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2020 ; 64
(7
): 482-488
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Mortality of people with intellectual disabilities during the 2017/2018 influenza
epidemic in the Netherlands: potential implications for the COVID-19 pandemic
#MMPMID32458565
Cuypers M
; Schalk BWM
; Koks-Leensen MCJ
; Nägele ME
; Bakker-van Gijssel EJ
; Naaldenberg J
; Leusink GL
J Intellect Disabil Res
2020[Jul]; 64
(7
): 482-488
PMID32458565
show ga
BACKGROUND: Data on the development of Covid-19 among people with intellectual
disabilities (IDs) are scarce and it is uncertain to what extent general
population data applies to people with ID. To give an indication of possible
implications, this study investigated excess mortality patterns during a previous
influenza epidemic. METHODS: Using Dutch population and mortality registers, a
historical cohort study was designed to compare mortality during the 2017-2018
influenza epidemic with mortality in the same period in the three previous years.
People with ID were identified by entitlements to residential ID-care services as
retrieved from a national database. RESULTS: Data covered the entire adult Dutch
population (12.6 million; GenPop), of which 91 064 individuals were identified
with an ID. During the influenza epidemic, mortality among people with ID
increased almost three times as much than in the GenPop (15.2% vs. 5.4%), and
more among male individuals with ID (+19.5%) than among female individuals with
ID (+10.6%), as compared with baseline. In both cohorts, comparable increases in
mortality within older age groups and due to respiratory causes were seen.
Particularly in the ID-cohort, excess deaths also occurred in younger age groups,
due to endocrine diseases and ID-specific causes. CONCLUSIONS: During the
2017-2018 influenza epidemic, excess mortality among people with ID was three
times higher than in the general Dutch population, appeared more often at young
age and with a broader range of underlying causes. These findings suggest that a
pandemic may disproportionally affect people with ID while population data may
not immediately raise warnings. Early detection of diverging patterns and faster
implementation of tailored strategies therefore require collection of good
quality data.