Work context and clinical manifestations of COVID-19 in health professionals

To analyze associations between work context and clinical manifestations of COVID-19 in health professionals. Methods: This is a cross-sectional study, with health professionals from the northeast of Brazil, from the medical, nursing and physiotherapy categories from different areas of expertise. A Google Forms questionnaire was sent through social networks, gathering demographic, academic, work context, clinical manifestations and data related to testing for COVID-19 (the test performed was not specified) and whether the result confirmed infection active or presence of antibodies (categorized as positive). Pearson's chi-square test and multivariate binary logistic regression analysis were performed, with Wald's chi-square test, considering p-value <0.05, Odds Ratio and 95% confidence interval. Results: A total of 1,354 professionals agreed to participate in the study. Of these, 324 reported a positive test for COVID-19, with a prevalence of 23.9% (324/1,354). There was a statistical association between symptom onset and positive result (p=0.000). The work context characteristics related to the number of jobs, practice setting, contact with critically ill patients and employment in the capital were the independent variables associated with a positive result for COVID-19 (p<0.05). It was identified that 54.8% of the dependent variable can be related to the work sector, number of jobs, fever, loss of smell and taste. Conclusion: Health professionals from urban centers, hospitals, critical care units and those with more than one job are more affected by COVID-19, with the positive test result being closely related to the symptoms of fever, loss of smell and taste that are characteristic of the illness. © 2022 Departamento de Enfermagem/Universidade Federal de Sao Paulo. All rights reserved.

The long-term effects of the Covid-19 infection on cardiac symptoms.

BACKGROUND: Besides the lungs, coronavirus disease 2019 (COVID-19) can affect the cardiovascular, digestive, urinary, hepatic, and central nervous systems. Other than its short-term effects, COVID-19 may also cause long-term complications. In this study, we assessed long-term COVID-19 cardiovascular symptoms among patients in a cardiovascular clinic. METHOD: A retrospective cohort was conducted between October 2020 to May 2021 on patients at an outpatient cardiovascular clinic in Shiraz, Iran. Patients with a history of COVID-19 at least one year before their referral were included. Baseline information was extracted from the clinic's database. Data were collected regarding symptoms like dyspnea, chest pain, fatigue, and palpitations after a year of COVID-19. We also noted any major adverse cardiac events (MACE). RESULTS: Most common symptoms after a year of COVID-19 were exertional dyspnea (51.2%), dyspnea at rest (41.6%), fatigue (39%), and chest pain (27.1%). The symptoms were more prevalent in hospitalized patients than in non-hospitalized patients. The prevalence of MACE was about 6.1% during the 12-month follow-up, with this rate being higher in those with a history of hospitalization or comorbid diseases. CONCLUSION: The prevalence of cardiovascular symptoms was fairly high in patients at our clinic a year after COVID-19, and the most common symptom was dyspnea. Hospitalized patients had more MACE. (Clinicaltrial.gov number: NCT05715879)(04/02/2023).

Etiological factors of chronic pain syndrome in young adults with post-coronavirus disease 2019 condition.

PURPOSE: The coronavirus disease 2019 (COVID-19) generates long-term sequelae, but studies investigating patients with chronic pain syndrome (CPS) are limited. This study aimed to establish the etiological factors of CPS in patients with post-COVID-19 conditions. METHODS: This was a case-control retrospective study. The predictor variables were sex, diabetes mellitus, obesity (predisposing factors), unfavorable socioeconomic conditions, impaired rehabilitation (disabling factors), repeated exposure to COVID-19 (precipitating factor), home isolation, stress overload, fear of dying, admission to intensive care unit, prone positioning, and use of medications (reinforcing factors). The outcome variable was the presence of CPS. FINDINGS: This study included 120 individuals. Prolonged days of isolation (p = 0.005), fear (p < 0.001), stress overload (p < 0.001), and impaired rehabilitation (p = 0.003) were significantly associated with CPS. CONCLUSIONS: A significant relationship was found between prolonged days of isolation, fear, stress overload, impaired rehabilitation, and CPS. IMPLICATIONS FOR NURSING PRACTICE: The study findings can assist nurses by promoting their knowledge of the causes of CPS and supporting the care planning needs of patients with post-COVID-19 conditions, in addition to promoting the use of the NANDA-International taxonomy.

Bioinformatic Screening of Compounds from Iranian Lamiaceae Family Members against SARS-CoV-2 Spike Protein

Background: COVID-19 (coronavirus disease 2019) is still a major challenge worldwide. The disease is caused by binding the coronavirus to ACE2 receptors on lung cells, infecting the cells and triggering the onset of symptoms. The prevention of such a binding in which the virus is eventually unable to enter the cell could be a promising therapeutic approach.Methods: In this in silico study, 306 compounds of Lamiaceae family native in Iran (native Mints) were retrieved from several databases as 3D structures, and after that molecular docking and virtual screening, the compounds with inhibitory potential were selected in terms of free energy binding against the spike protein of the virus. The pharmacokinetic profile of selected compounds was evaluated, and by molecular dynamic simulation and MM/PBSA, four compounds were further assessed for binding affinities against the receptor-binding domain of the spike.Results: The results showed the Catechin gallate and Perovskone B from Stachys and Salvia genus generated a stronger binding affinity, and therefore could act as potential inhibitory compounds of RBD of the SARS-CoV-2 spike protein.Conclusion: This study revealed that some members of the Lamiaceae family could be employed to inhibit SARS-CoV-2 activity through interaction with spike protein and therefore could be used for further investigation in vitro and in vivo.

Isolation and Characterization of Porcine Sapelovirus from the PDCoV-Positive Sample and Its Molecular Epidemiology in Henan Province, China

Porcine sapelovirus (PSV) is an emerging swine enteric virus that can cause various disorders including acute diarrhea, respiratory distress, reproductive failure, and polioencephalomyelitis in pigs. In this study, we isolated a PSV strain HNHB-01 from a clinical porcine deltacoronavirus- (PDCoV-) positive intestinal content of a diarrheic piglet. PSV was first identified using the small RNA deep sequencing and assembly, and further identified by the electron microscopic observation and the immunofluorescence assay. Subsequently, this virus was serially passaged in swine testis (ST) cells, and the complete genomics of PSV HNHB-01 passage 5 (P5), P30, P60, and P100 were sequenced and analyzed. 9 nucleotide mutations and 7 amino acid changes occurred in the PSV HNHB-01 P100 strain when compared with the PSV HNHB-01 P5. Pathogenicity investigation showed that orally inoculation of PSV HNHB-01 P30 could cause obvious clinical symptoms and had broad tissue tropism in 5-day-old piglets. Epidemiological investigation revealed that PSV infections and the coinfections of diarrhea coronaviruses were highly prevalent in swine herds. The complete genomes of 8 representative PSV epidemic strains were sequenced and analyzed. Phylogenetic analysis revealed that the PSV epidemic strains were closely related to other PSV reference strains that located in the Chinese clade. Furthermore, recombination analysis revealed that the recombination events were occurred in downstream of the 2C region in our sequenced PSV HNNY-02/CHN/2018 strain. Our results provided theoretical basis for future research studies of the pathogenic mechanism, evolutionary characteristics, and the development of vaccines against PSV.

Clinical and occupational characteristics of university hospital workers with COVID-19 signs and symptoms during the pandemic

Objective: to understand the sociodemographic and occupational characteristics and risk exposure among workers of a university hospital who presented COVID-19 symptoms during the first wave of the pandemic. Methods: a cross-sectional study (July to September 2020), on staff from the Hospital Puerta de Hierro Majadahonda (Madrid, Spain) who were working during the first wave of the pandemic. An ad hoc survey was designed, which included the worker profile, COVID-19 symptoms, exposure, clinical course, and healthcare, among others. Descriptive analysis was conducted, and Chi-square and Student's t-test were used for statistical hypothesis testing. Results: the study included 992 subjects;34.3% (n= 340) presented COVID-19 symptoms;283 (84.0%) were female;82.9% (n= 282) of them were healthcare staff;36.8% (n= 125) were nurses;63.5% (n= 216) worked at high risk units;36.2% (n= 123) had a previous medical condition. Of the participants, 83.3% (n= 194) admitted having worked previously at high risk units;84.5% (n= 229) stated that they have felt exposed to the infection during work;49.7% (n= 98) had some incidence of risk;and 73.7% (n= 202) presented asthenia. There was a higher prevalence of healthcare staff with COVID symptoms vs. non-healthcare staff, based on care activities (92.9% vs. 50.0%;p< 0.001), work at COVID areas (74.2% vs. 48.1%;p< 0.001), and activity in high risk Units (73.4% vs. 15.5%;p< 0.001). Conclusions: among the workers with COVID symptoms, there was a higher proportion of healthcare staff, women, nurses, workers at COVID areas, risk units, and previous exposure to patients with confirmed or suspected infection. Differences between healthcare and non-healthcare staff were determined by their place of work during the pandemic and their risk of exposure to COVID-19. © 2023 DAE Editorial, Grupo Paradigma. All rights reserved.

Investigation of COVID-19 symptoms using deep learning based image enhancement scheme for x-ray medical images

Image enhancement is the inevitable technique for investigating various biological features. The biological image data can be obtained from computer tomography (CT), magnetic resonance imaging (MRI), and X-ray imaging. X-ray imaging is useful for getting the information from lungs and respiratory system. COVID-19 is a life-threatening contiguous disease for the past two years in the world. Patient's chest images playing an important role in the diagnosis of early detection of disease intensity. We propose a generative adversarial network (GAN) method that identifies COVID-19 from medical images and improves diagnostic sensitivity. Here we used virtual colouring methods and a platform for training the images by using a deep parental training method. Similarly, it gives optimal classification results with the help of well-defined image enhancement techniques and image extraction approaches. In our method, the accuracy level lies between 87.8% and 89.6% correspondingly for the dataset and synthetic dataset.

INSIGHT OF PANDEMIC COVID-19: DEVELOPMENTS AND CHALLENGES

This review focuses on the characteristics of coronavirus disease-19 (COVID-19) including virus structure, ecoepidemiology and pathophysiology, signs and symptoms in infected people, and data on virus pathogenicity, severity, and survivability in COVID-19 infected patients. The emphasis is on immunological reactions, diagnosis, prophylactic methods, and the zoonotic significance of COVID-19. The authors feel that the review's contents will be valuable to epidemiologists, virologists, public health officials, diagnosticians, laboratory workers, environmentalists, and socioeconomic experts. It has information on the many types of coronavirus variants, the disease situation in Pakistan and the WHO criteria for COVID-19 prevention is given. Moreover, lessons learned from the COVID-19 pandemic are also outlined.

Knowledge, perceptions and preventive practices towards COVID-19 early in the outbreak among Jimma university medical center visitors, Southwest Ethiopia

Background Novel-coronavirus disease-2019 (COVID-19) is currently a pandemic and public health emergency of international concern, as avowed by the World Health Organization (WHO). Ethiopia has become one of the affected countries as of March 15, 2020. Objective This study aimed to assess the knowledge, perceptions, and practices among the Jimma University medical center (JUMC) visitors in Jimma town. Methods A cross-sectional study was conducted on 247 sampled visitors, from 20–24 March 2020. Consecutive sampling was used to recruit the participants. The study tools were adapted from WHO resources. The data were analyzed using the Statistical Package for Social Sciences (SPSS) version 20.0. Descriptive statistics were used to describe the status of knowledge, perception, and practices. Logistic regression was executed to assess the predictors of dominant preventive practices. Results Of the 247 respondents, 205 (83.0%) knew the main clinical symptoms of COVID-19. 72.0% knew that older people who have chronic illnesses are at high risk of developing a severe form of COVID-19. About 95.1% knew that the COVID-19 virus spreads via respiratory droplets of infected people, while 77 (31.2%) of the respondents knew about the possibility of asymptomatic transmission. Only 15 (6.1%) knew that children and young adults had to involve preventive measures. Overall, 41.3% of the visitors had high knowledge. The majority, 170(68.8%), felt self-efficacious to controlling COVID-19. 207(83.3%) believed that COVID-19 is a stigmatized disease. Frequent hand washing (77.3%) and avoidance of shaking hands (53.8%) were the dominant practices. Knowledge status and self-efficacy (positively), older age, and unemployment (negatively) predicted hand washing and avoidance of handshaking. Conclusions The status of knowledge and desirable practices were not sufficient enough to combat this rapidly spreading virus. COVID-19 risk communication and public education efforts should focus on building an appropriate level of knowledge while enhancing the adoption of recommended self-care practices with special emphasis on high-risk audience segments.

Physical activity and mental health in Brazilian university students: An analysis in different sexes during the COVID-19 pandemic

Study aim: To identify symptoms of depression, anxiety, and stress in Brazilian university students of both sexes and the association of physical activity parameters during the COVID-19 pandemic.Material and methods: An online cross-sectional study was conducted from March to April 2021. Data on occupational and social variables and mental health symptoms were investigated using the Beck Anxiety Inventory, Hamilton depression rating scale, and Perceived Stress Scale questionnaires. Physical activity levels were assessed using the International Physical Activity Questionnaire.Results: In total, 277 college students over eighteen years old participated in the study (66% female;46.7% brown race). Higher scores and symptoms of anxiety and depression were observed in women (p < 0.0001). Anxiety symptoms were negatively associated with physical activity levels in women. Sedentary time, including sitting correlated with depression scores in women (r = 0.171;p < 0.05).Conclusions: University students are a risk group for the appearance of symptoms related to mental health. In addition, these disorders occur more frequently in females, and sedentary habits, such as more time sitting, were related to higher scores in depression and anxiety.

Nutritional assessment of Covid-19 patients admitted in intensive care units in Pakistan

Coronavirus disease 2019 (COVID-19) can be life threating if untreated. Early diagnosis and effective nutritional management can save life. To assess the nutritional status and predict possible outcomes of critical patients Sequential Organ Failure Assessment (SOFA), nutrition risk in critically ill patients (NUTRIC), and acute physiology and chronic health evaluation (APACHE) score has been used. This retrospective observational study was conducted on confirmed COVID-19 cases in Intensive Care Unit (ICU) of Shifa hospital between November 24, 2020 to May 31, 2021. The demographic, clinical and laboratory information was obtained from hospital records. Risk factors for COVID-19 were identified and compared using multivariate logistic regression analysis. The nutritional risk for each patient was assessed. In this study 162 COVID-19 patients with median age of 64 years (IQR: 56-74) were included. Hypertension (59.2%) was found to be the most common comorbidity and the most prevalent symptoms upon admission were fever (54.9%). The patients in critical condition were supplied nutrients through nasogastric route (61.7%) while 37.7% and 0.6 % were assisted through oral and total parenteral nutrition (TPN) route. The Glasgow comma score was found to be mild (72.2%) (GCS>12) with increased creatinine, white blood cell count, C-reactive protein (CRP C), and glycosylated haemoglobin HbA1c level were present. Interestingly based on SOFA, APACHE and NUTRIC score low insignificant malnutrition risk was observed. Our study found different demographic factors and comorbidities have a substantial impact on COVID19 patients, as evidenced by demographic, laboratory, clinical, and nutritional risk factors.

A Combined Method Based on the FIPV N Monoclonal Antibody Immunofluorescence Assay and RT-nPCR Method for the Rapid Diagnosis of FIP-Suspected Ascites

Feline infectious peritonitis (FIP), which is caused by feline infectious peritonitis virus (FIPV), is a fatal and immunologically mediated infectious disease among cats. At present, due to the atypical clinical symptoms and clinicopathological changes, the clinical diagnosis of FIP is still difficult. The gold standard method for the differential diagnosis of FIP is immunohistochemistry (IHC) which is time-consuming and requires specialized personnel and equipment. Therefore, a rapid and accurate clinical diagnostic method for FIPV infection is still urgently needed. In this study, based on the etiological investigation of FIPV in parts of southern China, we attempted to explore a new rapid and highly sensitive method for clinical diagnosis. The results of the etiological investigation showed that the N gene of the FIPV BS8 strain had the highest homology with other strains. Based on this, a specific FIPV BS8 N protein monoclonal antibody was successfully prepared by expression of the recombinant proteins, immunization of mice, fusion and selection of hybridoma cell lines, and screening and purification of monoclonal antibodies. Furthermore, we carried out a time-saving combination method including indirect immunofluorescence assay (IFA) and nested reverse transcription polymerase chain reaction (RT-nPCR) to examine FIP-suspected clinical samples. These results were 100% consistent with IHC. The results revealed that the combined method could be a rapid and accurate application in the diagnosis of suspected FIPV infection within 24 hours. In conclusion, the combination of IFA and RT-nPCR was shown to be a fast and reliable method for clinical FIPV diagnosis. This study will provide insight into the exploitation of FIPV N antibodies for the clinical diagnosis of FIP-suspected ascites samples.

Una alternativa de análisis de redes en la exploración de los estados de salud mental, condiciones crónicas y COVID-19

El análisis de redes es una técnica estadística gráfica que permite visualizar e interpretar intuitivamente asociaciones entre síntomas y múltiples variables vinculadas al funcionamiento y espectro de diversas condiciones de salud. Siendo de relevancia clínica en el contexto actual de la pandemia de COVID-19, y ante su poca difusión en Sudamérica, se tuvo como objetivo un análisis narrativo de este modelo de red durante la pandemia. Se realizó una revisión narrativa de los estudios empíricos publicados desde mayo de 2020 a julio de 2021 en la base de datos de PubMed y ScienceDirect. Se seleccionaron las investigaciones que utilizaron redes psicométricas de correlación parcial en participantes evaluados durante la pandemia de COVID-19. Esta revisión reporta 13 estudios de red que utilizaron mayormente síntomas relacionados a la ansiedad (7 estudios), depresión (6 estudios) y estrés (6 estudios). La información resultante se agrupa en 3 grupos (publicaciones en revistas de psiquiatría, ciencias psicológicas, medicina y afines). La revisión presentada refiere que este análisis de red permite una nueva forma de identificar aspectos clínicos mportantes como la comorbilidad, concurrencia de los síntomas y medidas no sintomatológicas, agrupaciones de síntomas con otras variables de naturaleza latente u observable que comparten una causa común, la exploración de nuevas hipótesis clínicas holísticas con variables epidemiológicas, psicológicas, biomédicas y contextuales de mayor interés, como la comparación de sistemas de asociación causal de variables de múltiples niveles en el proceso psicobiológico y sus factores de riesgo y protección en varios periodos de tiempo.Alternate : Network analysis is a graphical statistical technique that allows visualizing and intuitively interpreting the spectrum of various health conditions, being of clinical relevance in the current context of the COVID-19 pandemic. Given its limited dissemination in South America, we aimed at a narrative analysis of thisnetwork model during the pandemic. A narrative review of empirical studies published from May 2020 to July 2021 in the PubMed and ScienceDirect database was performed. We selected research that used partial correlation psychometric networks in participantsassessed during the COVID-19 andemic. This review reports 13 network studies that used mostly ymptoms related to anxiety (7 studies), depression (6 studies) and stress (6 studies). The resulting information is grouped into 3 clusters (publications in sychiatry, psychological sciences, medicine and related journals). The presented review refers that this network analysis allows a new way of identifying important clinical aspects uch as comorbidity, concurrence of symptoms and nonsymptomatologic measures, groupings of symptomswith other variables of latent or bservable nature that share a major common cause, the exploration of new holistic clinical hypotheses with pidemiological, psychological, biomedical and contextual variables of major current interest such as the comparison of causal association systems of multilevel variables in the psychobiological process, and their risk and protective factors in various time periods.

Differentiating Between COVID-19 and Tuberculosis Using Machine Learning and Natural Language Processing

Over 10 million people around the world are affected by tuberculosis (TB) every year, making it a major global health concern. With the advent of the COVID-19 pandemic, TB services in many countries have been temporarily disrupted, leading to a potential delay in the diagnosis of TB cases and many cases going under the radar. Since both diseases sometimes present similarly and generally affect the lungs, there is also a risk of misdiagnosis. This study aims to analyse the differences between COVID-19 and TB in different patients, as a first step in the creation of a TB screening tool. 180 COVID-19 and 215 TB case reports were collected from ScienceDirect. Using Natural Language Processing tools, the patient's age, gender, and symptoms were extracted from each report. Tree-based machine learning algorithms were then used to classify each case report as belonging to either disease. Overall, the cases included 252 male and 117 female patients, with 26 cases not reporting the patient's sex. The patients' ages ranged from 0 to 95 years old, with a median age of 41.5. There were 33 cases with missing age values. The most frequent symptom in the TB cases was weight loss while most COVID-19 cases listed fever as a symptom. Of all algorithms implemented, XGBoost performed best in terms of ROC AUC (86.9 %) and F1-score macro (78%). The trained model is a good starting point, which can be used by medical staff to aid in referring potential TB patients in a timely manner. This could reduce the delay in TB diagnosis as well as the TB death toll, especially in highly infected countries.

COVID-19: Challenges, Preventive Measures and Remediation

This review highlights origin, symptoms, diagnosis, causative agents, mode of transmission and persistence of coronavirus disease (COVID-19) through human activities. In the current scenario researchers, doctors and scientists are striving to combat the transmission of COVID-19 among society. Origin and growth of pandemic has raised the serious concern to address the causative agents, mode of transmission, persistence, preventive measures, diagnosis and possibilities of treatment. The broad-spectrum antiviral antiphrastic, complementary and alternative medicines are currently proposed for possible eradication of the pandemic. The current world is relying on, prevention and control of infection through sanitization and quarantine and onwards waiting for appropriate virucidal agents, sanitizers and strategic vaccination and immunization to combat the pandemic of SARS-CoV-2. Eradication of COVID-19 under stringent guidelines of WHO regarding social practices, intensive care, administration of complementary medicines and innovation of vaccines are under active considerations across the world to combat the pandemic.

Probability Analysis of a Stochastic Non-Autonomous SIQRC Model with Inference

When an individual with confirmed or suspected COVID-19 is quarantined or isolated, the virus can linger for up to an hour in the air. We developed a mathematical model for COVID-19 by adding the point where a person becomes infectious and begins to show symptoms of COVID-19 after being exposed to an infected environment or the surrounding air. It was proven that the proposed stochastic COVID-19 model is biologically well-justifiable by showing the existence, uniqueness, and positivity of the solution. We also explored the model for a unique global solution and derived the necessary conditions for the persistence and extinction of the COVID-19 epidemic. For the persistence of the disease, we observed that Rs0>1, and it was noticed that, for Rs<1, the COVID-19 infection will tend to eliminate itself from the population. Supplementary graphs representing the solutions of the model were produced to justify the obtained results based on the analysis. This study has the potential to establish a strong theoretical basis for the understanding of infectious diseases that re-emerge frequently. Our work was also intended to provide general techniques for developing the Lyapunov functions that will help the readers explore the stationary distribution of stochastic models having perturbations of the nonlinear type in particular.

Climate influences on COVID‐19 prevalence rates: An application of a panel data spatial model

The present study aims to measure the impact of climate characteristics on the prevalence rate of coronavirus disease 2019 (COVID‐19) in Brazilian states given the exogenous nature of these variables. We used a daily panel for the period from March 10 to April 10, 2020, the first phase of the pandemic, as there were few intervention policies to contain the spread of COVID‐19 during that period, and it was estimated through generalized least squares (GLS) spatial models to control the presence of spatial spillover, first‐order autoregressive errors, and correlation between cross‐sections. Considering the COVID‐19 incubation period and the time it takes for COVID‐19 symptoms to manifest, the econometric models were estimated using the 14‐, 11‐, and 7‐day moving averages of the climate variables. The results showed that increases of 1% in the solar incidence, average temperature, and relative humidity of the air reduced COVID‐19 prevalence rates by 0.16%, 0.049%, and 0.22%, respectively, considering the 11‐day moving average.Alternate :El presente estudio tiene como objetivo medir el impacto de las características climáticas en la prevalencia de la enfermedad por coronavirus 2019 (COVID‐19) en los estados brasileños, dada la naturaleza exógena de estas variables. Se utilizó un panel diario para el período comprendido entre el 10 de marzo y el 10 de abril de 2020, la primera fase de la pandemia, ya que hubo pocas políticas de intervención para contener la propagación de COVID‐19 durante ese período, y se estimó mediante modelos espaciales de mínimos cuadrados generalizados (GLS) para controlar la presencia de spillover espacial, errores autorregresivos de primer orden y la correlación entre muestras representativas. Teniendo en cuenta el periodo de incubación de COVID‐19 y el tiempo que tardan en manifestarse los síntomas de COVID‐19, los modelos econométricos se estimaron utilizando las medias móviles de 14, 11 y 7 días de las variables climáticas. Los resultados mostraron que aumentos del 1% en la incidencia solar, la temperatura media y la humedad relativa del aire redujeron la prevalencia de COVID‐19 en un 0,16%, 0,049% y 0,22%, respectivamente, teniendo en cuenta la media móvil de 11 días.Alternate :抄録本稿では、ブラジルの各州における新型コロナウイルス感染症 (COVID‐19)の罹患率に対する気候特性の影響を、これらの変数の外因性を考慮して、測定する。パンデミックの第一波である2020年3月10日~4月10日の期間は、COVID‐19の拡散を封じ込めるための介入政策がほとんどなかったが、この期間の毎日のパネルデータを使用し、一般化最小二乗法 (GLS)による空間モデルを用いて、空間スピルオーバー、1次自己回帰のエラー、および横断面間の相関の存在を制御して、推定した。COVID‐19の潜伏期間と発症までにかかる時間を考慮し、気候変数の14、11、7日間の移動平均を用いて計量経済モデルを推定した。結果から、11日間の移動平均を考慮すると、太陽光の入射、平均気温、空気中の相対湿度の1%増加が、それぞれCOVID‐19罹患率を0.16%、 0.049%、0.22%減少させることが示された。

Impact of Vaccination on COVID-19 Spread in Real Time: Visualization and Analysis Tool

Coronaviruses have been around for years, they are a large family of viruses that can create a variety of anomaly in humans and even in animals, the first symptoms are summed up by a simple cold with fever but it can spread to very serious respiratory problems. This disease has caused a global crisis on all levels;it's a very big challenge that we have lived it since the Second World War. The challenging problem of COVID-19 data science is considered in this paper, where we propose a new data warhouse, that best meets the needs of scientists. The proposed data warhouse as of February 24, 2020, is based on heterogeneous data provided by Our World in Data GitHub and Kaggle database, which are collected daily from Our World in Data COVID-19. Furthermore, this data warehouse is used to feed dashboards in real time that helps the decision-makers to strengthening of the coronavirus screening network, track the spread of the virus before and after vaccination around the world to fight against this dangerous disease.

Physical Activity and Post-COVID-19 Syndrome in Older Adults: A Systematic Review

Background: Physical activity (PA) may play a significant role in managing post-Coronavirus Disease (COVID)-19 syndrome, a significant public health concern among older adults. This study aimed to systematically review the evidence on post-COVID-19 symptoms, signs, risk factors, and the effects of PA programs in managing post-COVID-19 syndrome among older adults. Method: This systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) recommendation. The systematic search was conducted in August 2022 using Scopus and MEDLINE (via PubMed) databases. Results: There were 51 documents screened, among which 10 (7 observational and 3 experimental studies) met the selection criteria. The reported post-COVID-19 symptoms and signs associated with physical health included dyspnea, fatigue, diarrhea, and sarcopenia, abnormal lung function, cardiac pathology, immunological changes, reduced physical performance, respectively, while those associated with mental health included depression, poor concentration and memory, and anxiety. Patients with higher body mass indexes were more likely to experience more symptoms. Older patients had greater difficulties in performing daily activities and mobility. A multidisciplinary-based PA program is suggested to be feasible and effective in improving fatigue, ability to walk, balance, and cognitive function. For patients with sarcopenia, a low-intensity aerobic training exercise appears to improve muscle strength, kinesiophobia, and quality of life. Conclusion: Various post-COVID-19 symptoms have been reported along with their risk factors, and PA programs are potentially used for managing these symptoms. More research, however, is recommended to explore the PA program for specific post-COVID-19 symptoms.

COVID-19, long-COVID and return-to-work a questionnaire to investigate the experience of the occupational physicians from an Italian region

IntroductionThe issues related to return-to-work (RTW) after COVID-19, and the impact of long-COVID on workers' health engaged in different occupations are far to be fully acknowledged. Occupational Physicians (OPs) represent an important and competent source for the evaluation of these issues in workplaces, scant considered in research up now.Material And MethodsA literature search was performed to develop a questionnaire targeting the Italian OPs. The survey collects data on COVID-19 related RTW issues and on long-COVID symptoms occurrence in workers of Emilia-Romagna region (Italy).ResultsThe questionnaire involves three sections. The first with general information on the OPs activity (industrial sector and types of companies followed, main occupational hazards, health surveillance programs carried out). The second section is about long-COVID, defined according to the World Health Organization and the U.S. Centers for Disease Control and Prevention. A list of 22 symptoms based on a systematic search in MedLine has been developed asthenia;air hunger;chest tightness;memory/concentration problems;mental confusion;joint/muscle pain;sleep disorders;heart palpitations;dizziness;tingling/dysesthesia;gastrointestinal problems;depression and/or anxiety;tinnitus;inappetence;low-grade fever;high-grade fever;cough;headache;sore-throat;changes in smell/taste;skin rashes;other symptoms (to be specified). The main characteristics of the workers with long-COVID (age, gender, concomitant diseases, vaccination, smoking habit, body weight and previous infections etc.) and the frequency of the long-COVID symptoms are collected. The last section investigates RTW issues, to quantify the impact of the phenomenon in terms of workers involved, main characteristics of subjects with RTW problems, and implications for their work-ability.ConclusionsUsing the OPs direct experience as source of information, the study is aimed to develop new knowledge on the long-term impacts of the SARS-CoV-2 pandemic on workers' health, specifically considering RTW issues and the occurrence of long-COVID symptoms.