We examine 10 hypothetical patients suffering from some of the symptoms of COVID 19 (modified) using topological concepts on topological spaces created from equality and similarity interactions and our information system. This is determined by the degree of accuracy obtained by weighing the value of the lower and upper figures. In practice, this approach has become clearer.

BACKGROUND: Coronavirus current pandemic (COVID-19) is the striking subject worldwide hitting countries in an unexplained non-universal pattern. Bacillus Calmette–Guérin (BCG) vaccine was an adopted recent justification depending on its non-specific immune activation properties. Still the problem of post-vaccine short duration of protection needs to be solved. The same protective mechanism was identified in active or latent tuberculosis (TB). For each single patient of active TB, there are about nine cases of asymptomatic latent TB apparently normal individuals living within the community without restrictions carrying benefits of immune activation and involved in re-infection cycles in an excellent example of repeated immunity tr

After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings

By March 2020, a pandemic had been emerged Corona Virus Infection in 2019 (COVID-19), which was triggered through the sensitive pulmonary syndrome (SARS disease corona virus- 2 (SARS COV-2). Overall precise path physiology of SARS COV-2 still unknown, as does the involvement of every element of the acute or adaptable immunity systems. Additionally, evidence from additional corona virus groups, including SARS COV as well as the Middle East pulmonary disease, besides that, fresh discoveries might help researchers fully comprehend SARS CoV-2. Toll-like receptors (TLRs) serve a critical part in both detection of viral particles as well as the stimulation of the body's immune response. When TLR systems are activated, pro-inflammatory cy

At the end of 2019, a new form of Coronavirus (later dubbed COVID-19) emerged in China and quickly spread to other regions of the globe. Despite the virus’s unique and unknown characteristics, it is a widely distributed infectious illness. Finding the geographical distribution of the virus transmission is therefore critical for epidemiologists and governments in order to respond to the illness epidemic rapidly and effectively. Understanding the dynamics of COVID-19’s spatial distribution can help to understand the pandemic’s scope and effects, as well as decision-making, planning, and community action aimed at preventing transmission. The main focus of this study is to investigate the geographic patterns of COVID-19 disseminat

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV 2) or 2019 novel coronavirus (2019-nCoV) is quickly spreading to the rest of the world, from its origin in Wuhan, Hubei Province, China. And becoming a global pandemic that affects the world's most powerful countries. The goal of this review is to assist scientists, researchers, and others in responding to the current Coronavirus disease (covid-19) is a worldwide public health contingency state. This review discusses current evidence based on recently published studies which is related to the origin of the virus, epidemiology, transmission, diagnosis, treatment, and all studies in Iraq for the effect of covid-19 diseases, as well as provide a reference for future research

Background: the coronavirus leads to upper respiratory tract-associated manifestations like nasal congestion, sore throat, and smell disorder

Objectives: To reveal the impact of COVID-19 pandemic on otolaryngology symptoms using our daily medical practice.

Subject and Methods: A cross-sectional study that was carried on in the isolation wards at Al-Kindy and Al-Nu’man Teaching Hospitals during three months from the 1st of Jun. till the end of Aug. 2020. It included 1270 patients who were diagnosed with COVID-19 infection seen in the ENT consultation clinic and admitted to the isolation wards.

Results: Otolaryngological manifestations were shown

Since its discovery in December 2019, corona virus was outbreak worldwide with very rapid rate, so it described by WHO as pandemic. It associated with severe acute respiratory distress syndrome, and can enter to cells through Angiotensin Converting Enzyme 2 (ACE 2) receptor which play an important role as regulator for blood pressure. Hypertension is a potential risk factor for sever acute respiratory syndrome COVID-19, and associated with high mortality rate as shown in many epidemiological studies. Moreover, specific antihypertensive medications that infected patients were receiving are not known; only data about renin-angiotensin-aldosterone system (RAAS) are available.  

Background:SARS-CoV-2 infection has caused a global pandemic that continues to negatively impact human health. A large group of microbial domains including bacteria co-evolved and interacted in complex molecular pathogenesis along with SARS-CoV-2. Evidence suggests that periodontal disease bacteria are involved in COVID-19, and are associated with chronic inflammatory systemic diseases. This study was performed to investigate the association between bacterial loads of Porphyromonas gingivalis and pathogenesis of SARS-CoV-2 infection. Fifty patients with confirmed COVID-19 by reverse transcriptase-polymerase chain reaction, their age ranges between 20-76 years, and 35 healthy volunteers (matched accordingly with age and sex to th

              Automated clinical decision support system (CDSS) acts as new paradigm in medical services today. CDSSs are utilized to increment specialists (doctors) in their perplexing decision-making. Along these lines, a reasonable decision support system is built up dependent on doctors' knowledge and data mining derivation framework so as to help with the interest the board in the medical care gracefully to control the Corona Virus Disease (COVID-19) virus pandemic and, generally, to determine the class of infection and to provide a suitable protocol treatment depending on the symptoms of patient. Firstly, it needs to determine the three early symptoms of COVID-19 pandemic criteria (fever, tiredness, dry cough and breat