Causal associations between type 1 diabetes and COVID-19 infection and prognosis: a two-sample Mendelian randomization study.

INTRODUCTION: It has been suggested that type 1 diabetes was associated with increased COVID-19 morbidity and mortality. However, their causal relationship is still unclear. Herein, we performed a two-sample Mendelian randomization (MR) to investigate the causal effect of type 1 diabetes on COVID-19 infection and prognosis. RESEARCH DESIGN AND METHODS: The summary statistics of type 1 diabetes were obtained from two published genome-wide association studies of European population, one as a discovery sample including 15 573 cases and 158 408 controls, and the other data as a replication sample consisting of 5913 cases and 8828 controls. We first performed a two-sample MR analysis to evaluate the causal effect of type 1 diabetes on COVID-19 infection and prognosis. Then, reverse MR analysis was conducted to determine whether reverse causality exists. RESULTS: MR analysis results showed that the genetically predicted type 1 diabetes was associated with higher risk of severe COVID-19 (OR=1.073, 95% CI: 1.034 to 1.114, pFDR=1.15×10-3) and COVID-19 death (OR=1.075, 95% CI: 1.033 to 1.119, pFDR=1.15×10-3). Analysis of replication dataset showed similar results, namely a positive association between type 1 diabetes and severe COVID-19 (OR=1.055, 95% CI: 1.029 to 1.081, pFDR=1.59×10-4), and a positively correlated association with COVID-19 death (OR=1.053, 95% CI: 1.026 to 1.081, pFDR=3.50×10-4). No causal association was observed between type 1 diabetes and COVID-19 positive, hospitalized COVID-19, the time to the end of COVID-19 symptoms in the colchicine treatment group and placebo treatment group. Reverse MR analysis showed no reverse causality. CONCLUSIONS: Type 1 diabetes had a causal effect on severe COVID-19 and death after COVID-19 infection. Further mechanistic studies are needed to explore the relationship between type 1 diabetes and COVID-19 infection and prognosis.

Network analysis between neuron dysfunction and neuroimmune response based on neural single-cell transcriptome of COVID-19 patients

Despite global vaccination efforts, COVID-19 breakthrough infections caused by variant virus continue to occur frequently, long-term sequelae of COVID-19 infection like neuronal dysfunction emerge as a noteworthy issue. Neuroimmune disorder induced by Inflammatory factor storm was considered as a possible reason, however, little was known about the functional factors affecting neuroimmune response to this virus. Here, using medial prefrontal cortex single cell data of COVID-19 patients, expression pattern analysis indicated that some immune-related pathway genes expressed specifically, including genes associated with T cell receptor, TNF signaling in microglia and Cytokine-cytokine receptor interaction and HIF-1 signaling pathway genes in astrocytes. Besides the well-known immune-related cell type microglia, we also observed immune-related factors like IL17D, TNFRSF1A and TLR4 expressed in Astrocytes. Based on the ligand-receptor relationship of immune-related factors, crosstalk landscape among cell clusters were analyzed. The findings indicated that astrocytes collaborated with microglia and affect excitatory neurons, participating in the process of immune response and neuronal dysfunction. Moreover, subset of astrocytes specific immune factors (hinged neuroimmune genes) were proved to correlate with Covid-19 infection and ventilator-associated pneumonia using multi-tissue RNA-seq and scRNA-seq data. Function characterization clarified that hinged neuroimmune genes were involved in activation of inflammation and hypoxia signaling pathways, which could lead to hyper-responses related neurological sequelae. Finally, a risk model was constructed and testified in RNA-seq and scRNA data of peripheral blood.

Factors Affecting University Students' Sleep Quality during the Normalisation of COVID-19 Epidemic Prevention and Control in China: A Cross-Sectional Study

Background: Insufficient and poor-quality sleep have significant negative health consequences for university students in China. In this study, we aimed to assess the subjective sleep quality of university students during the normalisation of COVID-19 epidemic prevention and control in China and to identify key factors affecting their sleep quality. Materials and Methods: A cross-sectional survey was conducted among 1326 university students from Hubei Province, China. Latent profile analysis was conducted on the results of class-difference tests of sleep patterns. Multinomial logistic regression was used to explore the relationship between the influencing factors and three classes of sleep quality. Results: The overall score of sleep quality (9.18 ±3.22) among university students was assessed by using the PSQI scale, and 427 (32.20%) students reported poor sleep quality. Three distinct classes of sleep patterns were identified, namely, good sleepers (Class 1, 70.44%), poor sleep quality with less medication use (Class 2, 26.55%) and poor sleepers (Class 3, 3.01%). Conclusions: Compared with 'good sleepers', students having 'poor sleep quality with less hypnotic drug use' were influenced by their education stage, smoking habits, physical activity, depression and anxiety. Meanwhile, 'poor sleepers' may be affected by their age, origins, smoking habits, mental stress, depression and anxiety. Significant heterogeneity was confirmed in the sleep patterns of university students. Their behavioural lifestyles and mental health-related factors demonstrated different relationship patterns with sleep quality. Multiple sleep promotion interventions, including moderate aerobic exercises, psychological counselling and mindfulness training, should be regularly performed in groups to improve their sleep quality.

Genetic screening for hypertension and COVID-19 reveals functional variant of SPEG associated with severe COVID-19 in female (preprint)

The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused more than 6.4 million deaths worldwide and is still spreading among global populations. The prevalent comorbidity between hypertension and severe COVID-19 suggests common genetic factors may affect the outcome of both diseases. As both hypertension and severe COVID-19 demonstrate sex-specific prevalence, common genetic factors among the two diseases may display gender-based differential associations. By evaluating COVID-19 association signals of 172-candidate hypertension single nucleotide polymorphisms derived from more than one million European individuals in two severe COVID-19 genome-wide association studies from UK BioBank with European ancestry, we revealed one functional cis expression quantitative trait locus of SPEG (rs12474050) associating with both hypertension and severe COVID-19 in female. The risk allele of rs12474050*T is correlated with lower SPEG expression in muscle-skeletal, heart-atrial appendage, and heart-left ventricle; among these tissues the SPEG expression is higher in female than in male COVID-19 patients. Further analysis revealed SPEG is mainly expressed in cardiomyocytes in heart and is upregulated upon SARS-CoV-2 infection, with significantly higher folder change of SPEG expression observed in female compared to male COVID-19 patients. Taken together, our analyses strongly suggest the involvement of SPEG in both hypertension and severe COVID-19 in female, which provides new insights for sex-specific effect of severe COVID-19 in female.

Guidelines for COVID-19 Laboratory Testing for Emergency Departments From the New Diagnostic Technology Team of the Taiwan Society of Emergency Medicine

COVID-19 tests have different turnaround times (TATs), accuracy levels, and limitations, which emergency physicians should be aware of. Nucleic acid amplification tests (NAATs) can be divided into standard high throughput tests and rapid molecular diagnostic tests at the point of care (POC). The standard NAAT has the advantages of high throughput and high accuracy with a TAT of 3–4 hours. The POC molecular test has the same advantages of high accuracy as standard high throughput PCR, but can be done in 13–45 minutes. Roche cobas Liat is the most commonly used machine in Taiwan, displaying 99%–100% sensitivity and 100% specificity, respectively. Abbott ID NOW is an isothermal PCR-based POC machine with a sensitivity of 79% and a specificity of 100%. A high rate of false positives and false negatives is associated with rapid antigen testing. Antibody testing is mostly used as part of public health surveys and for testing for immunity.

The Balanced Allocation of Medical and Health Resources in Urban Areas of China from the Perspective of Sustainable Development: A Case Study of Nanjing

The balanced allocation of medical and health resources is an important basis for the sustainable development of health undertakings. In recent years, China has made remarkable achievements in the medical and health services, but there is still a phenomenon of unbalanced allocation of medical and health resources among different regions, which has become an urgent problem to be solved in deepening the reform of the medical and health system during the 14th Five-Year Plan period. From the perspective of people’s needs for health, this study analyzed the equity and efficiency of urban medical and health resources allocation in China by using the Theil index method and DEA method. Meanwhile, the authors used the coupling coordination degree model to construct a balanced development model with equity and efficiency as subsystems, taking the city of Nanjing as an example to analyze its balanced allocation of medical and health resources from 2008 to 2019. In general, taking Nanjing as an example, it shows that the balanced allocation of medical and health resources in Chinese cities is good, but in geographical dimension, the level of balanced allocation is low, and there are still significant differences in the equity and efficiency of allocation among regions. In the future, the government can strengthen the rationality of regional planning, appropriately increasing health investment and medical supply, considering both equity and efficiency to further realize the balanced allocation of medical and health resources and improve the sustainability of urban medical service system. The main contribution of this paper lies in that, from the perspective of sustainable development, the evaluation system is integrated to measure the equity and efficiency respectively, and the balanced development model is used to investigate the allocation of urban medical and health resources. The research results can provide reference for optimizing resources allocation and promoting the sustainable development of medical and health undertakings.

Empirical Study of Virtual Reality to Promote Intergenerational Communication: Taiwan Traditional Glove Puppetry as Example

Based on glove puppetry, a traditional cultural pursuit of Taiwan, this study designed a virtual reality (VR) intergenerational game to bring together the elderly and young participants. In the game, a system of cooperation and sharing was constructed which would lead to an exchange between experience and knowledge of traditional culture and digital technology and result in intergenerational interaction and communication learning. Through interviews with eight subjects after the empirical study, this study explored the operation and experience of this game, the perception of interaction and dialogue, and the cultural heritage and learning. According to the research findings, VR game cultural elements and technology learning positively influence intergenerational relations and communication. Key factors of VR intergenerational games include the following: (1) the game content must be attractive for the elderly;(2) the operating procedure of the game and affordance of the interface for the elderly must be simplified;and (3) the game must establish a sense of achievement for players.

A Blockchain-Based Federated Learning Method for Smart Healthcare.

The development of artificial intelligence and worldwide epidemic events has promoted the implementation of smart healthcare while bringing issues of data privacy, malicious attack, and service quality. The Medical Internet of Things (MIoT), along with the technologies of federated learning and blockchain, has become a feasible solution for these issues. In this paper, we present a blockchain-based federated learning method for smart healthcare in which the edge nodes maintain the blockchain to resist a single point of failure and MIoT devices implement the federated learning to make full of the distributed clinical data. In particular, we design an adaptive differential privacy algorithm to protect data privacy and gradient verification-based consensus protocol to detect poisoning attacks. We compare our method with two similar methods on a real-world diabetes dataset. Promising experimental results show that our method can achieve high model accuracy in acceptable running time while also showing good performance in reducing the privacy budget consumption and resisting poisoning attacks.

SARS-COV-2 INFECTION IN PRIMARY CARE: A SINGLE-CENTERED, RETROSPECTIVE, OBSERVATIONAL STUDY (preprint)

ABSTRACT Purpose to describe the clinical characteristics of patients with confirmed SARS-CoV-2 infection in primary care and to analyze the predictive role of different risk factors on prognosis, especially living conditions. Methods Retrospective longitudinal observational retrospective study by reviewing medical records from a primary care center since March 1 to April 30, 2020. Case definition of confirmed SARS-CoV-2 infection, sociodemographic data, clinical characteristics, comorbidity and living conditions were collected. The statistical analysis consisted in description of the sample, comparison of prognosis groups and analysis of prognostic factors. Results A sample of 70 patients with confirmed SARS-CoV-2 infection was obtained, with comorbidity mainly related to arterial hypertension, overweight/obesity, hypercholesterolemia, diabetes and chronic pulmonary pathology. Pneumonia was present in 66%. Exitus occurred in 14% of the sample. Factors associated with mortality were advanced age (84 vs 55; p<0.0001), arterial hypertension (78% vs 41%; p=0.040), asthma-COPD (56% vs 13%; p=0.008) and atrial fibrillation (56% vs 5%; p=0.001). Conclusions The study reflects the clinical practice of a primary care center. This kind of studies are essential to strengthen and reorganize the Health System and to try to anticipate the medium- to long-term consequences of COVID-19 on global health.

In a Stressful Social Environment, Can Using Sports Apps Relieve the Physical and Mental Stress of the Elderly? From the Perspective of Industry 4.0

The purpose of this research was to understand the current physical and mental health of the elderly using sports apps under the COVID-19 pandemic. A total of 711 questionnaires were collected using purposive sampling and the snowball method and were analyzed by Statistical Product and Service Solutions 22.0 and Analysis of Moment Structures 20.0 software. The survey found that elderly people who exercise at intervals of one month are more physically and mentally stressed, but that different exercise frequencies also have different levels of physical and mental health problems;the lower the exercise intensity, the more obvious the negative emotions, the stronger or the less time they spend in exercise, and the greater the pressure of sports. In a high-risk social environment, even if the elderly use sports apps to exercise, they will still change the intensity and time of the exercise, but they will not change the frequency of exercise that has become a daily habit. [ FROM AUTHOR] Copyright of Mathematical Problems in Engineering is the property of Hindawi Limited and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all Abstracts.)

Eating behavior associated family factors of preschool children during the COVID-19 epidemic

Objective: To investigate eating behavior and associated family factors of preschool children during the prevalence of Corona Virus Disease(COVID-19), and to provide scientific basis for healthy eating behavior for preschool children.

The prognostic value of IL-8 for the death of severe or critical patients with COVID-19.

ABSTRACT: Inflammation has been believed to contribute to coronavirus disease 2019 (COVID-19). Risk factors for death of COVID-19 pneumonia have not yet been well established.In this retrospective cohort study, we included the deceased patients in COVID-19 specialized ICU with laboratory-confirmed COVID-19 from Guanggu hospital area of Tongji Hospital from February 8th to March 30th. Demographic, clinical, laboratory, and outcome data were extracted from electronic medical records using a standard data collection form. We used Spearman rank correlation and Cox regression analysis to explore the risk factors associated with in-hospital death, especially the association between inflammatory cytokines and death.A total of 205 severe/critical COVID-19 pneumonia patients were admitted in the COVID-19 specialized ICU and 75 deceased patients were included in the final analysis. The median age of the deceasing patients was 70 years (IQR 65-79). The common symptoms were fever (78.9%), cough (70.4%), and expectoration (39.4%). The BNP and CRP levels were far beyond the normal reference range. In the Spearman rank correlation analysis, IL-8 was found to be significantly associated with the time from onset to death (rs= -0.30, P = .034) and that from admission to death (rs= -0.32, P = .019). Cox regression showed after adjusting age and sex, IL-8 levels were still significantly associated with the time from onset to death (P = .003) and that from admission to death (P  = .01).IL-8 levels were associated with in-hospital death in severe/critical COVID-19 patients, which could help clinicians to identify patients with high risk of death at an early stage.

Genomic epidemiology of SARS-CoV-2 in the United Arab Emirates reveals novel virus mutation, patterns of co-infection and tissue specific host responses (preprint)

Background: The United Arab Emirates is a major business hub with substantial amount of international travel. Like many other countries, it was greatly affected by the COVID-19 pandemic since late January 2020, with recurring waves of infection. This study aimed at combining genomic and epidemiological data to unravel the source of SARS-CoV-2 introduction, transmission and evolution in the country. Methods: We performed meta-transcriptomic sequencing of 1,067 nasopharyngeal swab samples collected from qRT-PCR positive COVID-19 patients in Abu Dhabi, UAE, between May 9th and June 29th 2020. We investigated the genetic diversity and transmission dynamics of the viral population and analyzed the infection and transmission potential of novel genomic clusters. Within-host SARS-CoV-2 genetic variation was analyzed to determine the occurrence and prevalence of multiple infections. Finally, we evaluated innate host responses during the prolonged period of local infection. Results: All globally known SARS-CoV-2 clades were identified within the UAE sequenced strains, with a higher occurrence of European and East Asian clades. We defined 5 subclades based on 11 unique genetic variants within the UAE strains, which were associated with no significantly different viral loads. Multiple infection of different SARS-CoV-2 strains was observed for at least 5% of the patients. We also discovered an enrichment of cytosine-to-uracil mutation among the viral population collected from the nasopharynx, that is different from the adenosine-to-inosine change previously observed in the bronchoalveolar lavage fluid samples. This observation is accompanied with an upregulation of APOBEC4, an under-studied putative cytidine-uridine editing enzyme in the infected nasopharynx. Conclusions: The genomic epidemiological and molecular biological knowledge obtained in the study provides new insights for the SARS-CoV-2 evolution and transmission. We highlight the importance of sustained surveillance of the virus mutation using genomic sequencing as a public health strategy. Keywords: SARS-CoV-2, meta-transcriptomic sequencing, novel mutations and subclades, co-infection, cyosine depletion, host RNA editing

Genomic Epidemiology of SARS-CoV-2 in the United Arab Emirates Reveals Novel Insights into the Virus Mutation, Co-Infection and Host-Dependent RNA Editing (preprint)

Background: The United Arab Emirates is a major business hub with substantial amount of international travel. Like many other countries, it was greatly affected by the COVID-19 pandemic since late January 2020, with recurring waves of infection. This study aimed at combining genomic and epidemiological data to unravel the source of SARS-CoV-2 introduction, transmission and evolution in the country.Methods: We performed meta-transcriptomic sequencing of 1,067 nasopharyngeal swab samples collected from qRT-PCR positive COVID-19 patients in Abu Dhabi, UAE, between May 9th and June 29th 2020. We investigated the genetic diversity and transmission dynamics of the viral population and analyzed the infection and transmission potential of novel genomic clusters. Within-host SARS-CoV-2 genetic variation was analyzed to determine the occurrence and prevalence of multiple infections. Finally, we evaluated innate host responses during the prolonged period of local infection.Findings: All globally known SARS-CoV-2 clades were identified within the UAE sequenced strains, with a higher occurrence of European and East Asian clades. We defined 5 subclades based on 11 unique genetic variants within the UAE strains, which were associated with higher viral loads (p<0.001). Multiple infection of different SARS-CoV-2 strains was observed for at least 5% of the patients. We also observed a host-defense mechanism via RNA editing, likely mediated by APOBEC3 rather than ADAR in nasopharyngeal samples.Interpretation: The SARS-CoV-2 epidemic in the UAE was founded by international importation followed by local transmission, leading to prevalent multiple infection and large subclade descendances. While RNA editing mechanisms mutate the viral population, newly arisen genetic variation can contribute to a heavier viral burden. Meta-transcriptomic sequencing can help to determine the transmission patterns of SARS-CoV-2.Funding: Department of Health of Abu Dhabi, UAE and National Natural Science Foundation of China.Declaration of Interests: None to declareEthics Approval Statement: The study was approved by the Abu Dhabi COVID19 Research IRB Committee (approval number DOH/CVDC/2020/1945).

How many COVID-19 PCR positive individuals do weexpect to see on the Diamond Princess cruise ship? (preprint)

When COVID-19 was detected among passengers on Diamond Princess (DP) cruise ship in the end of January and beginning of February of this year, unfortunately it has become an ideal experimental model for studying the transmission potential of COVID-19 in a closed environment while it is hard to do so in the wider open population. Information collected from such an outbreak is crucial for policy makers to understand and manage the epidemic. To disclose the information such as infection onset time, transmission time, and so on from the available observed incomplete data, we must develop valid statistic models and solid inference methods. Due to the fact that the priority for RT-PCR test for COVID-19 was given to symptomatic and their close contacts and elderly individuals, we have to take this selection bias into considerations in the statistic inference. Based on RT-PCR test data performed on the Diamond Princess cruise, in this paper we propose a novel mixture model where the mixing proportions vary with time to estimate the infection distribution and the total infected individuals after a 14-day of quarantine. Compared with the epidemiologic description of COVID-19 spread in open space, we have found some unique features in the Diamond Princess cruise ship. Our fndings may shed lights on preventing future pandemic outbreaks in cruise ship.

The associations between fasting plasma glucose levels and mortality of COVID-19 in patients without diabetes.

AIMS: Coronavirus disease 2019 (COVID-19) which is a novel pneumonia can rapidly progress to acute respiratory distress syndrome, septic shock, and multiple organ dysfunction syndrome. It has appeared in 196 countries around the world. We aimed to clarify the associations between fasting plasma glucose levels and mortality of COVID-19 in patients without diabetes. METHODS: We performed a retrospective, single-center study of 151 patients without diabetes in Tongji Hospital from January 1, 2020 to February 28, 2020. Past medical histories, clinical features and laboratory parameters were collected in these patients. RESULTS: Compared with survivors, non-survivors were more likely to have underlying medical conditions including hypertension and chronic pulmonary diseases. Non-survivors had higher C-reactive protein (CRP), procalcitonin (PCT), interleukin (IL)-2R, IL-6, IL-8 and, tumor necrosis factor-α (TNF-α) levels, while lower lymphocyte counts as compared with those of survivors (all P<0.05). Besides, patients with higher fasting plasma glucose (FPG) had higher IL-6, IL-8, CRP levels and mortality; while lower lymphocyte counts. After adjusting for age and gender, each tertile increment of FPG levels conferred 3.54-fold higher risks of death (odds ratio, 3.54; 95% confidential interval, 1.25-10.06, P=0.018). CONCLUSIONS: Non-survivors combined with more comorbidities, more severe infection, and worse liver, kidney and cardiac function in patients without diabetes. Additionally, fasting plasma glucose levels were significantly associated with the risk of death in patients even with normal FPG and HbA1c levels.

Analysis and Prediction of COVID-19 using SIR, SEIR, and Machine Learning Models: Australia, Italy, and UK Cases (preprint)

The novel Coronavirus disease, known as COVID-19, is an outbreak that started in Wuhan, one of the Central Chinese cities. In this report, a short analysis focusing on Australia, Italy, and the United Kingdom has been conducted. The analysis includes confirmed and recovered cases and deaths, the growth rate in Australia as compared with Italy and the United Kingdom, and the outbreak in different Australian cities. Mathematical approaches based on the susceptible, infected, and recovered case (SIR) and susceptible, exposed, infected, and recovered (SEIR) models were proposed to predict the epidemiology in the countries. Since the performance of the classic form of SIR and SEIR depends on parameter settings, some optimization algorithms, namely, the Broyden–Fletcher–Goldfarb–Shanno (BFGS), conjugate gradients (CG), L-BFGS-B, and Nelder-Mead are proposed to optimize the parameters of SIR and SEIR  models and improve its predictive capabilities. The results of optimized SIR  and SEIR models are compared with the Prophet algorithm and logistic function as two known ML algorithms. The results show that different algorithms display different behaviours in different countries. However, the improved version of the SIR and SEIR models have a better performance compared with other mentioned algorithms described in this study. Moreover, the Prophet algorithm works better for Italy and the United Kingdom cases than for Australian cases and Logistic function compared with Prophet algorithm has a better performance in these cases. It seems that Prophet algorithm is suitable for data with increasing trend in pandemic situations. Optimization of the SIR and SEIR models parameters has yielded a significant improvement in the prediction accuracy of the models. Although there are several algorithms for prediction of this Pandemic, there is no certain algorithm that would be the best one for all cases. 

Two Color Single Molecule Sequencing on GenoCare 1600 Platform to Facilitate Clinical Applications (preprint)

With the rapid development of precision medicine industry, DNA sequencing becomes increasingly important as a research and diagnosis tool. For clinical applications, medical professionals require a platform which is fast, easy to use, and presents clear information relevant to definitive diagnosis. We have developed a single molecule desktop sequencing platform, GenoCare 1600. Fast library preparation (without amplification) and simple instrument operation make it friendlier for clinical use. Here we presented sequencing data of E. coli sample from GenoCare 1600 with consensus accuracy reaches 99.99%. We also demonstrated sequencing of microbial mixtures and COVID-19 samples from throat swabs. Our data show accurate quantitation of microbial, sensitive identification of SARS-CoV-2 virus and detection of variants confirmed by Sanger sequencing.

A Review on COVID-19 Forecasting Models (preprint)

The Novel coronavirus (COVID-19) has distributed to more than 200 territory worldwide leading to about 24 million confirmed cases as of August 25, 2020. Several models have been released that forecast the outbreak globally. This work presents a review of the most important forecasting models against COVID-19 and shows a short analysis of each one. The work presented in this study possesses two parts. A detailed scientometric analysis was done in the first section that provides an influential tool for describing bibliometric analyses. The analysis was performed on data corresponding to COVID-19 using the Scopus and Web of Science databases. For analysis, keywords and subject areas were addressed while classification of forecasting models, criteria evaluation and comparison of solution approaches were done in the second section of the work. Conclusion and discussion are provided as the final sections of this study.

Covid-19: Global Progress in Developing Vaccines and Mechanisms for Equitable Distribution

The serious unique infectious pneumonia (COVID-19), caused by the new coronavirus (SARS-coV-2) in Wuhan, China in late 2019, has rapidly spread and become a global pandemic. It resulted in crises menacing people's health, lives, international engagement and economic systems. Thus, a vaccine holds most potential for a rapid means of resolving the pandemic before the end of 2021. There are 23 different candidate vaccines worldwide that have entered into clinical trials. Among them, the two that have progressed the fastest are Sinovac Biotech's inactivated vaccine and the recombinant vaccine (ChAdOx1-S) developed by Oxford University, which are already in the third phase of clinical trials. In late April 2020, WHO, EU and the Bill and Melinda Gates Foundation launched the ACT Accelerator Plan to acquire more COVID-19 tools. Also, GAVI, CEPI and WHO are jointly promoting the COVAX Facility, responsible for coordinating and integrating resources among worldwide vaccine developers and manufacturers. In addition to assuming risks of vaccine development, they also provide early investment in candidate vaccine products. These efforts increase chances of successful vaccine development as they expedite safe, efficient development and mass manufacturing of COVID-19 vaccines. This will result in the common goal of equitable distribution of vaccines for every nation.