Types Of Respiratory Diseases Research Articles

Auscultation-Based Pulmonary Disease Detection through Parallel Transformation and Deep Learning.

Respiratory diseases are among the leading causes of death, with many individuals in a population frequently affected by various types of pulmonary disorders. Early diagnosis and patient monitoring (traditionally involving lung auscultation) are essential for the effective management of respiratory diseases. However, the interpretation of lung sounds is a subjective and labor-intensive process that demands considerable medical expertise, and there is a good chance of misclassification. To address this problem, we propose a hybrid deep learning technique that incorporates signal processing techniques. Parallel transformation is applied to adventitious respiratory sounds, transforming lung sound signals into two distinct time-frequency scalograms: the continuous wavelet transform and the mel spectrogram. Furthermore, parallel convolutional autoencoders are employed to extract features from scalograms, and the resulting latent space features are fused into a hybrid feature pool. Finally, leveraging a long short-term memory model, a feature from the latent space is used as input for classifying various types of respiratory diseases. Our work is evaluated using the ICBHI-2017 lung sound dataset. The experimental findings indicate that our proposed method achieves promising predictive performance, with average values for accuracy, sensitivity, specificity, and F1-score of 94.16%, 89.56%, 99.10%, and 89.56%, respectively, for eight-class respiratory diseases; 79.61%, 78.55%, 92.49%, and 78.67%, respectively, for four-class diseases; and 85.61%, 83.44%, 83.44%, and 84.21%, respectively, for binary-class (normal vs. abnormal) lung sounds.

Retrospective study of 540 cats with respiratory diseases in Japan (2003-2020).

Few epidemiological studies on respiratory medicine and the relationship between clinical signs and various respiratory diseases in cats have been reported. This retrospective study aimed to investigate the prevalence and breed predisposition to feline respiratory diseases in Japan and determine the association between clinical signs, duration and type of respiratory diseases. The medical records of cats with feline respiratory diseases were examined to obtain information on age, sex, breed, final diagnosis, clinical signs and duration. The odds ratios (ORs) and 95% confidence intervals were calculated to evaluate breed predispositions. Mann-Whitney U, Kruskal-Wallis and Dunn's tests were used to assess the duration of clinical signs. This study included 540 cats with 615 respiratory diagnoses. The American Shorthair breed was predisposed to bronchopneumonia (BP; OR: 5.0) and pulmonary tumour (PT; OR: 3.6), while the Russian Blue breed exhibited a predisposition to inflammatory lower airway diseases (OR: 3.4), BP (OR: 6.1) and interstitial lung diseases (OR: 11.1). Similarly, the Scottish Fold breed displayed predisposition to PTs (OR: 5.8). The duration of clinical signs among nasal diseases, nasopharyngeal diseases and lower tracheal/bronchial and pulmonary diseases differed significantly (p = 0.001, p = 0.012, p < 0.0001, respectively). The results suggest that some popular breeds in Japan are predisposed to feline respiratory diseases, especially the American Shorthair, Russian Blue and Scottish Fold breeds. The characteristics of occurrence, clinical signs and duration of each disease will aid in diagnosing, treating, preventing and elucidating the pathophysiology of feline respiratory disease.

Comprehensive surveillance of acute respiratory infections during the COVID-19 pandemic: a methodological approach using sentinel networks, Castilla y León, Spain, January 2020 to May 2022.

BackgroundSince 1996, epidemiological surveillance of acute respiratory infections (ARI) in Spain has been limited to seasonal influenza, respiratory syncytial virus (RSV) and potential pandemic viruses. The COVID-19 pandemic provides opportunities to adapt existing systems for extended surveillance to capture a broader range of ARI.AimTo describe how the Influenza Sentinel Surveillance System of Castilla y León, Spain was rapidly adapted in 2020 to comprehensive sentinel surveillance for ARI, including influenza and COVID-19.MethodsUsing principles and methods of the health sentinel network, we integrated electronic medical record data from 68 basic surveillance units, covering 2.6% of the regional population between January 2020 to May 2022. We tested sentinel and non-sentinel samples sent weekly to the laboratory network for SARS-CoV-2, influenza viruses and other respiratory pathogens. The moving epidemic method (MEM) was used to calculate epidemic thresholds.ResultsARI incidence was estimated at 18,942 cases per 100,000 in 2020/21 and 45,223 in 2021/22, with similar seasonal fold increases by type of respiratory disease. Incidence of influenza-like illness was negligible in 2020/21 but a 5-week epidemic was detected by MEM in 2021/22. Epidemic thresholds for ARI and COVID-19 were estimated at 459.4 and 191.3 cases per 100,000 population, respectively. More than 5,000 samples were tested against a panel of respiratory viruses in 2021/22.ConclusionExtracting data from electronic medical records reported by trained professionals, combined with a standardised microbiological information system, is a feasible and useful method to adapt influenza sentinel reports to comprehensive ARI surveillance in the post-COVID-19 era.

Effects of radiation on respiratory disease mortality: analysis of the national registry for radiation workers in United Kingdom

Purpose While some evidence of an effect of radiation exposure on respiratory disease at low dose levels has now emerged, there is heterogeneity in the risks between different studies and countries. In this paper, we aim to show the effect of radiation on three different sub-types of respiratory disease mortality through the analysis of the NRRW cohort in UK. Materials and methods The NRRW cohort consisted of 174,541 radiation workers. Doses to the surface of the body were monitored using individual film badges. Most of the doses are associated with X-rays and gamma rays and to a less extent of beta and neutron particles. The overall mean 10-year lagged lifetime external dose was 23.2 mSv. Some workers were potentially exposed to alpha particles. However, doses from internal emitters were not available for the NRRW cohort. 25% of male workers and 17% of female workers were identified as being monitored for internal exposure. The Poisson regression methods for grouped survival data with a stratified baseline hazard function were used to describe the dependence of the risk on cumulative external radiation dose. The disease was analyzed by the following subgroups: Pneumonia (1066 cases including 17 cases of influenza), COPD and allied disease (1517 cases) and other remaining respiratory diseases (479 cases). Results There was very little radiation effect on pneumonia mortality, but evidence of a reduction in mortality risk for COPD and allied disease (ERR/Sv= −0.56, 95%CI: −0.94, −0.06; p = .02) and an increase in risk for other respiratory disease mortality (ERR/Sv = 2.30, 95%CI: 0.67, 4.62; p = .01) with increasing cumulative external dose were observed. The effects of radiation were more prominent amongst workers monitored for internal exposure. The reduction in mortality risk of COPD and allied disease per cumulative external dose was statistically significant for the radiation workers monitored for internal exposure (ERR/Sv= −0.59, 95%CI: −0.99, −0.05; p = .017) but not significant among the workers who were not monitored (ERR/Sv= −0.43, 95%CI: −1.20, 0.74; p = .42). A statistically significant increased risk was observed for other respiratory diseases among monitored radiation workers (ERR/Sv = 2.46, 95%CI: 0.69, 5.08; p = .019), but not among unmonitored workers (ERR/Sv = 1.70, 95%CI: −0.82, 5.65; p = .25). Conclusion The effects of radiation exposure can be different depending on the type of respiratory disease. No effect was seen in pneumonia; a reduction in mortality risk of COPD, and increased mortality risk of other respiratory diseases were observed with cumulative external radiation dose. More studies are needed to verify these findings.

Patterns of Emergency Room Visits for Respiratory Diseases in New York State in Relation to Air Pollution, Poverty and Smoking.

We have explored differences in rates of emergency room (ER) visits for respiratory diseases in the counties of New York State (NYS) in relation to levels of air pollution, poverty, and smoking. Air pollution information was derived from the National Emissions Inventory, which provides information on road, non-road, point, and non-point sources of 12 different air pollutants. This information is only available at the county level. Four types of respiratory diseases were considered: asthma, chronic obstructive pulmonary disease (COPD), acute lower respiratory diseases, and acute upper respiratory diseases. Asthma ER visits were elevated in counties with greater total air pollution. All forms of respiratory diseases were elevated in counties with a greater rate of poverty, although this may reflect the fact that poor people often use ERs for routine care. There was a very strong association between rates of smoking for COPD and acute lower respiratory diseases. There was an apparent negative association between smoking and asthma ER visits, but this must reflect the fact that smoking was much more common in upstate counties while asthma was more common in the New York City area, where air pollution is high. Air pollution was much greater in urban than in rural areas. Our evidence indicates that air pollution is the greatest risk factor for asthma attacks, whereas smoking is the greatest risk factor for chronic obstructive pulmonary disease (COPD) and lower respiratory disease. Poor people are more vulnerable to all forms of respiratory diseases.

Cluster Analysis of Covid-19 in Indonesia Using K-means Method

These days technology are rapidly increasing and developing in various fields, especially data storage. The information that has been stored in a database usually called a dataset. Covid-19 is a new type of respiratory disease that attacks the respiratory system with rapid transmission, followed by the increasing number of Covid-19 cases that continues to increase every day in all provinces in Indonesia. This study aims to cluster the spread of Covid-19 in every province in Indonesia by using the data that obtained from the website named kaggle with many data variables. The method used in this research is K-Means. From many variables in the data, for this study only 3 variables were taken, which are: Number of Recovery, Number of Deaths, and Number of total Cases in Covid-19 in Indonesia. These 3 variables then will be applied using the K-Means method and formed 3 provincial groups. By using the clustering method and the K-means algorithm, this research can be carried out to find the characteristics of the distribution in each province in Indonesia by looking at the best clusters.

The application of multi-omics in the respiratory microbiome: Progresses, challenges and promises

The study of the respiratory microbiome has entered a multi-omic era. Through integrating different omic data types such as metagenome, metatranscriptome, metaproteome, metabolome, culturome and radiome surveyed from respiratory specimens, holistic insights can be gained on the lung microbiome and its interaction with host immunity and inflammation in respiratory diseases. The power of multi-omics have moved the field forward from associative assessment of microbiome alterations to causative understanding of the lung microbiome in the pathogenesis of chronic, acute and other types of respiratory diseases. However, the application of multi-omics in respiratory microbiome remains with unique challenges from sample processing, data integration, and downstream validation. In this review, we first introduce the respiratory sample types and omic data types applicable to studying the respiratory microbiome. We next describe approaches for multi-omic integration, focusing on dimensionality reduction, multi-omic association and prediction. We then summarize progresses in the application of multi-omics to studying the microbiome in respiratory diseases. We finally discuss current challenges and share our thoughts on future promises in the field.

Prognostic value of lactate in cats presented in respiratory distress to the emergency room.

Studies demonstrating the prognostic utility of plasma lactate concentration and lactate clearance in cats are limited. The objective of this study was to determine the prognostic utility of plasma lactate concentration upon admission and plasma lactate clearance in cats presented to the emergency room with respiratory distress attributed to underlying cardiac or respiratory disease. Additionally, we sought to determine if plasma lactate concentration on admission was significantly associated with the underlying cause of respiratory distress (cardiac vs. respiratory), type of respiratory disease, and vital parameters. Seventy-one cats presented in respiratory distress to the ER at a university teaching hospital were enrolled in this retrospective study. Admission lactate concentration was not associated with survival, duration of hospitalization, vital parameters, or underlying etiology for respiratory distress. In contrast, lactate clearance was significantly associated with survival and length of hospitalization. While a statistically significant association between lactate clearance and length of hospitalization was identified, this finding lacked clinical significance where an increase in lactate concentration by 1% was associated with an increased length of hospitalization by 11.4 min (p = 0.035). Results of this study suggest that lactate clearance may have prognostic utility in this population of cats. Further studies including the larger population of cats with underlying cardiac or respiratory disease are warranted.

Assessment of Clinical Diagnostic Efficacy of Pulmonary Function Test Based on DBN-SVM of Pediatric Asthma and Cough Variant Asthma.

The diagnosis of asthma depends on the unprejudiced proof of the varying airflow obstruction. The pulmonary function tests are carried out to evaluate the clinical value of different types of respiratory diseases in children or infants. This study is focused on the clinical evaluation of the pulmonary function tests in the diagnosis of pediatric asthma and cough variant asthma. A differential diagnosis method for chronic obstructive pulmonary disease (COPD) and asthma-COPD overlap with complementary diagnostic value is proposed. For the pulmonary function tests, the COPD gene dataset was selected and feature selection was performed using the DBN-SVM scoring method. For analysis and comparison, the differential diagnosis models were built using ROC curves for the accuracy of the deep belief network model and the support vector machine model. The sensitive features associated with COPD and ACO classification using the deep belief network model were found to be in good agreement with known clinical diagnostic strategies. The clinical diagnosis tests for pulmonary pediatric asthma and cough variant asthma were conducted on two groups of children, with both groups containing a basis of comparison. 80 cases of pediatric asthma and cough variant asthma were admitted from 2013 to 2014 and 80 cases of children with a healthy physical examination. The results of the two groups were compared. The results showed that the levels of FEV1, PEF, and FVC were significantly lower (P < 0.05), in healthy children, and FEV1/FVC%, RV, and RV/TCL% were significantly higher (P < 0.05) in children with asthma and cough variant asthma during acute exacerbation and chronic persistence. There were no statistically significant differences in the duration of clinical remission (P > 0.05). Thus, the study suggests that confirmed cases of the diagnosis of pediatric asthma and cough variant asthma by pulmonary function tests were significantly higher than those of conventional tests (P < 0.05). From this study, we can conclude that pulmonary function tests can accurately diagnose pediatric asthma and cough variant asthma, and also accurately reflect the development of the child's disease, which is of high clinical value.

Direct capture and smartphone quantification of airborne SARS-CoV-2 on a paper microfluidic chip

SARS, a new type of respiratory disease caused by SARS-CoV, was identified in 2003 with significant levels of morbidity and mortality. The recent pandemic of COVID-19, caused by SARS-CoV-2, has generated even greater extents of morbidity and mortality across the entire world. Both SARS-CoV and SARS-CoV-2 spreads through the air in the form of droplets and potentially smaller droplets (aerosols) via exhaling, coughing, and sneezing. Direct detection from such airborne droplets would be ideal for protecting general public from potential exposure before they infect individuals. However, the number of viruses in such droplets and aerosols is too low to be detected directly. A separate air sampler and enough collection time (several hours) are necessary to capture a sufficient number of viruses. In this work, we have demonstrated the direct capture of the airborne droplets on the paper microfluidic chip without the need for any other equipment. 10% human saliva samples were spiked with the known concentration of SARS-CoV-2 and sprayed to generate liquid droplets and aerosols into the air. Antibody-conjugated submicron particle suspension is then added to the paper channel, and a smartphone-based fluorescence microscope isolated and counted the immunoagglutinated particles on the paper chip. The total capture-to-assay time was <30 min, compared to several hours with the other methods. In this manner, SARS-CoV-2 could be detected directly from the air in a handheld and low-cost manner, contributing to slowing the spread of SARS-CoV-2. We can presumably adapt this technology to a wide range of other respiratory viruses.

Human microphysiological models of airway and alveolar epithelia.

Human organ-on-a-chip models are powerful tools for preclinical research that can be used to study the mechanisms of disease and evaluate new targets for therapeutic intervention. Lung-on-a-chip models have been one of the most well-characterized designs in this field and can be altered to evaluate various types of respiratory disease and to assess treatment candidates prior to clinical testing. These systems are capable of overcoming the flaws of conventional two-dimensional (2-D) cell culture and in vivo animal testing due to their ability to accurately recapitulate the in vivo microenvironment of human tissue with tunable material properties, microfluidic integration, delivery of precise mechanical and biochemical cues, and designs with organ-specific architecture. In this review, we first describe an overview of currently available lung-on-a-chip designs. We then present how recent innovations in human stem cell biology, tissue engineering, and microfabrication can be used to create more predictive human lung-on-a-chip models for studying respiratory disease. Finally, we discuss the current challenges and future directions of lung-on-a-chip designs for in vitro disease modeling with a particular focus on immune and multiorgan interactions.

Monitoring of PM10 Concentration and Evaluation of its Effect on Respiratory Diseases in Aizawl City, Mizoram

Particulate matter (PM), a primary component of air pollution has been implicated in various respiratory and cardiovascular diseases and was found to be the 13th leading cause of mortality worldwide by the World Health Organisation. The concentration of PM10 (Coarse particulate matters with aerodynamic diameter between 2.5–10 μm ) was assessed for Aizawl City, Mizoram for a period of two years from June 2014–May 2016. The annual mean concentration of PM10 was found to fall within the permissible limit of the National Ambient Air Quality Standard and was highest in Khatla station (71.67 µg/m3) followed by Bawngkawn station (39.75 µg/m3) and Laipuitlang station (33.25 µg/m3) and the lowest annual mean concentration was seen in Mizoram University station (0.85 µg/m3). Seasonal variations have been observed in the mean concentration of PM10 with the highest concentration in winter season (51.3µg/m3±28.27)and the lowest in monsoon season (22.58 µg/m3 ±2.37). Despite the low concentration of PM10, a strong association was found between PM10 exposure and three types of respiratory diseases namely Corrosion of respiratory tract (CORT), chronic obstructive pulmonary disease (COPD) and vasomotor rhinitis (VR).

Interactive Effects between Temperature and Humidity on Outpatient Visits of Respiratory Diseases in Lanzhou, China

AbstractThis study assessing the lag and interactive effects between the daily average temperature and relative humidity on respiratory disease (RD) morbidity in Lanzhou, China, using data from daily outpatient visits for RD between 2014 and 2017 and meteorological and pollutant data during the same period analyzed with Poisson generalized linear model and distributed lag nonlinear models; the effects are further explored by classifying the RD by gender, age, and disease type. The results showed that the effect of temperature and relative humidity on outpatient visits of different populations and types of RD is nonlinear, with a significant lag effect. Relative to 11°C, every 1°C decrease in temperature is associated with 10.98% [95% confidence interval (CI): 9.87%–12.11%] increase for total RD. Chronic obstructive pulmonary disease is affected only by low temperature, upper respiratory tract infection is affected by both low and high temperatures, and asthma is influenced by high temperature. When the relative humidity is less than 32%, every 1% decrease in relative humidity is associated with 6.00% (95% CI: 3.00%–9.11%) increase for total RD; relative humidity has different effects on the outpatient risk of different types of RD. Temperature and relative humidity have an obvious interactive effect on different types and populations of RD: when both temperature and humidity are at low levels, the number of outpatient visits for RD is higher. When the relative humidity is ≤50% and the temperature is ≤11°C, total RD outpatient visits increase by 4.502% for every 1°C drop in temperature; that is, a dry environment with low temperature has the most significant impact on RD.

High-flow nasal cannula compared with continuous positive airway pressure in the treatment of obstructive sleep apnea.

Continuous positive airway pressure (CPAP) is a standard treatment for obstructive sleep apnea (OSA). However, CPAP has limitations. High-flow nasal cannula (HFNC) is already in use for various types of respiratory diseases. As HFNC generates positive airway pressure, it may be a potential candidate for OSA treatment. This prospective study compared the therapeutic effects of HFNC to CPAP in patients with OSA. Patients whose apnea-hypopnea index (AHI) was > 5 events/h were enrolled in this study. All participants were randomly divided into two groups. The first group underwent CPAP the first night and HFNC the second night. Conversely, the second group received HFNC the first night and CPAP the second night. Their respiratory events and sleep quality were compared using baseline polysomnography, CPAP, and HFNC. In total, 28 participants completed this study. Median [interquartile range] AHI (35.0 [20.0-48.6] vs. 10.8 [5.5-20.6] events/h; p < 0.001) was significantly improved by the HFNC. However, sleep quality was not improved. When CPAP was compared directly with HFNC, CPAP demonstrated a more favorable effect for respiratory events (AHI 5.0 [2.0-7.0] vs. 10.8 [5.5-20.6] events/h; p < 0.001) and sleep efficiency (88.1 [79.9-92.5] vs. 77.9 [69.2-86.6] %; p = 0.001). The efficacy of CPAP was superior to HFNC for both respiratory events and sleep quality. ClinicalTrials.gov Identifier: NCT03843372; URL: www. gov ; Date of registration: November 2, 2019.

Achievements of the K1 &amp; K4 Program with Standard Practices of Pregnancy Services during the Covid-19 Pandemic

WHO has designated the Covid-19 (Corona Virus 2019) case as a Pandemic. Covid-19, caused by the coronavirus (SARS-CoV-2), is a new type of respiratory disease (pneumonia) and is contagious. The state has made various efforts to control covid-19, but there are still many infected victims. Pregnant women have changes in their immune system and anatomy, making them susceptible to viral infections. Pregnancy examinations at the hospital will be at risk of transmitting covid-19 to pregnant women, while antenatal care is very important to identify any pregnancy complications. This study aims to identify the K1 and k4 programs' achievements with midwives' practice in standard pregnancy services during the Covid 19 Pandemic, using a questionnaire given to midwives as health service workers. The study design used a cross-sectional with a chi-square statistical test, with 30 midwives as respondents who opened independent practice services during the Covid-19 pandemic. The research instrument used a questionnaire. This study indicates that 70% of midwives have good knowledge but do not implement standard pregnancy care during the pandemic. The analysis results show no relationship between knowledge and standard practice of pregnancy services during the Covid-19 pandemic. Conclusion: Most midwives have good knowledge and do not practice standard pregnancy services during the Covid-19 pandemic. Suggestion. The following research is to identify the achievements of the pregnancy care program during the Covid-19 pandemic.

Pengetahuan dan Praktik Bidan tentang Standar Pelayanan Kehamilan di Era Pandemi Covid-19

Coronavirus 2019 (COVID-19) is a highly contagious new type of respiratory disease (pneumonia) caused by coronavirus 2 (SARS-CoV-2). All countries are making various efforts to control covid-19, but there are still many infected victims, so WHO has designated this case as a Covid-19 Pandemic. Pregnant women are more susceptible to viral infections; this is due to changes in the immune system and body anatomy. Pregnancy checks in the hospital will be a significant risk for the threat of covid-19 transmission, while services during pregnancy are essential to avoid complications that can occur during pregnancy. This study aims to identify midwives' knowledge and practice regarding the standard of pregnancy services during the Covid 19 pandemic, using a questionnaire given to midwives as health care workers. The study design used a crosssectional study with a chi-square statistical test to determine health services barriers during the pandemic. They were analyzed descriptively. Samples took with quota sampling, with a total of 30 midwives in Candi Sidoarjo sub-district. The research instrument used a questionnaire. This study indicates that 70% of midwives have good knowledge but do not implement standard pregnancy care during the pandemic. The analysis results show that there is no relationship between knowledge and standard practice of pregnancy services during the Covid-19 pandemic. Conclusion: Most midwives have good knowledge and do not practice standard pregnancy services during the Covid- 19 pandemic. Suggestion. The next research is to identify the achievements of the pregnancy service program during the Covid-19 pandemic

Food service industry in the era of COVID-19: trends and research implications.

Coronavirus disease 2019 (COVID-19) is a new type of respiratory disease that has been announced as a pandemic. The COVID-19 outbreak has changed the way we live. It has also changed the food service industry. This study aimed to identify trends in the food and food service industry after the COVID-19 outbreak and suggest research themes induced by industry trends. This study investigated the industry and academic information on the food and food service industry and societal trends resulting from the COVID-19 outbreak. The most noticeable changes in the food industry include the explosive increase in home meal replacement, meal-kit consumption, online orders, take-out, and drive-through. The adoption of technologies, including robots and artificial intelligence, has also been noted. Such industry trends are discussed in this paper from a research perspective, including consumer, employee, and organizational strategy perspectives. This study reviews the changes in the food service industry after COVID-19 and the implications that these changes have rendered to academia. The paper concludes with future expectations that would come in the era of COVID-19.

LncRNA TUG1 knockdown mitigates inflammatory injury induced by cigarette smoke extract in chronic obstructive pulmonary disease via miR-34c/BRD4 axis.

Chronic obstructive pulmonary disease (COPD) is a type of respiratory disease. The dysregulation of long non-coding RNA (lncRNA) taurine upregulated gene 1 (TUG1) has been reported in diverse diseases. This study aimed to explore the functions and mechanism of TUG1 in COPD. The levels of TUG1 and BRD4 were significantly up-regulated, and the level of miR-34c was apparently down-regulated in COPD patients or CSE-treated BEAS-2B cells. TUG1 was verified to sponge to miR-34c, and BRD4 was validated as a target of miR-34c. TUG1 depletion or miR-34c overexpression promoted cell proliferation but restrained apoptosis, inflammatory response in CSE-treated BEAS-2B cells. MiR-34c inhibitor mitigated the inhibitory effect on cell proliferation and the promotion effects on cell apoptosis, inflammatory response in CSE-treated BEAS-2B cells induced by TUG1 silencing. Mechanistically, TUG1 modulated BRD4 expression in CSE-treated BEAS-2B cells by sponging miR-34c. TUG1 modulated BRD4 to regulate cell proliferation, cell apoptosis and inflammatory response in CSE-treated BEAS-2B cells by sponging miR-34c.

Corona viral disease: a threat to global health, economy and political stability

Coronavirus is a group of viruses that cause several types of respiratory disease, such as mers and sars. The current outbreak, which began in the Chinese province of Wuhan in december, is a novel strain, dubbed 2019-nCoV. Unlike the previous viral disease outbreaks that were easily contained, this current covid 19 is significant because of its’ rapid spread and high mortality rate therefore WHO declared a state of emergency on the disease. Covid 19= I ≤1.5m (d1,d2,d3,d4 ⋯dn). Where I=index case, 1.5 metres distance is the magnetic field outside which the susceptibility of contact to be infected by the virus is reduced.If thorough interventions are not deployed and cultural practices that promote good health emphasized, spread is inevitable. Boarder porosity is a major spread factor especially in African countries where borders are not well manned, not all boarders are legal. This can enhance the transmission of this deadly disease. Africa’s porous land borders remain a cause for concern among policy makers and health professionals, who fear that unchecked migration and transport between countries could spread the virus quickly. Also religious practices could enhance the spread of the deadly disease. Prayer pattern in some religions around the world encourages crowding and clustering of people together. Climate change definitely has an impact on the outbreak of infectious diseases says Eike Hertig at the University of Augsburg Germany. Political systems will also be hampered. It is unique because it can be transmitted through election materials. Crowding and clustering cannot be divorced from electioneering. International observers for elections will not be free to cross countries to authenticate electioneering process. Economic shortage cannot be avoided, according to a report published on the 9th of March 2020, ‘the state giant oil Saudi Aramco led financial losses, dropping by 10% on Riyadh’s Tadawul stock exchange.

Severe acute respiratory syndrome coronavirus 2 infection in renal transplant recipients: A case report

The novel coronavirus is a newly discovered pathogen in late December 2019, and its source is currently unknown, which can lead to asymptomatic infection, new coronavirus pneumonia or serious complications, such as acute respiratory failure. Corona virus disease 2019 (COVID-19) is a new type of respiratory disease that is currently spreading all over the world and caused by this coronavirus. Its common symptoms are highly similar to those of other viruses, such as fever, cough and dyspnea. There is currently no vaccine or treatment for COVID-19. Everyone is susceptible to infection with this disease, and owing to the long-term use of immunosuppressants, the immunity of kidney transplant recipients is suppressed, and it is more likely to be infected with the disease. At present, its impact on kidney transplant recipients is unclear. This article reports the clinical features and therapeutic course of novel coronavirus infection in a patient after renal transplantation. A 37-year-old female patient who received a kidney transplant 6 months before was diagnosed with novel coronavirus pneumonia. The patient's symptoms (such as fever, chills, dry cough, muscle aches), laboratory tests (such as decreased white blood cell count, elevated liver enzymes and D-dimer, positive viral nucleic acid test), and chest CT (multiple left lower lung plaque ground glass shadow) were similar to those of non-transplanted novel coronavirus pneumonia patients. In terms of treatment, because the immunity of kidney transplant recipients has been suppressed for a long time, it is a very common strategy to suspend the use of immunosuppressive agents. Therefore, the patient immediately discontinued the immunosuppressive agent after admission, so that she could restore immunity against infection in a short time. At the same time, the use of glucocorticoids was also very important. Its immunosuppressive and anti-inflammatory effects played a large role in the treatment process.In addition, prophylactic antibiotics was needed, and nephrotoxic drugs should be used with caution. Finally, following discounting the use of immunosuppressant and a low-dose glucocorticoid-based treatment regimen, COVID-19 in this renal transplant recipient was successfully cured. The cure of this case was of great significance, and this adjuvant nonspecific antiviral therapy could provide a template for the treatment of other such patients.