Background: Since the coronavirus disease 2019 (COVID-19) was declared a pandemic, there was no doubt that vaccination is the ideal protocol to tackle it. Within a year, a few COVID-19 vaccines have been developed and authorized. This unparalleled initiative in developing vaccines created many uncertainties looming around the efficacy and safety of these vaccines. This study aimed to assess the side effects and perceptions following COVID-19 vaccination in Jordan. Methods: A cross-sectional study was conducted by distributing an online survey targeted toward Jordan inhabitants who received any COVID-19 vaccines. Data were statistically analyzed and certain machine learning (ML) tools, including multilayer perceptron (MLP), eXtreme gradient boosting (XGBoost), random forest (RF), and K-star were used to predict the severity of side effects. Results: A total of 2213 participants were involved in the study after receiving Sinopharm, AstraZeneca, Pfizer-BioNTech, and other vaccines (38.2%, 31%, 27.3%, and 3.5%, respectively). Generally, most of the post-vaccination side effects were common and non-life-threatening (e.g., fatigue, chills, dizziness, fever, headache, joint pain, and myalgia). Only 10% of participants suffered from severe side effects; while 39% and 21% of participants had moderate and mild side effects, respectively. Despite the substantial variations between these vaccines in the presence and severity of side effects, the statistical analysis indicated that these vaccines might provide the same protection against COVID-19 infection. Finally, around 52.9% of participants suffered before vaccination from vaccine hesitancy and anxiety; while after vaccination, 95.5% of participants have advised others to get vaccinated, 80% felt more reassured, and 67% believed that COVID-19 vaccines are safe in the long term. Furthermore, based on the type of vaccine, demographic data, and side effects, the RF, XGBoost, and MLP gave both high accuracies (0.80, 0.79, and 0.70, respectively) and Cohen’s kappa values (0.71, 0.70, and 0.56, respectively). Conclusions: The present study confirmed that the authorized COVID-19 vaccines are safe and getting vaccinated makes people more reassured. Most of the post-vaccination side effects are mild to moderate, which are signs that body’s immune system is building protection. ML can also be used to predict the severity of side effects based on the input data; predicted severe cases may require more medical attention or even hospitalization.

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), which emerged in December 2019 and caused the coronavirus disease 2019 (COVID-19) pandemic, took the world by surprise with an unprecedented public health emergency. Since this pandemic began, extraordinary efforts have been made by scientists to understand the pathogenesis of COVID-19, and to fight the infection by providing various preventive, diagnostic and treatment opportunities based on either novel hypotheses or past experiences. Despite all the achievements, COVID-19 continues to be an accelerating health threat with no specifically approved vaccine or therapy. This review highlights the recent advances in COVID-19 infection, with a particular emphasis is put on nanomedicine applications that can help to succeed in the development of effective vaccines or therapeutics against COVID-19. A novel future perspective has been proposed in this review based on utilizing polymersome nano-objects for effectively suppressing the cytokine storm, which may reduce the severity of COVID-19 infection.

Paratyphoid fever is caused by the bacterium Salmonella enterica serovar Paratyphi (A, B and C), and contributes significantly to global disease burden. One of the major challenges in the diagnosis of paratyphoid fever is the lack of a proper gold standard. Given the absence of a licensed vaccine against S. Paratyphi, this diagnostic gap leads to inappropriate antibiotics use, thus, enhancing antimicrobial resistance. In addition, the symptoms of paratyphoid overlap with other infections, including the closely related typhoid fever. Since the development and utilization of a standard, sensitive, and accurate diagnostic method is essential in controlling any disease, this review discusses a new promising approach to aid the diagnosis of paratyphoid fever. This advocated approach is based on the use of surface plasmon resonance (SPR) biosensor and DNA probes to detect specific nucleic acid sequences of S. Paratyphi. We believe that this SPR-based genoassay can be a potent alternative to the current conventional diagnostic methods, and could become a rapid diagnostic tool for paratyphoid fever.