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Developing new antibody assays for emerging SARS‐CoV‐2 variants is challenging. SARS‐CoV‐2 surrogate virus neutralization tests (sVNT) targeting Omicron BA.1 and BA.5 have been devised, but their performance needs to be validated in comparison with quantitative immunoassays. First, using 1749 PRNT‐positive sera, we noticed that log‐transformed optical density (OD) ratio of wild‐type (WT) sVNT exhibited better titer‐correlation with plaque reduction neutralization test (PRNT) than % inhibition value. Second, we tried 798 dilutional titration tests with 103 sera, but nonlinear correlation between OD ratio and antibody concentration limited titration of sVNT. Third, the titer‐correlations of two sVNT kits for BA.1 and two quantitative immunoassays for WT were evaluated with BA.1 and BA.5 PRNT. All tested kits exhibited a linear correlation with PRNT titers, but the sVNT kits exhibited high false‐negative rates (cPass‐BA.1 kit, 45.4% for BA.1 and 44.2% for BA.5; STANDARD F‐BA.1 kit, 1.9% for BA.1 and 2.2% for BA.5), while quantitative immunoassays showed 100% sensitivity. Linear mixed‐effects model suggested superior titer‐correlation with PRNT for quantitative immunoassays compared to sVNT kits. Taken together, the use of quantitative immunoassays for WT, rather than rapid development of new kits, would be practical for predicting neutralizing activities against emerging new variants. [ABSTRACT FROM AUTHOR]

Background: A majority (>70%) of Q fever patients in South Korea do not have a history of animal contact. Therefore, unconscious environmental exposure is suspected. The aim of this study was to investigate exposure of Q fever patients to environmental contamination and animal shedding. Methods: Two goat farmers were enrolled. One was diagnosed with Q fever 3 years ago (Farm 1). Among 20 goats on Farm 1, five were tested randomly and found to be Q fever PCR‐positive. Three of the five were Q fever ELISA‐positive. Two of five environmental samples taken in 2015 were PCR‐positive. In 2018, 17 of 18 environmental samples were PCR‐positive. On Farm 2, 54 of the 77 goats were PCR‐positive, and 63 were ELISA‐positive. Twelve of 14 environmental samples were PCR‐positive. Repeat administration of oxytetracycline to goats led to a gradual reduction in PCR‐positive tests over a 5‐month period. However, PCR‐positivity of the farm environment persisted for 5 months. Conclusion: The environment on farms owned by Q fever patients was contaminated extensively and persistently, even after antibiotic treatment of goats and environmental decontamination. Undetected environmental contamination can be a major source of sporadic Q fever infection in South Korea. Q fever is a zoonotic disease that is transmitted to humans via inhalation of the causative organism (Coxiella burnetii) or via direct contact with infected animals. Farms owned by Q fever patients' in South Korea were investigated. We found that most animals were infected with C. burnetii and shed the bacteria for up to 5 months despite antibiotic treatment. The farm environment was also extensively contaminated with C. burnetii. Epidemiologic and geographic data, including animals and the environment, around Q fever patients will provide a more accurate picture of the risk of Q fever in each area. [ABSTRACT FROM AUTHOR]

Background: After pandemic, A(H1N1)pdm09 is generally known to be associated with younger adults' infection and greater severity than seasonal A(H3N2) but some inconsistences between recent studies exist. Objectives: We aimed to compare the epidemiology and clinical outcomes of A(H1N1)pdm09 and A(H3N2) to verify and consolidate about the knowledge of known differences of subtypes. Methods: Data were retrospectively collected from the hospital‐based influenza morbidity and mortality surveillance in South Korea in nine tertiary care hospitals, from August 31, 2014, to August 25, 2018. Patients with H1N1pdm09 or H3N2 infection admitted in the emergency room or ward were recruited. Results: A total of 1747 patients had influenza A and were divided into two groups those with A(H1N1)pdm09 (n = 240) and those with A(H3N2) (n = 1507). A(H1N1)pdm09 group had younger age (mean age ± standard deviation 50.0 ± 18.8 in H1N1 vs 53.4 ± 21.1 in H3N2, P =.030), lower influenza vaccination (27.9% vs 43.9%, P <.001) and pneumococcal vaccination rates (41.0% vs 51.9%, P <.001), and fewer underlying diseases (67.5% vs 74.0%, P =.035) than the A(H3N2) group. Influenza A subtypes were not associated with pneumonia risk (adjusted odds ratios [AOR] of A(H1N1)pdm09: 0.7 [95% confidence interval [CI]: 0.4‐1.2, P =.172]) and in‐hospital mortality (hazard ratio (HR) of A(H1N1)pdm09: 1.0 (95% CI: 0.3‐3.1, P =.983)). Influenza vaccination reduced in‐hospital mortality in hospitalized patients (HR: 0.3 (95% CI: 0.1‐0.7), P =.005). Conclusions: A(H1N1)pdm09 infection was more common in younger patients without significant difference in pneumonia risk and in‐hospital mortality between subtypes. Influenza vaccination was associated with reduced in‐hospital mortality. [ABSTRACT FROM AUTHOR]

Background: The influenza virus is reportedly associated with 3‐5 million cases of severe illness and 250 000‐500 000 deaths annually worldwide. Objectives: We investigated the variation of influenza A virus in Korea and examined the association with death. Methods: A total of 13 620 cases were enrolled in the Hospital‐based Influenza Morbidity & Mortality surveillance system in Korea during 2011‐2016. Among these cases, a total of 4725 were diagnosed with influenza using RT‐PCR (influenza A; n = 3696, influenza B; n = 928, co‐infection; n = 101). We used 254 viral sequences from the 3696 influenza A cases for phylogenetic analysis using the BioEdit and MEGA 6.06 programs. Results: We found that the sequences of A/H3N2 in the 2011‐2012 season belong to subgroup 3C.1, whereas the sequences in the 2012‐2013 season pertain to subgroup 3C.2. The sequences in the 2013‐2014 and 2014‐2015 seasons involve subgroups 3C.3a and 3C.2a. The A/H1N1pdm09 subtype belongs to subgroup 6 and contains two clusters. In addition, sequence analysis confirmed the several substitutions of internal genes and gene substitutions associated with drug resistance (I222V in NA and S31N in M2) in the fatal cases. While statistical analysis found no significant associations between genetic differences in the viruses and mortality, mortality was associated with certain host factors, such as chronic lung disease. Conclusions: In conclusion, influenza A virus clade changes occurred in Korea during the 2011‐2016 seasons. These data, along with antigenic analysis, can aid in selecting effective vaccine strains. We confirmed that fatality in influenza A cases was related to underlying patient diseases, such as chronic lung disease, and further studies are needed to confirm associations between mortality and viral genetic substitutions. [ABSTRACT FROM AUTHOR]

The Hospital-based Influenza Morbidity and Mortality ( HIMM) surveillance system is an emergency room ( ER)-based influenza surveillance system in Korea that was established in 2011. The system was established under the assumption that integrated clinical and virologic surveillance could be performed rapidly and easily at seven tertiary hospitals' ER. Here, we assessed the correlation between data generated from the HIMM surveillance system and the Korean national influenza surveillance systems during the 2011-2012 influenza season using cross-correlation analysis and found strong correlations. Rapid antigen-test-based HIMM surveillance would predict the start of influenza epidemic earlier than pre-existing influenza-like-illness-based surveillance. [ABSTRACT FROM AUTHOR]

Influenza epidemics occur annually with variations in size and severity. Hospital-based Influenza Morbidity & Mortality was established to monitor influenza epidemics and their severity, which is composed of two surveillance systems: emergency room-based and inpatient-based surveillance. Regarding emergency room-based surveillance, influenza-like illness index (influenza-like illness cases per 1,000 emergency room-visiting subjects), number of laboratory-confirmed cases and the distribution of influenza types were estimated weekly. Inpatient-based surveillance included monitoring for hospitalization, complications, and mortality. The emergency room influenza-like illness index correlated well with the number of laboratory-confirmed influenza cases, and showed a bimodal peak at Week 4 (179.2/1,000 emergency room visits) and Weeks 13-14 (169.6/1,000 emergency room visits) of 2012. Influenza A was the predominant strain during the first epidemic peak, while influenza B was isolated exclusively during the second peak. In 2011-2012 season, the mean admission rate of emergency room-visiting patients with influenza-like illness was 16.3% without any increase over the epidemic period. Among the hospitalized patients with influenza, 33.6% (41 out of 122 patients) were accompanied by complications, and pneumonia (28.7%, 35 out of 122 patients) was the most common. Most fatal cases were caused by influenza A (96.2%) after the first epidemic peak. In conclusion, Hospital-based Influenza Morbidity & Mortality was effective for monitoring the trends in circulating influenza activity concurrently with its severity. In the 2011-2012 season, the influenza epidemic persisted for a ≥5-month period, with a bimodal peak of influenza A and B in sequence. Overall, influenza A was more severe than influenza B. J. Med. Virol. 85:910-917, 2013. © 2013 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]