Reported Adverse Effects and Attitudes among Arab Populations Following COVID-19 Vaccination: A Large-Scale Multinational Study Implementing Machine Learning Tools in Predicting Post-Vaccination Adverse Effects Based on Predisposing Factors

Abstract

Background: The unprecedented global spread of coronavirus disease 2019 (COVID-19) has imposed huge challenges on the healthcare facilities, and impacted every aspect of life. This has led to the development of several vaccines against COVID-19 within one year. This study aimed to assess the attitudes and the side effects among Arab communities after receiving a COVID-19 vaccine and use of machine learning (ML) tools to predict post-vaccination side effects based on predisposing factors. Methods: An online-based multinational survey was carried out via social media platforms from June 14 to 31 August 2021, targeting individuals who received at least one dose of a COVID-19 vaccine from 22 Arab countries. Descriptive statistics, correlation, and chi-square tests were used to analyze the data. Moreover, extensive ML tools were utilized to predict 30 post vaccination adverse effects and their severity based on 15 predisposing factors. The importance of distinct predisposing factors in predicting particular side effects was determined using global feature importance employing gradient boost as AutoML. Results: A total of 10,064 participants from 19 Arab countries were included in this study. Around 56% were female and 59% were aged from 20 to 39 years old. A high rate of vaccine hesitancy (51%) was reported among participants. Almost 88% of the participants were vaccinated with one of three COVID-19 vaccines, including Pfizer-BioNTech (52.8%), AstraZeneca (20.7%), and Sinopharm (14.2%). About 72% of participants experienced post-vaccination side effects. This study reports statistically significant associations (p < 0.01) between various predisposing factors and post-vaccinations side effects. In terms of predicting post-vaccination side effects, gradient boost, random forest, and XGBoost outperformed other ML methods. The most important predisposing factors for predicting certain side effects (i.e., tiredness, fever, headache, injection site pain and swelling, myalgia, and sleepiness and laziness) were revealed to be the number of doses, gender, type of vaccine, age, and hesitancy to receive a COVID-19 vaccine. Conclusions: The reported side effects following COVID-19 vaccination among Arab populations are usually non-life-threatening; flu-like symptoms and injection site pain. Certain predisposing factors have greater weight and importance as input data in predicting post-vaccination side effects. Based on the most significant input data, ML can also be used to predict these side effects; people with certain predicted side effects may require additional medical attention, or possibly hospitalization.

Side Effects of COVID-19 Inactivated Virus vs. Adenoviral Vector Vaccines: Experience of Algerian Healthcare Workers

“…The history of infection with COVID-19 increased significantly the risk of developing side effects even in both vaccine groups. The same results were found in multiple previous studies for different COVID-19 vaccines, including the mRNA-based ones ( 23 , 24 , 27 , 28 , 50 , 57 ). Moreover, the antibody titer after COVD-19 vaccination was higher among individuals with a past history of SARS-CoV-2 infection than those who had not been in contact with this pathogen ( 44 ).…”

“…However, these side effects emerged generally with low frequencies than previously reported, especially with the adenoviral vector vaccines, i.e., AZD1222 where injection site pain was reported with a prevalence higher than 58% ( 24 , 27 , 47 – 49 ). Similarly, a large-scale multinational study covering more than 10,000 vaccinees in the Arab countries reported that more than 58% of the participants suffered from injection site pain and swelling ( 50 ).…”

Perceptions and experiences of COVID-19 vaccines’ side effects among healthcare workers at an Egyptian University Hospital: a cross-sectional study

“…The most commonly reported side effect among the studied HCWs who received the three types of vaccines was fatigue. Many Egyptian, large-scale Arab world and global studies concluded that fatigue was one of the most prevalent s observed following COVID-19 vaccination [ 4 , 22 , 28 , 42 – 44 ].…”

“…The majority of them are non-life threatening, with most cases being mild to moderate in intensity and resolving in a few days. Good knowledge of vaccinations and their adverse effects was substantially related to the vaccination acceptance rate [ 44 ]. As a result, contradicting the rumors, misconceptions, and conspiracy theories regarding COVID-19 vaccinations and their real adverse effects could boost public trust and confidence in COVID-19 vaccines.…”

Do Attitudes, Mental Health Status, and Interpersonal Factors Predict COVID-19 Vaccine Hesitancy at the Early Phase of the Pandemic? A Longitudinal Study in Chinese College Students

“…Therefore, these factors may also be applicable to understanding COVID-19 vaccination intention. Indeed, it has been reported that positive attitudes toward the vaccine against COVID-19, such as high levels of perceived efficacy and benefits of the vaccine, had a positive association with COVID-19 vaccine acceptance ( Detoc et al, 2020 ; Faasse and Newby, 2020 ; Graffigna et al, 2020 ; Neumann-Böhme et al, 2020 ; Wang et al, 2020 ; Wong et al, 2020 ; Guidry et al, 2021 ; Kateeb et al, 2021 ; Riad et al, 2021b ), while pessimism about side effects, vaccine efficacy and safety have been reported to increase COVID-19 vaccine hesitancy ( Machida et al, 2021 ; Mo et al, 2021a ; Skjefte et al, 2021 ; Hatmal et al, 2022 ). However, all these studies are cross-sectional.…”