Active Surveillance for Safety Monitoring of COVID-19 Vaccines in Saudi Arabia

Introduction: At the end of 2019, a novel coronavirus was identified as the cause of a cluster of pneumonia cases in Wuhan, China [1, 2]. It is generally accepted that the world will not return to the pre-pandemic normally situation until safe and effective vaccines become available. However, the rare and unknown adverse events following immunization (AEFIs) are not usually detected in the clinical trials. Thus, monitoring the safety of COVID-19 vaccines in real-world population is essential. Objective(s): To perform a post-marketing safety surveillance of AEFIs of COVID-19 vaccines. Method(s): A prospective cohort study conducted and followed subjects who received COVID-19 vaccines from the first day of vaccination for seven days after the first and second doses, then biweekly for three months. All vaccinee demographic information, vaccine type, co-morbidities, concomitant medications and AEFIs were collected by phone through a standardized online questionnaire. Baseline characteristics and AEFIs were analyzed descriptively by SPSS software. AEFIs were classified according to medical Dictionary for Regulatory Activities (MedDRA). Result(s): 544 subjects of 8867 agreed to be part of the study. Among them 218 subjects completed the study, of them 110 individual were male (50.5%) and 108 (49.5%) were female;the median age was 33 year. Out of 218, 87 (39.91%) individual received Pfizer-BioNTech vaccine, 45(20.64%) individual received Oxford/AstraZeneca vaccine, 5(2.3%) individual received Moderna vaccine, and 81 (37.2%) received two different COVID-19 vaccines. The reported events were categorized to system organ class (SOC) according to MedDRA. The most reported SOCs were respiratory, thoracic and mediastinal disorders (n = 8 with Pfizer-BioNTech vaccine, n = 4 with Oxford/ AstraZeneca vaccine, n = 1 with Moderna vaccine), Injection site reactions (n = 66 with Pfizer-BioNTech vaccine, n = 34 with Oxford/ AstraZeneca vaccine, n = 5 with Moderna vaccine), nervous system disorder (n = 20 with Pfizer-BioNTech vaccine, n = 18 with Oxford/ AstraZeneca vaccine, n = 3 with Moderna vaccine),infections and infestations (n = 23 with Pfizer-BioNTech vaccine, n = 33 with Oxford/AstraZeneca vaccine, n = 4 with Moderna vaccine), musculoskeletal disorders (n = 53 with Pfizer-BioNTech vaccine, n = 46 with Oxford/AstraZeneca vaccine, n = 7 with Moderna vaccine). Only 10 (4.6%) cases were serious and required medical intervention to overcome the harm. Conclusion(s): The preliminary results of the study shows the shortterm safety profiles of included COVID-19 vaccines are acceptable in Saudi Arabia.

Active Surveillance for Safety Monitoring of COVID-19 Vaccines in Saudi Arabia: An International Journal of Medical Toxicology and Drug Experience

Introduction: At the end of 2019, a novel coronavirus was identified as the cause of a cluster of pneumonia cases in Wuhan, China [1, 2]. It is generally accepted that the world will not return to the pre-pandemic normally situation until safe and effective vaccines become available. However, the rare and unknown adverse events following immunization (AEFIs) are not usually detected in the clinical trials. Thus, monitoring the safety of COVID-19 vaccines in real-world population is essential. Objective: To perform a post-marketing safety surveillance of AEFIs of COVID-19 vaccines. Methods: A prospective cohort study conducted and followed subjects who received COVID-19 vaccines from the first day of vaccination for seven days after the first and second doses, then biweekly for three months. All vaccinee demographic information, vaccine type, co-morbidities, concomitant medications and AEFIs were collected by phone through a standardized online questionnaire. Baseline characteristics and AEFIs were analyzed descriptively by SPSS software. AEFIs were classified according to medical Dictionary for Regulatory Activities (MedDRA). Results: 544 subjects of 8867 agreed to be part of the study. Among them 218 subjects completed the study, of them 110 individual were male (50.5%) and 108 (49.5%) were female;the median age was 33 year. Out of 218, 87 (39.91%) individual received Pfizer-BioNTech vaccine, 45(20.64%) individual received Oxford/AstraZeneca vaccine, 5(2.3%) individual received Moderna vaccine, and 81 (37.2%) received two different COVID-19 vaccines. The reported events were categorized to system organ class (SOC) according to MedDRA. The most reported SOCs were respiratory, thoracic and mediastinal disorders (n = 8 with Pfizer-BioNTech vaccine, n = 4 with Oxford/ AstraZeneca vaccine, n = 1 with Moderna vaccine), Injection site reactions (n = 66 with Pfizer-BioNTech vaccine, n = 34 with Oxford/ AstraZeneca vaccine, n = 5 with Moderna vaccine), nervous system disorder (n = 20 with Pfizer-BioNTech vaccine, n = 18 with Oxford/ AstraZeneca vaccine, n = 3 with Moderna vaccine),infections and infestations (n = 23 with Pfizer-BioNTech vaccine, n = 33 with Oxford/AstraZeneca vaccine, n = 4 with Moderna vaccine), musculoskeletal disorders (n = 53 with Pfizer-BioNTech vaccine, n = 46 with Oxford/AstraZeneca vaccine, n = 7 with Moderna vaccine). Only 10 (4.6%) cases were serious and required medical intervention to overcome the harm. Conclusion: The preliminary results of the study shows the shortterm safety profiles of included COVID-19 vaccines are acceptable in Saudi Arabia.

Development of a Robust Mathematical Model to Estimate COVID-19 Cases in Lebanon Based on SEIRDV Modified Model

COVID-19 pandemic triggered a global crisis, whether it comes to a huge global health emergency or to the global economic crisis situation. It is one of the greatest challenges this generation is facing. Computational simulations are playing a huge rule in the prediction of the current pandemic. Such simulations enable early predictions for future projections of the pandemic and are useful to estimate the efficiency of control action taken against this virus. The SEIR (Susceptible-Exposed-Infectious-Recovered) model is a commonly used model to compute the simulations of any infectious viral diseases and was widely used before to model and simulate SARS, EBOLA, Spanish Flu, etc. This paper presents a modified SEIR model with additional parameters taken into consideration such as the death, recovered and recovered with the chance of being infected again, vaccination and control efficiency;where the control represents the effectiveness of the lockdown. This factor is being controlled in order to extend the projections into controlled death, recovery, and infection. Specific information including time delay on the development of the pandemic due to control action measures, ageing factor of the population, and resusceptibility with temporal immune response are also included in the model. After that, the model examines the outcome of the system after adding a controllable vaccine with taking into consideration the vaccination rate and vaccine's efficacy. The numerical results are demonstrated to show the predictability range of this model.