combined LAIV + GBSV vaccination were associated with a prevalence of lung interferon-γ messenger RNA expression. Thus, combined viral and bacterial intranasal immunization using H7N3 LAIV and recombinant bacterial polypeptides induced balanced adaptive immune response, providing protection against potential pandemic influenza H7N9 and bacterial complications.

Comparative Epidemiology of Human Fatal Infections with Novel, High (H5N6 and H5N1) and Low (H7N9 and H9N2) Pathogenicity Avian Influenza A Viruses

This study aimed to assess the mortality risks for human infection with high (HPAI) and low (LPAI) pathogenicity avian influenza viruses. The HPAI case fatality rate (CFR) was far higher than the LPAI CFR [66.0% (293/444) vs. 68.75% (11/16) vs. 40.4% (265/656) vs. 0.0% (0/18) in the cases with H5N1, H5N6, H7N9, and H9N2 viruses, respectively; p < 0.001]. Similarly, the CFR of the index cases was greater than the secondary cases with H5N1 [100% (43/43) vs. 43.3% (42/97), p < 0.001]. Old age [22.5 vs. 17 years for H5N1, p = 0.018; 61 vs. 49 years for H7H9, p < 0.001], concurrent diseases [18.8% (15/80) vs. 8.33% (9/108) for H5N1, p = 0.046; 58.6% (156/266) vs. 34.8% (135/388) for H7H9, p < 0.001], delayed confirmation [13 vs. 6 days for H5N1, p < 0.001; 10 vs. 8 days for H7N9, p = 0.011] in the fatalities and survivors, were risk factors for deaths. With regard to the H5N1 clusters, exposure to poultry [67.4% (29/43) vs. 45.2% (19/42), p = 0.039] was the higher risk for the primary than the secondary deaths. In conclusion, old age, comorbidities, delayed confirmation, along with poultry exposure are the major risks contributing to fatal outcomes in human HPAI and LPAI infections.