Outbreak Of Atypical Pneumonia Research Articles

Reuse of drugs in the treatment of COVID-19

After an outbreak of atypical pneumonia in the city of Wuhan, China, there were epidemiological alerts due to the unknown factor. On January 7, 2020, Chinese scientists isolated a strain of coronavirus, in which the etiologic agent was identified. It quickly spread around the world and, therefore, it was declared a pandemic on March 11, 2020. From then on, the need arises to search for treatments and prevention of the disease, through some existing drugs, such as Chloroquine, Hydroxychloroquine, Ivermectin and Azithromycin. Objective: The objective of this study is to discuss existing drugs used for the possible treatment of COVID-19, clarify their mechanisms of action and studies that prove their effectiveness or not. Methodology: The narrative review of the literature was based on a search in the Google Scholar, Capes, Scielo and PubMed journals databases published in the last 3 years, using the terms: “covid-19 drugs in vitro/in vivo”; "SARS-CoV-2"; “coronavirus”. Results: From the analysis of the articles, it can be noted that there is not enough evidence to prove the effectiveness of these drugs in the fight against COVID-19. The studies that showed results in combating SARS-CoV-2 were in vitro, in addition to being at higher doses than recommended for humans. Conclusion: Therefore, its therapeutic safety for the prevention and treatment of COVID-19 has not yet been clarified and determined, thus, its indiscriminate use can potentiate adverse effects.

Optimal timing and effectiveness of COVID-19 outbreak responses in China: a modelling study

BackgroundIn January 2020, an outbreak of atypical pneumonia caused by a novel coronavirus, SARS-CoV-2, was reported in Wuhan, China. On Jan 23, 2020, the Chinese government instituted mitigation strategies to control spread. Most modeling studies have focused on projecting epidemiological outcomes throughout the pandemic. However, the impact and optimal timing of different mitigation approaches have not been well-studied.MethodsWe developed a mathematical model reflecting SARS-CoV-2 transmission dynamics in an age-stratified population. The model simulates health and economic outcomes from Dec 1, 2019 through Mar 31, 2020 for cities including Wuhan, Chongqing, Beijing, and Shanghai in China. We considered differences in timing and duration of three mitigation strategies in the early phase of the epidemic: city-wide quarantine on Wuhan, travel history screening and isolation of travelers from Wuhan to other Chinese cities, and general social distancing.ResultsOur model estimated that implementing all three mitigation strategies one week earlier would have averted 35% of deaths in Wuhan (50% in other cities) with a 7% increase in economic impacts (16-18% in other cities). One week’s delay in mitigation strategy initiation was estimated to decrease economic cost by the same amount, but with 35% more deaths in Wuhan and more than 80% more deaths in the other cities. Of the three mitigation approaches, infections and deaths increased most rapidly if initiation of social distancing was delayed. Furthermore, social distancing of working-age adults was most critical to reducing COVID-19 outcomes versus social distancing among children and/or the elderly.ConclusionsOptimizing the timing of epidemic mitigation strategies is paramount and involves weighing trade-offs between preventing infections and deaths and incurring immense economic impacts. City-wide quarantine was not as effective as city-wide social distancing due to its much higher daily cost than social distancing. Under typical economic evaluation standards, the optimal timing for the full set of control measures would have been much later than Jan 23, 2020 (status quo).

Developing an Intelligent System for Diagnosis of COVID-19 Based on Artificial Neural Network

An outbreak of atypical pneumonia termed coronavirus disease 2019 (COVID-19) has spread worldwide since the beginning of 2020. It poses a significant threat to the global health and the economy. Physicians face ambiguity in their decision-making for COVID-19 diagnosis and treatment. In this respect, designing an intelligent system for early diagnosis of the disease is critical for mitigating virus spread and resource optimization. This study aimed to establish an artificial neural network (ANNs)-based clinical model to diagnose COVID-19. The retrospective dataset used in this study consisted of 400 COVID-19 case records (250 positives vs. 150 negatives) and 18 columns for the diagnostic features. The backpropagation technique was used to train a neural network. After designing multiple neural network configurations, the area under the receiver-operating characteristic curve (AUC), accuracy, sensitivity, and specificity values were calculated to measure the model performance. The two nested loops architecture of 9-10-15-2 (10 and 15 neurons used in layer one and layer two, respectively) with the ROC of 98.2%, sensitivity of 96.4%, specificity of 90.6%, and accuracy of 94 % were introduced as the best configuration model for COVID-19 diagnosis. ANN is valuable as a decision-support tool for clinicians to improve the COVID-19 diagnosis. It is promising to implement the ANN model to improve the accuracy and speed of the COVID-19 diagnosis for timely screening, treatment, and careful monitoring. Further studies are warranted for verifying and improving the current ANN model.

The Relationships among Anxiety, Subjective Well-Being, Media Consumption, and Safety-Seeking Behaviors during the COVID-19 Epidemic.

The COVID-19 epidemic has been confirmed as the largest scale outbreak of atypical pneumonia since the outbreak of severe acute respiratory syndrome (SARS) in 2003 and it has become a public health emergency of international concern. It exacerbated public confusion and anxiety, and the impact of COVID-19 on people needs to be better understood. Indeed, prior studies that conducted meta-analysis of longitudinal cohort research compared mental health before versus during the COVID-19 pandemic and proved that public health polices (e.g., city lockdowns, quarantines, avoiding gatherings, etc.) and COVID-19-related information that circulates on new media platforms directly affected citizen’s mental health and well-being. Hence, this research aims to explore Taiwanese people’s health status, anxiety, media sources for obtaining COVID-19 information, subjective well-being, and safety-seeking behavior during the COVID-19 epidemic and how they are associated. Online surveys were conducted through new media platforms, and 342 responses were included in the analysis. The research results indicate that the participants experienced different aspects of COVID-19 anxiety, including COVID-19 worry and perceived COVID-19 risk. Among the given media sources, the more participants searched for COVID-19 information on new media, the greater they worried about COVID-19. Furthermore, COVID-19 worry was positively related to safety-seeking behavior, while perceived COVID-19 risk was negatively related to subjective well-being. This paper concludes by offering some suggestions for future studies and pointing out limitations of the present study.

COVID-19 Pandemic: Huge Stress Test for Health System Could Be a Great Opportunity to Update the Workflow in a Modern Surgical Pathology.

Simple SummaryThe COVID-19 pandemic has hit Northern Italy’s regions hard in terms of deaths since February 2020. Containment measures have been applied to avoid contagion and reduce the patient infection rate. In this manuscript, we report the experience of the Pathology Department of the Fondazione IRCCS Istituto Nazionale Tumori in Milan, during the period of the first lockdown that occurred in Lombardy from March to May 2020, focusing on the variation in terms of exams between the pre-COVID-19 and COVID-19 periods and describing the measures applied to guarantee the safeguarding of workers. Moreover, we calculated if changes introduced within the workflow affected the average diagnosis time using Turn-Around-Time (TAT) metrics released by the Lombardy Region. We showed a sharp slowdown in exams during the first wave of COVID-19 and that the measures applied for the safeguarding of the personnel turned out to be feasible and did not affect the overall performance of the Pathology Department.Background: On December 2019, an outbreak of atypical pneumonia, known as COVID-19, was identified in Wuhan, China. This disease, characterized by the rapid human-to-human transmission of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spread rapidly in more than 200 countries. Northern Italy’s regions have been hit hard in terms of deaths. Here, we report the experience of the Pathology Department of the Fondazione IRCCS Istituto Nazionale Tumori (INT) in Milan, the first Italian public cancer center, in the period of the lockdown that took place in Lombardy from March to May 2020. Method: The variation in terms of exams was calculated in two different timeframes: December 2019–February 2020 (pre-COVID-19) and March–May 2020 (COVID-19). During these periods, Turn-Around-Time (TAT) metrics released by the Lombardy Region were calculated to assess if changes applied to guarantee the safeguarding of workers affected the average diagnosis time. Results: In the COVID-19 period, there was a decrease for all the performed exams. The most considerable decrease was observed for PAP tests (−81.6%), followed by biopsies (−48.8%), second opinions (−41.7%), and surgical (−31.5%), molecular (−29.4%) and cytological (−18.1%) tests. Measures applied within the Pathology Department, such as digital pathology, remote working, rotations and changes in operating procedures, improved the diagnostic performance as required by the guidelines of the Lombardy Region in terms of TAT. At the same time, the measures applied for the safeguarding of the personnel turned out to be feasible and did not affect the overall performance of the Pathology Department. Conclusions: The sharp slowdown in cancer screening during the first wave of COVID-19 could seriously endanger cancer prevention in the near future.

COVID-19, diabetes y el sistema inmunológico

En el año de 2019 en la provincia de Wuhan, China, se reportó un brote de neumonías atípicas, con síntomas similares a los del Síndrome Respiratorio Agudo Severo (SARS), brote reportado en el 2003, y al Síndrome Respiratorio del Oriente Medio (MERS), brote reportado en 2012 en Arabia Saudita. Esta enfermedad emergente fue causada por el nuevo coronavirus “Síndrome Respiratorio Agudo Severo Coronavirus 2” (SARS-CoV-2) o también denominada COVID-19 del inglés Coronavirus desease 2019, caracterizado por presentar severos problemas respiratorios y diversas manifestaciones extrapulmonares. Al momento se ha reportado una elevada tasa de mortalidad en individuos del sexo masculino, en adultos mayores de 60 años, y en personas con comorbilidades como diabetes obesidad, hipertensión y problemas cardiacos. La diabetes es una enfermedad caracterizada por resistencia a insulina, pérdida de función de células β en el páncreas, y desbalance del sistema inmune por el estado de inflamación crónica. En pacientes graves con COVID-19, se ha observado una secreción alterada de citocinas pro inflamatorias, si esto ocurre en un paciente diabético, que ya tiene un estado inflamatorio per se, se induce inflamación exacerbada y una falla multiorgánica que puede desencadenar en la muerte de los pacientes. Diversos autores señalan como hipótesis que la hiperglicemia favorece la replicación viral, por lo que en un paciente “diabético con infección COVID-19”, es primordial mantener un control glicémico adecuado. Los tratamientos para COVID-19 se han enfocado en disminuir los síntomas, el uso de antivirales, antiinflamatorios, anticuerpos monoclonales y plasma convaleciente COVID-19 ha mostrado resultados variables. Para el control de esta infección viral es necesaria una vacuna, al momento existen más de 150 candidatos, con una eficiencia que va del rango de 70 al 95%, pero aún falta determinar la inmunidad a largo plazo en las personas vacunadas. Esta revisión aborda las características de la infección por SARS-CoV2 y la respuesta inmunitaria en pacientes diabéticos frente a COVID-19.

ACE2 models of frequently contacted animals provide clues of their SARS-CoV-2 S protein affinity and viral susceptibility.

The outbreak of atypical pneumonia (coronavirus disease 2019 [COVID‐19]) has been a global pandemic and has caused severe losses to the global economy. The virus responsible for COVID‐9, severe acute respiratory syndrome coronavirus‐2 (SARS‐CoV‐2), has a spike glycoprotein (S protein) that binds angiotensin‐converting enzyme 2 (ACE2) present on host cell membranes to gain entry. Based on the full‐length human ACE2 cryo‐EM structure, we generated homology models of full‐length ACE2 proteins from various species (gorilla, monkey, pig, bovine, sheep, cat, dog, mouse, and rat). Although these ACE2 molecules were found to share similar overall structures, their S–ACE2 interface residues differed. These differences likely result in variations in the ACE2 binding affinities to the SARS‐CoV‐2 S protein. The highest affinities are predicted for human, gorilla, and monkey, while mouse and rat ACE2 are predicted to have the lowest affinities. Cat ACE2 is predicted to have a lower S protein affinity than dog ACE2. Although affinity is not the only factor that affects viral susceptibility, it is one of the most important factors. Thus, we believe that care should be taken with these animals to prevent the spread of SARS‐CoV‐2 among animal and human populations.

ONE YEAR AFTER THE WHO ALERT FOR COVID-19: WHAT IS NEXT? / UM ANO APÓS O ALERTA DA OMS PARA COVID-19: O QUE VEM A SEGUIR?

In December 2019, an outbreak of atypical pneumonia was discovered, later revealed to be due to a new virus identified as SARS-CoV-2, responsible for causing the coronavirus disease (COVID-19). The purpose is brings the main changes and discoveries, after a year that PHEIC was declared. We argue that after one year since PHEIC was declared, a lot has changed since then, in this sense, carried out a bibliographic review. We conducted a survey of articles published in the PUBMED and Google Scholar databases, from January 2020 to January 2021, which released data from studies related to transmission, treatment, vaccines, new variants for COVID-19. After the novel virus spread to other countries and caused hundreds of deaths, the World Health Organization issued its alarm on January 30, 2020, known as PHEIC. After a year that the alarm was given a lot has changed. The first major change was the beginning of a COVID-19 pandemic on March 11, 2020. Many discoveries were made, from a better understanding of transmission, treatment, vaccines and challenges with new strains that arose after selective pressure.

Psychological Morbidity Among Post-COVID-19 Patients: A Cross-sectional Study from Chennai, South India

Background: The COVID-19 pandemic is a global health threat and is by far the largest outbreak of atypical pneumonia, since the SARS outbreak in 2003. A range of psychiatric morbidities such as persistent depression, anxiety, panic attacks, delirium and suicidality were observed in the post infectious state across the world. Hence, the aim of the study was to understand the psychological status of the patients affected by COVID during their post-COVID follow-up period and to examine the socio-demographic and clinical factors associated with high psychological morbidity. Materials and Methods: A cross sectional study conducted in the post-COVID follow up clinic, at a tertiary care hospital between the months of August - November 2020, using a semi structured proforma and rating scales such as Patient Health Questionnaire-9 (PHQ-9), Hospital Anxiety and Depression Scale (HADS) and Insomnia Severity Index (ISI) for depression, anxiety and insomnia, respectively. Results: The study results indicate that the prevalence of depression and anxiety among post-COVID-19 patients was 21.9% and 11.9%, respectively. Insomnia was observed among 21.7%Among various sociodemographic and clinical variables examined, it was observed that female gender, patients with ongoing stressors and patients with post-COVID-19 persistent physical symptoms were found to be associated with greater depression and anxiety among the study population. Conclusions: Persistent physical symptoms and ongoing life stressors are found to be associated with depression and anxiety among post-COVID-19 patients. Hence, periodic screening for individuals with persisting physical symptoms and care for the vulnerable population such as those with ongoing stressors will provide a significant advantage in the follow up of the mental health of the patients affected with COVID-19.

Epidemiologija kovid-19 - šta smo naučili do sada?

The first case in the outbreak of atypical pneumonia of unknown etiology, later confirmed as disease caused by SARS-CoV-2, was described in Wuhan (China) on December 8, 2019. The rapid expansion of COVID-19 cases prompted the World Health Organization (WHO) to declare a global health emergency, and on March 11, 2020, COVID-19 was officially classified as a pandemic disease by the WHO. It is generally accepted that both genders and all ages in the population are susceptible to SARS-CoV-2 infection. Data from the real life also show difficulties in reaching the threshold of herd immunity. Thanks to the vaccination, some populations are approaching the theoretical threshold of immunity, but the spread of the virus is still difficult to stop. If we add to that the fact that we still do not know how long immunity lasts after the infection, the conclusion is that vaccination is unlikely to completely stop the spread of the virus, and that we must think about it. Vaccines certainly significantly reduce the hospitalization rate and mortality rate, and the assumption is that the virus will not disappear soon, but the severity of the disease and its fatality will be of marginal importance. The development of the epidemiological situation related to the COVID-19 is constantly changing and it significantly differs in various parts of the world, which is affected by differences in financial resources, health infrastructure and awareness of prevention and control of the COVID-19. Attempts are being made to make dynamically adjusted strategies in response to the COVID-19 pandemic, that is, the new normality.

Performance analysis of data mining algorithms for diagnosing COVID-19.

BACKGROUND:An outbreak of atypical pneumonia termed COVID-19 has widely spread all over the world since the beginning of 2020. In this regard, designing a prediction system for the early detection of COVID-19 is a critical issue in mitigating virus spread. In this study, we have applied selected machine learning techniques to select the best predictive models based on their performance.MATERIALS AND METHODS:The data of 435 suspicious cases with COVID-19 which were recorded from the Imam Khomeini Hospital database between May 9, 2020 and December 20, 2020, have been taken into consideration. The Chi-square method was used to determine the most important features in diagnosing the COVID-19; eight selected data mining algorithms including multilayer perceptron (MLP), J-48, Bayesian Net (Bayes Net), logistic regression, K-star, random forest, Ada-boost, and sequential minimal optimization (SMO) were applied in data mining. Finally, the most appropriate diagnostic model for COVID-19 was obtained based on comparing the performance of the selected algorithms.RESULTS:As the result of using the Chi-square method, 21 variables were identified as the most important diagnostic criteria in COVID-19. The results of evaluating the eight selected data mining algorithms showed that the J-48 with true-positive rate = 0.85, false-positive rate = 0.173, precision = 0.85, recall = 0.85, F-score = 0.85, Matthews Correlation Coefficient = 0.68, and area under the receiver operator characteristics = 0.68, respectively, had the higher performance than the other algorithms.CONCLUSION:The results of evaluating the performance criteria showed that the J-48 can be considered as a suitable computational prediction model for diagnosing COVID-19 disease.

Psychological Morbidity Among Post-COVID-19 Patients: A Cross-sectional Study from Chennai, South India

Background: The COVID-19 pandemic is a global health threat and is by far the largest outbreak of atypical pneumonia, since the SARS outbreak in 2003. A range of psychiatric morbidities such as persistent depression, anxiety, panic attacks, delirium and suicidality were observed in the post infectious state across the world. Hence, the aim of the study was to understand the psychological status of the patients affected by COVID during their post-COVID follow-up period and to examine the socio-demographic and clinical factors associated with high psychological morbidity. Materials and Methods: A cross sectional study conducted in the post-COVID follow up clinic, at a tertiary care hospital between the months of August - November 2020, using a semi structured proforma and rating scales such as Patient Health Questionnaire-9 (PHQ-9), Hospital Anxiety and Depression Scale (HADS) and Insomnia Severity Index (ISI) for depression, anxiety and insomnia, respectively. Results: The study results indicate that the prevalence of depression and anxiety among post-COVID-19 patients was 21.9% and 11.9%, respectively. Insomnia was observed among 21.7%Among various sociodemographic and clinical variables examined, it was observed that female gender, patients with ongoing stressors and patients with post-COVID-19 persistent physical symptoms were found to be associated with greater depression and anxiety among the study population. Conclusions: Persistent physical symptoms and ongoing life stressors are found to be associated with depression and anxiety among post-COVID-19 patients. Hence, periodic screening for individuals with persisting physical symptoms and care for the vulnerable population such as those with ongoing stressors will provide a significant advantage in the follow up of the mental health of the patients affected with COVID-19.

Immediate Psychological Impact of Dental Students on COVID-19 Epidemic in India - A Cross Sectional Study.

Introduction:The 2019 coronavirus disease (COVID-19) epidemic is a global health threat and is by far the largest outbreak of atypical pneumonia since after SARS over the past few decades. Within weeks of the initial outbreak the total number of cases and deaths exceeded those of SARS. Such mass Casualties often trigger waves of heightened fear and anxiety in many population.Aim:To assess the psychological impact and mental health status among the dental students studying in the Vinayaka Mission's Sankarachariyar Dental College, Salem, India.Materials and Method:A total of 21 psychological state questionnaires along with demographic aspects were distributed to 460 under graduate dental students from Vinayaka Mission's Sankarachariyar Dental College, Salem, Tamilnadu. The Psychological state was assessed using the Depression, Anxiety and Stress Scale (DASS).Results:404 questionnaires were taken for our study as they responded all questions. The results were calculated based on the responses obtained year wise, gender, Place of residence, Living with family, Steady family income and Acquaintance affected with covid and compared among the three psychological assessments Depression, Anxiety and stress. The results of the study were done using SPSS (V21.0IBM, Chicago) Software.Conclusion:We attempted to correlate the socio demographic datas with psychological status of the dental students' in our university using the DAS scale. This study focused on the need for treating the psychological impact of the society at this outbreak as the mental health is the most important to deal with.

Déjà Vu - A New Coronavirus Challenge.

Déjà Vu - A New Coronavirus Challenge.

Neurological manifestations due to, during and after COVID-19

With the ongoing pandemic of coronavirus disease 2019 (COVID-19), many neurological manifestations have been linked to what began as an outbreak of atypical pneumonia. Like other corona viruses, severe acute respiratory syndrome coronavirus (SARS-CoV-2) has potential for neurotropism. Viral invasion and likely pathogenecity has been associated with expression of ACE-2 receptors along endothelia and olfactory mucosa. Hyperinflammatory response after systemic infection is in part responsible for the severity and multi-organ dysfunction seen in severe cases. Features like encephalitis, central and peripheral demyelinating disorders, cranial neuropathies, stroke are seen not only in patients with severe illness but at times preceding any systemic symptoms. Neurological disorders are not only part of acute illness phase but also seen in postinfectious phase likely due to immune mediated effect. Also, long term sequelae in patients with moderate to severe COVID-19, either due to systemic complications or direct virus mediated effect are a matter of concern. High suspicion and early recognition of possible presenting features and neurological complications in severely affected patients is key for management. With the rapidity and enormity of ongoing pandemic whether these observations are causal or casual is yet to be determined. Further collaborations for comparisons of observations across the world in necessary to understand the potential impact of COVID-19. Accessing these observations will help in better understanding the agent host and environmental factors determining the expected impact of this pandemic. Reorganizing health care facilities to apt for better handling COVID-19 over time to come will help to mitigate the impact. Keywords: COVID-19; neurological manifestations; encephalitis; stroke; neurotropism

SARS-CoV-2 exhibits intra-host genomic plasticity and low-frequency polymorphic quasispecies.

In December 2019, an outbreak of atypical pneumonia (Coronavirus disease 2019 -COVID-19) associated with a novel coronavirus (SARS-CoV-2) was reported in Wuhan city, Hubei province, China. The outbreak was traced to a seafood wholesale market and human to human transmission was confirmed. The rapid spread and the death toll of the new epidemic warrants immediate intervention. The intra-host genomic variability of SARS-CoV-2 plays a pivotal role in the development of effective antiviral agents and vaccines, as well as in the design of accurate diagnostics. We analyzed NGS data derived from clinical samples of three Chinese patients infected with SARS-CoV-2, in order to identify small- and large-scale intra-host variations in the viral genome. We identified tens of low- or higher- frequency single nucleotide variations (SNVs) with variable density across the viral genome, affecting 7 out of 10 protein-coding viral genes. The majority of these SNVs (72/104) corresponded to missense changes. The annotation of the identified SNVs but also of all currently circulating strain variations revealed colocalization of intra-host as well as strain specific SNVs with primers and probes currently used in molecular diagnostics assays. Moreover, we de-novo assembled the viral genome, in order to isolate and validate intra-host structural variations and recombination breakpoints. The bioinformatics analysis disclosed genomic rearrangements over poly-A / poly-U regions located in ORF1ab and spike (S) gene, including a potential recombination hot-spot within S gene. Our results highlight the intra-host genomic diversity and plasticity of SARS-CoV-2, pointing out genomic regions that are prone to alterations. The isolated SNVs and genomic rearrangements reflect the intra-patient capacity of the polymorphic quasispecies, which may arise rapidly during the outbreak, allowing immunological escape of the virus, offering resistance to anti-viral drugs and affecting the sensitivity of the molecular diagnostics assays.

Evidence of increasing diversification of emergingSevere Acute Respiratory Syndrome Coronavirus 2 strains.

On 30th January 2020, an outbreak of atypical pneumonia caused by a novel betacoronavirus, named severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), was declared a public health emergency of international concern by the World Health Organization. For this reason, a detailed evolutionary analysis of SARS‐CoV‐2 strains currently circulating in different geographic regions of the world was performed. A compositional analysis as well as a Bayesian coalescent analysis of complete genome sequences of SARS‐CoV‐2 strains recently isolated in Europe, North America, South America, and Asia was performed. The results of these studies revealed a diversification of SARS‐CoV‐2 strains in three different genetic clades. Co‐circulation of different clades in different countries, as well as different genetic lineages within different clades were observed. The time of the most recent common ancestor was established to be around 1st November 2019. A mean rate of evolution of 6.57 × 10−4 substitutions per site per year was found. A significant migration rate per genetic lineage per year from Europe to South America was also observed. The results of these studies revealed an increasing diversification of SARS‐CoV‐2 strains. High evolutionary rates and fast population growth characterizes the population dynamics of SARS‐CoV‐2 strains.

Assessment of Mental Health and Various Coping Strategies among general population living Under Imposed COVID-Lockdown Across world: A Cross-Sectional Study

The 2019 corona virus disease (COVID-19) which outbreak in December 2019, in the Chinese city of Wuhan has became a global threat and is currently the largest known outbreak of atypical pneumonia affecting every continent of the world with about 6,416,828 cases and 382,867 deaths. Disease enforced lockdowns are known to cause heightened levels of depression, anxiety, and stress. Our study aimed to investigate the immediate impact of the COVID-19 pandemic enforced lockdown on mental health and quality of life among general population aged 18 years and to identify various coping strategies used under lockdown. An online survey was conducted between 1st of April–10th of May, 2020; using a validated questionnaire based on DASS-42, employing a snowball sampling technique. A total of 418 responses from 16 different countries were received. The respondents had a high level of depression and anxiety scores, which were significantly different among genders. Also, participants from developing countries–India and Pakistan had severe depression while as participants from India, Pakistan and Kingdom of Saudi Arabia had severe anxiety. We also found that among the various coping strategies, (a) watching television for entertainment, (b) social networking, (c) listening to music, (d) sleeping, (e) doing mundane house chores like cleaning, washing, etc. (f) eating well, and (g) clearing/finishing thepiled-up work were ranked among the most utilized coping strategies by all participants. This study identifies the need to provide the free professional and psychological services to help cope with stress during the disease-enforced lockdown.

Yeni Koronavirüsün (Covid-19) Moleküler Yapısı ve Genomik Karakterizasyonu

SARS-CoV-2, transmitted from person to person and associated with the outbreak of atypical pneumonia, first emerged in Wuhan, China. Although bats, SARS-CoV and MERS-CoV are the primary reservoirs for COVID-19, it turns out that SARS-CoV may have been transmitted from the civet in China, MERS-CoV from camels in the Middle East, and COVID-19 from the bat to humans via the pangolin (scaly anteater). SARS-CoV, MERS-CoV and SARS-CoV-2 are coronaviruses belonging to the Coronaviridae family and Betacoronavirus genus, which cause epidemiological outbreaks, are enveloped viruses with approximately 32 Kb long positive sense, ssRNA, and play a role in the pathogenesis of proinflammatory responses with high mortality rates associated with infection. The 2019-nCoV genome has 89% nucleotide identity with bat SARS-like CoVZXC21 and 82% with human SARS-CoV. ACE2 is the receptor of this severe acute respiratory syndrome coronavirus. The aim of this review is to reveal the molecular structure and genetic features of the SARS-CoV-2 virus and the clinical effects of the disease, which causes COVID-19 acute respiratory disease, and to compare it to SARS and MERS. Clarifying the specific molecular details of COVID-19 will guide researchers to the discovery of its treatment. Thus, the development of the molecular genetic methods for COVID-19 will increase our control measures against the virus in the future.

Spatiotemporal distribution and trend of COVID-19 in the Yangtze River Delta region of the People's Republic of China.

An outbreak of atypical pneumonia, now called COVID-19 and known to be caused by the novel coronavirus SARS-CoV-2, first detected in Wuhan, Hubei Province of the People's Republic of China in December 2019 and afterwards rapidly spread worldwide. Wuhan and the Yangtze River Delta (YRD) region implemented first-level public health emergency responses to stop the spread of the virus on January 23rd, 2020. We tracked the geographical gravity centre of the disease and calculated spatial autocorrelation to explore the spatiotemporal patterns of distribution of imported and locally disseminated COVID-19 cases under the emergency-response control measure. We also applied polynomial regression analysis to estimate the trend of the COVID-19 in the YRD region before and after the control activities against the spread of the infection were instituted. The results show that the control measures applied have been effective. And, in the YRD region, areas with a large influx of population flow from Wuhan and Hubei Province had high risks of COVID-19. Therefore, identification of the spatiotemporal trends should be the first step when developing effective policies to manage and control any new epidemic. The results are not only informative locally but also useful for the rest of the world.