Examining potential factors underlying the increased risk of severe COVID-19 experienced by people with Autism Spectrum Disorder (ASD)
Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by differences in social communication and interaction, repetitive and restrictive behaviours and differences in sensory preferences. Over the course of the pandemic, different subpopulations were shown to be at more risk of COVID-19 infection, severity and mortality than others. However, there are conflicting reports on COVID-19 infection and mortality risk for autistic people and no studies have investigated predictors for severe COVID-19 (i.e., hospitalisation or mortality due to COVID-19) in autistic people.
Genetic and immunological characteristics of autism may put autistic people at increased risk for COVID-19 infection, such as proneness to bacterial and viral infections and abnormal immune responses. Moreover, several physical and mental health conditions that have been linked to increased COVID-19 infection and severity in the general population, such as obesity and psychotic disorders, are highly prevalent in the autistic population. Similarly, polypharmacy and particularly antipsychotic use have been shown to contribute to increased COVID-19 morbidity and mortality in the general population. Despite both polypharmacy and antipsychotic use being prevalent in the autistic population, their effects on COVID-19 severity and mortality have not been investigated in the autistic population.
The current study sought to investigate the differences in COVID-19 hospitalisation and mortality rates between autistic and non-autistic people. Further, it aimed to investigate whether demographic and clinical risk factors could be used to predict severe COVID-19 (defined as hospitalisation or mortality due to COVID-19) in the autistic population. Predictors such as age, sex, IMD decile, ethnicity, vaccination doses, multimorbidity, polypharmacy, and antipsychotic/antidepressant/anticonvulsant use were used in binary logistic regression modelling, hierarchical regression modelling, Blinder-Oaxaca decomposition analysis, and survival modelling.
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- View the analysis code used in NHS England's SDE for England
- View the phenotyping algorithms and codelists used in NHS England's SDE for England
This is a sub-project of project CCU030 approved by the CVD-COVID-UK / COVID-IMPACT Approvals & Oversight Board (sub-project: CCU030_02).
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