The emergence and successful elimination of SARS-CoV-2 dominant strains with increasing epidemic potential in Taiwan's 2021 outbreak.

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.

Airborne Avian Influenza Virus in Ambient Air in the Winter Habitats of Migratory Birds.

Outbreaks of avian influenza virus (AIV) have raised public concerns recently. Airborne AIV has been evaluated in live poultry markets and case farms; however, no study has discussed airborne AIV in ambient air in the winter habitats of migratory birds. Therefore, this study aimed to evaluate airborne AIV, specifically H5, H7, and H9, in a critical winter habitat of migratory birds and assess the factors influencing airborne AIV transmission in ambient air to provide novel insights into the epidemiology of avian influenza. A total of 357 ambient air samples were collected in the Aogu Wetland, Taiwan, Republic of China, between October 2017 and December 2019 and analyzed using quantitative real-time polymerase chain reaction. The effects of environmental factors including air pollutants, meteorological factors, and the species of the observed migratory birds on the concentration of airborne AIV were also analyzed. To our knowledge, this is the first study to investigate the relationship between airborne AIV in ambient air and the influence factors in the winter habitats of migratory birds, demonstrating the benefits of environmental sampling for infectious disease epidemiology. The positive rate of airborne H7 (12%) was higher than that of H5 (8%) and H9 (10%). The daily mean temperature and daily maximum temperature had a significant negative correlation with influenza A, H7, and H9. Cold air masses and bird migration were significantly associated with airborne H9 and H7, respectively. In addition, we observed a significant correlation between AIV and the number of pintails, common teals, Indian spot-billed ducks, northern shovelers, Eurasian wigeons, tufted ducks, pied avocets, black-faced spoonbills, and great cormorants. In conclusion, we demonstrated the potential for alternative surveillance approaches (monitoring bird species) as an indicator for influenza-related risks and identified cold air masses and the presence of specific bird species as potential drivers of the presence and/or the airborne concentration of AIV.

Impact of prior infection and repeated vaccination on post-vaccination antibody titers of the influenza A(H1N1)pdm09 strain in Taiwan schoolchildren: Implications for public health.

BACKGROUND: The objective of this study was to evaluate the effects of prior-infection and repeated vaccination on post-vaccination antibody titers. METHODS: A(H1N1)pdm09 strain was included in 2009 pandemic monovalent, 2010-2011, and 2011-2012 trivalent influenza vaccines (MIVpdm09, TIV10/11, TIV11/12) in Taiwan. During the 2011-2012 influenza season, we conducted a prospective sero-epidemiological cohort study among schoolchildren from grades 1 - 6 in the two elementary schools in Taipei with documented A(H1N1)pdm09 vaccination records since 2009. Serum samples were collected at pre-vaccination, 1-month, and 4-months post-vaccination (T1, T2, T3). Anti-A(H1N1)pdm09 hemagglutination inhibition titers (HI-Ab-titers) were examined. We also investigated the impact of four vaccination histories [(1) no previous vaccination (None), (2) vaccinated in 2009-2010 season (09v), (3) vaccinated in 2010-2011 season (10v), and (4) vaccinated consecutively in 2009-2010 and 2010-2011 seasons (09v + 10v)] and pre-vaccination HI-Ab levels on post-vaccination HI-Ab responses as well as adjusted vaccine effectiveness (aVE) against serologically-defined infection from T2 to T3. RESULTS: TIV11/12 had zero serious adverse events reported. A(H1N1)pdm09 strain in TIV11/12 elicited seroprotective Ab-titers in 98% of children and showed promising protection (aVE: 70.3% [95% confidence interval (CI): 51.0-82.1%]). Previously unvaccinated but infected children had a 3.96 times higher T2 geometric mean titer (T2-GMT) of HI-Ab than those naïve to A(H1N1)pdm09 (GMT [95% CI]: 1039.7[585.3-1845.9] vs. 262.5[65.9-1045], p = 0.046). Previously vaccinated children with seroprotective T1-Ab-titers had a higher T2-GMT and a greater aVE than those with non-seroprotective T1-Ab-titers. Repeatedly vaccinated children had lower T2-GMT than those receiving primary doses of TIV11/12. However, after controlling prior infection and T1-Ab-titers, differences in T2-GMT among the four vaccination histories became insignificant (p = 0.16). CONCLUSION: This study supports the implementation of annual mass-vaccination with A(H1N1)pdm09 in schoolchildren for three consecutive influenza seasons when vaccine and circulating strains were well matched, and found that prior infection and pre-vaccination HI-Ab levels positively impacted post-vaccination HI-Ab responses.

Taiwan's Response to Influenza: A Seroepidemiological Evaluation of Policies and Implications for Pandemic Preparedness.

OBJECTIVES: To evaluate class suspension and mass vaccination implemented among Taipei schoolchildren during the 2009 influenza pandemic and investigate factors affecting antibody responses. METHODS: We conducted 2 cohort studies on: (1) 972 schoolchildren from November 2009-March 2010 to evaluate pandemic policies and (2) 935 schoolchildren from November 2011-March 2012 to verify factors in antibody waning. Anti-influenza H1N1pdm09 hemagglutination inhibition antibodies (HI-Ab) were measured from serum samples collected before vaccination, and at 1 and 4 months after vaccination. Factors affecting HI-Ab responses were investigated through logistic regression and generalized estimating equation. RESULTS: Seroprevalence of H1N1pdm09 before vaccination was significantly higher among schoolchildren who experienced class suspensions than those who did not (59.6% vs 47.5%, p<0.05). Participating in after-school activities (adjusted odds ratio [aOR]=2.47, p=0.047) and having ≥3 hours per week of exercise (aOR=2.86, p=0.019) were significantly correlated with H1N1pdm09 infection. Two doses of the H1N1pdm09 vaccine demonstrated significantly better antibody persistence than 1 dose (HI-Ab geometric mean titer: 132.5 vs 88.6, p=0.047). Vaccine effectiveness after controlling for preexisting immunity was 86% (32%-97%). Exercise ≥3 hours per week and preexisting immunity were significantly associated with antibody waning/maintenance. CONCLUSIONS: This study is the first to show that exercise and preexisting immunity may affect antibody waning. Further investigation is needed to identify immune correlates of protection.

A multitope SARS-CoV-2 vaccine provides long-lasting B cell and T cell immunity against Delta and Omicron variants.

BackgroundThe Delta and Omicron variants of SARS-CoV-2 are currently responsible for breakthrough infections due to waning immunity. We report phase I/II trial results of UB-612, a multitope subunit vaccine containing S1-RBD-sFc protein and rationally designed promiscuous peptides representing sarbecovirus conserved helper T cell and cytotoxic T lymphocyte epitopes on the nucleocapsid (N), membrane (M), and spike (S2) proteins.MethodWe conducted a phase I primary 2-dose (28 days apart) trial of 10, 30, or 100 µg UB-612 in 60 healthy young adults 20 to 55 years old, and 50 of them were boosted with 100 µg of UB-612 approximately 7 to 9 months after the second dose. A separate placebo-controlled and randomized phase II study was conducted with 2 doses of 100 µg of UB-612 (n = 3,875, 18-85 years old). We evaluated interim safety and immunogenicity of phase I until 14 days after the third (booster) dose and of phase II until 28 days after the second dose.ResultsNo vaccine-related serious adverse events were recorded. The most common solicited adverse events were injection site pain and fatigue, mostly mild and transient. In both trials, UB-612 elicited respective neutralizing antibody titers similar to a panel of human convalescent sera. The most striking findings were long-lasting virus-neutralizing antibodies and broad T cell immunity against SARS-CoV-2 variants of concern (VoCs), including Delta and Omicron, and a strong booster-recalled memory immunity with high cross-reactive neutralizing titers against the Delta and Omicron VoCs.ConclusionUB-612 has presented a favorable safety profile, potent booster effect against VoCs, and long-lasting B and broad T cell immunity that warrants further development for both primary immunization and heterologous boosting of other COVID-19 vaccines.Trial RegistrationClinicalTrials.gov: NCT04545749, NCT04773067, and NCT04967742.FundingUBI Asia, Vaxxinity Inc., and Taiwan Centers for Disease Control, Ministry of Health and Welfare.

Machine learning for emerging infectious disease field responses.

Emerging infectious diseases (EIDs), including the latest COVID-19 pandemic, have emerged and raised global public health crises in recent decades. Without existing protective immunity, an EID may spread rapidly and cause mass casualties in a very short time. Therefore, it is imperative to identify cases with risk of disease progression for the optimized allocation of medical resources in case medical facilities are overwhelmed with a flood of patients. This study has aimed to cope with this challenge from the aspect of preventive medicine by exploiting machine learning technologies. The study has been based on 83,227 hospital admissions with influenza-like illness and we analysed the risk effects of 19 comorbidities along with age and gender for severe illness or mortality risk. The experimental results revealed that the decision rules derived from the machine learning based prediction models can provide valuable guidelines for the healthcare policy makers to develop an effective vaccination strategy. Furthermore, in case the healthcare facilities are overwhelmed by patients with EID, which frequently occurred in the recent COVID-19 pandemic, the frontline physicians can incorporate the proposed prediction models to triage patients suffering minor symptoms without laboratory tests, which may become scarce during an EID disaster. In conclusion, our study has demonstrated an effective approach to exploit machine learning technologies to cope with the challenges faced during the outbreak of an EID.

Risk mapping of highly pathogenic avian influenza H5 during 2012-2017 in Taiwan with spatial bayesian modelling: Implications for surveillance and control policies.

During 2012-2017, a total of 1,144 highly pathogenic avian influenza (HPAI) H5 outbreaks were reported in Taiwan. We conjectured the current 3-km radius of the post-outbreak containment policy could fail to effectively alleviate the current ongoing epidemics of HPAI H5 in Taiwan. The high intensity of localized transmission of HPAI H5 at certain focal hotspots was identified to follow the spatial distribution of poultry-raising locations through our hotspot analyses on the HPAI H5 outbreak locations from 2015 to 2017. We then applied 3-, 5- and 7-km circular buffer zones to 15,444 registered poultry-raising locations to inspect the characteristics of the poultry-raising neighbourhood. Three spatial regression models using Bayesian inference were established to infer the risks attributable to poultry-raising characteristics in the corresponding buffer areas. The different buffer radii were treated as a sensitivity analysis of the influential range of neighbouring farms on the HPAI H5 outbreak occurrence, so as to evaluate the effective radius for post-outbreak containment. Evidence showed that the risks of outbreak occurrence were associated with increasing numbers of poultry-raising locations in both 3-km (relative risk [RR] 1.005, 95% confidence interval [CI] 1.002-1.008) and 5-km buffer areas (RR 1.005, 95% CI 1.004-1.007), whereas in the 7-km buffer model, no association between densely populated locations and increasing risks of outbreaks was observed (RR 1.000, 95% CI 0.999-1.001). Therefore, an extension to a 7-km radius for the post-outbreak containment policy (rather than a 3-km radius as in the current policy) is recommended to effectively mitigate further spreading of HPAI H5 outbreaks among neighbouring farms. Overall, we demonstrated that the densely populated locations with multiple poultry species raised in proximity as defined with 3-, 5- and 7-km buffer areas facilitated H5 HPAI outbreak diffusion and shaped the scale of HPAI H5 epidemics in Taiwan.

Learning from the past: Taiwan's responses to COVID-19 versus SARS.

OBJECTIVES: To evaluate the prevalence of infection prevention behaviors in Taiwan-wearing facemasks and alcohol-based hand hygiene (AHH)-and compare their practice rates during SARS and COVID-19. METHODS: We surveyed 2328 Taiwanese from July 29 to August 6, 2020, assessing demographics, information sources, and preventive behaviors during the 2003 SARS outbreaks, 2009 pandemic influenza H1N1, COVID-19, and with post-survey intentions. Characteristics associated with the practice of preventive behaviors in 2020 were identified through logistic regression. RESULTS: Preventive behaviors were conscientiously practiced by 70.2% of participants. Compared with 2003 SARS/2009 H1N1, the percentages of facemask use (66.6% vs 99.2% [indoors], P < 0.001) and on-person AHH (44.2% vs 65.4% [hand sanitizers], P < 0.001) significantly increasedduring 2020 COVID-19. Highest adherence to preventive behaviors in 2020 was among females (adjusted odds ratio [aOR], 1.72), those receiving government COVID-19 information (aOR, 1.52), participants recruited from primary-care clinics (aOR, 1.43), and those who practiced AHH during 2003 SARS/2009 H1N1 (aOR, 1.37). CONCLUSIONS: Government leadership, healthcare providers risk communication, and public cooperation rapidly mitigated the spread of COVID-19 in Taiwan even before vaccination. Future global efforts must implement such population-based preventive behaviors at a level above the viral-transmission-threshold, particularly in areas with fast-spreading SARS-CoV-2 variants.

Use of seroprevalence to guide dengue vaccination plans for older adults in a dengue non-endemic country.

A shift in dengue cases toward the adult population, accompanied by an increased risk of severe cases of dengue in the elderly, has created an important emerging issue in the past decade. To understand the level of past DENV infection among older adults after a large dengue outbreak occurred in southern Taiwan in 2015, we screened 1498 and 2603 serum samples from healthy residents aged ≥ 40 years in Kaohsiung City and Tainan City, respectively, to assess the seroprevalence of anti-DENV IgG in 2016. Seropositive samples were verified to exclude cross-reaction from Japanese encephalitis virus (JEV), using DENV/JEV-NS1 indirect IgG ELISA. We further identified viral serotypes and secondary DENV infections among positive samples in the two cities. The overall age-standardized seroprevalence of DENV-IgG among participants was 25.77% in Kaohsiung and 11.40% in Tainan, and the seroprevalence was significantly higher in older age groups of both cities. Although the percentages of secondary DENV infection in Kaohsiung and Tainan were very similar (43.09% and 44.76%, respectively), DENV-1 and DENV-2 spanned a wider age range in Kaohsiung, whereas DENV-2 was dominant in Tainan. As very few studies have obtained the serostatus of DENV infection in older adults and the elderly, this study highlights the need for further investigation into antibody status, as well as the safety and efficacy of dengue vaccination in these older populations.

Comparing machine learning with case-control models to identify confirmed dengue cases.

In recent decades, the global incidence of dengue has increased. Affected countries have responded with more effective surveillance strategies to detect outbreaks early, monitor the trends, and implement prevention and control measures. We have applied newly developed machine learning approaches to identify laboratory-confirmed dengue cases from 4,894 emergency department patients with dengue-like illness (DLI) who received laboratory tests. Among them, 60.11% (2942 cases) were confirmed to have dengue. Using just four input variables [age, body temperature, white blood cells counts (WBCs) and platelets], not only the state-of-the-art deep neural network (DNN) prediction models but also the conventional decision tree (DT) and logistic regression (LR) models delivered performances with receiver operating characteristic (ROC) curves areas under curves (AUCs) of the ranging from 83.75% to 85.87% [for DT, DNN and LR: 84.60% ± 0.03%, 85.87% ± 0.54%, 83.75% ± 0.17%, respectively]. Subgroup analyses found all the models were very sensitive particularly in the pre-epidemic period. Pre-peak sensitivities (<35 weeks) were 92.6%, 92.9%, and 93.1% in DT, DNN, and LR respectively. Adjusted odds ratios examined with LR for low WBCs [≤ 3.2 (x103/µL)], fever (≥38°C), low platelet counts [< 100 (x103/µL)], and elderly (≥ 65 years) were 5.17 [95% confidence interval (CI): 3.96-6.76], 3.17 [95%CI: 2.74-3.66], 3.10 [95%CI: 2.44-3.94], and 1.77 [95%CI: 1.50-2.10], respectively. Our prediction models can readily be used in resource-poor countries where viral/serologic tests are inconvenient and can also be applied for real-time syndromic surveillance to monitor trends of dengue cases and even be integrated with mosquito/environment surveillance for early warning and immediate prevention/control measures. In other words, a local community hospital/clinic with an instrument of complete blood counts (including platelets) can provide a sentinel screening during outbreaks. In conclusion, the machine learning approach can facilitate medical and public health efforts to minimize the health threat of dengue epidemics. However, laboratory confirmation remains the primary goal of surveillance and outbreak investigation.

FluConvert and IniFlu: a suite of integrated software to identify novel signatures of emerging influenza viruses with increasing risk.

BACKGROUND: The pandemic threat of influenza has attracted great attention worldwide. To assist public health decision-makers, new suites of tools are needed to rapidly process and combine viral information retrieved from public-domain databases for a better risk assessment. RESULTS: Using our recently developed FluConvert and IniFlu software, we automatically processed and rearranged sequence data by standard viral nomenclature, determined the group-related consensus sequences, and identified group-specific polygenic signatures. The software possesses powerful ability to integrate viral, clinical, and epidemiological data. We demonstrated that both multiple basic amino acids at the cleavage site of the HA gene and also at least 11 more evidence-based viral amino acid substitutions present in global highly pathogenic avian influenza H5N2 viruses during the years 2009-2016 that are associated with viral virulence and human infection. CONCLUSIONS: FluConvert and IniFlu are useful to monitor and assess all subtypes of influenza viruses with pandemic potential. These programs are implemented through command-line and user-friendly graphical interfaces, and identify molecular signatures with virological, epidemiological and clinical significance. FluConvert and IniFlu are available at https://apps.flutures.com or https://github.com/chinrur/FluConvert_IniFlu.

Recommendations for protecting against and mitigating the COVID-19 pandemic in long-term care facilities.

The COVID-19 outbreak has drawn heightened attention from public health scholars researching ways to limit its spread. Much of the research has been focused on minimizing transmission in hospitals and in the general community. However, a particularly vulnerable community that has received relatively little attention is elders residing in long-term care facilities (LTCFs). In this article we address this relative lack of attention, arguing that enhanced traffic control bundling (eTCB) can and should be adopted and implemented as a means of protecting LTCF residents and staff. Enhanced TCB has been widely applied in hospital settings and has proven effective at limiting droplet and fomite transmissions both within hospitals and between hospitals and the general community. By effectively adapting eTCB to LTCF conditions, particularly by incorporating compartmentalization within zones plus active surveillance, COVID-19 transmission into and throughout LTCFs can be minimized, thereby saving numerous lives among an especially vulnerable population.

Suppressed humoral immunity is associated with dengue nonstructural protein NS1-elicited anti-death receptor antibody fractions in mice.

Dengue virus (DENV) infections may cause life-threatening dengue hemorrhagic fever (DHF). Suppressed protective immunity was shown in these patients. Although several hypotheses have been formulated, the mechanism of DENV-induced immunosuppression remains unclear. Previously, we found that cross-reactive antibodies against tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) receptor 1 (death receptor 4 [DR4]) were elicited in DHF patients, and that anti-DR4 autoantibody fractions were elicited by nonstructural protein 1 (NS1) immunizations in experimental mice. In this study, we found that anti-DR4 antibodies could suppress B lymphocyte function in vitro and in vivo. Treatment with the anti-DR4 immunoglobulin (Ig) induced caspase-dependent cell death in immortalized B lymphocyte Raji cells in vitro. Anti-DR4 Igs elicited by NS1 and DR4 immunizations markedly suppressed mouse spleen transitional T2 B (IgM+IgD+), bone marrow pre-pro-B (B220+CD43+), pre-B (B220+CD43-), and mature B cell (B220+IgD+) subsets in mice. Furthermore, functional analysis revealed that the pre-elicitation of anti-NS1 and anti-DR4 Ig titers suppressed subsequently neutralizing antibody production by immunization with DENV envelop protein. Our data suggest that the elicitation of anti-DR4 titers through DENV NS1 immunization plays a suppressive role in humoral immunity in mice.

Interrupting COVID-19 transmission by implementing enhanced traffic control bundling: Implications for global prevention and control efforts.

We argue that enhanced Traffic Control Bundling (eTCB) can interrupt the community-hospital-community transmission cycle, thereby limiting COVID-19's impact. Enhanced TCB is an expansion of the traditional TCB that proved highly effective during Taiwan's 2003 SARS outbreak. TCB's success derived from ensuring that Health Care Workers (HCWs) and patients were protected from fomite, contact and droplet transmission within hospitals. Although TCB proved successful during SARS, achieving a similar level of success with the COVID-19 outbreak requires adapting TCB to the unique manifestations of this new disease. These manifestations include asymptomatic infection, a hyper-affinity to ACE2 receptors resulting in high transmissibility, false negatives, and an incubation period of up to 22 days. Enhanced TCB incorporates the necessary adaptations. In particular, eTCB includes expanding the TCB transition zone to incorporate a new sector - the quarantine ward. This ward houses patients exhibiting atypical manifestations or awaiting definitive diagnosis. A second adaptation involves enhancing the checkpoint hand disinfection and gowning up with Personal Protective Equipment deployed in traditional TCB. Under eTCB, checkpoint hand disinfection and donning of face masks are now required of all visitors who seek to enter hospitals. These enhancements ensure that transmissions by droplets, fomites and contact are disrupted both within hospitals and between hospitals and the broader community. Evidencing eTCB effectiveness is Taiwan's success to date in containing and controlling the community-hospital-community transmission cycle.

Protecting Healthcare Workers During the Coronavirus Disease 2019 (COVID-19) Outbreak: Lessons From Taiwan's Severe Acute Respiratory Syndrome Response.

During major epidemic outbreaks, demand for healthcare workers (HCWs) grows even as the extreme pressures they face cause declining availability. We draw on Taiwan's severe acute respiratory syndrome (SARS) experience to argue that a modified form of traffic control bundling (TCB) protects HCW safety and by extension strengthens overall coronavirus disease 2019 (COVID-19) epidemic control.

National retrospective cohort study to identify age-specific fatality risks of comorbidities among hospitalised patients with influenza-like illness in Taiwan.

OBJECTIVES: This study aimed to examine comprehensively the prognostic impact of underlying comorbidities among hospitalised patients with influenza-like illness (ILI) in different age groups and provide recommendations targeting the vulnerable patients. SETTING AND PARTICIPANTS: A retrospective cohort of 83 227 hospitalised cases with ILI were identified from Taiwan's National Health Insurance Research Database from January 2005 to December 2010. Cases were stratified into three different age groups: paediatric (0-17 years), adult (18-64 years) and elderly (≧65 years), and their age, sex, comorbidity and past healthcare utilisation were analysed for ILI-associated fatality. MAIN OUTCOME MEASURES: ORs for ILI-related fatality in different age groups were performed using multivariable analyses with generalised estimating equation models and adjusted by age, sex and underlying comorbidities. RESULTS: Hospitalised ILI-related fatality significantly increased with comorbidities of cancer with metastasis (adjusted OR (aOR)=3.49, 95% CI: 3.16 to 3.86), haematological malignancy (aOR=3.02, 95% CI: 2.43 to 3.74), cancer without metastasis (aOR=1.72, 95% CI: 1.54 to 1.91), cerebrovascular (aOR=1.24, 95% CI: 1.15 to 1.33) and heart diseases (aOR=1.19, 95% CI: 1.11 to 1.27) for all age groups. Adult patients with AIDS; adult and elderly patients with chronic kidney disease, tuberculosis and diabetes were significantly associated with elevated risk of death. Severe liver diseases and hypothyroidism among elderly, and dementia/epilepsy among elderly and paediatrics were distinctively associated with likelihood of ILI-related fatality. CONCLUSIONS: Different age-specific comorbidities were associated with increasing risk of death among hospitalised ILI patients. These findings may help update guidelines for influenza vaccination and other prevention strategies in high-risk groups for minimising worldwide ILI-related deaths.

Inter- and intra-host sequence diversity reveal the emergence of viral variants during an overwintering epidemic caused by dengue virus serotype 2 in southern Taiwan.

Purifying selection during dengue viral infection has been suggested as the driving force of viral evolution and the higher complexity of the intra-host quasi-species is thought to offer an adaptive advantage for arboviruses as they cycle between arthropod and vertebrate hosts. However, very few studies have been performed to investigate the viral genetic changes within (intra-host) and between (inter-host) humans in a spatio-temporal scale. Viruses of different serotypes from various countries imported to Taiwan cause annual outbreaks. During 2001-2003, two consecutive outbreaks were caused by dengue virus serotype 2 (DENV-2) and resulted in a larger-scale epidemic with more severe dengue cases in the following year. Phylogenetic analyses showed that the viruses from both events were similar and related to the 2001 DENV-2 isolate from the Philippines. We comprehensively analyzed viral sequences from representative dengue patients and identified three consensus genetic variants, group Ia, Ib and II, with different spatio-temporal population dynamics. The phylodynamic analysis suggested group Ib variants, characterized by lower genetic diversity, transmission rate, and intra-host variant numbers, might play the role of maintenance variants. The residential locations among the patients infected by group Ib variants were in the outer rim of case clusters throughout the 2001-2003 period whereas group Ia and II variants were located in the centers of case clusters, suggesting that group Ib viruses might serve as "sheltered overwintering" variants in an undefined ecological niche. Further deep sequencing of the viral envelope (E) gene directly from individual patient serum samples confirmed the emergence of variants belonging to three quasi-species (group Ia, Ib, and II) and the ancestral role of the viral variants in the latter phase of the 2001 outbreak contributed to the later, larger-scale epidemic beginning in 2002. These findings enhanced our understanding of increasing epidemic severity over time in the same epidemic area. It also highlights the importance of combining phylodynamic and deep sequencing analysis as surveillance tools for detecting dynamic changes in viral variants, particularly searching for and monitoring any specific viral subpopulation. Such subpopulations might have selection advantages in both fitness and transmissibility leading to increased epidemic severity.

Correction: The Critical Role of Early Dengue Surveillance and Limitations of Clinical Reporting - Implications for Non-Endemic Countries.

[This corrects the article DOI: 10.1371/journal.pone.0160230.].

Virulence of Japanese Encephalitis Virus Genotypes I and III, Taiwan.

The virulence of genotype I (GI) Japanese encephalitis virus (JEV) is under debate. We investigated differences in the virulence of GI and GIII JEV by calculating asymptomatic ratios based on serologic studies during GI- and GIII-JEV endemic periods. The results suggested equal virulence of GI and GIII JEV among humans.