Abstract
Vaccination has long been recognized as the most effective means for disease prevention, yet concerns have raised globally regarding possible side effects. These concerns were very serious with the COVID-19 vaccines due to the accelerated development process, which did not follow the traditional vaccine lifecycle. This paper describes a dataset that captures a range of long-term symptoms in patients after recovering from the virus including information on vaccination status and self-reported memory issues. The research was carried out in the Kurdistan region of Iraq, and as a result, The Kurdistan Long Term COVID Dataset (KLTCD) was established. The dataset is publicly available online. Basic statistical analysis, measures and machine learning logistic algorithm have been used to evaluate the hypothesis. The established dataset contains numerous features, variables, and labels, making it one of the most information-rich datasets on long-term COVID-19. It may be used to support or refute various hypothesis related to the virus.