Since early 2020, an unprecedented public global health emergency caused by coronavirus (COVID-19) resulted in national governments’ imposing confinement measures. Lockdowns and isolation during pandemics complicate disease management and medication adherence. Chronic conditions, such as epilepsy, require linear adherence patterns to prevent breakthrough seizures and to reduce the risk of sudden unexpected death. Limited access to health care facilities for routine care and medicines management further hampers this. Social isolation exacerbates stress, depression and decreases social support, which may combine to reduce adherence to antiseizure medication (ASM) during the pandemic.
We conducted a literature scoping review to explore ASM adherence among people with epilepsy, non-infected or infected SARS-CoV-2 or recovered from COVID-19 during the pandemic and explore risk factors for adherence. We search Pubmed for articles up to 16 September 2021. Search terms included the thematic of ASM adherence and COVID-19. We adhered to the PRISMA guidelines for reporting scoping reviews.
Six articles were retained after the screening, which covered four overarching themes: change of ASM compliance and as risk factors, lack of follow-up, difficulties accessing ASM, and behavioural risk factors. Our review underscores the lack of evidence on ASM adherence among people with epilepsy infected or recovered from COVID-19. No study retrieved took place in a low-income setting, warranting a cautionary approach to be employed when extrapolating findings on a global scale.
Missing information on past SARS-CoV2 infections impact people with epilepsy precludes exploring a direct effect of SARS-CoV2 on ASM adherence. A more comprehensive chronic disease model based on the burden of co-cardiovascular and neuro-behavioural comorbidities should be envisaged for this population in preparation for future pandemics. A monitoring algorithm needs to be in place to establish a telemedicine framework and community pharmacists’ potential to contribute to the model recognised.