"I wouldn't really believe statistics" - Challenges with influenza vaccine acceptance among healthcare workers in Singapore.

BACKGROUND: Influenza vaccine acceptance among healthcare workers (HCWs) is a worldwide problem, but relatively little research has focussed on Asia, including Singapore. Despite widespread access and recommendations from public health authorities, influenza vaccine uptake remains suboptimal among HCWs. METHODS: Our qualitative study used focus group discussions to identify and explain factors limiting influenza vaccine acceptance among HCWs in Singapore. A total of 73 doctors, nurses, allied health and ancillary staff across three public hospitals were included. RESULTS: Challenges identified include a fear of contracting influenza from vaccination exacerbated by negative anecdotes regarding vaccine safety and efficacy, distrust of published efficacy data, uncertainty regarding relevance of existing data for Singapore, reluctance to introduce chemicals or overmedicate, pain from injection, low risk attributed to influenza and limited awareness of influenza transmission with a preference for alternatives in patient protection. Differences in attitudes were observed across vocational groups. Lack of overt promotion by hospital leadership in some institutions, perceived vaccine hesitancy among doctors, access, and work culture that implicitly encourages working through illness were further barriers. CONCLUSION: Our findings highlight a combination of misperceptions about influenza vaccination and cognitive biases at the individual level, and challenges at the institutional level limiting uptake. Findings indicate an urgent need to provide targeted education and communication. Rather than providing more data, we recommend a widely-disseminated, locally-compiled synthesis addressing specific concerns of hesitant HCWs. Tailoring interventions to specific vocational groups should be considered. Institutional norms and culture may have a powerful influence in setting default behaviours: more effort is needed in improving influenza vaccine promotion and priority at some institutions, integrating vaccine-related communication with other infection control communication and addressing influenza vaccine hesitancy among doctors as a priority. Finally, further study of strategies to address cognitive biases affecting influenza vaccine acceptance in Singapore is desirable

Klebsiella pneumoniae Carbapenemase-producing Enterobacteria in Hospital, Singapore

10.3201/eid1808.110893Emerging Infectious Diseases1881381-1383EIDI

mcr-3 and mcr-4 Variants in Carbapenemase-Producing Clinical Enterobacteriaceae Do Not Confer Phenotypic Polymyxin Resistance

The worldwide distribution of plasmid-mediated colistin resistance determinants (mcr-1, mcr-2, mcr-3, and mcr-4) coupled to the emerging observation that colistin resistance is more prevalent in carbapenem-resistant Enterobacteriaceae (CRE) (1, 2) presents a daunting challenge in combatting antimicrobial resistance. Undoubtedly, next-generation sequencing approaches have expedited the discovery of mobile colistin resistance determinants (3). In this study, we undertook the in silico screening of 500 phenotypically carbapenem-resistant carbapenemase-producing Enterobacteriaceae whole genomes for the presence of the mcr gene, using CLC Genomics Workbench (CLC Bio-Qiagen, Aarhus, Denmark). The isolates comprised clinical and screening pure cultures submitted to the national reference laboratory for mandatory CRE surveillance. Locally, the presence of mcr-1 as well as its cocarriage with KPC-2 had been previously well described (4, 5); hence, we did not look further into the distribution of mcr-1. mcr-2 was not detected among the genomes analyzed. mcr-3 was identified in one Escherichia coli genome (ENT1955) by the use of both read mapping and de novo assembly.MOH (Min. of Health, S’pore)Published versio

Genomic study of blaIMI-positive Enterobacter cloacae complex in Singapore over a five-year study period

The blaIMI gene is rarely detected outside the Enterobacter genus. Genomic characterization of 87 blaIMI-positive Enterobacter cloacae complex members revealed that the largest phylogenomic clade was made up of E. cloacae subsp. cloacae (71.3%), followed by the newly described species E. bugandensis (13.8%), E. sichuanensis (10.3%), and E. roggenkampii (4.6%). IMI-1 was the predominant carbapenemase variant (86/87, 98.9%). All the blaIMI genes were associated with chromosomally integrated Xer-dependent integrative mobile elements (IMEXs), with two new variants detected.Ministry of Education (MOE)National Medical Research Council (NMRC)Published versionGrant support was provided by the NMRC Clinician-Scientist Individual ResearchGrant (NMRC/CIRG/1463/2016), Singapore Ministry of Education Academic ResearchFund Tier 2 grant: New Delhi Metallo-Beta-Lactamase: A global multicenter, whole-genome study (MOE2015-T2-2-096), NMRC Collaborative Grant: Collaborative SolutionsTargeting Antimicrobial Resistance Threats in Health Systems (CoSTAR-HS) (NMRCCGAug16C005), and NMRC Clinician Scientist Award (NMRC/CSA-INV/0002/2016)

Dengue and COVID-19: Managing Undifferentiated Febrile Illness during a “Twindemic”

Background: During the COVID-19 pandemic, distinguishing dengue from COVID-19 in endemic areas can be difficult, as both may present as undifferentiated febrile illness. COVID-19 cases may also present with false-positive dengue serology. Hospitalisation protocols for managing undifferentiated febrile illness are essential in mitigating the risk from both COVID-19 and dengue. Methods: At a tertiary hospital contending with COVID-19 during a dengue epidemic, a triage strategy of routine COVID-19 testing for febrile patients with viral prodromes was used. All febrile patients with viral prodromes and no epidemiologic risk for COVID-19 were first admitted to a designated ward for COVID-19 testing, from January 2020 to December 2021. Results: A total of 6103 cases of COVID-19 and 1251 cases of dengue were managed at our institution, comprising a total of 3.9% (6103/155,452) and 0.8% (1251/155,452) of admissions, respectively. A surge in dengue hospitalisations in mid-2020 corresponded closely with the imposition of a community-wide lockdown. A total of 23 cases of PCR-proven COVID-19 infection with positive dengue serology were identified, of whom only two were true co-infections; both had been appropriately isolated upon admission. Average length-of-stay for dengue cases initially admitted to isolation during the pandemic was 8.35 days (S.D. = 6.53), compared with 6.91 days (S.D. = 8.61) for cases admitted outside isolation (1.44 days, 95%CI = 0.58–2.30, p = 0.001). Pre-pandemic, only 1.6% (9/580) of dengue cases were admitted initially to isolation-areas; in contrast, during the pandemic period, 66.6% (833/1251) of dengue cases were initially admitted to isolation-areas while awaiting the results of SARS-CoV-2 testing. Conclusions: During successive COVID-19 pandemic waves in a dengue-endemic country, coinfection with dengue and COVID-19 was uncommon. Routine COVID-19 testing for febrile patients with viral prodromes mitigated the potential infection-prevention risk from COVID-19 cases, albeit with an increased length-of-stay for dengue hospitalizations admitted initially to isolation

The impact of healthcare associated infections on mortality and length of stay in Singapore - A time-varying analysis

Objective: Methods that include the time-varying nature of healthcare-associated infections (HAIs) avoid biases when estimating increased risk of death and excess length of stay. We determined the excess mortality risk and length of stay associated with HAIs among inpatients in Singapore using a multistate model that accommodates the timing of key events. Design: Analysis of existing prospective cohort study data. Setting: Seven public acute-care hospitals in Singapore. Patients: Inpatients reviewed in a HAI point-prevalence survey (PPS) conducted between June 2015 and February 2016. Methods: We modeled each patient's admission over time using 4 states: susceptible with no HAI, infected, died, and discharged alive. We estimated the excess mortality risk and length of stay associated with HAIs, with adjustment for the baseline characteristics between the groups for mortality risk. Results: We included 4,428 patients, of whom 469 had ≥1 HAI. Using a multistate model, the expected excess length of stay due to any HAI was 1.68 days (95% confidence interval [CI], 1.15-2.21 days). Surgical site infections were associated with the longest excess length of stay of 4.68 days (95% CI, 2.60-6.76 days). After adjusting for baseline differences, HAIs were associated with increased hazards of in-hospital mortality (adjusted hazard ratio [aHR], 1.32; 95% CI, 1.09-1.65) and decreased hazards in being discharged (aHR, 0.75; 95% CI, 0.67-0.84). Conclusions: HAIs are associated with increased length of hospital stay and mortality in hospitalized patients. Avoiding nosocomial infections can improve patient outcomes and free valuable bed days. </p

Relapsing COVID-19 infection as a manifestation of Good syndrome: a case report and literature review

Good syndrome (GS) is a rare acquired immunodeficiency disease characterized by the presence of thymoma with combined B and T cell immunodeficiency in adults. Recurrent bacterial infections, particularly sinopulmonary infections caused by encapsulated bacteria, remain the most common infective presentation of GS; however, relapsing viral infections have also been reported, likely due to impaired T cell-mediated immunity. Relapsing COVID-19 infection, however, has not been previously reported as a manifestation of GS. We present two cases of relapsing COVID-19 infection in patients with GS; in one case, relapsing COVID-19 was the first manifestation of newly diagnosed GS

Comparison of Various HIV Screening Programmes ^*.

<p>* Results for years 2010 to 2012</p><p>Comparison of Various HIV Screening Programmes ^{<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0116987#t005fn001" target="_blank">*</a>}.</p

Reasons for Opting in (<i>n</i> = 21).

<p>* A total of 21 patients who opted in answered the questions above; percentage was calculated as a proportion of 21</p><p>Reasons for Opting in (<i>n</i> = 21).</p