To overcome this pandemic, vaccination is the hope for a safe and effective way to help build protection and reduce disease spread. Over 140 million infected and 3 million deaths are reported from COVID-19 by April 2021, with the death rate accelerating according to WHO, the case fatality ratio (CFR) of SARS-CoV-2 ranges from less than 0.1% to over 25% depending on the country.
The SARS-CoV-2 infection causes the coronavirus disease 2019 (COVID-19) that became a global pandemic and public health crisis. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a non-segmented positive-sense, single-stranded ribonucleic acid (RNA) beta coronavirus that was first reported in Wuhan, China. Remarkably few experienced extreme adverse effects and all stimulated robust immune responses. The mRNA-based vaccines had higher side effects. The adenovirus-vectored and mRNA-based vaccines for COVID-19 showed the highest efficacy after first and second doses, respectively. Aluminum-adjuvanted vaccines had the lowest systemic and local side effects between vaccines’ adjuvant or without adjuvant, except for injection site redness.
The mRNA-based vaccines had the highest level of side effects reported except for diarrhea and arthralgia. Efficacy of the adenovirus-vectored vaccine after the first (97.6% 95% CI 0.939–0.997) and second (98.2% 95% CI 0.980–0.984) doses was the highest against receptor-binding domain (RBD) antigen after 3 weeks of injections. In total, mRNA-based and adenovirus-vectored COVID-19 vaccines had 94.6% (95% CI 0.936–0.954) and 80.2% (95% CI 0.56–0.93) efficacy in phase II/III RCTs, respectively. A total of 25 RCTs (123 datasets), 58,889 cases that received the COVID-19 vaccine and 46,638 controls who received placebo were included in the meta-analysis. All relevant publications were systematically searched and collected from major databases up to 12 March 2021.
Citing comprehensive meta analysis 3.3 license#
Keywords: vader,sentiment,analysis,opinion,mining,nlp,text,data,text analysis,opinion analysis,sentiment analysis,text mining,twitter sentiment,opinion mining,social media,twitter,social,mediaĬlassifier: Development Status :: 5 - Production/StableĬlassifier: Intended Audience :: Science/ResearchĬlassifier: License :: OSI Approved :: MIT LicenseĬlassifier: Programming Language :: Python :: 3.The current study systematically reviewed, summarized and meta-analyzed the clinical features of the vaccines in clinical trials to provide a better estimate of their efficacy, side effects and immunogenicity.
Citing comprehensive meta analysis 3.3 code#
If you use either the dataset or any of the VADER sentiment analysis tools (VADER sentiment lexicon or Python code for rule-based sentiment analysis engine) in your research, please cite the above paper. It is fully open-sourced under the (we sincerely appreciate all attributions and readily accept most contributions, but please don’t hold us liable). VADER (Valence Aware Dictionary and sEntiment Reasoner) is a lexicon and rule-based sentiment analysis tool that is specifically attuned to sentiments expressed in social media.