Executive dysfunction following SARS-CoV-2 infection: A cross-sectional examination in a population-representative sample

23 24

Prior studies have documented reliable associations between SARS-CoV-2 infection and 25 adverse cognitive impact in older adults. The current study sought to determine whether SARS-CoV-2 26 infection and COVID-19 symptom severity are associated with cognitive dysfunction among young adults 27 and middled-aged adults in the general population. 28

The Canadian COVID-19 Experiences Project (CCEP) survey involves 1,958 adults with equal 29 representation of vaccinated and vaccine hesitant adults between the ages of 18 and 54 years. The 30 sample comprised 1,958 adults with a mean age of 37 years (SD=10.4); 60.8% were female. The 31 primary outcome was symptoms of cognitive dysfunction assessed via an abbreviated form of the Barkley 32 Deficits in Executive Functioning Scale (BDEFS) and performance on a validated decision-making task. 33 34

Young and middle-aged adults with a positive SARS-CoV-2 infection history reported a 35 significantly higher number of symptoms of executive dysfunction (Madj=1.89, SE=0.08, CI: 1.74, 2.04; 36 n=175) than their non-infected counterparts (Madj=1.63, SE=0.08, CI: 1.47,1.80; n=1,599; β =0.26, 37 p=.001). Among those infected, there was a dose-response relationship between COVID-19 symptom 38 severity and level of executive dysfunction, with moderate (β =0.23, CI: 0.003-0.46) and very/extremely 39 severe (β = 0.69, CI: 0.22-1.16) COVID-19 symptoms being associated with significantly greater 40 dysfunction, compared to asymptomatic. These effects remained reliable and of similar magnitude after 41 controlling for age, sex, vaccination status, income, and geographic region, and after removal of those 42 who had been intubated during hospitalization. Similar effects were found for the decision-making task. 43 44

Positive SARS-CoV-2 infection history and COVID-19 symptom severity are associated 45 with executive dysfunction among young and middle-aged adults with no history of medically induced 46 coma. These findings are evident on self-reported and task-related indicators of cognitive function. 47 48 Key words: SARS-CoV-2; COVID-19; brain; cognition; executive function 49 . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 10, 2022. ; https://doi.org/10.1101/2022.01.01.22268614doi: medRxiv preprint NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice. Executive dysfunction 2

50 Cognitive dysfunction is one of the potential adverse consequences of SARS-CoV-2 51 infection, and this risk may extend well below the age margins for increased mortality 52 risk. It is understood that SARS-CoV-2 could impact the brain through a number of non-53 exclusive, indirect mechanisms including hypoxia, thrombosis, coagulopathy, cytokine 54 storm, and megakaryocyte invasion.1–6 Studies of predominantly older, hospitalized 55 patients have revealed cognitive deficits in the areas of memory, spatial navigation, 56 attention, short-term memory, and executive function.5–7 Further, the cognitive 57 impairments following SARS-Cov-2 infection may persist after the acute phase of 58 infection,5 a phenomenon known as “long covid”.8,9 59 Several studies have reported reliable evidence of cognitive dysfunction among 60 those previously infected with SARS-CoV-2.7,10–13 However, some of these studies are 61 limited by non-representative samples and lack of comparison to non-infected controls 62 in the general population. Examination of a population-based sample including 63 asymptomatic and minimally symptomatic individuals, coupled with a control sample of 64 non-infected individuals from the same population facilitates quantification of the 65 reliability and magnitude of SARS-CoV-2 infection impacts on cognition, if they do 66 indeed exist. Beyond the above, relatively little is known about the extent to which 67 cognitive deficits are predicted by age or sex, as demographic moderators. The extent 68 to which SARS-CoV-2 adversely impacts cognitive function among younger and middle-69 aged adults is relatively unknown. Of particular interest are the executive functions, 70 which are especially susceptible to environmental and systemic insult. 71 Executive functions are partially supported by the lateral prefrontal cortex, as well as 72 the medial orbitofrontal cortex (mOFC). The mOFC is of particular interest, being the 73 brain subregion most anatomically close to the hypothesized point of SARS-CoV-2 74 neuroinvasion. Decision-making processes supported by the OFC can be best 75 assessed using decision-making paradigms with heavy temporal and evaluative 76 demands, such as a delay discounting task.14–17 Delay discounting is a neurobehavioral 77 process reflecting the extent to which future rewards are devalued based on their delay 78 in time18 and summarized relative balance between the prefrontal cortices and the 79 limbic systems.14 Greater delay discounting is reflected in the tendency to choose a 80 lower value option that is immediately available over a higher value option that is 81 delayed in time. 82 Prior studies have shown that damage to the mOFC is associated with increased 83 delay discounting.16,17 Impulsive choice of rewards is mediated by dopaminergic activity 84 within the mOFC,19 in contrast with choices to avoid punishment, which are mediated by 85 the lateral OFC.20 The most anterior aspect of the mOFC has further been proposed as 86 the subregion most clearly involved in processing of abstract rewards (e.g., money), in 87 contrast with the posterior mOFC, which is involved in computation of basic rewards 88 (e.g., food, physical pleasure).20 Importantly, the anterior mOFC is located immediately 89 superior to the olfactory bulb and nasal mucous membrane, the primary hypothesized 90 . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 10, 2022. ; https://doi.org/10.1101/2022.01.01.22268614doi: medRxiv preprint Executive dysfunction 3 sites for SARS-CoV-2 neuroinvasion, and the presumed source of symptoms of 91 anosmia and ageusia reported by some infected individuals.21 This may be a partial 92 explanation for the diverse neuropsychiatric symptoms22 displayed by many patients 93 with severe COVID-19. 94 The current study reports findings from a large national survey of adults in the 95 general population, who reported cognitive status, SARS-CoV-2 infection history, and 96 COVID-19 symptom severity. It was hypothesized based on prior research7,10–13 that 97 positive SARS-CoV-2 infection history would be associated with greater self-reported 98 cognitive dysfunction, and that severity of COVID-19 symptoms would be positively 99 correlated with severity of cognitive dysfunction, in a dose response manner. Finally, 100 based on the proximity of the mOFC to the hypothesized site of neuroinvasion of SARS-101 CoV-2, it was expected that deficits would be evident on a delay discounting task. 102 103 1. Methods 104 Participants 105 Participants were recruited as part of the Canadian COVID-19 Experiences Project 106 (CCEP)23, a multi-study project which includes a national cohort survey of 1,958 adults 107 aged 18 to 54. One research objective was to examine differences between fully 108 vaccinated and vaccine-hesitant individuals on a broad set of demographic, 109 psychosocial, and experiential variables. Thus, the cohort was recruited to have an 110 equal proportion of fully vaccinated and vaccine-hesitant Canadians: 50.2% received 111 two vaccine doses, 43.3% had received no doses, and 6.5% received one vaccine 112 dose, but were not intending to receive a second. The mean age was 37 (SD=10.4) and 113 60.8% were female. 114 Procedure 115 The survey was conducted from 28 September to 21 October 2021, when the 116 predominant SARS-CoV-2 variant in Canada was Delta (4 weeks prior to the 117 appearance of Omicron).24 Participants were contacted by email with an invitation to 118 participate in the survey. A link to the survey was provided for eligible participants, and 119 all measures were completed online following provision of informed consent. A quota 120 target of equal number of vaccinated and vaccine hesitant was applied to obtain a 121 balanced sample with respect to both vaccinated and vaccine-hesitant populations. 122 Within each quota target, the sample was recruited from ten Canadian provinces 123 through an online survey panel (Leger Opinion, the largest nationally representative 124 probability-based panel in Canada). The survey firm and University of Waterloo 125 monitored survey response in the sample of each quota to achieve the final 126 representative sample. This study was reviewed and received ethics clearance from the 127 institutional research ethics board of the University of Waterloo. 128 . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 10, 2022. ; https://doi.org/10.1101/2022.01.01.22268614doi: medRxiv preprint Executive dysfunction 4 Measures 129 Executive dysfunction. Symptoms of executive dysfunction were assessed using four 130 “self-restraint” subscale items from the Deficits in Executive Functioning Scale, short 131 form (BDEFS-SF)25. Respondents were asked how often they have experienced each 132 the four problems during the past 6 months, including “I am unable to inhibit my 133 reactions or responses to events or to other people”, “I make impulsive comments to 134 others”, “I am likely to do things without considering the consequences for doing them”, 135 and “I act without thinking”. Responses were indicated on a numerical scale where 1= 136 never or rarely, 2=sometimes, 3=often, and 4=very often. Cronbach’s alpha for the 4 137 items was 0.89, indicating acceptable reliability. The four executive dysfunction items 138 were averaged for this analysis to create a composite executive dysfunction measure. 139 Delay discounting. To assess delay discounting, participants competed a validated 5-140 trial delay discounting task wherein they were presented with a series of hypothetical 141 choices between a smaller monetary amount ($500) immediately or a larger amount 142 ($1,000) at various time delays (e.g.,1 month, 3 months).26 Delay discounting was 143 calculated as a k value, reflecting the steepness of a hyperbolic devaluation of delayed 144 rewards; higher values of k indicate more impulsive choice. 145 SARS-CoV-2 infection status: Infection status was assessed using the question “What 146 best describes YOUR experience with [SARS-CoV-2] infection?” where 1= I have NOT 147 been infected, 2 =I have been infected, and 3= not stated. 148 Symptom severity: COVID-19 symptom severity was assessed among those who have 149 been infected by SARS-CoV-2 using two questions. (1) “How do you know that you 150 HAVE BEEN infected with [SARS-CoV-2]?” responses were given the answers of 1= 151 had symptoms but did not get tested, 2= had symptoms and tested positive, and 3 = 152 had no symptoms but tested positive. (2) “How severe was your [SARS-CoV-2] illness?” 153 The five-point response scale was 1=not at all severe, 2=slightly severe, 3=moderately 154 severe, 4=very severe, 5=extremely severe. Those reporting “had no symptoms but 155 tested positive” were incorporated into the second question as 1=not at all severe. 156 Statistical analysis 157 Samples were post-stratified by geographic/language regions: Alberta, British Columbia, 158 Manitoba + Saskatchewan, Ontario, Quebec English, and Quebec French, and Atlantic 159 provinces (Nova Scotia, New Brunswick, Prince Edward Island, Newfoundland and 160 Labrador). For each of the vaccinated and vaccine hesitant group separately, sampling 161 weights were computed using a raking procedure and calibrated to target marginal joint 162 population distributions of the geographic/language regions, and the gender and age 163 group combinations, based on population figures in the 2016 Canadian census data and 164 the disposition code in the sample, thus allowing generalization to the Canadian 165 population. Survey linear regression models incorporating survey strata and weights 166 were applied to estimate composite executive dysfunction scores and their associations 167 with SARS-CoV-2 infection status and COVID-19 symptom severity. Regression models 168 . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 10, 2022. ; https://doi.org/10.1101/2022.01.01.22268614doi: medRxiv preprint Executive dysfunction 5 controlled for respondents’ gender and age groups (18-24, 25-39 and 40-54). All models 169 were conducted in SAS with SUDAAN V11. All confidence intervals (CI) and statistical 170 significance were assessed at the 95% confidence level. 171 172 173 2. Results 174 Baseline characteristics of the sample are presented in Table 1. The majority of the 175 participants were female (60%) and from the 25-39 (40%) or 40-54 (43%) age groups. 176 84% of participants reported that they had not been infected; those who reported having 177 been infected reported symptoms to be “not at all severe” (3%), “slightly severe” (2.4%), 178 “moderately severe” (2.7%), with relatively few experiencing “very/extremely severe” 179 symptoms (1%). The two cognitive measures were positively correlated (r=0.17, 180 p<.001). 181 Self-reported Executive Dysfunction 182 Those who reported a prior SARS-CoV-2 infection reported a significantly higher 183 number of symptoms of executive dysfunction (Madj=1.89, SE=0.08, CI: 1.74, 2.04; 184 n=175) than their non-infected counterparts (Madj=1.63, SE=0.08, CI: 1.47,1.80; 185 n=1,599; β =0.26, p=.001). Men were likely to experience more executive dysfunction 186 than women (β = 0.15, p<.001); younger adults (25-39 years) were more likely to 187 experience executive dysfunction than middle aged adults (40-54 years; β = 0.30, 188 p<.001). 189 Among those who were infected, there was a dose-response relationship between 190 COVID-19 symptom severity and executive dysfunction. Participants who reported 191 “moderately severe” (Madj = 1.85, 95% CI 1.63 – 2.08) and “very” or “extremely severe” 192 (Madj = 2.32, 95% CI 1.85 – 2.78) COVID-19 symptoms were significantly more likely to 193 have higher levels of executive dysfunction compared to non-infected individuals (Madj = 194 1.62, 95% CI 1.58 – 1.66) (Table 2). A dose-response relationship between COVID-19 195 symptom severity and cognitive dysfunction was evident, those with moderate (β =0.23, 196 CI: 0.003-0.46) and very/extremely severe (β = 0.69, CI: 0.22-1.16) COVID-19 197 symptoms being associated with significantly greater degrees of executive dysfunction, 198 compared to those not infected and those with asymptomatic infections (Figure 2). 199 Removing the those who reported having been intubated (n=5) or hospitalized without 200 intubation (n=5) did not change the findings. Likewise, following further adjustment for 201 vaccination status, income, and geographical region, those in the very/extremely severe 202 symptom categories continued to report significantly greater symptoms of executive 203 dysfunction than the non-infected reference group (β =0.71, 95% CI 0.22 - 1.19, p=.004). 204 Delay Discounting Task Performance 205 Participants infected with SARS-CoV-2 displayed significantly higher delay 206 discounting rates (k =1.22, SE=0.48, CI: 0.27, 2.16) than non-infected participants 207 (k=0.37, SE=0.08, CI: 0.21, 0.52; β =.31, p=.017; Table 3). With respect to dose-208 . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 10, 2022. ; https://doi.org/10.1101/2022.01.01.22268614doi: medRxiv preprint Executive dysfunction 6 response effects of symptom severity, among infected individuals, those reporting “very 209 severe” COVID-19 symptoms demonstrated significantly higher delay discounting rates 210 than those reporting no infection history, with the remaining severity categories falling 211 between these two values. Discount curves for infected versus non-infected, and 212 among severity levels ranging from asymptomatic and very severe are presented in 213 Figure 1 panel b. 214 In general, males had marginally steeper discount rates than females (β =-.10, 215 p=.066), and individuals reporting high incomes had significantly lower discounting rates 216 than individuals reporting low income (β =-.30, p<.001). No significant age differences in 217 k values were observed (see supplementary materials). No two-way interactions were 218 observed between sex and infection status predicting delay discounting were observed 219 (Wald F=0.09, p=0.91), or between age and infection status predicting delay discounting 220 (Wald F=0.90, p=0.46). Likewise, the three-way interaction term between sex, age and 221 infection status in predicting delay discounting was non-significant (Wald F=1.37, 222 p=0.22). 223 Sensitivity Analyses 224 Further adjustment for education and geographical region (i.e., province) had no 225 overall effect on the findings. In education and province-adjusted models, those 226 reporting a SARS-CoV-2 infection continued to show a significantly greater degree of 227 delay discounting than those non-infected (β =-0.32, CI:-0.57,-0.06, p=.014). Also similar 228 to earlier analyses, those in the “very severe” COVID-19 symptom severity category 229 showed greater discounting than those in the non-infected group (β =1.28, CI: 0.35,2.21, 230 p=.007). Likewise, removal of 5 cases reporting being placed on mechanical ventilator 231 did not change the effects of SARS-CoV-2 infection status (β =.23, CI: 0.01,0.45, 232 p=.043) or COVID-19 symptom severity (β =.95, CI: 0.20,1.71, p=.014) on delay 233 discounting rate. Finally, when limiting the “infected” group to only those whom reported 234 having their infection confirmed by a positive PCR test, the effect of SARS-CoV-2 235 infection remained significant, and somewhat stronger in magnitude (β =.40; CI: 0.07, 236 0.72, p=.016). 237 238 3. Discussion 239 In this population-representative cohort of community-dwelling adults, those with a 240 positive history of SARS-CoV-2 infection reported more symptoms of cognitive 241 dysfunction than those with no such history. This effect was evident on both self-242 reported symptoms of executive dysfunction and on a validated decision-making task. A 243 dose-response relationship between COVID-19 symptom severity and magnitude of 244 cognitive dysfunction was evident such that increasing infection severity was associated 245 with greater symptoms of cognitive dysfunction for both self-reported symptoms and 246 task performance. Importantly, reliable effects of positive SARS-CoV-2 infection history 247 and COVID-19 symptom severity on cognitive dysfunction were evident—on both 248 . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 10, 2022. ; https://doi.org/10.1101/2022.01.01.22268614doi: medRxiv preprint Executive dysfunction 7 measures—even in this sample of individuals not typically subject to age-related 249 cognitive decline (ages 18 to 54) and not exposed to medically induced coma via 250 hospital-based treatment for severe COVID-19. Our findings were similar to a prior 251 report of executive dysfunction as correlated with COVID-19 symptom severity in a 252 large population sample13, but extend them to include self-reported symptoms of 253 interpersonal significance, and a standardized decision making paradigm previously 254 linked to the site of hypothesized neuroinvasion of the SARS-CoV-2 virus (the mOFC; 255 Figure 1 panel A). 256 There are several hypothesized mechanisms by which SARS-CoV-2 infection may 257 produce cognitive dysfunction, including encephalitis, coagulopathy, cytokine storm, 258 hypoxia, and megakaryocyte invasion.4–6 The current investigation cannot distinguish 259 among these neurophysiological mechanisms, or others that may yet be identified. The 260 current findings do not preclude the possibility that symptoms of cognitive dysfunction 261 are influenced by reporting biases among those who are continuing to experience 262 emotional distress following the measurement period. Given that the effects of negative 263 mood on symptom reporting is causally established,27,28 and given that mood impacts of 264 the COVID-19 pandemic are well-documented,29–33 this possibility cannot be definitively 265 excluded. However, at least one prior population-based study has found similar dose-266 response effects using performance-based measures of cognitive function (i.e., 267 cognitive tasks rather than reported symptoms).7 It is further noteworthy that the same 268 patterns were evident on our decision-making task. 269 It is not clear why there appeared to be a stronger link between SARS-CoV-2 270 infection and cognitive dysfunction in younger adults as compared with middle-aged 271 adults. It is possible that such deficits were more salient to younger adults, given that a 272 higher proportion would be in educational programs wherein lapses in attention and 273 concentration may have been more impactful. In either case, it is not clear how 274 consequential symptoms of cognitive dysfunction would be expected to be, even if 275 reliable across studies. It is not uncommon for other types of viral infections to cause 276 symptoms of cognitive dysfunction, including the seasonal flu, herpes, MERS, Zika and 277 Varicella (chickenpox).34–38 Documenting the stability and functional impact of any 278 SARS-CoV-2 infection impairments in cognition will be important. However, in the 279 meantime, reductions in unnecessary exposure to SARS-CoV-2 infection may be an 280 important public health strategy even for young and middle aged adults, despite the 281 limited mortality risk. 282 Finally, given that the predominant SARS-CoV-2 variant during the time of the 283 survey was Delta, the findings are applicable only to the Delta and earlier variants. 284 Moreover, the retrospective nature of the study does not allow us to determine with 285 confidence which infections were attributable to Delta versus earlier variants. We also 286 cannot conclude that the same associations would be observed with the Omicron 287 variant, in particular because of the lower COVID-19 symptom severity apparent with 288 Omicron in comparison with earlier variants, at least based on early data.39–41 In the 289 . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 10, 2022. ; https://doi.org/10.1101/2022.01.01.22268614doi: medRxiv preprint Executive dysfunction 8 current (pre-Omicron) sample, we found that only moderate and higher COVID-19 290 symptom severities were associated with significantly elevated symptoms of executive 291 dysfunction. Further analyses of follow-up waves of the CCEP data will enable 292 examination of the relative impact of the Omicron variant on symptoms of executive 293 dysfunction. 294 Strengths and Limitations 295 There are several strengths of the current study. One strength is the use of a large 296 population-representative sample, consisting of infected individuals of a wide range of 297 disease symptom severities—ranging from asymptomatic to hospitalized—as well as 298 non-infected controls. Another strength is the use of a validated measure of subjective 299 symptomology assessing everyday function rather than more sensitive but less 300 ecologically valid performance-based measures. Finally, the finding of similar effects on 301 a decision-making task performance increases confidence that the findings were not a 302 function of self-report methodology alone. In terms of limitations, by virtue of the survey 303 format, it was not possible to validate the infection status of individuals by testing. This 304 may lead to under- or over-estimation of effect size and statistical significance of tests, 305 vis-a-vis misreporting of infection status. This is a limitation of many survey studies of 306 COVID-19 and cognitive dysfunction, however. Finally, the cross-sectional design limits 307 our ability to draw causal inferences. 308 Future studies should examine the longevity of cognitive dysfunction symptoms over 309 time, as well as the extent to which the dose-response and age gradients observed here 310 are replicable across samples. Finally, additional studies examining neurological 311 impacts at the level of the brain itself will be required, using functional brain imaging 312 paradigms to quantify structural and functional impacts of SARS-CoV-2 infection. In 313 particular studies are needed that follow individuals forward from the point of infection to 314 examine changes over time, in a prospective manner. 315

316 In summary, the current study used a population-representative sample consisting of 317 a balanced proportion of vaccinated and unvaccinated individuals to estimate the 318 association between SARS-CoV-2 infection and symptoms of cognitive dysfunction. 319 Findings indicated that individuals previously infected with SARS-CoV-2 reported 320 significantly greater symptoms of cognitive dysfunction than non-infected individuals. 321 Further, among those reporting a positive infection history, a dose-response relationship 322 between COVID-19 symptom severity and cognitive dysfunction was evident, such that 323 those with moderate to severe symptoms were more likely to experience symptoms of 324 cognitive dysfunction. The above pattern was evident for both self-reported symptoms 325 of cognitive dysfunction and performance on a decision-making task. Taken together 326 with findings from other studies, cognitive dysfunction appears to be a correlated of 327 SARS-CoV-2 infection, particularly among those with at least moderate COVID-19 328 symptom severity. If such cognitive effects are long-lasting, this may be one piece of 329 . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 10, 2022. ; https://doi.org/10.1101/2022.01.01.22268614doi: medRxiv preprint Executive dysfunction 9 evidence in support of public health strategies that eliminate exposure to SARS-CoV-2 330 infection, even for young adults and those below the typical high-risk age threshold for 331 mortality. 332 333 Research ethics statement 334 This study protocol was reviewed by and received approval from the University of 335 Waterloo Office of Research Ethics. 336 337 Funding statement 338 Funding for this study was provided by a grant from the Canadian Institutes of Health 339 Research (GA3-177733) to P. Hall (PI), G. Fong (co-PI) and S. Hitchman (co-I). 340 341 Data Availability Statement 342 Data will be available upon reasonable request to either of the corresponding authors. 343 344 Conflicts of Interests 345 The authors declare no conflicts of interest. 346 347

348 We thank Anne C.K. Quah and Thomas Agar for their assistance with survey design 349 and management. 350 351 Figure 1 Legend 352 Conceptual diagram (A) and delay discounting curves for non-infected and ranges of 353 COVID-19 symptom severity from asymptomatic to “very severe” (B). 354 355 Figure 2 Legend 356 Effects of SARS-CoV-2 infection status and COVID-19 symptom severity on BDEFS 357 scores; BDEFS=Barkley Deficits in Executive Functioning Scale. 358 359 . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 10, 2022. ; https://doi.org/10.1101/2022.01.01.22268614doi: medRxiv preprint Executive dysfunction 10 Table 1: Sample characteristics. 360 Variables n % Executive function (unadjusted) Executive function (adjusted) Mean, 95% CI Mean, 95% CI Gender Male 747 39.27 - - Female 1155 60.73 - - Age Group 18-24 313 16.46 - - 25-39 769 40.43 - - 40-54 820 43.11 - - Infection Status Not infected 1599 84.07 1.62 (1.58, 1.66) 1.62 (1.58, 1.66) Infected: Not at all severe 57 3.00 1.72 (1.52, 1.93) 1.73 (1.54, 1.91) Infected: Slightly severe 46 2.42 1.78 (1.44, 2.11) 1.75 (1.45, 2.05) Infected: Moderately severe 51 2.68 1.83 (1.60, 2.06) 1.85 (1.63, 2.08) Infected: Very/extremely severe 21 1.10 2.29 (1.82, 2.76) 2.32 (1.85, 2.78) Not stated 128 6.73 1.64 (1.46, 1.81) 1.63 (1.47, 1.80) Note: Executive dysfunction mean is the average of the four BDEFS items. Participants 361 who had no COVID-19 symptoms, but tested positive for SARS-CoV-2, were classified 362 as “not at all severe”. The adjusted parameters are adjusted by sex and group. Table 1 363 includes the sample used in the current analysis (N = 1,902). 364 365 366 . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 10, 2022. ; https://doi.org/10.1101/2022.01.01.22268614doi: medRxiv preprint Executive dysfunction 11 Table 2: Associations between SARS-CoV-2 infection status, COVID-19 symptom 367 severity and BDEFS scores. 368 Variables Beta (95% CI) p Gender Male 0.15 (0.07, 0.22) <0.001 Female Ref Ref Age Group 18-24 0.30 (0.19, 0.41) <0.001 25-39 0.06 (-0.02, 0.14) 0.138 40-54 Ref Ref COVID-19 Infection Status Not infected Ref Ref Infected: Not at all severe 0.10 (-0.09, 0.29) 0.284 Infected: Slightly severe 0.13 (-0.17, 0.42) 0.406 Infected: Moderately severe 0.23 (0.00, 0.46) 0.047 Infected: Very/Extremely severe 0.69 (0.22, 1.16) 0.004 Not stated 0.01 (-0.16, 0.18) 0.903 369 370 . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 10, 2022. ; https://doi.org/10.1101/2022.01.01.22268614doi: medRxiv preprint Executive dysfunction 12 Table 3: Associations between SARS-CoV-2 infection status, COVID-19 symptom 371 severity and delay discounting. 372 Variables Beta p Infection Status COVID-19 infection status Infected 0.31 (0.06, 0.56) 0.017 Not infected Ref Ref Not stated -0.01 (-0.22, 0.20) 0.91 Symptom Severity Gender Male -0.10 (-0.20, 0.01) 0.066 Female Ref Ref Age group 18-24 -0.04 (-0.18, 0.11) 0.618 25-39 0.01 (-0.11, 0.13) 0.893 40-54 Ref Ref Income Low Ref Ref Moderate 0.02 (-0.17, 0.21) 0.838 High -0.30 (-0.45, -0.16) <0.001 No answer -0.34 (-0.57, -0.12) 0.002 COVID-19 infection status Not infected Ref Ref Infected: Asymptomatic -0.01 (-0.29, 0.27) 0.934 Infected: Slightly severe 0.24 (-0.09, 0.57) 0.147 Infected: Moderately severe 0.34 (-0.11, 0.79) 0.141 Infected: Very severe 1.26 (0.31, 2.21) 0.009 Not stated -0.01 0.92 373 374 . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 10, 2022. ; https://doi.org/10.1101/2022.01.01.22268614doi: medRxiv preprint Executive dysfunction 13 Author Contributions 375 376 PH, GF, and SH conceived the study, planned and oversaw the statistical analyses, and 377 wrote the final draft. GM planned and completed all statistical analyses and contributed 378 to the writing of the final draft. MNS, AH, JM, and WB contributed to the writing of the 379 final draft. 380 381 . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 10, 2022. ; https://doi.org/10.1101/2022.01.01.22268614doi: medRxiv preprint Executive dysfunction 14

382 383 1. Boldrini M, Canoll PD, Klein RS. How COVID-19 Affects the Brain. JAMA 384 Psychiatry. 2021;78(6):682. doi:10.1001/jamapsychiatry.2021.0500 385 2. Mao L, Jin H, Wang M, et al. Neurologic Manifestations of Hospitalized Patients 386 With Coronavirus Disease 2019 in Wuhan, China. JAMA Neurol. 2020;77(6):683-387 690. doi:10.1001/jamaneurol.2020.1127 388 3. McFadyen JD, Stevens H, Peter K. The Emerging Threat of (Micro)Thrombosis in 389 COVID-19 and Its Therapeutic Implications. Circ Res. 2020;127(4):571-587. 390 doi:10.1161/CIRCRESAHA.120.317447 391 4. Nauen DW, Hooper JE, Stewart CM, Solomon IH. Assessing Brain Capillaries in 392 Coronavirus Disease 2019. JAMA Neurol. 2021;78(6):760-762. 393 doi:10.1001/jamaneurol.2021.0225 394 5. Ritchie K, Chan D. The emergence of cognitive COVID. World Psychiatry. 395 2021;20(1):52-53. doi:10.1002/wps.20837 396 6. Solomon T. Neurological infection with SARS-CoV-2 — the story so far. Nat Rev 397 Neurol. 2021;17(2):65-66. doi:10.1038/s41582-020-00453-w 398 7. Jaywant A, Vanderlind WM, Alexopoulos GS, Fridman CB, Perlis RH, Gunning FM. 399 Frequency and profile of objective cognitive deficits in hospitalized patients 400 recovering from COVID-19. Neuropsychopharmacology. 2021;46(13):2235-2240. 401 doi:10.1038/s41386-021-00978-8 402 8. Ladds E, Rushforth A, Wieringa S, et al. Persistent symptoms after Covid-19: 403 qualitative study of 114 “long Covid” patients and draft quality principles for 404 services. BMC Health Serv Res. 2020;20(1):1144. doi:10.1186/s12913-020-06001-405 y 406 9. Rubin R. As Their Numbers Grow, COVID-19 “Long Haulers” Stump Experts. 407 JAMA. 2020;324(14):1381-1383. doi:10.1001/jama.2020.17709 408 10. Becker JH, Lin JJ, Doernberg M, et al. Assessment of Cognitive Function in 409 Patients After COVID-19 Infection. JAMA Netw Open. 2021;4(10):e2130645. 410 doi:10.1001/jamanetworkopen.2021.30645 411 11. Liu YH, Wang YR, Wang QH, et al. Post-infection cognitive impairments in a cohort 412 of elderly patients with COVID-19. Mol Neurodegener. 2021;16(1):48. 413 doi:10.1186/s13024-021-00469-w 414 12. Almeria M, Cejudo JC, Sotoca J, Deus J, Krupinski J. Cognitive profile following 415 COVID-19 infection: Clinical predictors leading to neuropsychological impairment. 416 Brain Behav Immun - Health. 2020;9:100163. doi:10.1016/j.bbih.2020.100163 417 . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 10, 2022. ; https://doi.org/10.1101/2022.01.01.22268614doi: medRxiv preprint Executive dysfunction 15 13. Hampshire A, Trender W, Chamberlain SR, et al. Cognitive Deficits in People Who 418 Have Recovered from COVID-19 Relative to Controls: An N=84,285 Online Study.; 419 2020:2020.10.20.20215863. doi:10.1101/2020.10.20.20215863 420 14. McClure SM, Laibson DI, Loewenstein G, Cohen JD. Separate Neural Systems 421 Value Immediate and Delayed Monetary Rewards. Science. 2004;306(5695):503-422 507. doi:10.1126/science.1100907 423 15. Massar SAA, Libedinsky C, Weiyan C, Huettel SA, Chee MWL. Separate and 424 overlapping brain areas encode subjective value during delay and effort 425 discounting. NeuroImage. 2015;120:104-113. 426 doi:10.1016/j.neuroimage.2015.06.080 427 16. Peters J, D’Esposito M. Effects of Medial Orbitofrontal Cortex Lesions on Self-428 Control in Intertemporal Choice. Curr Biol. 2016;26(19):2625-2628. 429 doi:10.1016/j.cub.2016.07.035 430 17. Sellitto M, Ciaramelli E, di Pellegrino G. Myopic Discounting of Future Rewards 431 after Medial Orbitofrontal Damage in Humans. J Neurosci. 2010;30(49):16429-432 16436. doi:10.1523/JNEUROSCI.2516-10.2010 433 18. Bickel WK, Marsch LA. Toward a behavioral economic understanding of drug 434 dependence: delay discounting processes. Addiction. 2001;96(1):73-86. 435 doi:10.1046/j.1360-0443.2001.961736.x 436 19. Winstanley CA, Theobald DEH, Dalley JW, Cardinal RN, Robbins TW. Double 437 Dissociation between Serotonergic and Dopaminergic Modulation of Medial 438 Prefrontal and Orbitofrontal Cortex during a Test of Impulsive Choice. Cereb 439 Cortex. 2006;16(1):106-114. doi:10.1093/cercor/bhi088 440 20. Kringelbach ML, Rolls ET. The functional neuroanatomy of the human orbitofrontal 441 cortex: evidence from neuroimaging and neuropsychology. Prog Neurobiol. 442 2004;72(5):341-372. doi:10.1016/j.pneurobio.2004.03.006 443 21. Vaira LA, Salzano G, Deiana G, De Riu G. Anosmia and Ageusia: Common 444 Findings in COVID-19 Patients. The Laryngoscope. 2020;130(7):1787-1787. 445 doi:10.1002/lary.28692 446 22. Taquet M, Geddes JR, Husain M, Luciano S, Harrison PJ. 6-month neurological 447 and psychiatric outcomes in 236/i2 379 survivors of COVID-19: a retrospective 448 cohort study using electronic health records. Lancet Psychiatry. 2021;8(5):416-427. 449 doi:10.1016/S2215-0366(21)00084-5 450 23. Hall P, Fong G, Hitchman S. The Canadian COVID-19 Experiences Survey: Study 451 Protocol. medRxiv. Published online 2021. 452 24. Canada PHA of. COVID-19 daily epidemiology update. aem. Published April 19, 453 2020. Accessed January 2, 2022. https://health-infobase.canada.ca/covid-454 . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 10, 2022. ; https://doi.org/10.1101/2022.01.01.22268614doi: medRxiv preprint Executive dysfunction 16 19/epidemiological-summary-covid-19-455 cases.html?stat=rate&measure=total_last14&map=pt 456 25. Barkley RA. Barkley Deficits in Executive Functioning Scale (BDEFS). Guilford 457 Press; 2011. 458 26. Koffarnus MN, Bickel WK. A 5-trial adjusting delay discounting task: Accurate 459 discount rates in less than one minute. Exp Clin Psychopharmacol. 460 2014;22(3):222-228. doi:10.1037/a0035973 461 27. Howren MB, Suls J. The symptom perception hypothesis revised: Depression and 462 anxiety play different roles in concurrent and retrospective physical symptom 463 reporting. J Pers Soc Psychol. 20110110;100(1):182. doi:10.1037/a0021715 464 28. Reimers S, Maylor EA, Stewart N, Chater N. Associations between a one-shot 465 delay discounting measure and age, income, education and real-world impulsive 466 behavior. Personal Individ Differ. 2009;47(8):973-978. 467 doi:10.1016/j.paid.2009.07.026 468 29. Czeisler MÉ, Lane RI, Petrosky E, et al. Mental Health, Substance Use, and 469 Suicidal Ideation During the COVID-19 Pandemic — United States, June 24–30, 470 2020. Morb Mortal Wkly Rep. 2020;69(32):1049-1057. 471 doi:10.15585/mmwr.mm6932a1 472 30. Xiong J, Lipsitz O, Nasri F, et al. Impact of COVID-19 pandemic on mental health 473 in the general population: A systematic review. J Affect Disord. 2020;277:55-64. 474 doi:10.1016/j.jad.2020.08.001 475 31. Duan L, Shao X, Wang Y, et al. An investigation of mental health status of children 476 and adolescents in china during the outbreak of COVID-19. J Affect Disord. 477 2020;275:112-118. doi:10.1016/j.jad.2020.06.029 478 32. Daly M, Sutin AR, Robinson E. Longitudinal changes in mental health and the 479 COVID-19 pandemic: evidence from the UK Household Longitudinal Study. 480 Psychol Med. Published online November 13, 2020:1-10. 481 doi:10.1017/S0033291720004432 482 33. Hall PA, Sheeran P, Fong GT, et al. Biobehavioral Aspects of the COVID-19 483 Pandemic: A Review. Psychosom Med. 2021;83(4):309-321. 484 doi:10.1097/PSY.0000000000000932 485 34. Goenka A, Michael BD, Ledger E, et al. Neurological Manifestations of Influenza 486 Infection in Children and Adults: Results of a National British Surveillance Study. 487 Clin Infect Dis. 2014;58(6):775-784. doi:10.1093/cid/cit922 488 35. Kim JE, Heo JH, Kim H ok, et al. Neurological Complications during Treatment of 489 Middle East Respiratory Syndrome. J Clin Neurol. 2017;13(3):227. 490 doi:10.3988/jcn.2017.13.3.227 491 . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 10, 2022. ; https://doi.org/10.1101/2022.01.01.22268614doi: medRxiv preprint Executive dysfunction 17 36. de Araújo TVB, Rodrigues LC, de Alencar Ximenes RA, et al. Association between 492 Zika virus infection and microcephaly in Brazil, January to May, 2016: preliminary 493 report of a case-control study. Lancet Infect Dis. 2016;16(12):1356-1363. 494 doi:10.1016/S1473-3099(16)30318-8 495 37. Berger JR, Houff S. Neurological Complications of Herpes Simplex Virus Type 2 496 Infection. Arch Neurol. 2008;65(5). doi:10.1001/archneur.65.5.596 497 38. Gilden DH, Kleinschmidt-DeMasters BK, LaGuardia JJ, Mahalingam R, Cohrs RJ. 498 Neurologic Complications of the Reactivation of Varicella–Zoster Virus. N Engl J 499 Med. 2000;342(9):635-645. doi:10.1056/NEJM200003023420906 500 39. Christie B. Covid-19: Early studies give hope omicron is milder than other variants. 501 BMJ. 2021;375:n3144. doi:10.1136/bmj.n3144 502 40. Abdullah F, Myers J, Basu D, et al. Decreased severity of disease during the first 503 global omicron variant covid-19 outbreak in a large hospital in tshwane, south 504 africa. Int J Infect Dis. Published online December 2021:S120197122101256X. 505 doi:10.1016/j.ijid.2021.12.357 506 41. Sheikh A, Kerr S, Woolhouse M, McMenamin J, Robertson C. Severity of Omicron 507 variant of concern and vaccine effectiveness against symptomatic disease: national 508 cohort with nested test negative design study in Scotland. Published online 509 December 22, 2021. Accessed January 2, 2022. 510 https://www.research.ed.ac.uk/en/publications/severity-of-omicron-variant-of-511 concern-and-vaccine-effectiveness- 512 513 . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 10, 2022. ; https://doi.org/10.1101/2022.01.01.22268614doi: medRxiv preprint . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 10, 2022. ; https://doi.org/10.1101/2022.01.01.22268614doi: medRxiv preprint . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted January 10, 2022. ; https://doi.org/10.1101/2022.01.01.22268614doi: medRxiv preprint