Modified transport medium for improving influenza virus detection.

Background: Accurate detection of influenza virus in clinical samples requires correct execution of all aspects of the detection test. If the viral load in a sample is below the detection limit, a false negative result may be obtained. To overcome this issue, we developed a modified transport medium (MTM) for clinical sample transportation to increase viral detection sensitivity. Method: We first validated the MTM using laboratory-stocked influenza A viruses (IAVs: H1N1, H3N2, H7N3, H9N2) and influenza B viruses (IBVs: Yamagata, Victoria). We also tested clinical samples. A total of 110 patients were enrolled and a pair of samples were collected to determine the sensitivity of real-time polymerase chain reaction (RT-PCR) following MTM treatment. Result: After 24 h culturing in MTM, the viral loads were increased, represented by a 10-fold increase in detection sensitivity for H1N1, H9N2, and IBVs, a 100-fold increase for H3N2, and a 1,000-fold increase for H7N3. We further tested the effects of MTM on 19 IAV and 11 IBV stored clinical samples. The RT-PCR results showed that the positive detection rate of IAV samples increased from 63.16% (12/19) without MTM culturing to 78.95% (15/19) after 48 h culturing, and finally 89.47% (17/19) after 72 h culturing. MTM treatment of IBV clinical samples also increased the positive detection rate from 36.36% (4/11, 0 h) to 63.64% (7/11, 48 h) to 72.73% (8/11, 72 h). For clinical samples detected by RT-PCR, MTM outperformed other transport mediums in terms of viral detection rate (11.81% increase, P=0.007). Conclusion: Our results demonstrated that the use of MTM for clinical applications can increase detection sensitivity, thus facilitating the accurate diagnosis of influenza infection.

The Impact of Medical Resources and Oral Antiviral Drugs on SARS-CoV-2 Mortality - Hong Kong SAR, China, 2022.

Introduction: The Omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) demonstrates increased transmissibility compared to earlier strains, contributing to a significant number of fatalities in Hong Kong Special Administrative Region (HKSAR), China. Adequate medical resources and medications are essential in mitigating these deaths. This study evaluates the effects of supplementary resources from the Chinese mainland during the fifth wave of the pandemic in HKSAR. Methods: Vector autoregression (VAR) was employed to analyze data from the Oxford coronavirus disease 2019 (COVID-19) Government Response Tracker to assess the effectiveness of control measures during five waves of the pandemic in HKSAR. Additionally, a transmission dynamics model was created to investigate the influence of supplementary medical resources from the Chinese mainland and oral medications on mortality. Results: In the initial four waves, workplace closures, restrictions on public events, international travel bans, and shielding the elderly significantly influenced pandemic management. Contrarily, during the fifth wave, these measures showed no notable effects. When comparing a situation without extra medical resources or COVID-19 oral medication, there was a 17.7% decrease in COVID-19 fatalities with mainland medical resources and an additional 10.2% reduction with oral medications. Together, they contributed to a 26.6% decline in fatalities. Discussion: With the rapid spread of the virus, regional reallocation of medical resources may reduce mortality even when the local healthcare system is overstretched.

Molecular epidemiology and phylogenetic analysis of influenza viruses A (H3N2) and B/Victoria during the COVID-19 pandemic in Guangdong, China.

BACKGROUND: Non-pharmaceutical measures and travel restrictions have halted the spread of coronavirus disease 2019 (COVID-19) and influenza. Nonetheless, with COVID-19 restrictions lifted, an unanticipated outbreak of the influenza B/Victoria virus in late 2021 and another influenza H3N2 outbreak in mid-2022 occurred in Guangdong, southern China. The mechanism underlying this phenomenon remains unknown. To better prepare for potential influenza outbreaks during COVID-19 pandemic, we studied the molecular epidemiology and phylogenetics of influenza A(H3N2) and B/Victoria that circulated during the COVID-19 pandemic in this region. METHODS: From January 1, 2018 to December 31, 2022, we collected throat swabs from 173,401 patients in Guangdong who had acute respiratory tract infections. Influenza viruses in the samples were tested using reverse transcription-polymerase chain reaction, followed by subtype identification and sequencing of hemagglutinin (HA) and neuraminidase (NA) genes. Phylogenetic and genetic diversity analyses were performed on both genes from 403 samples. A rigorous molecular clock was aligned with the phylogenetic tree to measure the rate of viral evolution and the root-to-tip distance within strains in different years was assessed using regression curve models to determine the correlation. RESULTS: During the early period of COVID-19 control, various influenza viruses were nearly undetectable in respiratory specimens. When control measures were relaxed in January 2020, the influenza infection rate peaked at 4.94% (39/789) in December 2021, with the influenza B/Victoria accounting for 87.18% (34/39) of the total influenza cases. Six months later, the influenza infection rate again increased and peaked at 11.34% (255/2248) in June 2022; influenza A/H3N2 accounted for 94.51% (241/255) of the total influenza cases in autumn 2022. The diverse geographic distribution of HA genes of B/Victoria and A/H3N2 had drastically reduced, and most strains originated from China. The rate of B/Victoria HA evolution (3.11 × 10-3, P < 0.05) was 1.7 times faster than before the COVID-19 outbreak (1.80 × 10-3, P < 0.05). Likewise, the H3N2 HA gene's evolution rate was 7.96 × 10-3 (P < 0.05), which is 2.1 times faster than the strains' pre-COVID-19 evolution rate (3.81 × 10-3, P < 0.05). CONCLUSIONS: Despite the extraordinarily low detection rate of influenza infection, concealed influenza transmission may occur between individuals during strict COVID-19 control. This ultimately leads to the accumulation of viral mutations and accelerated evolution of H3N2 and B/Victoria viruses. Monitoring the evolution of influenza may provide insights and alerts regarding potential epidemics in the future.