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Introduction: Coronavirus Disease 2019 (COVID-19) pandemic is caused by SARS-CoV-2 which spreads rapidly throughout the world and causes clinical manifestations in various organs, especially in the lungs. Clinical symptoms arise from asymptomatic, mild, moderate, severe, and critical symptoms in patients with or without comorbid disease. Chest X-ray examination is one of the modalities in the management of COVID-19 which is cheap and easy to do.Methods: This study was performed by analyzing medical record data of confirmed COVID-19 patients from March to December 2020. This study aimed to examine the relationship between chest X-ray and the degree of disease severity.Results: The results showed that from the examined 542 total samples, the highest number was found in the age group of 40-49 years old (23.6%), women (53%), mild degree of COVID-19 (67.9%), normal chest X-ray (54.6%), predominance on the lower zone of the lung, peripheral and bilateral on abnormal chest X-ray, no comorbid (56.3%), hypertensive in comorbid disease (26.6%). There was a significant relationship between chest X-ray and comorbidity towards COVID-19 severity (p = 0.000).Conclusion:Chest X-ray can determine disease severity, therefore it can be used as the first modality for triage and treatment evaluation in COVID-19 patients.

Introduction: Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is the cause of clinical disease, better known as COVID-19. The most common method to detect COVID-19 is serological testing of IgM and IgG in response to viral infections using rapid diagnostic test (RDT). Several other guidelines consider polymerase chain reaction (PCR) as the gold standard for diagnosis becausePCR has high sensitivity and specificity values in detecting SARS-CoV-2.Methods: This was a descriptive analytical study. The samples were taken from medical records of COVID-19 patients in Ulin General Hospital Banjarmasin from March to October 2020. Statistical Package for the Social Sciences (SPSS) 16.0 software and Chi-Square test were used for data analysis.Results: From 751 COVID-19 patients, 408 patients (54.32%) had rapid antibody with positive PCR, 132 patients (17.57%) had reactive rapid antibody with negative PCR, 152 patients (20.23%) had non-reactive rapid antibody with positive PCR, and 59 patients (7.85%) had non-reactive rapid antibody with negative PCR. The rapid antibody had sensitivity of 72.85% and specificity of 30.89%. From Chi-Square test, reactive rapid antibody was not correlated with PCR positive results; values of p = 0.320, odds ratio (OR) 1.20.Conclusion: The rapid test antibody could not be recommended as a diagnostic tool. In this study, it was also found that there was no relationship between reactive rapid test results and positive SARS-CoV PCR.

This paper presents a forecasting model for the mortality rates of COVID-19 in six of the top most affected countries depending on the hybrid Genetic Algorithm and Autoregressive Integrated Moving Average (GA-ARIMA). It was aimed to develop an advanced and reliable predicting model that provides future forecasts of possible confirmed cases and mortality rates (Total Deaths per 1 million Population of COVID-19) that could help the public health authorities to develop plans required to resolve the crisis of the pandemic threat in a timely and efficient manner. The study focused on predicting the mortality rates of COVID-19 because the mortality rate determines the prevalence of highly contagious diseases. The Genetic algorithm (GA) has the capability of improving the forecasting performance of the ARIMA model by optimizing the ARIMA model parameters. The findings of this study revealed the high prediction accuracy of the proposed (GA-ARIMA) model. Moreover, it has provided better and consistent predictions compared to the traditional ARIMA model and can be a reliable method in predicting expected death rates as well as confirmed cases of COVID-19. Hence, it was concluded that combining ARIMA with GA is further accurate than ARIMA alone and GA can be an alternative to find the parameters and model orders for the ARIMA model.

To contain the outbreak of COVID-19 in Wuhan, unprecedented interventions, including city lockdown and community closure, have been implemented. However, most of the current studies focused on evaluation of the city lockdown, but paid limited attention to the impacts of the community containment measures within the city. This research addressed this important issue from the perspective of urban planning, based on the epidemic and remote sensing data of 194 communities of Wuhan. We found that the number of confirmed cases of communities is highly related to urban planning factors, e.g. area percentage of buildings and density of neighboring markets. These factors are relevant to the residents’ activity patterns, which therefore impact the mode of virus transmission. Our research confirmed the effectiveness of the community-oriented control strategies, provided a valuable reference for other cities that are suffering from the epidemic, and exhibited new thoughts into future urban planning.

Objecive : This study aimed to evaluate whether Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) can be detected in the tears in the eyes of Coronavirus Disease 2019 (COVID-2019) infect...

The article presents an overview of methods of treatment of coronavirus infection based on available data from recent clinical studies and methodological recommendations. Drugs recommended as pathogenetic therapy are considered. Data from clinical trials and expert opinions are analyzed.

Cleaning workers was one of high risk workers in Covid-19 infection who exposed to garbage from individuals, households and business waste every day. During Covid-19 pandemic there was increased disposal of infectious waste such as masks and gloves from households without sorting process which increasing risk of infection for cleaning workers. Preventive effort of cleaning workers was needed as vigilance in daily activities. Therefore, an education was carried out about prevention of infectious disease related Covid-19 pandemic to improving knowledge and understanding of cleaning workers as preventive measure. Education program was carried out to 50 cleaning workers in Environmental Department of Padang on 29-30 June 2020. Modules, videos, and demonstrations procedures of hand washing, mask and glove using were used in these educations. Education program consist of basic concepts and preventive measures against infectious disease related Covid-19 pandemic. The results showed there was increased knowledge of cleaning workers about preventive way against infectious disease related Covid-19 pandemic after participating in education program.

The present novel corona virus (2019-nCoV) infection has created a global emergency situation by spreading all over the world in a large scale within very short time period. The infection induced death rate is also very high. There is no vaccine or anti-viral medicine for such infection. So at this moment a major worldwide problem is that how we can control this pandemic. On the other hand, India is a high population density country, where the corona virus disease (COVID-19) has started to spread from $1^{st}$ week of March, 2020 in a significant number of COVID-19 positive cases. Due to this high population density human to human social contact rate is very high in India. So control of the pandemic COVID-19 in early stage is very urgent and challenging problem. Mathematical models are employed in this paper to study the COVID-19 dynamics, to identify the influential parameters and to find the proper prevention strategies to reduce the outbreak size. In this work, we have formulated a deterministic compartmental model to study the spreading of COVID-19 and estimated the model parameters by fitting the model with reported data of ongoing pandemic in India. Sensitivity analysis has been done to identify the key model parameters. The basic reproduction number has been estimated from actual data and the effective basic reproduction number has been studied on the basis of reported cases. Some effective preventive measures and their impacts on the disease dynamics have also been studied. Future trends of the disease transmission has been Predicted from our model with some control measures. Finally, the positive measures to control the disease have been summarized.

Sejak awal tahun 2020 terjadi peningkatan jumlah kasus infeksi virus COVID-19, yang sebelumnya dikenal dengan nama 2019-nCov. Diketahui hingga bulan Februari 2020 sudah terkonfirmasi lebih dari 70.000 kasus positif infeksi COVID-19. COVID-19 diketahui merupakan virus dari keluarga coronaviridae, yang juga merupakan keluarga dari virus SARS-CoV dan MERS-CoV yang pernah menyebabkan wabah pada tahun 2002 dan 2012 silam. Patogenesis COVID-19 belum diketahui secara pasti, namun diduga mirip dengan patogenesis SARS-CoV dan MERS-CoV. Rerata mortalitas COVID-19 adalah 2.3%, lebih rendah dibandingkan dengan mortalitas SARS-CoV dan MERS-CoV. Outbreak COVID-19 juga diduga dimulai dari sebuah pasar penjualan makanan laut lokal pada musim dingin, lingkungan yang hampir sama pada saat outbreak virus SARS. Pada artikel ilmiah ini akan dibahas secara mendalam mengenai definisi operasional yang dapat dipakai dalam manajemen pasien dengan dugaan infeksi COVID-19. Akan dibahas pula manifestasi klinis dan tata laksana pada pasien dengan dugaan dan konfirmasi infeksi COVID-19.

Coronavirus disease 2019 (COVID-2019) is a viral infection which is rapidly spreading on a global scale and causing a severe acute respiratory syndrome that affects today about four and a half million registered cases of people around the world. The aim of this narrative review is to provide an urgent guidance for the doctors who take care of these patients. Recommendations contained in this protocol are based on limited, non-definitive, evidence and experience-based opinions about patients with low and medium intensity of care. A short guidance on the management of COVID-19 is provided for an extensive use in different hospital settings. The evidence-based knowledge of COVID-19 is rapidly evolving, and we hope that, in the near future, a definitive and most efficacious treatment will be available including a specific vaccine for SARS-CoV-2.

As it spread globally, the new SARS-CoV-2 virus was first confirmed in Romania in February 2020, and since then over 40000 cases were diagnosed with COVID-19. Considering climate charges that showed a continuously increasing temperature and also the fact that nowadays air conditioning devices are used on daily bases not only in personal homes but also in healthcare facilities we raised the question if cooling air devices could contribute to the spread of SARS CoV-2 virus. For that, we searched data in the speciality literature regarding the potential of transmission of the virus through air conditioning. Incorrect ventilation in indoor spaces can be associated with an increased transmission rate of respiratory infections as studies suggested. Heating, Ventilation and Air Conditioning Systems (HVAC) are used as one of the infection disease control measure. However, if those are not correctly used, they can contribute to the transmission of an airborne diseases as suggested by data from Japan, Germany, and the Diamond Princess Cruise Ship. There are no clear data that can confirm if there is a link between aerosols produced by HVAC system and transmission of SARS CoV-2 virus and further extensive studies should be performed to either confirm or infirm this hypothesis.

Introduction: Coronavirus is an infection disease with respiratory symptoms and it is a virus that can be transmitted between humans as a mutated virus. Coronavirus-19 disease can lead to stress and anxiety among hospital staff. At present, one of the most important factors affected the occupational performance of the treatment staff and their ability to perform the overshadowed tasks effectively is Covid-19 disease. Therefore, this study was conducted to investigate the relationship between job stress and job performance of nurses in the covid-19 epidemic from the perspective of nurses in Zahedan teaching hospitals in 2021. Materials and Methods: This descriptive-analytical study was performed by available sampling method. Data were obtained using forms collected during three months in the inpatient ward of covid-19 in Zahedan teaching hospitals. The research samples were 235 nurses working in different wards of the hospital participated in this study and answered the three-part questionnaire containing demographic and job information, stress resulted by covid-19 and job performance. The collected data were statistically analyzed using SPSS software, version 20. There were used the descriptive and analytical statistics including frequency, mean, standard deviation and t test. Results: Most of the participants in this study were women (68%) under the age of 30 (59.4%). There is a significant relationship between the effect of Covid-19 on job stress and job performance. Thus, the effect of Covid-19 on job stress is direct, i.e. with the greater effect of Covid-19, the amount of stress increases by 39% ) p = 0.00, r = 0.39(. The effect of Covid-19 on the job performance was inversely so that with increasing the effect of Covid-19, job performance decreased by -20% (-r= 0.20, p=0.01). The findings showed there is a significant relationship between stress resulted by Covid-19 and the job performance. Discussion: The level of stress in nurses working in Covid-19-related wards in Zahedan teaching hospitals is moderate. It seems that paying attention to nurses' education to deal with critical situations similar to Covid-19 and increasing personal protective equipment can be effective in preventing nurses from developing stress and anxiety, and then their job performance will be improved. Keywords: Nurses, Covid-19, Job stress, Job performance

Forecasting is a method that is often used to view future events using past time data. Past time data have useful information to use in obtaining the future. The aim of this study was to forecast infection fatality rate (IFR) of COVID-19 in Brazil using NNAR and ARIMA. ARIMA and NNAR are used because (1) ARIMA is a simple stochastic time series method that can be used to train and predict future time points and ARIMA also capable of capturing dynamic interactions when it uses error terms and observations of lagged terms; (2) the Artificial Neural Network (ANN) is a technique capable of analyzing certain non-linear interactions between input regressor and responses, and Neural Network Time Series (NNAR) is one method of ANN in which lagged time series values were used as inputs to a neural network. Data included in this study were derived from the total data of confirmed cases and the total data of death of COVID-19. The data of COVID-19 in Brazil from February 15, 2020 to April 30, 2020 were collected from the Worldometer (https://www.worldometers.info/coronavirus/) and Microsoft Excel 2013 was used to build a time-series table. Forecasting was accomplished by means of a time series package (forecast package) in R Software. Neural Network Time Series and ARIMA models were applied to a dataset consisting of 76 days. The accuracy of forecasting was examined by means of an MSE. The forecast of IFR of COVID-19 in Brazil from May 01, 2020 to May 10, 2020 with NNAR (1,1) model was around in 6,85% and ARIMA (0,2,1) was around in 7.11%.

CONQUEST (COroNavirus QUESTionnaire) is an online survey of contacts, behaviour, and COVID-19 symptoms for University of Bristol (UoB) staff/students. We analysed survey results from the start of the 2020/2021 academic year, prior to the second national lockdown (14/09/2020-01/11/2020), where COVID-19 outbreaks led to lockdown of some student halls of residence. The aim of these analyses was to enhance knowledge of student contact patterns to inform infection disease mathematical modelling approaches.Responses captured information on demographics, contacts on the previous day, symptoms and self-isolation during the prior week, and COVID-19 status.740 students provided 1261 unique records. Of 42 (3%) students testing positive in the prior fortnight, 99% had been self-isolating. The median number of contacts on the previous day was 2 (interquartile range: 1-5), mode: 1, mean: 6.1; 8% had ≥20 contacts. 57% of student contacts were other UoB students/staff.Most students reported few daily contacts but there was heterogeneity, and some reported many. Around 40% of student contacts were with individuals not affiliated with UoB, indicating potential for transmission to non-students/staff.

Waiting for the vaccine and/or the best antiviral treatment for coronavirus infection disease 2019 (COVID-19), after its outbreak in China at the beginning of 2020 and its viral diffusion around the world in the following weeks, several drugs have been suggested for their potential adjuvant support against infection. Several drugs have been suggested to have a potential ancillary antiviral role. Circulating proteins, in particular proteases and peptidases regulated by drug functions, may interact with well-known drugs like anticoagulants, antihypertensives, antiserotoninergics, and so also with viral proteases. We here report a brief list of these drugs (i.e., heparinoids, flavonoids, antiplatelets, anticoagulants) that may interact with COVID-19.

А model of coronavirus incidence is proposed. Process of disease development is represented as analogue of first- and second order phase transition in physical systems. The model is very simple in terms of the data necessary for the calculations. To verify the proposed model, only data on the current incidence rate are required. However, the determination coefficient of model R2 is very high and exceeds 0.95 for most countries. The model permits the accurate prediction of the pandemics dynamics at intervals of up to 10 days. The ADL(autoregressive distributed lag)-model was introduced in addition to the phase transition model to describe the development of the disease at the exponential phase.The ADL-model allows describing nonmonotonic changes in relative infection over the time, and providing to governments and health care decision makers the possibility to predict the outcomes of their decisions on public health.

PurposeTo investigate the epidemiology and clinical features of discharged adult patients with coronavirus infection disease 2019 (COVID-19) in Yichang.MethodThe retrospective study recruited 197 cases of COVID-19 discharged from Yichang Central People’s Hospital and Yichang Third People’s Hospital from Jan 17 to Feb 26, 2020. All cases were confirmed by real-time RT-PCR or chest computer tomography (CT). The survivors were followed up until March 4,2020. Clinical data, including demographic characteristic, presentation, underlying illness, exposure history, laboratory examination, radiology and prognosis were enrolled and analyzed by SPSS 19.0 software.ResultsThere were 197 adult discharged patients with COVID-19 in this study. Statistical analysis indicated that the average age was 55.94 years, and female patients were 99(50.3%).Those patients mainly resided in urban with exposure history in 2 weeks, while 7 medical staffs were infected. Fever (77.6%%), cough (43.6%) and weakness (14.7%) were the common symptoms. Leukocytes were mainly normal or decreased in 185 patients (92.9%), both lymphocytes and eosinophils were below normal range, the ratios were 56.9% and 50.3%, respectively. On the contrary, lactate dehydrogenases raised in 65 patients. C-reactive protein (72.4%) elevated in the most of patients. The sensitivity of RT-PCR was 63.5%. Chest CT indicated that bilateral patchy shadows (69.0%) were the most common imaging manifestations.169(85.8%) patients recovered and transferred to a designated hospital for observation, and the others (14.2%) turned worst and died of acute respiratory failure.ConclusionCOVID-19 infection with highly contagious have become a life-threaten public healthy problem, the sensitivity of RT-PCR was limited. Chest CT scan was recommended for the suspected patients. Furthermore, lymphocytopenia and eosinophils declining without leukocytes increasing may be considered as a useful evidence for the diagnosis.

2019 novel coronavirus (SARS‐CoV‐2), which originated in Wuhan, China, has attracted the world's attention over the last month. The Chinese government has taken emergency measures to control the outbreak and has undertaken initial steps in the diagnosis and treatment of 2019 novel coronavirus infection disease (COVID‐19). However, SARS‐CoV‐2 possesses powerful pathogenicity as well as transmissibility and still holds many mysteries that are yet to be solved, such as whether the virus can be transmitted by asymptomatic patients or by mothers to their infants. Our research presents selected available cases of COVID‐19 in China to better understand the transmission and diagnosis regarding this infectious disease., Research Highlights The research includes important information regarding the transmission and diagnosis of COVID‐19.The clinical report could be very useful for clinicians.SARS‐CoV‐2 possesses powerful pathogenicity and transmissibility.Patients with negative swabs may also be diagnosed with COVID‐19.

In this paper, we evaluate the impact of Wuhan COVID-19 (Coronavirus Disease 2019) on four strategic sectors - i.e. tourism, air transportation, international trade, and electricity consumption of the Chinese economy. To do so, we develop and apply a new model - the economic crisis from massive contagious infection diseases simulator (ECMCID-Simulator). The simulator deploys a macro-dynamic analysis under different possible scenarios to evaluate the impact of a massive contagious infection disease on the short-run economic performance of a country.

During the normalized phase of COVID-19, droplets or aerosol particles produced by infected personnel are considered as the potential source of infection with uncertain exposure risk. As such, in densely populated open spaces, it is necessary to adopt strategies to mitigate the risk of infection disease transmission while providing sufficient ventilation air. An example of such strategies is use of physical barriers. In this study, the impact of barrier heights on the spread of aerosol particles is investigated in an open office environment with the well-designed ventilation mode and supply air rate. The risk of infection disease transmission is evaluated using simulation of particle concentration in different locations and subject to a number of source scenarios. It was found that a barrier height of at least 60 cm above the desk surface is needed to effectively prevent the transmission of viruses. For workstations within 4 m from the outlet, a 70 cm height is considered, and with a proper ventilation mode, it is shown that the barriers can reduce the risk of infection by 72%. However, for the workstations further away from the outlet (beyond 4 m), the effect of physical barrier cannot be that significant. In summary, this study provides a theoretical analysis for implementing physical barriers, as a low-cost mitigation strategy, subject to various height scenarios and investigation of their effectiveness in reducing the infection transmission probability.

Background: Dialyzed patients are vulnerable to coronavirus infection disease 2019 (COVID-19). The incidence and outcome of COVID-19 in hemodialysis (HD) patients in Taiwan remain unclear. A series of preventive measures were executed to combat COVID-19 transmission among HD patients. Methods: We carried out a series of forward-looking and practical preventive strategies of COVID-19 control in our HD center. Incidences of COVID-19 of our HD unit were compared with those of national and local estimates from a community outbreak from 15 May to 30 June 2021. Prognostic factors associated with mortality were analyzed. Results: The national incidence of COVID-19 was 0.062%, being highest in Taipei City (0.173%), followed by New Taipei City (0.161%) and Keelung (0.083%). The overall incidence in Keelung HD patients was 0.666%. One patient of our HD center contracted COVID-19 from the household, however, we have contained secondary transmission in our HD center by implementing strict preventive measures. The mortality rate of HD patients in Keelung was 66.6%. The median Ct value of HD patients was 17.53 (11.75–27.90) upon diagnosis. The deceased patients had a higher cardiac/thoracic ratio than alive (0.61 vs. 0.55, p = 0.036). Conclusions: Taking aggressive and proactive infection preventive measures impedes the secondary transmission of COVID-19 in HD facilities. COVID-19-associated mortality was high in HD patients, being the high cardiac-thoracic ratio, an important prognostic factor for clinical outcome of infected HD patients.

At present, effective antivirals against the coronavirus infection disease 2019 (COVID-19) do not seem to be available, and hence medical practitioners and governments are vying for any useful information on the treatment and management of this outbreak. Research journals have played their part by promotingCOVID-19 research to ensure that the stakeholders have immediate access to adequate information.

At the end of December 2019, coronavirus disease 2019 (COVID-19) appeared in Wuhan city, China. As of April 15, 2020, >1.9 million COVID-19 cases were confirmed worldwide, including >120,000 deaths. There is an urgent need to monitor and predict COVID-19 prevalence to control this spread more effectively. Time series models are significant in predicting the impact of the COVID-19 outbreak and taking the necessary measures to respond to this crisis. In this study, Auto-Regressive Integrated Moving Average (ARIMA) models were developed to predict the epidemiological trend of COVID-19 prevalence of Italy, Spain, and France, the most affected countries of Europe. The prevalence data of COVID-19 from 21 February 2020 to 15 April 2020 were collected from the World Health Organization website. Several ARIMA models were formulated with different ARIMA parameters. ARIMA (0,2,1), ARIMA (1,2,0), and ARIMA (0,2,1) models with the lowest MAPE values (4.7520, 5.8486, and 5.6335) were selected as the best models for Italy, Spain, and France, respectively. This study shows that ARIMA models are suitable for predicting the prevalence of COVID-19 in the future. The results of the analysis can shed light on understanding the trends of the outbreak and give an idea of the epidemiological stage of these regions. Besides, the prediction of COVID-19 prevalence trends of Italy, Spain, and France can help take precautions and policy formulation for this epidemic in other countries., Graphical abstract Unlabelled Image, Highlights • Europe has become the epicentre of the virus and hit the continent harder than China. • The apparent mortality rate of COVID-19 is approximately 13% in Italy, 11% in Spain, and 15% in France. • Time series models are significant in predicting the prevalence of the COVID-19 pandemic. • ARIMA (0,2,1), ARIMA (1,2,0), and ARIMA (0,2,1) were chosen as the best models for Italy, Spain, and France, respectively.

The World Vaccine Congress Europe 2019, organized by Terrapinn, was held in Barcelona, Spain, with more than 600 attendees and brought together vaccinology experts from all around the world to discuss current topics in vaccine development and manufacture Topics covered over the duration of the congress were preparation for an infection disease pandemic, new immunotherapies for different conditions (e g , cancer, respiratory infection, emerging diseases), optimization of vaccine manufacturing and formulation, eradication of diseases, the role of vaccines in antimicrobial resistance, as well as the importance of strategy partnering for the vaccine industry The conference was co-located with the World Veterinary Vaccine Congress and the Immuno-oncology Profiling Congress This report focuses on presentations of ongoing studies of vaccines for different diseases Copyright © 2020 Clarivate Analytics