No credible evidence supporting claims of the laboratory engineering of SARS-CoV-2

Discovery of a novel merbecovirus DNA clone contaminating agricultural rice sequencing datasets from Wuhan, China

HKU4-related coronaviruses are a group of betacoronaviruses belonging to the same merbecovirus subgenus as Middle Eastern Respiratory Syndrome coronavirus (MERS-CoV), which causes severe respiratory illness in humans with a mortality rate of over 30%. The high genetic similarity between HKU4-related coronaviruses and MERS-CoV makes them an attractive subject of research for modeling potential zoonotic spillover scenarios. In this study, we identify a novel coronavirus contaminating agricultural rice RNA sequencing datasets from Wuhan, China. The datasets were generated by the Huazhong Agricultural University in early 2020. We were able to assemble the complete viral genome sequence, which revealed that it is a novel HKU4-related merbecovirus. The assembled genome is 98.38% identical to the closest known full genome sequence, Tylonycteris pachypus bat isolate BtTp-GX2012. Using in silico modeling, we identified that the novel HKU4-related coronavirus spike protein likely binds to human dipeptidyl peptidase 4 (DPP4), the receptor used by MERS-CoV. We further identified that the novel HKU4-related coronavirus genome has been inserted into a bacterial artificial chromosome in a format consistent with previously published coronavirus infectious clones. Additionally, we have found a near complete read coverage of the spike gene of the MERS-CoV reference strain HCoV-EMC/2012, and identify the likely presence of a HKU4-related-MERS chimera in the datasets. Our findings contribute to the knowledge of HKU4-related coronaviruses and document the use of a previously unpublished HKU4 reverse genetics system in apparent MERS-CoV related gain-of-function research. Our study also emphasizes the importance of improved biosafety protocols in sequencing centers and coronavirus research facilities.

ChatGPT Output Regarding Compulsory Vaccination and COVID-19 Vaccine Conspiracy: A Descriptive Study at the Outset of a Paradigm Shift in Online Search for Information

BACKGROUND

Being on the verge of a revolutionary approach to gathering information, ChatGPT (an artificial intelligence (AI)-based language model developed by OpenAI, and capable of producing human-like text) could be the prime motive of a paradigm shift on how humans will acquire information. Despite the concerns related to the use of such a promising tool in relation to the future of the quality of education, this technology will soon be incorporated into web search engines mandating the need to evaluate the output of such a tool. Previous studies showed that dependence on some sources of online information (e.g., social media platforms) was associated with higher rates of vaccination hesitancy. Therefore, the aim of the current study was to describe the output of ChatGPT regarding coronavirus disease 2019 (COVID-19) vaccine conspiracy beliefs. and compulsory vaccination.

METHODS

The current descriptive study was conducted on January 14, 2023 using the ChatGPT from OpenAI (OpenAI, L.L.C., San Francisco, CA, USA). The output was evaluated by two authors and the degree of agreement regarding the correctness, clarity, conciseness, and bias was evaluated using Cohen's kappa.

RESULTS

The ChatGPT responses were dismissive of conspiratorial ideas about severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) origins labeling it as non-credible and lacking scientific evidence. Additionally, ChatGPT responses were totally against COVID-19 vaccine conspiracy statements. Regarding compulsory vaccination, ChatGPT responses were neutral citing the following as advantages of this strategy: protecting public health, maintaining herd immunity, reducing the spread of disease, cost-effectiveness, and legal obligation, and on the other hand, it cited the following as disadvantages of compulsory vaccination: ethical and legal concerns, mistrust and resistance, logistical challenges, and limited resources and knowledge.

CONCLUSIONS

The current study showed that ChatGPT could be a source of information to challenge COVID-19 vaccine conspiracies. For compulsory vaccination, ChatGPT resonated with the divided opinion in the scientific community toward such a strategy; nevertheless, it detailed the pros and cons of this approach. As it currently stands, the judicious use of ChatGPT could be utilized as a user-friendly source of COVID-19 vaccine information that could challenge conspiracy ideas with clear, concise, and non-biased content. However, ChatGPT content cannot be used as an alternative to the original reliable sources of vaccine information (e.g., the World Health Organization [WHO] and the Centers for Disease Control and Prevention [CDC]).

COVID-19 detection using X-ray images and statistical measurements

The COVID-19 pandemic spread all over the world, starting in China in late 2019, and significantly affected life in all aspects. As seen in SARS, MERS, COVID-19 outbreaks, coronaviruses pose a great threat to world health. The COVID-19 epidemic, which caused pandemics all over the world, continues to seriously threaten people's lives. Due to the rapid spread of COVID-19, many countries' healthcare sectors were caught off guard. This situation put a burden on doctors and healthcare professionals that they could not handle. All of the studies on COVID-19 in the literature have been done to help experts to recognize COVID-19 more accurately, to use more accurate diagnosis and appropriate treatment methods. The alleviation of this workload will be possible by developing computer aided early and accurate diagnosis systems with machine learning. Diagnosis and evaluation of pneumonia on computed tomography images provide significant benefits in investigating possible complications and in case follow-up. Pneumonia and lesions occurring in the lungs should be carefully examined as it helps in the diagnostic process during the pandemic period. For this reason, the first diagnosis and medications are very important to prevent the disease from progressing. In this study, a dataset consisting of Pneumonia and Normal images was used by proposing a new image preprocessing process. These preprocessed images were reduced to 15x15 unit size and their features were extracted according to their RGB values. Experimental studies were carried out by performing both normal values and feature reduction among these features. RGB values of the images were used in train and test processes for MLAs. In experimental studies, 5 different Machine Learning Algorithms (MLAs) (Multi Class Support Vector Machine (MC-SVM), k Nearest Neighbor (k-NN), Decision Tree (DT), Multinominal Logistic Regression (MLR), Naive Bayes (NB)). The following accuracy rates were obtained in train operations for MLAs, respectively; 1, 1, 1, 0.746377, 0.963768. Accuracy results in test operations were obtained as follows; 0.87755, 0.857143, 0.857143, 0.877551, 0.938776.

A novel method using Covid-19 dataset and machine learning algorithms FOR THE MOST ACCURATE DIAGNOSIS that can be obtained in medical diagnosis

Pandemics and many other diseases threaten human life, health and quality of life by affecting many aspects. For this reason, the medical diagnosis to be applied for any disease is important in terms of the most accurate determination by the doctors and the appropriate treatment for the determined diagnosis. The COVID-19 pandemic that started in China in December 2019 spread all over the world in a short time. Researchers have begun to do different studies to make the most accurate diagnosis of COVID-19. Due to the rapid spread of COVID-19, doctors in the health sector of many countries were also caught off guard. Machine Learning Algorithms (MLAs) are of great importance in the development of computer-aided early and accurate diagnosis systems in today's medical field, as they greatly assist doctors in the medical diagnosis process. In this study, a method was proposed for the most accurate diagnosis of COVID-19 patients using the COVID-19 image data. Images were first standardized and features extracted using RGB values of 800x800 images, and these features were used in train and test processes for MLAs. 5 different MLAs were used in experimental studies using statistical measurements (k Nearest Neighbor (k-NN), Decision Tree (DT), Multinominal Logistic Regression (MLR), Naive Bayes (NB) and Support Vector Machine (SVM)). A method was proposed that automatically finds the highest classification success that these algorithms can achieve. In experimental studies, the following accuracy rates were obtained in train operations for MLAs, respectively; 1, 1, 1, 0.69565, 0.92753. Accuracy results in test operations were obtained as follows; 0.85714, 0.79591, 0.91836, 0.61224, 0.89795. After the application of the proposed method, the test success rate for MLR increased from 0.91 to 0.98. As a result of applying the proposed algorithm, more accurate results were obtained. The results obtained were given in the experimental studies section in detail. The results obtained proved to be very promising. According to the results, it was seen that the proposed method could be used effectively in future studies.

SARS-CoV-2 and the Missing Link of Intermediate Hosts in Viral Emergence - What We Can Learn From Other Betacoronaviruses

The emergence of SARS-CoV-2 in 2019 has resulted in a global pandemic with devastating human health and economic consequences. The development of multiple vaccines, antivirals and supportive care modalities have aided in our efforts to gain control of the pandemic. However, the emergence of multiple variants of concern and spillover into numerous nonhuman animal species could protract the pandemic. Further, these events also increase the difficulty in simultaneously monitoring viral evolution across multiple species and predicting future spillback potential into the human population. Here, we provide historic context regarding the roles of reservoir and intermediate hosts in coronavirus circulation and discuss current knowledge of these for SARS-CoV-2. Increased understanding of SARS-CoV-2 zoonoses are fundamental for efforts to control the global health and economic impacts of COVID-19.

COVID-19: A systematic review and update on prevention, diagnosis, and treatment

Since the rapid onset of the COVID-19 or SARS-CoV-2 pandemic in the world in 2019, extensive studies have been conducted to unveil the behavior and emission pattern of the virus in order to determine the best ways to diagnosis of virus and thereof formulate effective drugs or vaccines to combat the disease. The emergence of novel diagnostic and therapeutic techniques considering the multiplicity of reports from one side and contradictions in assessments from the other side necessitates instantaneous updates on the progress of clinical investigations. There is also growing public anxiety from time to time mutation of COVID-19, as reflected in considerable mortality and transmission, respectively, from delta and Omicron variants. We comprehensively review and summarize different aspects of prevention, diagnosis, and treatment of COVID-19. First, biological characteristics of COVID-19 were explained from diagnosis standpoint. Thereafter, the preclinical animal models of COVID-19 were discussed to frame the symptoms and clinical effects of COVID-19 from patient to patient with treatment strategies and in-silico/computational biology. Finally, the opportunities and challenges of nanoscience/nanotechnology in identification, diagnosis, and treatment of COVID-19 were discussed. This review covers almost all SARS-CoV-2-related topics extensively to deepen the understanding of the latest achievements (last updated on January 11, 2022).

Efficacy of mRNA, adenoviral vector, and perfusion protein COVID-19 vaccines

Coronavirus disease 2019 (COVID-19) has a devastating impact on global populations triggered by a highly infectious viral sickness, produced by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The third major cause of mortality in the United States, following heart disease and cancer in 2020, was undoubtedly COVID-19. The centers for disease control and prevention (CDC) and the world health organization (WHO) separately developed a categorization system for differentiating new strains of SARS-CoV-2 into variants of concern (VoCs) and variants of interest (VoIs) with the continuing development of various strains SARS-CoV-2. By December 2021, five of the SARS-CoV-2 VoCs were discovered from the onset of the pandemic depending on the latest epidemiologic report by the WHO: Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), Delta (B.1.617.2), and Omicron (B.1.1.529). Mutations in the receptor-binding domain (RBD) and n-terminal domain (NTD) have been found throughout all five identified VoCs. All strains other than the delta mutant are often found with the N501Y mutation situated on the RBD, resulting in higher binding between the spike protein and angiotensin-converting enzyme 2 (ACE2) receptors, enhanced viral adhesion, and following the entrance to host cells. The introduction of these new strains of SRAS-CoV-2 is likely to overcome the remarkable achievements gained in restricting this viral disease to the point where it is presented with remarkable vaccine developments against COVID-19 and strong worldwide mass immunization initiatives. Throughout this literature review, the effectiveness of current COVID-19 vaccines for managing and prohibiting SARS-CoV-2 strains is thoroughly described.

Jumping a Moving Train: SARS-CoV-2 Evolution in Real Time

The field of molecular epidemiology responded to the SARS-CoV-2 pandemic with an unrivaled amount of whole viral genome sequencing. By the time this sentence is published we will have well surpassed 1.5 million whole genomes, more than 4 times the number of all microbial whole genomes deposited in GenBank and 35 times the total number of viral genomes. This extraordinary dataset that accrued in near real time has also given us an opportunity to chart the global and local evolution of a virus as it moves through the world population. The data itself presents challenges that have never been dealt with in molecular epidemiology, and tracking a virus that is changing so rapidly means that we are often running to catch up. Here we review what is known about the evolution of the virus, and the critical impact that whole genomes have had on our ability to trace back and track forward the spread of lineages of SARS-CoV-2. We then review what whole genomes have told us about basic biological properties of the virus such as transmissibility, virulence, and immune escape with a special emphasis on pediatric disease. We couch this discussion within the framework of systematic biology and phylogenetics, disciplines that have proven their worth again and again for identifying and deciphering the spread of epidemics, though they were largely developed in areas far removed from infectious disease and medicine.

Fundamentals of genomic epidemiology, lessons learned from the coronavirus disease 2019 (COVID-19) pandemic, and new directions

The coronavirus disease 2019 (COVID-19) pandemic was one of the significant causes of death worldwide in 2020. The disease is caused by severe acute coronavirus syndrome (SARS) coronavirus 2 (SARS-CoV-2), an RNA virus of the subfamily Orthocoronavirinae related to 2 other clinically relevant coronaviruses, SARS-CoV and MERS-CoV. Like other coronaviruses and several other viruses, SARS-CoV-2 originated in bats. However, unlike other coronaviruses, SARS-CoV-2 resulted in a devastating pandemic. The SARS-CoV-2 pandemic rages on due to viral evolution that leads to more transmissible and immune evasive variants. Technology such as genomic sequencing has driven the shift from syndromic to molecular epidemiology and promises better understanding of variants. The COVID-19 pandemic has exposed critical impediments that must be addressed to develop the science of pandemics. Much of the progress is being applied in the developed world. However, barriers to the use of molecular epidemiology in low- and middle-income countries (LMICs) remain, including lack of logistics for equipment and reagents and lack of training in analysis. We review the molecular epidemiology literature to understand its origins from the SARS epidemic (2002-2003) through influenza events and the current COVID-19 pandemic. We advocate for improved genomic surveillance of SARS-CoV and understanding the pathogen diversity in potential zoonotic hosts. This work will require training in phylogenetic and high-performance computing to improve analyses of the origin and spread of pathogens. The overarching goals are to understand and abate zoonosis risk through interdisciplinary collaboration and lowering logistical barriers.

Host-specific asymmetric accumulation of mutation types reveals that the origin of SARS-CoV-2 is consistent with a natural process

The capacity of RNA viruses to adapt to new hosts and rapidly escape the host immune system is largely attributable to de novo genetic diversity that emerges through mutations in RNA. Although the molecular spectrum of de novo mutations-the relative rates at which various base substitutions occur-are widely recognized as informative toward understanding the evolution of a viral genome, little attention has been paid to the possibility of using molecular spectra to infer the host origins of a virus. Here, we characterize the molecular spectrum of de novo mutations for SARS-CoV-2 from transcriptomic data obtained from virus-infected cell lines, enabled by the use of sporadic junctions formed during discontinuous transcription as molecular barcodes. We find that de novo mutations are generated in a replication-independent manner, typically on the genomic strand, and highly dependent on mutagenic mechanisms specific to the host cellular environment. De novo mutations will then strongly influence the types of base substitutions accumulated during SARS-CoV-2 evolution, in an asymmetric manner favoring specific mutation types. Consequently, similarities between the mutation spectra of SARS-CoV-2 and the bat coronavirus RaTG13, which have accumulated since their divergence strongly suggest that SARS-CoV-2 evolved in a host cellular environment highly similar to that of bats before its zoonotic transfer into humans. Collectively, our findings provide data-driven support for the natural origin of SARS-CoV-2.

SARS-CoV-2, Covid-19, and the debunking of conspiracy theories

The emergence of a novel human coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has engaged considerable awareness and attention around the world. The associated disease, coronavirus disease 2019 (Covid-19), has now involved virtually all 200 countries. The total number of confirmed cases has been much more than in the two previous outbreaks of human coronaviruses, that is, SARS-CoV and Middle East respiratory syndrome coronavirus. In line with the outbreak escalation, false information about SARS-CoV-2 and its associated disease disseminated globally, particularly through online and social media. Believers in conspiracy theories promote misinformation that the virus is not contagious, is the result of laboratory manipulation or is created to gain profit by distributing new vaccines. The most dangerous effect of this widely disseminated misinformation is it will negatively influence the attitudes and behaviours for preventive measures to contain the outbreak. In this review, I discuss common conspiracy theories associated with SARS-CoV-2 and Covid-19 and consider how we can address and counterbalance these issues based on scientific information and studies.

Studying SARS-CoV-2 infectivity and therapeutic responses with complex organoids

Clinical management of patients with severe complications of COVID-19 has been hindered by a lack of effective drugs and a failure to capture the extensive heterogeneity of the disease with conventional methods. Here we review the emerging roles of complex organoids in the study of SARS-CoV-2 infection, modelling of COVID-19 disease pathology and in drug, antibody and vaccine development. We discuss opportunities for COVID-19 research and remaining challenges in the application of organoids.

Advances in Synthetic Biology and Biosafety Governance

Tremendous advances in the field of synthetic biology have been witnessed in multiple areas including life sciences, industrial development, and environmental bio-remediation. However, due to the limitations of human understanding in the code of life, any possible intended or unintended uses of synthetic biology, and other unknown reasons, the development and application of this technology has raised concerns over biosafety, biosecurity, and even cyberbiosecurity that they may expose public health and the environment to unknown hazards. Over the past decades, some countries in Europe, America, and Asia have enacted laws and regulations to control the application of synthetic biology techniques in basic and applied research and this has resulted in some benefits. The outbreak of the COVID-19 caused by novel coronavirus SARS-CoV-2 and various speculations about the origin of this virus have attracted more attention on bio-risk concerns of synthetic biology because of its potential power and uncertainty in the synthesis and engineering of living organisms. Therefore, it is crucial to scrutinize the control measures put in place to ensure appropriate use, promote the development of synthetic biology, and strengthen the governance of pathogen-related research, although the true origin of coronavirus remains hotly debated and unresolved. This article reviews the recent progress made in the field of synthetic biology and combs laws and regulations in governing bio-risk issues. We emphasize the urgent need for legislative and regulatory constraints and oversight to address the biological risks of synthetic biology.

Understanding the origin of COVID-19 requires to change the paradigm on zoonotic emergence from the spillover to the circulation model

While the COVID-19 pandemic continues to spread with currently more than 117 million cumulated cases and 2.6 million deaths worldwide as per March 2021, its origin is still debated. Although several hypotheses have been proposed, there is still no clear explanation about how its causative agent, SARS-CoV-2, emerged in human populations. Today, scientifically-valid facts that deserve to be debated still coexist with unverified statements blurring thus the knowledge on the origin of COVID-19. Our retrospective analysis of scientific data supports the hypothesis that SARS-CoV-2 is indeed a naturally occurring virus. However, the spillover model considered today as the main explanation to zoonotic emergence does not match the virus dynamics and somehow misguided the way researches were conducted. We conclude this review by proposing a change of paradigm and model and introduce the circulation model for explaining the various aspects of the dynamic of SARS-CoV-2 emergence in humans.

A comprehensive review on potential therapeutics interventions for COVID-19

COVID-19 is an infectious respiratory disease caused by SARS-CoV-2, a new beta coronavirus that emerged in Wuhan, China. Being primarily a respiratory disease, it is highly transmissible through both direct and indirect contacts. It displays a range of symptoms in different individuals and thus has been grouped into mild, moderate, and severe diseases. The virus utilizes spike proteins present on its surface to recognize ACE-2 receptors present on the host cells to enter the cell cytoplasm and replicate. The viral invasion of cells induces damage response, pyroptosis, infiltration of immune cells, expression of pro-inflammatory cytokines (cytokine storm), and activation of the adaptive immune system. Depending on viral load and host factors like age and underlying medical conditions, the immune responses mounted against SARS-CoV-2 may cause acute respiratory distress syndrome (ARDS), multiple organ failure, and death. In this review, we specify and justify both viral and host therapeutic targets that can be modulated to relieve the symptoms and treat the disease. Furthermore, we discuss vaccine development in the time of pandemic and the most promising vaccine candidates by far, according to WHO database. Finally, we discuss the conventional re-purposed drugs and potential alternative treatments as adjuvants.

A comprehensive review on potential therapeutics interventions for COVID-19

COVID-19 is an infectious respiratory disease caused by SARS-CoV-2, a new beta coronavirus that emerged in Wuhan, China. Being primarily a respiratory disease, it is highly transmissible through both direct and indirect contacts. It displays a range of symptoms in different individuals and thus has been grouped into mild, moderate, and severe diseases. The virus utilizes spike proteins present on its surface to recognize ACE-2 receptors present on the host cells to enter the cell cytoplasm and replicate. The viral invasion of cells induces damage response, pyroptosis, infiltration of immune cells, expression of pro-inflammatory cytokines (cytokine storm), and activation of the adaptive immune system. Depending on viral load and host factors like age and underlying medical conditions, the immune responses mounted against SARS-CoV-2 may cause acute respiratory distress syndrome (ARDS), multiple organ failure, and death. In this review, we specify and justify both viral and host therapeutic targets that can be modulated to relieve the symptoms and treat the disease. Furthermore, we discuss vaccine development in the time of pandemic and the most promising vaccine candidates by far, according to WHO database. Finally, we discuss the conventional re-purposed drugs and potential alternative treatments as adjuvants.

SARS-CoV-2 will continue to circulate in the human population: an opinion from the point of view of the virus-host relationship

At the population level, the virus-host relationship is not set up to end with the complete elimination of either or both. Pathogen-resistant individuals will always remain in the host population. In turn, the virus can never completely eliminate the host population, because evolutionarily such an event is a dead end for the virus as an obligate intracellular parasite. A certain existential balance exists in the virus-host relationship. Against this backdrop, viral epidemics and pandemics only become manifest and egregious to human beings when tens and hundreds of thousands of people die and the question emerges what caused the high mortality peaks on the death chart. The answer seems clear; the emerging strain of the virus is new to the host population, and new mutations of the virus and natural selection will lead to a survival of only genetically resistant individuals in a host population. The dangers inherent to a novel virus are due to new features generally inthe molecular structure of proteins, which enable the virus to infect the cells of the host organism more intensively, dramatically challenging host immunity, and thus be transmitted more readily in the host population. In this article, we will concentrate on the facts currently available about severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which has caused COVID-19 (coronavirus disease 2019) pandemic and try to predict its development and consequences based on the virus-host relationship. In fact, only two scenarios will occur simultaneously in the very near future: people who are genetically resistant to the virus will get sick, recover, and develop immunity, while people who are sensitive to the virus will need drugs and vaccines, which will have to be researched and developed if they are to recover. If the pandemic does not stop, in a few decades it is anticipated that SARS-CoV-2 will become as safe as the four non-severe acute respiratory syndrome human coronaviruses (HCoV-NL63, HCoV-HKU1, HCoV-OC43, and HCoV-229E) currently circulating but causing low mortality in the human population.

Do COVID-19 and SARS Gene Complexities and Variations Help Overcome the Knowledge Gap?

A whole new pathogen, to which humans have virtually no pre-existing immunity, has caused fear all over the world. Severe acute respiratory syndrome coronavirus (SARS CoV-2) is one of the types of human novel-coronavirus of the family coronavirus. The nature of transmission of the virus makes it one of the most infectious pathogenic diseases that has ever existed. Though the human coronaviruses have existed since the discovery of the human coronavirus 229E (HCoV-229E) and human coronavirus OC43 (HCoV-OC43) in 1960, it has been a challenge to develop an effective cure as well as vaccine for the diseases associated with coronaviruses. Commonly, human coronaviruses cause illnesses such as intestinal and respiratory tract illnesses. Nevertheless, the symptoms reflected after infection from the coronaviruses take some time before being identified. Thus, viruses can replicate and cause more harm to the human body before being detected. Moreover, research continues to explain why some gene variations in some individuals increase the risk of some infectious diseases, while others are not affected. Looking at gene variations in people infected with Coronavirus Disease 2019 (COVID-19) and studying how genes influence people's response to infection will help to develop a vaccine that will help strengthen the immune system. Knowing how the human genes respond to the virus COVID-19 will help to cure people more effectively.

Zoonotic origins of human coronavirus 2019 (HCoV-19 / SARS-CoV-2): why is this work important?

The ongoing pandemic of coronavirus disease 2019 (COVID-19), caused by infection with human coronavirus 2019 (HCoV-19 / SARS-CoV-2 / 2019-nCoV), is a global threat to the human population. Here, we briefly summarize the available data for the zoonotic origins of HCoV-19, with reference to the other two epidemics of highly virulent coronaviruses, SARS-CoV and MERS-CoV, which cause severe pneumonia in humans. We propose to intensify future efforts for tracing the origins of HCoV-19, which is a very important scientific question for the control and prevention of the pandemic.

The COVID-19 Pandemic: A Comprehensive Review of Taxonomy, Genetics, Epidemiology, Diagnosis, Treatment, and Control

A pneumonia outbreak with unknown etiology was reported in Wuhan, Hubei province, China, in December 2019, associated with the Huanan Seafood Wholesale Market. The causative agent of the outbreak was identified by the WHO as the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), producing the disease named coronavirus disease-2019 (COVID-19). The virus is closely related (96.3%) to bat coronavirus RaTG13, based on phylogenetic analysis. Human-to-human transmission has been confirmed even from asymptomatic carriers. The virus has spread to at least 200 countries, and more than 1,700,000 confirmed cases and 111,600 deaths have been recorded, with massive global increases in the number of cases daily. Therefore, the WHO has declared COVID-19 a pandemic. The disease is characterized by fever, dry cough, and chest pain with pneumonia in severe cases. In the beginning, the world public health authorities tried to eradicate the disease in China through quarantine but are now transitioning to prevention strategies worldwide to delay its spread. To date, there are no available vaccines or specific therapeutic drugs to treat the virus. There are many knowledge gaps about the newly emerged SARS-CoV-2, leading to misinformation. Therefore, in this review, we provide recent information about the COVID-19 pandemic. This review also provides insights for the control of pathogenic infections in humans such as SARS-CoV-2 infection and future spillovers.