Functional ANOVA approaches for detecting changes in air pollution during the COVID-19 pandemic (preprint)

Faced with novel coronavirus outbreak, the most hard-hit countries adopted a lockdown strategy to contrast the spread of virus. Many studies have already documented that the COVID-19 control actions have resulted in improved air quality locally and around the world. Following these lines of research, we focus on air quality changes in the urban territory of Chieti-Pescara (Central Italy), identified as an area of criticality in terms of air pollution. Concentrations of NO2, PM10, PM2.5 and benzene are used to evaluate air pollution changes in this Region. Data were measured by several monitoring stations over two specific periods: from 1st February to 10 th March 2020 (before lockdown period) and from 11st March 2020 to 18 th April 2020 (during lockdown period). The impact of lockdown on air quality is assessed through functional data analysis. Our work makes an important contribution to the analysis of variance for functional data (FANOVA). Specifically, a novel approach based on multivariate functional principal component analysis is introduced to tackle the multivariate FANOVA problem for independent measures, which is reduced to test multivariate homogeneity on the vectors of the most explicative principal components scores. Results of the present study suggest that the level of each pollutant changed during the confinement. Additionally, the differences in the mean functions of all pollutants according to the location and type of monitoring stations (background vs traffic), are ascribable to the PM10 and benzene concentrations for pre-lockdown and during-lockdown tenure, respectively. FANOVA has proven to be beneficial to monitoring the evolution of air quality in both periods of time. This can help environmental protection agencies in drawing a more holistic picture of air quality status in the area of interest.

ERS technical standards for using type III devices (limited channel studies) in the diagnosis of sleep disordered breathing in adults and children.

For more than three decades, type III devices have been used in the diagnosis of sleep disordered breathing in supervised as well as unsupervised settings. They have satisfactory positive and negative predictive values for detecting obstructive and central sleep apnoea in populations with moderately high pre-test probability of symptoms associated with these events. However, standardisation of commercially available type III devices has never been undertaken and the technical specifications can vary widely. None have been subjected to the same rigorous processes as most other diagnostic modalities in the medical field. Although type III devices do not include acquisition of electroencephalographic signals overnight, the minimum number of physical sensors required to allow for respiratory event scoring using standards outlined by the American Academy of Sleep Medicine remains debatable. This technical standard summarises data on type III studies published since 2007 from multiple perspectives in both adult and paediatric sleep practice. Most importantly, it aims to provide a framework for considering current type III device limitations in the diagnosis of sleep disordered breathing while raising research- and practice-related questions aimed at improving our use of these devices in the present and future.

Willingness to receive COVID-19 vaccine and associated factors among students of higher education institutions: the case of Rift Valley University, Adama, Central Ethiopia: a cross sectional study (preprint)

Introduction: The accelerated global spread of COVID-19 and its high death rate have prompted the World Health Organization to implement vaccination as an effective way to curb the spread of the disease. Accordingly, Ethiopia has launched a national vaccination campaign against the disease. However, the willingness of people to receive the vaccine was considered as an important pre-requisite for the success of the vaccination campaign. The aim of this study was to assess the magnitude of willingness towards COVID-19 vaccination and associated factors among students at Rift Valley University, Adama, Ethiopia, in 2022. Methods: A cross-sectional study was conducted from January 10 to January 25, 2022 among 490 randomly selected students at Rift Valley University, Adama campus. Data was collected by using an interviewer administered questionnaire and was entered into Epi Info version 7 and exported to SPSS version 21 for cleaning and analysis. Results: The proportion of willingness to receive the COVID-19 vaccine was 60.2% (95%CI: 55.9, 64.5). Being male (AOR: 2.72; 95% CI: 1.14, 2.76), having a family history of COVID-19 infection (AOR: 1.2, 95% CI: 1.07, 1.54), having ever taken any vaccine (AOR: 1.7, 95% CI: 1.14, 2.27), and respondents believing the COVID-19 vaccine has no severe side effects (AOR: 2.3, 95% CI: 1.27, 3.01) were all positive predictors of willingness. Conclusions: The proportion of willingness to get the COVID-19 vaccine among students of higher education institution in Adama town was far lower than that of the nationwide expected result. Male sex, having a family history of COVID-19 infection, having ever taken any vaccine, and the thought of respondents that the COVID-19 vaccine has no severe side effects were independent predictors of willingness to receive the vaccine.

Predictors of mortality in nursing home residents: a 2-year prospective longitudinal study. (preprint)

Background The age, multimorbidity, immunodeficiency and frailty of older people living in nursing homes make them vulnerable to COVID-19 and to mortality in general. For this reason, our objective is to verify the incidence of general and COVID-19 mortality and to analyse its predictive factors in older people living in nursing homes over a 2-year period.Methods A two-year prospective longitudinal multicenter study was carried out in 5 nursing homes in Central Catalonia (Spain) between 2020 and 2022. Date and causes of deaths were recorded. In addition, sociodemographic and health data were collected. For the effect of mortality, survival curves were performed using the Kaplan-Meier method and multivariate analysis using Cox regression.Results The total sample of 125 subjects had a mean age of 85.10 years (standard deviation = 7.3). A total of 59 (47.2%) deaths were recorded at 24 months (95% confidence interval [CI], 38.6–55.9) and 25 (20.0%) were due to COVID-19 most in first 3 months. In the multivariate analysis, functional impairment (hazard ratio [HR]: 2.40, 95% CI: 1.33–4.32, p = 0.003) was a significant risk factor for mortality independently of age (HR: 1.17, 95% CI: 0.69-2.00, p = 0.549) and risk of sarcopenia (HR: 1.40, 95% CI, 0.63–3.12, p = 0.403).Conclusions Nearly half of this sample of nursing home residents died within the 2-year period, and 20% were attributed to COVID-19. Functional impairment was a risk factor for overall mortality and COVID-19 mortality, independent of age and risk of sarcopenia.

Prevalence of respiratory infections during the 2018-2020 period in the paediatric population of primary care centres in Central Catalonia (preprint)

Following the COVID-19 pandemic, policies such as social distancing, hand washing and the use of masks were implemented which could play an important role in the reduction of infectious diseases. An observational, descriptive, cross-sectional study was conducted to observe the prevalence of respiratory infections in children under 15 years of age during the 2018-2020 period in Primary Care centres in Central Catalonia. In 2020, there was a 44.35 decrease in total consultations for respiratory infections compared to 2019. All respiratory infections exhibited a significant decrease except influenza, which increased by 41.76%. Children between the ages of 6 and 12 had the highest prevalence of influenza (87.68%), and the SARS-CoV-2-19 infection was most frequent (4.06%) among those between the ages of 12 and 15. Compared to urban centres, rural centres presented a higher prevalence of all infections except influenza and SARS-CoV-2. In conclusion, the COVID-19 pandemic caused a significant decrease in the number of consultations for respiratory infections in the paediatric population, except for influenza, which increased in cases in January and February 2020. No differences were found between sexes, although differences were found in the distribution of the different age groups.

SARS-CoV-2 Causing Transient Central Sleep Apnea in Patients Treated for Obstructive Sleep Apnea with Continuous Positive Airway Pressure.

BACKGROUND SARS-CoV-2 has globally affected humanity and devastated many families. Here, we attempt to identify which diseases are independent risk factors for severe SARS-CoV-2. There have been multiple studies that have evaluated the impact of obstructive sleep apnea (OSA) on SARS-CoV-2 outcomes, suggesting that OSA is an independent risk factor. SARS-CoV-2 has also been suggested to invade the central nervous system and be responsible for neurological signs and decreasing central respiratory drive. Central sleep apnea (CSA) is defined when apneas and hypopneas are associated with absent or reduced ventilatory effort, respectively, due to diminished central respiratory drive. CASE REPORT Here, we describe 2 cases involving patients with OSA that developed transient central sleep apnea after being diagnosed with SARS-CoV-2 by polymerase chain reaction. They had similar past medical histories and presentation of illness. The differences included compliance of continuous positive airway pressure (CPAP), recovery, and severity of central sleep index. We review and address alternate causes for the development of CSA. We hypothesize that continuous and compliant use of CPAP machines may be beneficial in reducing recovery and severity of SARS-CoV-2. CONCLUSIONS Our case report calls attention to the acquired central respiratory drive neurological complication associated with SARS-CoV-2. Our case report highlights the plausible existence of a relationship between development of central respiratory drive leading to CSA and SARS-CoV-2 infection. Further studies are needed to explore this relationship, including evaluating whether CSA occurs in SARS-CoV-2 patients with no history of OSA.

Influenza Vaccination in Coronavirus Times: Intention to Be Vaccinated by Primary Care Professionals in Central Catalonia (VAGCOVID) (preprint)

BackgroundInfluenza vaccination is the main measure of prevention against the epidemic flu, which annually produces a significant increase in the pressure on healthcare systems, in addition to influencing the absenteeism of health workers. Although it is recommended that health professionals be vaccinated, their vaccination coverage is low. The lack of knowledge about the evolution of influenza in the context of the SARS-CoV-2 coronavirus pandemic led to the continued recommendation of influenza vaccination to people at risk and to professionals. The aim of the study is to determine the intention to vaccinate against seasonal flu of health professionals in the 2020-21 campaign in the context of the SARS-CoV-2 pandemic, and to analyse the factors that influence it.MethodsCross-sectional study through a structured online survey aimed at Primary Care professionals in the region of central Catalonia.ResultsA total of 610 participants responded to the survey, 65.7% of whom intended to be vaccinated against the flu in this campaign and 11.1% did not yet know or did not answer. The intention to be vaccinated against flu is associated with the professional category, the years of professional practice, the fact of making face-to-face guards, and the perception of the risk of suffering from flu. It is also related to a history of influenza vaccination in the previous year and to having been vaccinated on another occasion. The profile of professionals who intend to be vaccinated against flu includes professionals with a history of vaccination, who were on duty and perceived that their staff were at risk of becoming ill with flu.ConclusionsDuring the SARS-CoV-2 pandemic, many professionals show a clear intention to get vaccinated against the flu, but there are still some who doubt it. In order to improve influenza vaccination coverage among health professionals, it is necessary to design strategies aimed at professionals who are hesitant or reluctant to vaccination.

Abnormal respiratory patterns classifier may contribute to large-scale screening of people infected with COVID-19 in an accurate and unobtrusive manner (preprint)

Research significance: During the epidemic prevention and control period, our study can be helpful in prognosis, diagnosis and screening for the patients infected with COVID-19 (the novel coronavirus) based on breathing characteristics. According to the latest clinical research, the respiratory pattern of COVID-19 is different from the respiratory patterns of flu and the common cold. One significant symptom that occurs in the COVID-19 is Tachypnea. People infected with COVID-19 have more rapid respiration. Our study can be utilized to distinguish various respiratory patterns and our device can be preliminarily put to practical use. Demo videos of this method working in situations of one subject and two subjects can be downloaded online. Research details: Accurate detection of the unexpected abnormal respiratory pattern of people in a remote and unobtrusive manner has great significance. In this work, we innovatively capitalize on depth camera and deep learning to achieve this goal. The challenges in this task are twofold: the amount of real-world data is not enough for training to get the deep model; and the intra-class variation of different types of respiratory patterns is large and the outer-class variation is small. In this paper, considering the characteristics of actual respiratory signals, a novel and efficient Respiratory Simulation Model (RSM) is first proposed to fill the gap between the large amount of training data and scarce real-world data. Subsequently, we first apply a GRU neural network with bidirectional and attentional mechanisms (BI-AT-GRU) to classify 6 clinically significant respiratory patterns (Eupnea, Tachypnea, Bradypnea, Biots, Cheyne-Stokes and Central-Apnea). The proposed deep model and the modeling ideas have the great potential to be extended to large scale applications such as public places, sleep scenario, and office environment.