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Psychiatric and neuropsychiatric sequelae of COVID-19 within 2 years: a multinational cohort study

BMC Medicine volume 23, Article number: 144 (2025) Cite this article

Abstract

Background

The long-term psychiatric and neuropsychiatric sequelae of COVID-19 across diverse populations remain not fully understood. This cohort study aims to investigate the short-, medium-, and long-term risks of psychiatric and neuropsychiatric disorders following COVID-19 infection in five countries.

Methods

This population-based multinational network study used electronic medical records from France, Italy, Germany, and the UK and claims data from the USA. The initial target and comparator cohorts were identified using an exact matching approach based on age and sex. Individuals diagnosed with COVID-19 or those with a positive SARS-CoV-2 screening test between December 1, 2019, and December 1, 2020, were included as targets. Up to ten comparators without COVID-19 for each target were selected using the propensity score matching approach. All individuals were followed from the index date until the end of continuous enrolment or the last healthcare encounter. Cox proportional hazard regression models were fitted to estimate the risk of incident diagnosis of depression, anxiety disorders, alcohol misuse or dependence, substance misuse or dependence, bipolar disorders, psychoses, personality disorders, self-harm and suicide, sleep disorders, dementia, and neurodevelopmental disorders within the first 6 months (short-term), 6 months to 1 year (medium-term), and 1 to 2 years (long-term) post-infection.

Results

A total of 303,251 individuals with COVID-19 and 22,108,925 individuals without COVID-19 from five countries were originally included. Within the first 6 months, individuals with COVID-19 had a significantly higher risk of any studied disorders in all databases, with Hazard Ratios (HRs) ranging from 1.14 (95% CI, 1.07–1.22) in Germany to 1.89 (1.64–2.17) in Italy. Increased risks were consistently observed for depression, anxiety disorders, and sleep disorders across almost all countries. During the medium- and long-term periods, higher risks were observed only for depression (medium-term: 1.29, 1.18–1.41; long-term: 1.36, 1.25–1.47), anxiety disorders (medium-term: 1.29, 1.20–1.38; long-term: 1.37, 1.29–1.47), and sleep disorders (medium-term: 1.10, 1.01–1.21; long-term: 1.14, 1.05–1.24) in France, and dementia (medium-term: 1.65, 1.28–2.10) in the UK.

Conclusions

Our study suggests that increased risks of psychiatric and neuropsychiatric outcomes were consistently observed only within, and not after, the 6-month observation period across all databases, except for certain conditions in specific countries.

Peer Review reports

Background

The COVID-19 pandemic has had unprecedented impacts on global health. In addition to its physical health consequences, concerns have been raised regarding the potential psychiatric and neuropsychiatric complications following infection [1,2,3,4,5]. Studies have indicated that SARS-CoV-2 can directly invade the central nervous system or trigger an immune response that leads to inflammation and subsequent psychiatric and neuropsychiatric manifestations [6,7,8,9]. Furthermore, psychosocial stressors associated with the pandemic, such as social isolation, financial insecurity, and fear of illness, may contribute to a higher incidence of psychiatric symptoms [5, 10, 11].

Several studies have examined the association between COVID-19 infection and psychiatric and neuropsychiatric disorders [3, 12,13,14,15]. Three USA-based studies using population-based electronic medical records found that COVID-19 infection was associated with an increased risk of psychiatric and neuropsychiatric diagnoses within 6 months post-infection, highlighting a particular vulnerability to mood disorders, anxiety disorders, psychotic disorders, substance use disorders, insomnia, and dementia among individuals with COVID-19 [12, 13, 15]. A recent study included over 400,000 individuals from the UK Biobank database between March 1, 2020, and September 30, 2021, and found that individuals with COVID-19 were more likely to receive subsequent diagnoses of psychotic, mood, anxiety, alcohol use, and sleep disorders than their COVID-19-free counterparts during the 1-year follow-up period [14]. Furthermore, a binational study indicated that during a follow-up period of up to 28 months, COVID-19 infection was associated with a higher risk of psychiatric disorders, including anxiety disorders and post-traumatic stress disorders, in the UK and Hong Kong [16].

While these studies provide valuable insights into the psychiatric and neuropsychiatric sequelae of COVID-19, most have limited follow-up periods, leaving knowledge gaps regarding the post-acute sequelae of SARS-CoV-2. Additionally, the generalizability of findings from specific countries, predominantly the USA and the UK, to other regions is uncertain due to varying healthcare systems and public health responses to the pandemic. Therefore, findings generated from multiple populations and diverse healthcare systems, with large sample sizes, extended follow-up periods, standardized study designs, and a broader range of psychiatric and neuropsychiatric outcomes, are essential to enhance the current understanding of the psychiatric and neuropsychiatric sequelae of COVID-19 [17].

This population-based multinational network study aims to comprehensively investigate the short-, medium-, and long-term psychiatric and neuropsychiatric sequelae of COVID-19 using electronic medical records and claims data from over 25 million individuals across five countries. This investigation sheds light on the potential psychiatric and neurological effects of COVID-19 at various stages, thereby informing the development of effective prevention and management strategies for affected individuals.

Methods

Data sources

We used data from five databases. These comprised four electronic medical record databases, the IQVIA Longitudinal Patient Database France (France IQVIA), IQVIA Disease Analyser Germany (Germany IQVIA), Longitudinal Patient Database Italy (Italy IQVIA), and IQVIA Medical Research Data UK (UK IMRD). The fifth database was the IQVIA PharMetrics Plus in the USA (US PharMetrics Plus), a claims-based database. All data were routinely collected and converted to the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM), version 5, maintained by the Observational Health Data Sciences and Informatics (OHDSI) network [18]. The standardized structure and content of these databases allow data partners to execute common analytical syntax locally and contribute aggregated results without sharing individual-level data. The databases used in this study are all population-based databases covering patients with diverse socioeconomic characteristics. These databases have been extensively used in previous studies to assess the physical and psychological consequences of the COVID-19 pandemic [19,20,21]. Detailed descriptions of these databases, including their representativeness and comparability, are presented in Additional file 1: Table S1 and have been previously reported [20,21,22].

Study design and participants

This study used data between December 1, 2018, and December 1, 2022. We identified target and comparator cohorts using an exact matching approach based on age and sex. The target cohort consisted of all individuals who received a diagnosis of COVID-19 or a positive SARS-CoV-2 screening test result between December 1, 2019, and December 1, 2020. Targets with any negative SARS-CoV-2 screening test results within 3 days of the index date were excluded to eliminate potential false positives. The diagnostic codes for identifying individuals with COVID-19 were determined through internal and external consultations with epidemiologists, clinicians, and data scientists, and the list was further adjusted during the preliminary testing process. Additional file 1: Table S2 shows the final list of diagnostic codes. The initial comparator cohort included individuals without any diagnosis or positive test results for COVID-19 between December 1, 2019, and December 1, 2022. The earliest date of COVID-19 confirmation was designated as the index date for the targets, and the same dates were assigned as the index date for their corresponding matched comparators.

Individuals were eligible for the study if they had continuous observation for at least 365 days prior to the index date and at least 1 day after the index date. A maximum of ten comparators for each target were selected using the propensity score matching approach, although some targets may have fewer than ten comparator candidates. The standardized difference of mean was used to assess the covariate balance between target and comparator cohorts, with a threshold of 0.2 [23]. The propensity scores were calculated based on a wide range of predefined generic characteristics, including demographics, diagnoses, drug exposures, measurement, medical procedures, and health service use behaviors observed 365 days prior to and on the index date [24, 25]. A large-scale regularized regression was employed for covariate selection and propensity score calculation, which has been widely used in previous research for confounding adjustment [25,26,27,28]. All individuals were followed from the index date until the end of continuous enrolment (for UK IMRD and US PharMetrics Plus) or the last healthcare encounter (for France IQVIA, Germany IQVIA, and Italy IQVIA). Our preliminary analysis identified 805,065 targets and 39,754,216 comparators in the US PharMetrics Plus database. Due to computational limitations, we used a stratified random sampling approach to select 20% of individuals from the target and comparator cohorts within each age and sex stratum for the US PharMetrics Plus database.

Outcomes

The study outcomes included depression, anxiety disorders, alcohol misuse or dependence, substance misuse or dependence, bipolar disorders, psychoses, personality disorders, self-harm and suicide, sleep disorders, dementia, and neurodevelopmental disorders. The corresponding diagnostic codes are shown in Additional file 1: Table S3. Only the first diagnosis of each outcome following the index date was used. We also estimated the risk of any of the 11 outcomes to assess the overall psychiatric and neuropsychiatric sequelae of COVID-19.

Statistical analysis

The short-, medium-, and long-term periods were defined as 6 months, 6 months to 1 year, and 1 to 2 years since the index date, respectively. For the analysis of each outcome, individuals were excluded if they had the outcome of interest within 365 days prior to the start of the short- (the index date), medium-, and long-term observation to ensure the identification of incident cases. We used the term “incident” broadly to represent a first-ever diagnosis and a potentially prevalent diagnosis that became active after at least 365 days. The exclusion was performed before the propensity score matching step. We tabulated baseline characteristics to evaluate covariate balance before and after propensity score adjustment and report the incidence of outcomes by disease and database. Cox proportional hazards regression models were fitted to quantify the short-, medium-, and long-term associations between each outcome of interest and COVID-19 infection. All parameters are expressed as hazard ratios (HRs) with 95% confidence intervals (95% CIs). Two-sided P values of 0.05 or below were considered indicative of statistical significance. We further stratified the analyses by sex and age group (i.e., < 18, 18–24, 25–44, 45–64, and 65 + years) to examine potential differences in associations related to sex and age [29, 30].

All analyses were conducted using statistical software R (version 4.2.0) [31]. The analysis packages were built on the open-source OHDSI CohortMethod and Cyclops R packages [26, 32, 33]. The study protocol and all statistical analysis packages were prespecified before the analysis. The data are reported following the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline [34].

Role of the funding source

The funders of this study had no role in the study design, data collection, data analysis, interpretation, or writing of the report.

Results

We initially identified 303,251 individuals with COVID-19 and 22,108,925 individuals without COVID-19 across five countries during the study period. Figure S1 in Supplement shows the study cohort selection procedure. After applying inclusion and exclusion criteria and conducting propensity score matching, the sample size varied by follow-up period, outcome, and database (Table 1). In the target cohorts, the majority of individuals included for the 6-month risk analysis were females and aged 45–64 years across all databases. The proportion of females ranged from 56.65% (N = 30,181) for substance misuse or dependence in France to 45.76% (1382) for personality disorders in the Germnay. The proportion of individuals aged 45–64 years ranged from 41.11% (3423) for personality disorders in Italy to 31.33% (11,131) for sleep disorders in the UK.

Table 1 Sample size, age and sex distribution, follow-up time, the number of psychiatric and neuropsychiatric events, and incidence rate in the short-term observation period by outcome and database
Full size table

The short-term (6 months) incidence rate was generally high for anxiety disorders, depression, and sleep disorders. The highest incidence of 130.16 per 1000 person-years was observed among individuals with COVID-19 for anxiety disorders in the USA, followed by 85.5 per 1000 person-years for anxiety disorders in France and 84.87 per 1000 person-years for sleep disorders in the USA. No self-harm and suicide cases were observed in Germany and Italy. Additional file 1: Tables S4–S5 show the sample size, sex and age distribution, follow-up time, and number and incidence of psychiatric and neuropsychiatric events for the medium- and long-term observation periods. The incidence of outcomes in the medium- and long-term observation periods was lower than the short-term results. The incidence of any outcome among individuals with COVID-19 for the short-, medium-, and long-term periods ranged from 40.71, 28.73, and 27.67 per 1000 person-years in the UK, to 243.41, 144.11, and 119.95 per 1000 person-years in the USA, respectively.

Table 2 shows selected baseline characteristics before and after propensity score matching for France IQVIA, using short-term depression risk as an example. Before propensity score matching, individuals with COVID-19 were more likely to have acute respiratory disease and use antibacterial, anti-inflammatory, antirheumatic, and opioid products, with standardized difference of mean up to 0.77. After propensity score matching, all standardized differences were less than 0.2, and most were less than 0.1, indicating that the samples of individuals with and without COVID-19 were well-balanced after matching. Additional file 1: Tables S6.1–S6.179 show the baseline characteristics for all outcomes in all databases, which had similar results.

Table 2 Selected baseline characteristics for France IQVIA, using short-term depression risk as an example
Full size table

Figure 1 and Additional file 1: Table S7 show the short-term risks of psychiatric and neuropsychiatric outcomes. During the first 6 months following the index date, individuals with COVID-19 had a significantly higher risk of developing any psychiatric and neuropsychiatric disorder than individuals without COVID-19 across all databases. The HRs ranged from 1.14 (95% CI, 1.07–1.22) in Germany to 1.89 (1.64–2.17) in Italy. Specifically, the risk of depression was higher in individuals with COVID-19 in all databases except for the UK, with HRs ranging from 1.05 (1.01–1.09) in the USA to 1.90 in Italy (1.55–2.31). Significant HRs for anxiety disorders were found in all databases except for Germany, ranging from 1.18 (1.14–1.21) in the USA to 2.43 (1.61–3.61) in Italy. An increased risk of psychoses was observed in Italy (HR 2.39, 95% CI 1.09–4.85) and the USA (1.41, 1.17–1.70). Increased risks of substance misuse or dependence and personality disorders were found among individuals with COVID-19 in the USA (1.14, 1.08–1.19) and Italy (1.55, 1.04–2.25), respectively. Additionally, COVID-19 was associated with an elevated risk of sleep disorders in France (1.34, 1.25–1.44), Italy (1.73, 1.39–2.14), and the USA (1.21, 1.16–1.25). Individuals with COVID-19 had an increased risk of dementia in the UK (1.86, 1.50–2.28), France (1.84, 1.12-2.91), and the USA (1.43, 1.26–1.63). A significant HR for neurodevelopmental disorders was observed only in France (2.20, 1.65–2.91).

Fig. 1
figure 1

Risk of developing outcome events among individuals with COVID-19 in the short-term observation period (within 6 months)

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No significant associations were observed between COVID-19 and any of the psychiatric and neuropsychiatric disorders in the medium-term (6 months to 1 year) or long-term (1 to 2 years) periods, except for France (medium-term: HR 1.26, 95% CI 1.19–1.34; long-term: 1.34, 1.27–1.41) (see Figs. 2 and 3 and Additional file 1: Table S7). In France IQVIA, individuals with COVID-19 had a higher risk of depression (HR 1.29, 95% CI 1.18–1.41), anxiety disorders (1.29, 1.20–1.38), and sleep disorders (1.10, 1.01–1.21) during the medium-term observation, compared to matched comparators. Additionally, in the UK, an elevated risk of dementia (1.65, 1.28–2.10) was observed during the medium-term. In the long-term, elevated risks were only observed for depression (1.36, 1.25–1.47), anxiety disorders (1.37, 1.29–1.47), and sleep disorders (1.14, 1.05–1.24) in France.

Additional file 1: Tables S8–S14 show the results of subgroup analyses. The risk of psychiatric and neuropsychiatric disorders associated with COVID-19 varied by sex and age group. For example, in the UK, there was an increased short-term risk of anxiety disorders (HR 1.59, 95% CI 1.24–2.01) and bipolar disorders (5.15, 1.35–17.09) among males, but not females.

Fig. 2
figure 2

Risk of developing outcome events among individuals with COVID-19 in the medium-term observation period (6 months to 1 year)

Full size image
Fig. 3
figure 3

Risk of developing outcome events among individuals with COVID-19 in the long-term observation period (1 year to 2 years)

Full size image

Additionally, a significantly higher short-term risk of substance misuse or dependence (HR 1.26, 1.18–1.34) was observed only among males in the USA. In age group-stratified analyses for short-, medium-, and long-term risks, significant HRs for sleep disorders were only observed among individuals aged 25 years or older in France, Italy, and the USA. An elevated risk of substance misuse or dependence was observed among individuals aged 18–44 years and those aged 65 years or older in Italy and the USA.

Discussion

In this multinational network study using population-based electronic medical records and claims data from four European countries and the USA, we compared the short-, medium-, and long-term risks of 11 psychiatric and neuropsychiatric disorders of individuals with and without COVID-19. During the first 6 months post-infection, an overall increased risk of psychiatric and neuropsychiatric disorders was evident across all databases, with increased risks consistently observed in depression, anxiety disorders, and sleep disorders. Increased risks were only observed for depression, anxiety disorders, sleep disorders in France, and dementia in the UK, in the medium- and long-term observation periods.

Previous studies have consistently demonstrated that a considerable number of individuals infected with COVID-19 suffer from mental and neurological health issues extending weeks to months beyond the acute phase of the illness. For instance, a meta-analysis of 51 studies involving approximately 19,000 subjects found that 27.4% of COVID-19 survivors experienced sleep disorders, 20.2% had cognitive impairment, 19.1% had anxiety disorders, and 12.9% had depression following the infection [35]. Furthermore, studies from Denmark, Estonia, Iceland, Norway, Sweden, the UK, and the USA indicated an increased risk of psychiatric and neuropsychiatric sequelae in COVID-19 survivors compared to those uninfected by the virus or those suffering from influenza or other respiratory infections [9, 12,13,14]. However, most of these studies had a follow-up period of less than 1 year, thus not necessarily capturing the potential long-term consequences or accounting for the possibility of delayed help-seeking due to barriers in accessing mental health services. Additionally, the applicability of these findings may be limited by variations in how the index date is determined and the absence of standardized measurements or tools for identifying outcomes [36, 37]. By applying standardized definitions and analytical codes across five population-based databases, our study contributes multinational, large-scale evidence on the psychiatric and neuropsychiatric consequences associated with COVID-19 during a 2-year post-infection timeframe.

Our study found that individuals with COVID-19 showed an increased likelihood of developing psychiatric and neuropsychiatric disorders within the 6 months following infection, consistent with existing research on COVID [9, 12,13,14], mirroring outcomes observed during past coronaviruses outbreaks [8], and supporting the direct and indirect impact of COVID-19 on mental and neuropsychiatric health. While some studies have suggested that immune dysfunction, including nonspecific neuroinflammation and antineural autoimmune dysregulation, may be associated with the psychiatric and neuropsychiatric sequelae of SARS-CoV-2 during the acute phase of the disease [38,39,40], the pathophysiological mechanisms underlying these manifestations still remain poorly understood. Additionally, pandemic-related psychosocial stressors, such as unprecedented social isolation due to lockdowns and quarantine, financial insecurity from economic downturns, and grief over the loss of loved ones might have contributed to psychiatric symptoms, although the impact should be similar between individuals with and without COVID-19 [41,42,43,44,45]. It is worth noting that our study focused on individuals infected by the early strain of COVID-19 in 2020, a period associated with greater disease severity [46]. The fear of illness, lack of vaccines, disrupted daily routines, and stigma associated with COVID-19 infection leading to social ostracization, further contributed to the psychological burden and heightened the risk of psychiatric manifestations among individuals with COVID-19 [47, 48].

While our investigation revealed several psychiatric and neuropsychiatric sequelae of COVID-19 in the 6 months following infection, significant differences in risk were observed only for depression, anxiety disorders and sleep disorders in France, and dementia in the UK during the medium- and long-term observation periods. This finding is partly consistent with a previous USA study, which reported that the risks of mood disorders, anxiety disorders, and insomnia associated with COVID-19 decreased 1 to 3 months after the infection, while the risks of dementia and psychotic disorder remained elevated after 2 years [15]. The attenuation of risk can be attributed to several reasons. First, individuals with an incident diagnosis of psychiatric and neuropsychiatric disorder during the first 6 months post-infection were excluded from the mid- and long-term analyses. Therefore, the risks after 6 months might be lower if an individual already “survived” the acute phase of the pandemic. Second, physical status gradually recovers over time, which includes the alleviation of the virus’s direct neurological effects that may have initially led to such disorders [49, 50]. Third, as the pandemic progressed, individuals adapted to the psychosocial stressors triggered by the pandemic. People have found appropriate coping mechanisms and adjusted to changed circumstances, reducing the impact of these stressors on mental health [51, 52]. Fourth, as public health measures control the spread of the virus and vaccines become widely available, the initial fear and uncertainty surrounding COVID-19 and its consequences diminish. Additionally, the implementation of specialized mental health services for COVID-19 survivors helps address and mitigate the long-term psychiatric and neuropsychiatric effects of the virus. However, explaining the considerable heterogeneity in relative risks between countries remains challenging, as the mechanisms underlying the association between COVID-19 infection and psychiatric and neuropsychiatric outcomes are not yet fully understood [38,39,40]. The significant medium- and long-term increased risks observed in France and the UK may reflect the diverse impacts of differences in COVID-19 containment strategies, health systems, and rates of socioeconomic recovery by country, rather than the pandemic itself. Furthermore, the results may be partially influenced by detection bias, given the severe underdiagnosis and considerable diagnostic delays associated with psychiatric and neuropsychiatric disorders. For instance, the longer effect on dementia observed in the UK could simply result from longer waiting times for dementia assessments. Further research is required to explore the causes of this discrepancy to mitigate potential long-lasting impacts.

Our study has several strengths. By utilizing data from over 25 million individuals across five countries and diverse healthcare settings, we have enabled a comprehensive investigation into the short-, medium-, and long-term psychiatric and neuropsychiatric sequelae of COVID-19. These enhance the precision, representativeness, and generalizability of our findings. To minimize potential confounding, we incorporated a significant amount of covariates into a large-scale regularized regression for covariate selection and propensity score calculation. Furthermore, using the OMOP CDM allowed us to standardize the study design, outcome definition, and analytical syntax within participating data partners. This standardization streamlined the process of generating and sharing results without disclosing individual-level data. It is important to note that our intention is not to compare the incidence or risks among different populations and healthcare systems, as database-specific properties are not comparable. Additionally, we have made the study package publicly available to encourage the reproduction of our findings and to foster collaboration.

This study has limitations. First, phenotype ascertainment may be affected by the inherent measurement issues within our real-world databases. Although we used standardized diagnostic codes to identify outcomes, heterogeneity in diagnostic accuracy and coding processes across different healthcare settings persisted. Moreover, the specific diagnostic codes within the original data sources have not been validated, and their sensitivity and specificity require further exploration [53]. Second, electronic medical record databases from four European countries (France, Italy, Germany, and the UK) were collected from primary care settings, which means inpatient records were not available for this study. Consequently, we could not capture outcomes diagnosed during hospital admissions. Third, several factors associated with the sequelae of COVID-19, such as infection severity, vaccination, and mortality, were not available in our databases, preventing detailed investigations into the effects of these factors on COVID-19 sequelae. Fourth, individuals in the comparator group might have had undiagnosed COVID-19 infection. To minimize the misclassification effect, we included all individuals with a COVID-19 diagnosis in healthcare institutions and positive SARS-CoV-2 screening test results from lab tests and adjusted the coding list for COVID-19 individuals’ ascertainment during the data testing process. Fifth, we only considered incident psychiatric and neuropsychiatric diagnoses. Individuals who sought help repeatedly (with prolonged and more severe symptoms) were excluded from the mid- and long-term analysis, potentially resulting in an underestimation of the results. Sixth, our study only included unvaccinated individuals infected with COVID-19 in 2020, most of whom likely had no prior infection. Caution is warranted when generalizing our findings to other populations, as clinical consequences may differ between primary infections, reinfections, and breakthrough infections. Seventh, due to dataset limitations, we were only able to use a 1-year look-back period to exclude prevalent cases. As a result, some included individuals may not be “true” incident cases. Eighth, this study aimed to provide an overview of the association between psychiatric and neuropsychiatric disorders and COVID-19 across multiple databases, grouping outcomes of interest into 11 relatively broad disease categories. This approach was intended to ensure sufficient statistical power in each database and to simply reporting. However, it is possible that specific conditions within a category may have distinct associations with COVID-19, warranting future investigations. Finally, as with other observational studies, residual confounding was likely present in our study. For instance, individuals without COVID-19 infection were less likely than those with COVID-19 to present at healthcare institutions during the pandemic, reducing the probability of receiving diagnoses for other conditions and potentially overestimating our results.

Conclusions

In this multinational network cohort study examining the short- (6 months), medium- (6 months to 1 year), and long-term (1 to 2 years) psychiatric and neuropsychiatric sequelae of COVID-19, we consistently observed short-term risks of these conditions associated with COVID-19 across different countries. Notably, there were very few differences in these risks between individuals with and without COVID-19 infection after 6 months. This phenomenon may be attributed to detection bias, the redirection of healthcare resources, diverse pandemic management strategies, and differing rates of socioeconomic recovery rather than the direct impact of COVID-19 itself. These findings underscore the complexity of the pandemic’s indirect effects on mental health. Further research is essential to elucidate the underlying causes of the medium- and long-term elevated risks of psychiatric and neuropsychiatric outcomes observed in France and the UK. Understanding these factors is crucial for developing targeted interventions and healthcare policies to mitigate these long-lasting impacts.

Data availability

Data are not available as the data custodians have not permitted data sharing due to patient confidentiality and privacy concerns.

Abbreviations

France IQVIA:

IQVIA Longitudinal Patient Database France

Germany IQVIA:

IQVIA Disease Analyser Germany

Italy IQVIA:

Longitudinal Patient Database Italy

UK IMRD:

IQVIA Medical Research Data UK

US PharMetrics Plus:

IQVIA PharMetrics Plus in the USA

OMOP CDM:

Observational Medical Outcomes Partnership Common Data Model

OHDSI:

Observational Health Data Sciences and Informatics

HRs:

Hazard Ratios

CIs:

Confidence Intervals

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Acknowledgements

Not applicable.

Funding

This work was supported by the Collaborative Research Fund, University Grants Committee, HKSAR Government (C7154-20GF).

Author information

Author notes

  1. Yi Chai and Ivan C. H. Lam are co-first authors.

Authors and Affiliations

  1. School of Public Health, Shenzhen University Medical School, Shenzhen University, Shenzhen, Guangdong, China

    Yi Chai

  2. Centre for Safe Medication Practice and Research, Department of Pharmacology and Pharmacy, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China

    Yi Chai, Ivan C. H. Lam, Kenneth K. C. Man, Eric Y. F. Wan, Xue Li, Wallis C. Y. Lau, Min Fan, Esther W. Chan & Ian C. K. Wong

  3. The Hong Kong Jockey Club Centre for Suicide Research and Prevention, The University of Hong Kong, Hong Kong SAR, China

    Yi Chai

  4. Research Department of Practice and Policy, School of Pharmacy, University College London, London, UK

    Kenneth K. C. Man & Wallis C. Y. Lau

  5. Laboratory of Data Discovery for Health (D24h), Hong Kong Science Park, Hong Kong SAR, China

    Kenneth K. C. Man, Eric Y. F. Wan, Xue Li, Celine S. L. Chui, Wallis C. Y. Lau & Esther W. Chan

  6. Division of Psychiatry, University College London, London, UK

    Joseph F. Hayes

  7. Camden and Islington NHS Foundation Trust, London, UK

    Joseph F. Hayes

  8. Department of Family Medicine and Primary Care, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China

    Eric Y. F. Wan

  9. Department of Medicine, School of Clinical Medicine, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China

    Xue Li

  10. School of Nursing, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China

    Celine S. L. Chui

  11. School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China

    Celine S. L. Chui

  12. Real-World Solutions, IQVIA, Durham, NC, USA

    Xiaoyu Lin & Can Yin

  13. The University of Hong Kong Shenzhen Institute of Research and Innovation, Shenzhen, Guangdong, China

    Esther W. Chan

  14. Aston Pharmacy School, Aston University, Birmingham, UK

    Ian C. K. Wong

  15. School of Public Health Sciences, University of Waterloo, Waterloo, ON, Canada

    Hao Luo

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  1. Yi Chai
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  14. Hao Luo
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Contributions

Yi Chai, Ivan C.H. Lam, and Hao Luo contributed to the concept and design of the study. Yi Chai, Ivan C.H. Lam, Xiaoyu Lin, and Can Yin performed data analyses. Ian C.K. Wong obtained the funding. Yi Chai, Ivan C.H. Lam, Kenneth K.C. Man, Joseph F. Hayes, Eric Y.F. Wan, Xue Li, Celine S.L. Chui, Wallis C. Y. Lau, Xiaoyu Lin, Can Yin, Min Fan, Esther W. Chan, Ian C.K. Wong, and Hao Luo provided clinical, statistical, and epidemiological advice and interpreted the results. Yi Chai, Ivan C.H. Lam, and Hao Luo wrote and revised the first draft. All authors revised the manuscript critically for important intellectual content. All authors read and approved the final manuscript.

Authors’ Twitter handles

Twitter handles: @Yi_Chai18 (Yi Chai); @IVANCHLAM (Ivan C.H. Lam); @HaoLuo429 (Hao Luo); @Ian_HKU (Ian C.K. Wong).

Corresponding author

Correspondence to Hao Luo.

Ethics declarations

Ethics approval and consent to participate

The data partners have obtained institutional review board exemption for their participation in this study. Informed consent was waived because the study used deidentified data, and no patients were contacted.

Consent for publication

Not applicable.

Competing interests

Kenneth K.C. Man reports grants from the CW Maplethorpe Fellowship, National Institute of Health Research, UK, Hong Kong Research Grant Council and the European Commission Horizon 2020 Framework, personal fees from IQVIA and grants from Amgen and GlaxoSmithKline, outside the submitted work; Joseph F. Hayes reports grants from UKRI, NIHR UCLH Biomedical Research Centre, and Wellcome Trust and Consultancy Fees from Wellcome Trust and juli Health, outside the submitted work; Xue Li reports grants from the Hong Kong Health and Medical Research Fund (HMRF, HMRF Fellowship Scheme, HKSAR), Research Grants Council Early Career Scheme (RGC/ECS, HKSAR), Janssen, and Pfizer, internal funding from the University of Hong Kong; and consultancy fees from Merck Sharp & Dohme and Pfizer, outside the submitted work; Eric Y.F. Wan reports grants from the Food and Health Bureau of the Government of the Hong Kong Special Administrative Region and the Hong Kong Research Grants Council, outside the submitted work; Celine S.L. Chui reports grants from the Food and Health Bureau of the Hong Kong Government, Hong Kong Research Grant Council, Hong Kong Innovation and Technology Commission, Pfizer, IQVIA, MSD, and Amgen and personal fees from PrimeVigilance, outside the submitted work; Wallis C.Y. Lau reports receiving grants from AIR@InnoHK administered by the Innovation and Technology Commission of Hong Kong, outside the submitted work; Esther W. Chan reports grants from Research Grants Council of Hong Kong, Research Fund Secretariat of the Food and Health Bureau of Hong Kong, National Natural Science Fund of China, Wellcome Trust, Bayer, Bristol-Myers Squibb, Pfizer, Janssen, Amgen, Takeda and Narcotics Division of the Security Bureau of Hong Kong; honorarium from Hospital Authority, outside the submitted work; Ian C.K. Wong reports grants from Amgen, Bristol-Myers Squibb, Pfizer, Janssen, Bayer, GSK and Novartis, the Hong Kong RGC, and the Hong Kong Health and Medical Research Fund in Hong Kong, National Institute for Health Research in England, European Commission, National Health and Medical Research Council in Australia, consulting fees from IQVIA, payment for expert testimony and is an independent non-executive director of Jacobson Medical in Hong Kong, outside of the submitted work; no other relationships or activities that could appear to have influenced the submitted work. Hao Luo reports grants from the Research Grants Council of Hong Kong, outside the submitted work; All other authors declare no competing interests.

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Supplementary Information

12916_2025_3952_MOESM1_ESM.pdf

Additional file 1: Fig. S1. Study cohort selection procedure, using short-term depression risk in France IQVIA as an example. Table S1. Descriptions of databases. Table S2. Diagnostic codes for COVID-19 identification. Table S3. Diagnostic codes for outcomes identification. Table S4. Sample size, sex and age distribution, follow-up time, the number of psychiatric and neuropsychiatric events, and incidence rate in the medium-term observation period by outcome and database. Table S5. Sample size, sex and age distribution, follow-up time, the number of psychiatric and neuropsychiatric events, and incidence rate in the long-term observation period by outcome and database. Table S6. Selected baseline characteristics for all outcomes in all databases. Table S7. Risk of developing outcome events among individuals with COVID-19 for the whole study sample. Table S8. Risk of developing outcome events among individuals with COVID-19 for males. Table S9. Risk of developing outcome events among individuals with COVID-19 for females. Table S10. Risk of developing outcome events among individuals with COVID-19 for individuals aged below 18 years. Table S11. Risk of developing outcome events among individuals with COVID-19 for individuals aged between 18 and 24 years. Table S12. Risk of developing outcome events among individuals with COVID-19 for individuals aged between 25 and 44 years. Table S13. Risk of developing outcome events among individuals with COVID-19 for individuals aged between 45 and 64 years. Table S14. Risk of developing outcome events among individuals with COVID-19 for individuals aged between 65 years or older.

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Chai, Y., Lam, I.C.H., Man, K.K.C. et al. Psychiatric and neuropsychiatric sequelae of COVID-19 within 2 years: a multinational cohort study. BMC Med 23, 144 (2025). https://doi.org/10.1186/s12916-025-03952-z

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Keywords

BMC Medicine

ISSN: 1741-7015

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