The Pulse of Singapore: Short-Term HRV Norms.

Short-term heart rate variability (HRV) is increasingly used to assess autonomic nervous system activity and found to be useful for monitoring and providing care due to its quick measurement. With evidence of low HRV associated with chronic diseases, mental disorders, and an increased risk of cardiovascular disease, having normative data of HRV across the age spectrum would be useful for monitoring health and well-being of a population. This study examines HRV of healthy Singapore sample, with ages ranging from 10 to 89 years. Short-term HRV of five minutes was measured from 2,143 participants. 974 males and 1,169 females, and overall HRV was found to be 42.4ms (RMSSD) and 52.0 ms (SDNN) with a further breakdown of HRV by age and gender. Overall HRV declined with age and gender, although gender differences dissipated in the 60s age range onwards, with the 50s age range having the sharpest decline in HRV. Short-term HRV norms were similar to Nunan et al.'s (2010) systematic review in various populations and less similar to Choi et al.'s (2020) study on Koreans.

COVID-19 vaccine hesitancy in Australian patients with solid organ cancers.

BackgroundVaccination is the cornerstone of the global public health response to the COVID-19 pandemic. Excess morbidity and mortality of COVID-19 infection is seen in people with cancer. COVID-19 vaccine hesitancy has been observed in this medically vulnerable population, although associated attitudes and beliefs remain poorly understood. Patients and MethodsAn online cross-sectional survey of people with solid organ cancers was conducted through nine health services across Australia. Demographics, cancer-related characteristics, and vaccine uptake were collected. Perceptions and beliefs regarding COVID-19 vaccination were assessed using the Oxford COVID-19 Vaccine Hesitancy Scale, the Oxford COVID-19 Vaccine Confidence and Complacency Scale, and the Disease Influenced Vaccine Acceptance Scale-6. ResultsBetween June and October 2021, 2691 people with solid organ cancers completed the survey. Median age was 62.5 years (SD=11.8; range 19-95), 40.9% were male, 71.3% lived in metropolitan areas, and 90.3% spoke English as their first language. The commonest cancer diagnoses were breast (36.6%), genitourinary (18.6%) and gastrointestinal (18.3%); 59.2% had localized disease and 56.0% were receiving anti-cancer therapy. Most participants (79.7%) had at least one COVID-19 vaccine dose. Vaccine uptake was higher in people who were older, male, metropolitan, spoke English as a first language, and had a cancer diagnosis for more than six months. Vaccine hesitancy was higher in people who were younger, female, spoke English as a non-dominant language and lived in a regional location, and lower in people with genitourinary cancer. Vaccinated respondents were more concerned about being infected with COVID-19 and less concerned about vaccine safety and efficacy. ConclusionsPeople with cancer have concerns about acquiring COVID-19, which they balance against vaccine-related concerns about the potential impact on their disease progress and/or treatment. Detailed exploration of concerns in cancer patients provides valuable insights, both for discussions with individual patients and public health messaging for this vulnerable population.

Serious underlying medical conditions and COVID-19 vaccine hesitancy.

ObjectiveTo examine vaccine uptake, hesitancy and explanatory factors amongst people with serious and/or chronic health conditions, including the impact of underlying disease on attitudes to vaccination. DesignCross-sectional survey. SettingTen Australian health services. Participants4683 patients (3560 cancer, 842 diabetes and 281 multiple sclerosis) receiving care at the health services participated in the 42-item survey, between June 30 to October 5, 2021. Main outcome measuresSociodemographic and disease-related characteristics, COVID-19 vaccine uptake, and the scores of three validated scales which measured vaccine hesitancy and vaccine-related beliefs generally and specific to the participants disease, including the Oxford COVID-19 Vaccine Hesitancy Scale, the Oxford COVID-19 Vaccine Confidence and Complacency Scale and the Disease Influenced Vaccine Acceptance Scale. Multivariable logistic regression was used to determine the associations between scale scores and vaccine uptake. ResultsOf all participants, 81.5% reported having at least one COVID-19 vaccine. Unvaccinated status was associated with younger age, female sex, lower education and income, English as a second language, and residence in regional areas (all p<0.05). Unvaccinated participants were more likely to report greater vaccine hesitancy and more negative perceptions toward vaccines (all p<0.05). Disease-related vaccine concerns were associated with unvaccinated status and hesitancy, including greater complacency about COVID-19 infection, and concerns relating to vaccine efficacy and impact on their disease and/or treatment (all p<0.05). ConclusionsDisease-specific concerns impact COVID-19 vaccine-related behaviours and beliefs in people with serious and/or chronic health conditions. This highlights the need to develop targeted strategies and education about COVID-19 vaccination to support medically vulnerable populations and health professionals. Trial registrationACTRN12621001467820

Epidemiological waves - types, drivers and modulators in the COVID-19 pandemic

IntroductionA discussion of waves of the COVID-19 epidemic in different countries is a part of the national conversation for many, but there is no hard and fast means of delineating these waves in the available data and their connection to waves in the sense of mathematical epidemiology is only tenuous. MethodsWe present an algorithm which processes a general time series to identify substantial, significant and sustained periods of increase in the value of the time series, which could reasonably be described as observed waves. This provides an objective means of describing observed waves in time series. ResultsThe output of the algorithm as applied to epidemiological time series related to COVID-19 corresponds to visual intuition and expert opinion. Inspecting the results of individual countries shows how consecutive observed waves can differ greatly with respect to the case fatality ratio. Furthermore, in large countries, a more detailed analysis shows that consecutive observed waves have different geographical ranges. We also show how waves can be modulated by government interventions and find that early implementation of non-pharmaceutical interventions correlates with a reduced number of observed waves and reduced mortality burden in those waves. ConclusionIt is possible to identify observed waves of disease by algorithmic methods and the results can be fruitfully used to analyse the progression of the epidemic.