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Background: Healthcare-associated COVID-19 infections caused by SARS-CoV-2 have increased morbidity and mortality. Hospitals and skilled nursing facilities (SNFs) have been challenged by infection control and management. Methods: This case study presents an outbreak investigation in a COVID-19-designated hospital and a hospital-based SNF. Real-time polymerase chain reaction (PCR) and other studies were performed on samples obtained from SNF residents, hospital patients, and healthcare workers (HCWs). The results of the laboratory tests and field epidemiological data were analyzed. Genome sequencing and phylogenetic analysis of SARS-CoV-2 were performed to identify the associations between cases. The tracer gas was released and recorded by a thermal imaging camera to investigate the spatial relations within clusters. Results: During the outbreak, 29 COVID-19 infections in 3 clusters were identified through hospital-wide, risk-guided, and symptom-driven PCR tests. This included 12 HCWs, 5 patients, and 12 SNF residents who had been hospitalized for at least 14 days. Serology tests did not identify any cases among the PCR-negative individuals. The phylogenetic analysis revealed that viral strains from the 3 clusters shared a common mutation of G3994T and were phylogenetically related, which suggested that this outbreak had a common source rather than multiple introductions from the community. Linked cases exhibited vertical spatial distribution, and the sulfur hexafluoride release test confirmed a potential airborne transmission. Conclusions: This report addressed the advantage of a multi-disciplinary team in outbreak investigation. Identifying an airborne transmission within an outbreak highlighted the importance of regular maintenance of ventilation systems.

Taiwan’s experience with severe acute respiratory syndrome coronavirus (SARS-CoV) in 2003 guided its development of strategies to defend against SARS-CoV-2 in 2020, which enabled the successful control of Coronavirus disease 2019 (COVID-19) cases from 2020 through March 2021. However, in late-April 2021, the imported Alpha variant began to cause COVID-19 outbreaks at an exceptional rate in Taiwan. In this study, we aimed to determine what epidemiological conditions enabled the SARS-CoV-2 Alpha variant strains to become dominant and decline later during a surge in the outbreak. In conjunction with contact-tracing investigations, we used our bioinformatics software, CoVConvert and IniCoV, to analyze whole-genome sequences of 101 Taiwan Alpha strains. Univariate and multivariable regression analyses revealed the epidemiological factors associated with viral dominance. Univariate analysis showed the dominant Alpha strains were preferentially selected in the surge’s epicenter (p = 0.0024) through intensive human-to-human contact and maintained their dominance for 1.5 months until the Zero-COVID Policy was implemented. Multivariable regression found that the epidemic periods (p = 0.007) and epicenter (p = 0.001) were two significant factors associated with the dominant virus strains spread in the community. These dominant virus strains emerged at the outbreak’s epicenter with frequent human-to-human contact and low vaccination coverage. The Level 3 Restrictions and Zero-COVID policy successfully controlled the outbreak in the community without city lockdowns. Our integrated method can identify the epidemiological conditions for emerging dominant virus with increasing epidemiological potential and support decision makers in rapidly containing outbreaks using public health measures that target fast-spreading virus strains.

Background: Human rhinovirus (HRV) can cause severe illnesses in hospitalized patients. However, there are no studies regarding the prevalence of HRV infection, particularly the recently identified HRV-C, in hospitalized patients reported from Taiwan. Methods: Respiratory specimens collected from 487 hospitalized patients in designated wards between 2013 and 2014 in a medical center in northern Taiwan were retrospectively detected for HRV. Positive specimens were further determined for genotyping. Medical charts of the HRV-positive patients were reviewed retrospectively. Results: Totally, 76 patients (15.6%) were HRV positive, of which 60 were pediatric patients. HRV-A was identified in 41 (54%) patients, HRV-B in 6 patients (7.9%) and HRV-C in 29 patients (38%). A total of 47 different genotypes were identified. HRV infections were predominant during fall and winter seasons. 21.1% were affected by HRV alone and 78.9% were found to be co-infected with other microorganisms. The detection rate of HRV in children (18.6%) was significantly higher than in adults (9.6%). Compared with pediatric patients, adult patients were significantly associated with underlying disease, Pneumocystis jirovesii pneumonia co-infection, a diagnosis of pneumonia, fatal outcome, hospital acquisition of HRV, antibiotics administration and requiring intensive care, while pediatric patients were significantly associated with viral co-infection. Conclusions: HRV was a common cause of respiratory tract infection in Taiwan, particularly in pediatric patients. Eighty percent of HRV-infected inpatients had other microorganisms co-infection. Adult patients were more likely to be associated with a severe respiratory disease entity. Keywords: Rhinovirus, Respiratory tract infection, Hospitalized patients, Taiwan

Background/Purpose: Influenza A/H3N2 viruses are characterized by highly mutated RNA genomes. In this study, we focused on tracing the phylodynamics of Taiwanese strains over the past four decades. Methods: All Taiwanese H3N2 HA1 sequences and references were downloaded from public database. A Bayesian skyline plot (BSP) and phylogenetic tree were used to analyze the evolutionary history, and Bayesian phylogeographic analysis was applied to predict the spatiotemporal migrations of influenza outbreaks. Results: Genetic diversity was found to have peaked near the summer of 2009 in BSP, in addition to the two earlier reported ones in summer of 2005 and 2007. We predicted their spatiotemporal migrations and found the summer epidemic of 2005 from Korea, and 2007 and 2009 from the Western United States. BSP also predicted an elevated genetic diversity in 2015–2017. Quasispecies were found over approximately 20% of the strains included in this time span. In addition, a first-time seen N31S mutation was noted in Taiwan in 2016–2017. Conclusion: We comprehensively investigated the evolutionary history of Taiwanese strains in 1979–2017. An epidemic caution could thus be raised if genetic diversity was found to have peaked. An example showed a newly-discovered cluster in 2016–2017 strains featuring a mutation N31S together with HA-160 quasispecies. Phylogeographic analysis, moreover, provided useful insights in tracing the possible source and migrations of these epidemics around the world. We demonstrated that Asian destinations including Taiwan were the immediate followers, while U.S. continent was predicted the origin of two summer epidemics in 2007 and 2009. Keywords: Influenza A/H3N2 viruses, Phylodynamics, Phylogeography, Summer epidemics, Viral quasispecies

The history of influenza in Taiwan can be traced up to the 1918 H1N1 Spanish flu pandemic, followed by several others including the 1957 H2N2, 1968 H3N2, and the 2009 new H1N1. A couple of avian influenza viruses of H5N1 and H7N9 also posed threats to the general public in Taiwan in the two recent decades. Nevertheless, two seasonal influenza A viruses and two lineages of influenza B viruses continue causing annual endemics one after the other, or appearing simultaneously. Their interplay provided interesting evolutionary trajectories for these viruses, allowing us to computationally model their global migrations together with the data collected elsewhere from different geographical locations. An island-wide laboratory-based surveillance network was also established since 2000 for systematically collecting and managing the disease and molecular epidemiology. Experiences learned from this network helped in encountering and managing newly emerging infectious diseases, including the 2003 SARS and 2009 H1N1 outbreaks. Keywords: Influenza, Pandemic, Genome evolution, Surveillance

Background & Aims: Gut dysbiosis plays a role in hepatic encephalopathy (HE), while its relationship at the acute episode of overt HE (AHE), the disease progression and clinical outcomes remains unclear. We aimed to identify AHE-specific microbiome and its association to patients’ outcomes. Methods: We profiled fecal microbiome changes for a cohort of 62 patients with cirrhosis and AHE i) before treatment, ii) 2-3 days after medication and iii) 2-3 months after recovery, and three control cohorts i) healthy individuals, patients with ii) compensated or iii) decompensated cirrhosis. Results: Comparison of the microbiome shift from compensated, decompensated cirrhosis, AHE to recovery revealed the AHE-specific gut-dysbiosis. The gut microbiome diversity was decreased during AHE, further reduced after medication, and only partially reversed during the recovery. The relative abundance of Bacteroidetes phylum in the microbiome decreased, whereas that of Firmicute, Proteobacteria and Actinobacteria increased in patients during AHE compared with those with compensated cirrhosis. A total of 70 operational taxonomic units (OTUs) were significantly different between AHE and decompensated cirrhosis abundances. Of them, the abundance of Veillonella parvula increased the most during AHE via a metagenomics recovery of the genomes. Moreover, the relative abundances of three (Alistipes, Bacteroides, Phascolarctobacterium) and five OTUs (Clostridium-XI, Bacteroides, Bacteroides, Lactobacillus, Clostridium-sedis) at AHE were respectively associated with HE recurrence and overall survival during the subsequent one-year follow-up. Conclusions: AHE-specific gut OTUs were identified that may be involved in HE development and able to predict clinical outcomes, providing new strategies for the prevention and treatment of HE recurrence in patients with cirrhosis. Keywords: Gut Microbiota, Gut Dysbiosis, Gut-Liver-Brain Axis, Veillonella parvula

An influenza A pandemic occurred in 2009–2010. A novel H1N1 virus (hereafter H1N1pdm) was responsible for this outbreak. H1N1pdm viruses have been largely seen in recent human influenza A viruses. This virus was descended from a triple-reassorted swine virus consisting of human, avian, and swine origins. As a result, the previously established species-associated signatures could be in jeopardy. Methods: We analyzed all influenza A sequences in the past 5 years after the inclusion of H1N1pdm into human viruses since 2009, and examined how human signatures may lose their distinctness by mixing with avian residues that H1N1pdm have brought in. In particular, we compared how those signatures were changed/shifted in the past 5 years for human-isolated avian influenza A viruses and discussed their implications. Results: Only eight out of 47 signatures remained human-like for human influenza A viruses in the past 5 years. They are PB2 271A; PB1 336I; PA 356R and 409N; NP 33I, 305K, and 357K; and NS1 227R. Although most avian-like residues were preserved in human-isolated avian influenza A viruses, a number of them were found to have become or on the verge of becoming human-like, including PB2 627, PA 100, 356, 404, 409, NP 33, 61, 305, 357, M2 20, and NS1 81. Conclusion: Analyzing how species-associated signatures are becoming human-like in human-isolated avian influenza A viruses helps in assessing their potential to go pandemic as well as providing insights into host adaptation.