Learning from the past: development of safe and effective COVID-19 vaccines.
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ABSTRACT:
SUBMITTER: Su S
PROVIDER: S-EPMC7566580 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ObjectiveTo evaluate the safety and efficacy of COVID-19 vaccines in pregnant women performing an updated meta-analysis.MethodsWe searched PubMed, Cochrane Central, and SCOPUS from inception to March 2022. Outcomes of interest were incidence of adverse maternal, fetal and neonatal consequences pertaining to safety of the vaccines. Secondarily, we analyzed the number of SARS-CoV-2 infections, hospitalization for COVID-19, and admission to the I.C.U. for COVID-19 assessing the effectiveness of vaccines. Results were pooled using a random effects model.ResultsTen observational studies (n=326,499) analyzing pregnant women were included. Our results suggest that COVID-19 vaccination prevents infection (OR: 0.56, 95% CI: 0.47, 0.67; P = <0.00001) and related hospitalizations (OR: 0.50, 95% CI: 0.31, 0.82; P = 0.006) effectively. It was also observed that vaccination does not change adverse outcomes in pregnancy, namely preeclampsia or eclampsia, stroke (four weeks of delivery), meconium-stained amniotic fluid, spontaneous vaginal delivery, operative vaginal delivery, cesarean delivery, postpartum hemorrhage, and blood transfusions. Furthermore, the vaccine was observed to be protective against neonatal COVID-19 I.C.U. admissions (OR: 0.85; 95% CI: 0.81, 0.90; P = <0.00001).ConclusionOur pooled analysis suggests that the COVID-19 vaccination in pregnant women prevents infection effectively and has no adverse outcomes. Future large-scale trials in a randomized fashion are needed to confirm our results.
| S-EPMC9394101 | biostudies-literature
Project description:In the current context of the pandemic triggered by SARS-COV-2, the immunization of the population through vaccination is recognized as a public health priority. In the case of SARS‑COV‑2, the genetic sequencing was done quickly, in one month. Since then, worldwide research has focused on obtaining a vaccine. This has a major economic impact because new technological platforms and advanced genetic engineering procedures are required to obtain a COVID‑19 vaccine. The most difficult scientific challenge for this future vaccine obtained in the laboratory is the proof of clinical safety and efficacy. The biggest challenge of manufacturing is the construction and validation of production platforms capable of making the vaccine on a large scale.
| S-EPMC7255458 | biostudies-literature
Project description:Novel corona virus caused pneumonia first reported in December, 2019 in Wuhan, China was later named COVID-19. Due to its special pathogenicity, COVID-19 transmitted with high speed beyond borders and has significantly affected normal life. Currently, no specific drugs, treatment or vaccines are available. Vaccine development for COVID-19 is a highly complex process involving viral genomic studies, identification of target for vaccine, vaccine design, manufacturing, storage and distribution, preclinical and clinical safety and efficacy studies. The high levels of efforts and global collaboration at this scale is unprecedented. The World Health Organization (WHO) has documented 160 different COVID-19 vaccine candidates as of July 13, 2020 with 26 currently on clinical evaluation while 137 vaccines on preclinical evaluation. COVID-19 vaccine efforts mark the first use of mRNA-type vaccines ever evaluated. Numerous research organizations have successfully initiated clinical evaluation of COVID-19 vaccines. This review aims to summarize the advances and challenges for COVID-19 vaccines development.
| S-EPMC7470435 | biostudies-literature
Project description:A 53-year-old male presents with cough, fever, and myalgias for 7 days. Vitals include temperature, 38.0°C; heart rate, 110; blood pressure, 118/70 mm Hg; respiration rate, 28; and oxygen saturation 83% on room air. His only past medical history is hypertension. Your community is in the midst of the coronavirus disease 2019 (COVID-19) pandemic. The patient is hypoxic but responds to oxygen supplementation with nasal cannula and a face mask. His chest x-ray demonstrates multifocal infiltrates. Are there any therapeutic agents currently available for COVID-19?
| S-EPMC7267102 | biostudies-literature
Project description:The current pandemic called COVID-19 caused by the SARS-CoV-2 virus brought the need for the search for fast alternatives to both control and fight the SARS-CoV-2 infection. Therefore, a race for a vaccine against COVID-19 took place, and some vaccines have been approved for emergency use in several countries in a record time. Ongoing prophylactic research has sought faster, safer, and precise alternatives by redirecting knowledge of other vaccines, and/or the development of new strategies using available tools, mainly in the areas of genomics and bioinformatics. The current review highlights the development of synthetic antigen vaccines, focusing on the usage of bioinformatics tools for the selection and construction of antigens on the different vaccine constructions under development, as well as strategies to optimize vaccines for COVID-19.
| S-EPMC8506811 | biostudies-literature
Project description:IntroductionThe coronavirus 19 (COVID-19) pandemic triggered a simultaneous global demand for preventative vaccines, which quickly became a high priority among governments as well as academia and the pharmaceutical industry. Within less than a year after COVID-19 was declared a pandemic, vaccines had received emergency approvals and vaccination campaigns were initiated.Areas coveredWe discuss the several factors that led to the unprecedented, accelerated development and approval of COVID-19 vaccines, which includes optimization of processes by regulatory authorities, redesign of sequential development processes, learnings from previous pandemics, and prior development of novel vaccine platforms.Expert opinionDespite unanticipated and complex challenges presented by real-time vaccine development in the context of the evolving COVID-19 pandemic and subsequent ever-changing landscape of public health measures and recommendations, important milestones were reached within extraordinarily short periods and, following roll-out to billions worldwide, the approved vaccines have proven to be well tolerated and effective. Whilst this is an exceptional feat and an example of what can be achieved with collaboration and innovation, there are lessons that can still be learned, including the need for further harmonization between regulatory authorities, modes to react to the pandemic's ever-evolving challenges, and ensuring equitable vaccine access among low-income countries.
| S-EPMC8935460 | biostudies-literature
Project description:ObjectivesTo evaluate the prevalence of infection prevention behaviors in Taiwan-wearing facemasks and alcohol-based hand hygiene (AHH)-and compare their practice rates during SARS and COVID-19.MethodsWe surveyed 2328 Taiwanese from July 29 to August 6, 2020, assessing demographics, information sources, and preventive behaviors during the 2003 SARS outbreaks, 2009 pandemic influenza H1N1, COVID-19, and with post-survey intentions. Characteristics associated with the practice of preventive behaviors in 2020 were identified through logistic regression.ResultsPreventive behaviors were conscientiously practiced by 70.2% of participants. Compared with 2003 SARS/2009 H1N1, the percentages of facemask use (66.6% vs 99.2% [indoors], P < 0.001) and on-person AHH (44.2% vs 65.4% [hand sanitizers], P < 0.001) significantly increasedduring 2020 COVID-19. Highest adherence to preventive behaviors in 2020 was among females (adjusted odds ratio [aOR], 1.72), those receiving government COVID-19 information (aOR, 1.52), participants recruited from primary-care clinics (aOR, 1.43), and those who practiced AHH during 2003 SARS/2009 H1N1 (aOR, 1.37).ConclusionsGovernment leadership, healthcare providers risk communication, and public cooperation rapidly mitigated the spread of COVID-19 in Taiwan even before vaccination. Future global efforts must implement such population-based preventive behaviors at a level above the viral-transmission-threshold, particularly in areas with fast-spreading SARS-CoV-2 variants.
| S-EPMC8178059 | biostudies-literature
Project description:COVID-19, the disease caused by infection with SARS-CoV-2, requires urgent development of therapeutic interventions. Due to their safety, specificity, and potential for rapid advancement into the clinic, monoclonal antibodies (mAbs) represent a highly promising class of antiviral or anti-inflammatory agents. Herein, by analyzing prior efforts to advance antiviral mAbs for other acute respiratory infections (ARIs), we highlight the challenges faced by mAb-based immunotherapies for COVID-19. We present evidence supporting early intervention immediately following a positive diagnosis via inhaled delivery of mAbs with vibrating mesh nebulizers as a promising approach for the treatment of COVID-19.
| S-EPMC7836766 | biostudies-literature
Project description:BackgroundFor the clinical care of patients with well-established diseases, randomized trials, literature, and research are supplemented with clinical judgment to understand disease prognosis and inform treatment choices. In the void created by a lack of clinical experience with COVID-19, artificial intelligence (AI) may be an important tool to bolster clinical judgment and decision making. However, a lack of clinical data restricts the design and development of such AI tools, particularly in preparation for an impending crisis or pandemic.ObjectiveThis study aimed to develop and test the feasibility of a "patients-like-me" framework to predict the deterioration of patients with COVID-19 using a retrospective cohort of patients with similar respiratory diseases.MethodsOur framework used COVID-19-like cohorts to design and train AI models that were then validated on the COVID-19 population. The COVID-19-like cohorts included patients diagnosed with bacterial pneumonia, viral pneumonia, unspecified pneumonia, influenza, and acute respiratory distress syndrome (ARDS) at an academic medical center from 2008 to 2019. In total, 15 training cohorts were created using different combinations of the COVID-19-like cohorts with the ARDS cohort for exploratory purposes. In this study, two machine learning models were developed: one to predict invasive mechanical ventilation (IMV) within 48 hours for each hospitalized day, and one to predict all-cause mortality at the time of admission. Model performance was assessed using the area under the receiver operating characteristic curve (AUROC), sensitivity, specificity, positive predictive value, and negative predictive value. We established model interpretability by calculating SHapley Additive exPlanations (SHAP) scores to identify important features.ResultsCompared to the COVID-19-like cohorts (n=16,509), the patients hospitalized with COVID-19 (n=159) were significantly younger, with a higher proportion of patients of Hispanic ethnicity, a lower proportion of patients with smoking history, and fewer patients with comorbidities (P<.001). Patients with COVID-19 had a lower IMV rate (15.1 versus 23.2, P=.02) and shorter time to IMV (2.9 versus 4.1 days, P<.001) compared to the COVID-19-like patients. In the COVID-19-like training data, the top models achieved excellent performance (AUROC>0.90). Validating in the COVID-19 cohort, the top-performing model for predicting IMV was the XGBoost model (AUROC=0.826) trained on the viral pneumonia cohort. Similarly, the XGBoost model trained on all 4 COVID-19-like cohorts without ARDS achieved the best performance (AUROC=0.928) in predicting mortality. Important predictors included demographic information (age), vital signs (oxygen saturation), and laboratory values (white blood cell count, cardiac troponin, albumin, etc). Our models had class imbalance, which resulted in high negative predictive values and low positive predictive values.ConclusionsWe provided a feasible framework for modeling patient deterioration using existing data and AI technology to address data limitations during the onset of a novel, rapidly changing pandemic.
| S-EPMC7901593 | biostudies-literature
Project description: Not available
| S-EPMC7574682 | biostudies-literature