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. 2023 Jan 20;254:1–7. doi: 10.1016/j.schres.2023.01.020

Epidemiology of infection, transmission and COVID-19 outcomes among mental health users and workers in a comprehensive network of long-term mental health facilities: Retrospective observational population-base study

Manuel Canal-Rivero a,b,c,1, Javier Vázquez-Hernández d,1, Marta León-Gómez a, Silvia Maraver-Ayala d, Luis Fernández-Portes d, Soraya Sánhez-Benítez d, Nathalia Garrido-Torres a,b,c, Miguel Ruiz-Veguilla a,b,c,e,⁎, Benedicto Crespo-Facorro a,b,c,e
PMCID: PMC9852313  PMID: 36736100

Abstract

Background

A high Coronavirus Disease 19 (COVID-19) morbidity and mortality have been reported among users and workers of long-term care facilities. The main objective of this work was to explore the prevalence and temporal pattern of COVID-19 in comprehensive network of long-term mental health facilities in Spain. Secondly, we aimed to estimate the effect of having a severe mental health diagnosis on prevalence and COVID-19 outcomes.

Methods

A cohort of 2552 participants were followed-up over a one-year. Sociodemographic and clinical data related to COVID-19 were recollected using a proforma. Frequency analyses were used to determine the prevalence of COVID-19 disease. Multivariable binary regression models sequentially adjusted by gender and age were employed to explore the potential role of severe mental health diagnosis on COVID-19 outcomes.

Results

Workers had higher risk of testing positive than mental health users (odds ratio [OR] 1.57 [95 % CI 1.01–2.43; p < 0.05] who presented an equivalent risk of testing positive after accounting for age and gender (OR 1.62 [95 % CI 0.98–2.66; p = 0.06].

Conclusions

The significant lower prevalence of COVID-19 among mental health users could be explained by the measures implemented to prevent COVID-19 as well as by the possible role that antipsychotic treatment could play in the prevention of SARS-CoV-2 infection.

Keywords: COVID-19, SARS-CoV-2, Mental health, Mental health long-term facilities

1. Introduction

Severe mental health patients have been identified as a risk population for Severe Acute Respiratory Syndrome due to Coronavirus-2 (SARS-CoV-2) infection (Crespo-Facorro, 2020; Yang et al., 2020a). Some of the reasons postulated for the increased risk of SARS-CoV-2 infection among this population are: i) lower awareness of risk, ii) the absence of adequate barriers against virus propagation such as congregate living, iii) the higher prevalence of cognitive impairment, iv) reduced access to appropriate physical care or v) immunological disturbances related to mental health disorders or treatment (Yao et al., 2020). On the other hand, main markers of Coronavirus Disease-19 (COVID-19) poor prognosis such as smoking, hypertension, diabetes as well as cardiovascular and respiratory diseases are highly prevalent among severe mental health patients (Kozloff et al., 2020).

To date, there is no scientific evidence to ensure a direct relationship between SARS-CoV-2 infection or severity of COVID-19 clinical outcomes and mental health illness (Tzur Bitan et al., 2021). Thus, Lee et al. (2020) reported that diagnosis of a mental disorder was not associated with increased likelihood of SARS-CoV-2 infection. (Lee et al., 2020). Conversely, Wang and colleagues informed of an increased risk to be infected, especially in those with a recent mental health diagnosis (Wang et al., 2020). In relation to mortality due to COVID-19, inconsistent results have also been published. In particular, while Nemani et al. (2021) showed that severe mental health patients had increased risk of mortality, Jeon et al. (2021) did not find significant differences in the proportion of deaths due to COVID-19 between schizophrenic patients and general population (Jeon et al., 2021; Nemani et al., 2021).

It is worth to note that most of our knowledge about the relationship between mental health diagnosis and COVID-19 is based on studies that have used electronic records data (Wang et al., 2020). None of these studies have taken into account the potential role of adherence to mental health medications (Boland and Dratcu, 2021) and rarely include sensitive information in the analyses such as socioeconomic or lifestyle conditions (Vai et al., 2021). Thus, it is difficult to extrapolating the findings of these studies to other health care systems from those in which the studies were carried out (Nemani et al., 2021).

Sociodemographic factors such as living in congregate housing has been recognised as risk factors to be infected by SARS-CoV-2 among mental health patients (Kozloff et al., 2020). In fact, it has been recognised that COVID-19 can spread rapidly within residential settings, including long-term mental health facilities (Burton et al., 2020). Moreover, among mental health users living in long-term care homes could be difficult to recognize COVID-19 typical symptoms due to the presence of other comorbidities such as those noted previously (Callaghan et al., 2020). Furthermore, workers in long-term facilities have been identified as risk population of COVID-19 transmission in long-term care facilities although this concern has been scarcely investigated so far (Seon et al., 2021).

Nevertheless, workers from long-term facilities have not only been targeted as potential transmitters of the SARS-CoV-2, but also as a population at risk of being infected by the virus. In particular, a study carried out in Spain reported that the prevalence of COVID-19 infection among workers in long-term facilities is almost twice as high than in general practitioners (Martín et al., 2020). It should be emphasised that the prevalence of COVID-19 among workers of nursing homes reported by Martin et al. (2020) was similar to the prevalence found in first line health care workers (Alonso et al., 2021; Gómez-Ochoa et al., 2021).

To the best of our knowledge no previous population-based cohort studies have analysed systematically infection, transmission and COVID-19 outcomes among mental health users and workers pertaining to a comprehensive network of long-term mental health facilities. Thus, the main objective of the present study was to explore the temporal pattern and prevalence of COVID-19 between March 2020 to March 2021 in a large sample of residential users and workers in one large health region in Spain. Secondly, we aimed to estimate the effect of severe mental health diagnosis on SARS-CoV-2 infection as well as on COVID-19 related symptomatology considering the potential role of sociodemographic factors such as gender and age.

2. Materials and methods

The study population included a total of 2552 individuals tracked over a one-year follow-up period, from March 2020 to March 2021. Two different cohorts were constructed: i) a cohort of mental health users of the public network of the Andalusian mental health residential settings and ii) a cohort of employees of the different long-term facilities. Two different proformas were specifically designed for this study to obtain the information from the participants of the study.

Fundación Pública Andaluza para la Integración Social de Personas con Enfermedad Mental (FAISEM) is responsible for the management of the entire public network of residential mental health facilities in the Autonomous Community of Andalusia (total population 8.476.718 inhabitants) (Instituto Nacional de Estadística, 2021).

The main aim of the foundation is the development and administration of social services for people with functional impairments and support needs resulting from severe mental health illness. Among the social services offered by the Foundation, the support home program is made up of three different types of residential facilities such as sheltered homes as well as supervised shared and individual apartments (FAISEM, n.d.).

Sociodemographic and clinical information as well as markers of COVID-19 poor prognosis, substance use, COVID-19 symptomatology, and hospitalization due to COVID-19 symptomatology among mental health users were recorded using proforma constructed for the study for mental health users. On the other hand, a proforma also designed for this study was employed to obtain sociodemographic and COVID-19 related information in employee's subsample. Sociodemographic and clinical information for both groups is displayed in Table 1 . Reverse transcription polymerase chain reaction (RT-PCR) tests were used to confirm SARS-CoV-2 infection, as is recommended by the World Health Organization.

Table 1.

Sociodemographic and clinical characteristics.

Total sample (n = 2552)
 Users
 Workers
Subtotal sample (n = 1143) Infected (n = 32) Non-infected (n = 1141) Subtotal sample (n = 1379) Infected (n = 58) Non-infected (n = 1321)
Age (years), mean ± SD 47.17 ± 17.02 52.23 ± 21.76 51.50 ± 10.14 52,25 ± 22,01 42.87 ± 9.67 47,02 ± 7,76 42,69 ± 9,71
Gender (male), n (%) 1088 (42.7 %) 387 (33.1 %) 22 (68.8 %) 760 (66,8 %) 306 (22.2 %) 12 (20,7 %) 294 (22,3 %)
Type of residential facility, (%)
 Sheltered homes 2036 (79.8 %) 770 (65.6 %) 26 (81,3 %) 744 (65,2 %) 1266 (91.8 %) 53 (91,4 %) 1213 (91,8 %)
 Supervised shared apartment 459 (18 %) 362 (30.9 %) 6 (18.8 %) 356 (32,2 %) 97 (7.1 %) 5 (8,6 %) 92 (7,1 %)
 Supervised individual apartment 41 (1.6 %) 41 (3.5 %) 0 (0 %) 41 (3,6 %) 0 (0 %) 0 (0 %) 0 (0 %)
 Workers at different residential facilities 16 (0.6 %) 0 (0 %) 0 (0 %) 0 (0 %) 16 (1.2 %) 0 (0 %) 16 (1,2 %)
Province, n (%)
 Almeria 239 (9.4 %) 107 (9,1 %) 1 (3,1 %) 106 (9,3 %) 132 (9.6 %) 3 (5,2 %) 129 (9,8 %)
 Cadiz 414 (16.2 %) 177 (15,1 %) 12 (37,5 %) 165 (14,5 %) 237 (17.2 %) 18 (31,1 %) 219 (16,6 %)
 Cordoba 198 (7.8 %) 103 (8,8 %) 103 9,1 95 (6.9 %) 4 6,9 91 6,9
 Granada 285 (11.2 %) 137 (11,7 %) 4 (12,5 %) 133 (11,7 %) 148 (10.7 %) 8 (13,8 %) 140 (10,6 %)
 Huelva 201 /7.9 %) 83 (7,1 %) 3 (9,4 %) 80 (7,1 %) 118 (8.6 %) 3 (5,2 %) 115 (8,7 %)
 Jaen 231 (9.1 %) 113 (9,6 %) 113 9,9 118 (8.6 %) 6 10,3 112 8,5
 Malaga 409 (16.1 %) 167 (14,2 %) 3 (9,4 %) 164 (14,4 %) 242 (17.5 %) 5 (8,6 %) 237 (17,9 %)
 Sevilla 575 (22.5 %) 286 (24,4 %) 9 (28,1 %) 277 (24,3 %) 289 (21.1 %) 11 (19,1 %) 278 (21,1 %)
Diagnosis, n (%)
 Schizophrenia Spectrum and Other Psychotic Disorders (−) 904 (77.2 %) 24 (75,1 %) 880 (77,3 %) (−) (−) (−)
 Bipolar and Related Disorders (−) 46 (3.9 %) 1 (3,1 %) 45 (3,9 %) (−) (−) (−)
 Depressive Disorders (−) 10 (0.9 %) (−) 10 (0,9 %) (−) (−) (−)
 Personality Disorders (−) 59 (5.1 %) (−) 59 (5,2 %) (−) (−) (−)
 Others (−) 152 (13.1 %) 7 (21,9 %) 145 (21,7 %) (−) (−) (−)
 Long-acting Injectable antipsychotic treatment (yes), n (%) (−) 647 (55.3 %) 14 (43,8 %) 633 (55,6 %) (−) (−) (−)
 Psychiatric Admissions to intensive care unit over the period observed (yes), n (%) (−) 28 (2.4 %) 0 (0 %) 28 (2,5 %) (−) (−) (−)
Comorbidities, n (%)
 Diabetes (−) 167 (14.2 %) 6 (18.8 %) 161 (85,9 %) (−) (−) (−)
 Obstructive pulmonary disease (−) 157 (13.4 %) 3 (9.4 %) 154 (13,5 %) (−) (−) (−)
 Asthma (−) 46 (3.9 %) 1 (3.1 %) 45 (3,9 %) (−) (−) (−)
 Cerebrovascular disease (−) 15 (1.3 %) 1 (3.1 %) 14 (1,2 %) (−) (−) (−)
 Dementia (−) 10 (0.9 %) 0 (0 %) 10 (0,9 %) (−) (−) (−)
 Other neurological diseases (−) 62 (5.3 %) 2 (6,3 %) 60 (5,3 %) (−) (−) (−)
 Cardiovascular disease (−) 78 (6.6 %) 2 (6,3 %) 76 (6,7 %) (−) (−) (−)
 Autoimmune disease (−) 25 (2.1 %) 0 (0 %) 25 (2,2 %) (−) (−) (−)
 Hypertension (−) 195 (16.6 %) 1 (3,1 %) 194 (17,1 %) (−) (−) (−)
 Kidney disease (−) 34 (2.9 %) 3 (9,4 %) 31 (2,7 %) (−) (−) (−)
 Obesity (BMI > 30) (−) 261 (22.3 %) 7 (21,9 %) 254 (22,3 %) (−) (−) (−)
 Hepatitis A (−) 2 (0.2 %) 0 (0 %) 2 (0,2 %) (−) (−) (−)
 Hepatitis B (−) 14 (1.2 %) 0 (0 %) 14 (1,2 %) (−) (−) (−)
 Hepatitis C (−) 54 (4.6 %) 4 (12,5 %) 50 (4,4 %) (−) (−) (−)
 Other hepatic diseases (−) 28 (2.4 %) 3 (9,4 %) 25 (2,2 %) (−) (−) (−)
 Cancer (−) 31 (2.6 %) 1 (3,1 %) 30 (2,6 %) (−) (−) (−)
 Other comorbidities (−) 201 (17.1 %) 3 (9,4 %) 198 (17,4 %) (−) (−) (−)
Substance use, n (%)
 Alcohol (−) 104 (8.9 %) 2 (6,3 %) 102 (8,9 %) (−) (−) (−)
 Cannabis (−) 69 (5.9 %) 3 (9,4 %) 66 (5,8 %) (−) (−) (−)
 Cocaine (−) 10 (0.9 %) 0 (0 %) 10 (0,9 %) (−) (−) (−)
 Heroin (−) 2 (0.2 %) 0 (0 %) 2 (0,2 %) (−) (−) (−)
 Polysubstance use (−) 5 (0.4 %) 0 (0 %) 5 (0,4 %) (−) (−) (−)
 Tobacco (−) 880 (75.1 %) 16 (50 %) 864 (75,7 %) (−) (−) (−)
COVID-19 symptomatology, n (%) (−) (−) 9 (28,1 %) (−) (−) 13 (22,4 %) (−)
 Fever (>38) 43 (3,6 %) (−) 5 (15,6 %) 30 (2,6 %) (−) 8 (13,8 %) (−)
 Dry cough 27 (2,3 %) (−) 0 (0 %) 25 (2,2 %) (−) 2 (3,4 %) (−)
 Difficulty breathing or shortness of breath 24 (2,1 %) (−) 1 (3,1 %) 21 (1,8 %) (−) 2 (3,4 %) (−)
 Loss of taste or smell 1 (0,1 %) (−) 0 (0 %) 0 (0 %) (−) 1 (1,7 %) (−)
 Diarrhea 25 (2,1 %) (−) 0 (0 %) 25 (2,2 %) (−) 0 (0 %) (−)
 Tiredness 18 (1,5 %) (−) 1 (3,1 %) 17 (1,5 %) (−) 0 (0 %) (−)
 Chest pain or pressure 14 (1,2 %) (−) 0 (0 %) 14 (1,2 %) (−) 0 (0 %) (−)
 Sore throat 13 (0,5 %) (−) 1 (3,1 %) 10 (0,9 %) (−) 2 (3,4 %) (−)
 Headache 30 (2,6 %) (−) 2 (6,3 %) 27 (2,4 %) (−) 1 (1,7 %) (−)
 Conjunctivitis 2 (0,2 %) (−) 0 (0 %) 2 (0,2 %) (−) 0 (0 %) (−)
 A rash on skin, or discolorations of finger or toes 4 (0,3 %) (−) 0 (0 %) 4 (0,4 %) (−) 0 (0 %) (−)
 Loss of speech or movement 5 (0,4 %) (−) 0 (0 %) 5 (0,4 %) (−) 0 (0 %) (−)
 Other 5 (0,4 %) (−) 0 (0 %) 4 (0,4 %) (−) 1 (1,7 %) (−)
Hospitalization due to COVID-19 symptomatology, (%) 2 (2.2 %) 1 (3.1 %) 1 (3,1 %) 0 (0 %) 1 (1.7 %) 1 (1,7 %) 0 (0 %)
Deaths by COVID-19, n (%) 2 (2.2 %) 1 (3.1 %) 1 (3,1 %) 0 (0 %) 1 (1.7 %) 1 (1,7 %) 0 (0 %)
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All procedures were in accordance with the Declaration of Helsinki (Association, 2013). The protocol was approved by the Local Ethics Committee of Virgen del Rocío University Hospital (PI-2578-N-20). All participants data were anonymized to ensure confidentiality. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline for cohort studies (Von Elm et al., 2008).

2.1. Statistical analyses

Descriptive and frequency analyses were used to determine characteristics and prevalence of the variables included in the study using Statistical Package for the Social Science (SPSS), version 24 (IBM Corp., 2016). For the second purpose of the study, we used logistic regression analysis. To investigate the extent to which mental health diagnosis could further be explained by age and gender, we sequentially adjusted for age and gender in a second model of the logistic regression model, including in the first model only the presence vs. absence of mental health diagnosis.

3. Results

3.1. Sample characteristics

A total of 2552 participants were included in the analyses. One thousand one hundred seventy-three of those (46 %) of the participants were mental health users living in the different residential facilities while 1379 (54 %) were workers. Subgroup analyses showed that a 2.7 % of the mental health users were infected by SARS-CoV-2 and a 4.2 % of the workers. Significant differences between users and workers were found in age (U = 40,033.5; p < 0.01; 42.87 ± 9.67 vs. 52.23 ± 21.76) and gender (X2 = 516.78; p < 0.01). Further details are shown in Table 1.

3.2. Prevalence of COVID-19

Ninety participants (3.5 %) of the study were infected by COVID-19. From those, 32 (35.6 %) were care home residents' users while 58 (64.4 %) were workers of the mental health long-care facilities. The month with highest number of COVID-19 infection was January 2021 (24 new cases; 11 mental health users vs. 13 workers). There were two months without infections (April and June 2020) taking into account both groups. It is noteworthy that no mental health users were infected by SASRS-CoV-2 from March 2020 to July 2020 (See Fig. 1 ).

Fig. 1.

Fig. 1

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Effect of mental health diagnosis on COVID-19.

3.3. SARS-CoV-2 infection

Workers were approximately 1.6 times more likely to be infected by SASRS-CoV-2 than the care home residents (odds ratio [OR] 1.57 [95 % CI 1.01–2.43; p < 0.05]. When sociodemographic variables (age and gender) were introduced into the logistic model regression, we observed that these variables had little effect on the likelihood that workers vs. mental health users testing positive for COVID-19 (OR 1.62 [95 % CI 0.98–2.66; p = 0.06]).

3.4. Symptomatology

Thirty-one (34.4 %) of the 90 participants infected by COVID-19 presented COVID-19 related symptomatology. From the 32 infected mental health users, 9 (28.1 %) reported COVID-19 symptomatology while in the workers group, 37.9 % of the infected people informed of the presence of COVID-19 related symptoms (22 workers). Multivariate analyses showed that no one of the groups presented higher risk to develop COVID-19 related symptoms (OR 0.74 [95 % CI 0.28–1.98; p = 0.55]) and that gender and age had little influence on the likelihood of study participants would develop symptoms of the disease (OR 0.61 [95 % CI 0.19–2.03; p = 0.42]).

4. Discussion

The main findings derived from this study were: i) mental health users and workers of the public network of mental health long-term care facilities did not present higher risk of SARS-CoV-2 infection than general population; ii) severe mental health users presented significantly less likelihood to be infected by SARS-CoV-2 than workers of the mental health long-term facilities; iii) there were no significant differences between mental health users and workers in symptomatology due to COVID-19 and iv) temporal pattern of COVID-19 among our sample resembled that of the general population, with no users infected from March 2020 to July 2020.

Over the period observed in this study (March 2020–March 2021) a total of 502.466 people were infected by SARS-CoV-2 in Andalusia which represents 5.9 % of the population (Junta de Andalucía, n.d.). In our sample, the prevalence of COVID-19 (3.5 %) was lower than in the general population (5.9 %) as well as in comparison with the data reported by Martín et al. (2020) who analysed the prevalence of SARS-CoV-2 in nursing homes in Spain (Martín et al., 2020). Furthermore, mental health users of the Junta de Andalusia's network of long-term mental health facilities presented no only significant less prevalence of SARS-CoV-2 infection (2.7 %) than workers of FAISEM (4.2 %), but also than users of other residential homes that provide care to populations who have also been identified as at risk for COVID-19, such as elderly people (Gardner et al., 2020). It should be underlined that preventive COVID-19 measures carried out in nursing homes are similar to those implemented in our long-term mental health facilities (Picardo García, 2021).

A previous study has analysed the transmission of COVID-19 among residents of long-term care rehabilitation facility showing that >70 % of the mental health users tested positive for COVID-19 despite adherence of the centre to country, state and federal policies and procedures (Xiong et al., 2020). The prevalence of SARS-CoV-2 infection in our sample was significantly lower than that reported by Xiong et al. (2020). One of the main reasons for this contradictory results could be due to the small sample size of Xiong's et al. (2020) study. However, our results are in accordance with those stated by an investigation carried out in a network of five inpatient psychiatric units. Specifically, the authors informed of a very low patient infection rate. In particular, mental health users presented lower prevalence of SARS-CoV-2 infection than the employees of the inpatients units (Li et al., 2021).

The significant low prevalence of SARS-CoV-2 infection among mental health users from our sample could be explained by the implementation of rapid and effective preventive measures carried out by FAISEM in the long-term care facilities under its management. In particular, from the beginning of the pandemic caused by COVID-19, FAISEM followed preventive and control measures such as: development of an infection preventive control (IPC) program, implementation of IPC such as hand hygiene, regular cleaning and disinfecting throughout the facilities, universal masking for all workers, service suppliers and users, physical distance, adequate ventilation, IPC policies for visitors, early detection of SARS-CoV-2 infections among workers through syndromic surveillance and for laboratory testing, expanding testing to all workers and users when a positive case of SARS-CoV-2 was identified in users or workers. On the other hand, when a resident was identified as suspected or confirmed COVID-19: implementation of contact, droplet and/or airborne precautions during care of the affected users, follow specific procedures for environmental cleaning and disinfection, waste and laundry management, isolate suspected or confirmed COVID-19 cases in single room, quarantine all contacts of confirmed COVID-19 cases in their rooms or separated from other residents and monitoring them for 14 days since the last contact (World Health Organization (WHO), 2020). In addition, when a worker was upon suspicion or confirmation of COVID-19 the workers were placed on paid sick leave.

Mental health users and workers did not differ in the prevalence of COVID-19 related symptomatology. Findings derived from our research seem to be contradictory to most of the results reported by previous investigations (Wang et al., 2020). However, contradictory results have also been published regarding this issue (Tzur Bitan et al., 2021). In fact, previous studies carried out with mental health inpatients have showed that none of the individuals included in the studies suffered COVID-19 severe clinical outcomes which is in line with our results (Li et al., 2021; Xiong et al., 2020).

One possible explanation for our findings is the potential role that antipsychotic treatments could play. In fact, our own group has recently published that long-acting injectable antipsychotics treatment could have potential protective effects against COVID-19 (Canal-Rivero et al., 2021b). Nevertheless, a recent systematic review and meta-analysis, antipsychotics were identified as a risk factor of COVID-19 mortality (Vai et al., 2021). Antipsychotics would precipitate cardiovascular and thromboembolic risks which might interfere with an adequate immune response and could cause pharmacokinetic and pharmacodynamic interactions with drugs used to treat COVID-19 (Bishara et al., 2020; Ostuzzi et al., 2020; Plasencia-García et al., 2021).

Nevertheless, antipsychotics have shown anti-inflammatory effects via the reduction of proinflammatory cytokines production, modulating monocytes response through TLR and the inhibition of the microglial activation (Kato et al., 2007; Obuchowicz et al., 2017). Cancer therapeutics, antipsychotics, and antimalarials have shown to be efficacious against MERS and SARS coronaviruses (Dyall et al., 2017). In fact, chlorpromazine protects mice from severe clinical disease and SARS-CoV-2 (Weston et al., 2020). Clozapine (atypical antipsychotic) has revealed to be effective in suppressing the proinflammatory cytokine expression by limiting the NLRP3 inflammasome activation in an in vitro model of schizophrenia (Giridharan et al., 2020). Interestingly, a research investigating approximately 12,000 drugs in clinical-stage or Food and Drug Administration (FDA)-approved small molecules to identify candidate drugs to treat COVID-19, reported that elopiprazole (a never marketed phenylpiperazine antipsychotic drug) was listed among the 21 most potent compounds to inhibit SARS-CoV infection (Riva et al., 2020).

On the other hand, aripiprazole (marked phenylpiperazine) reverted the changes caused by COVID-19 in gene expression which could validate aripiprazole as treatment for COVID-19 (Crespo-Facorro et al., 2021). Consistent with this, as was noted above, in a previous retrospective study we observed that those severe mental health patients who are on long-acting injectable antipsychotics treatment presented lower risk of SARS-CoV-2 infection as well as better outcome after infection than general population (Canal-Rivero et al., 2021, Canal-Rivero et al., 2021a). In fact, in congruence with our results, other research groups have also reported similar results (Dratcu and Boland, 2021; Prokopez et al., 2021).

One of the reasons for the contradictory results in relation to the role of antipsychotic treatments on COVID-19 could be explained on the one hand by the fact that the studies that have found significant relationship between antipsychotic treatments and COVID-19 morbidity/mortality have not adjusted their analyses by the adherence to these medication. In fact, low adherence to antipsychotic treatments has been demonstrated among patients to whom antipsychotics are prescribed (El Abdellati et al., 2020). On the contrary, antipsychotic treatments are highly prescribed in population at very high risk of COVID-19 mortality and with high prevalence of somatic comorbidities such as elderly and individuals with dementia (Behrman et al., 2018; Tampi et al., 2016) which could influence the results obtained by the studies that found significant association between antipsychotic treatments and severe COVID-19 outcomes.

It has been suggested that the relationship between mental health diagnosis and COVID-19 is to some extent influenced by the presence of somatic illness (Yang et al., 2020b). It has been recognised the barriers to somatic care experienced by mental health patients (Fond et al., 2021) as well as that mental health patients are less adherent to treatment recommendations for the somatic pathologies (Lee et al., 2020). Moreover, the lack of caregiver's support would exacerbate the incidence and impact that COVID-19 has on this population (Jeon et al., 2021). The health care policies carried out by FAISEM in the long-term facilities under his management such as the compliance with treatment recommendations regarding somatic pathologies, implementation of programs to reduce mental health stigma, adherence to mental health treatments as well as emotional support provided by the FAISEM's employees could contribute to the low rate of COVID-19 severe outcomes found in our study.

Official data show that the months with highest number of positive COVID-19 tests were November 2020 and January 2021. In particular, January 2021 was the worst month in terms of the number of newly COVID-19 cases, hospitalizations and deaths due to COVID-19 in Andalusia (Junta de Andalucía, n.d.). In congruence with these data, we observed that November 2020 and January 2021 were also the months with highest COVID-19 incidence in our sample, especially January 2021. Temporal concordance between the increases of COVID-19 cases in both subgroups could be explained on the one hand by the increased social and physical activity of the users as well as by the increased transmission of the virus by the workers, who could be more susceptible to contagion due to the greater spread of the SARS-CoV-2 virus in Andalusia.

Limitations from this study must be considered. Firstly, there are some missing values such as comorbidities in the worker's subsample or mental health diagnosis. The inclusion of these variables in the analyses could yield more precise results. On the other hand, SARS-CoV-2 infection as well as COVID-19 outcomes analysed in this study were rare events which could affect to the accuracy of the multivariate models. In fact, ought to the low number of cases of hospitalizations and deaths due COVID-19 we cannot carried out multivariate analyses on the effect of having mental health diagnosis on these COVID-19 outcomes. Moreover, we have not included in the analyses possible differences between the different types of medication in their role in preventing COVID-19 infection as well as mitigators of disease symptomatology which should be considered in consecutive studies. Despite these limitations, to the best of our knowledge, this is the first population-based study to include a subsample of workers as a control group who share with the mental health users not only space but also long periods of time. The inclusion of this control group allows us to assess more reliably the impact of severe mental health diagnosis on SARS-CoV-2 infection and COVID-19 prognosis. Finally, information was recorded using proformas specifically designed for this study which allows us to consider a greater number of covariables in the analyses than studies based on electronic records data.

Our results may have relevant significance to the understanding of SARS-CoV-2 infection among severe mental health users and workers of residential facilities. In particular, mental health users of mental health long-term facilities presented a very low rate of SARS-CoV-2 infection which could be due to the effectiveness of preventive infection measures, the potential role that medication could play in reducing the risk of COVID-19 as well as by the supportive health and emotional care facilities provided in the residential settings managed by FAISEM. On the other hand, workers from these services also demonstrated lower prevalence of COVID-19 than workers from another long-term facilities which could be interpreted as the effectiveness of the preventive measures carried out or the fact that mental health long-term facilities do not represent a place of risk of COVID-19 contagion. Further investigations in different catchment areas as well as the analysis of longer time periods are required to confirm the results observed in this study. Future lines of investigation must be directed to explore the impact of COVID-19 at long-term among mental health users as well as to explore the role of the COVID-19 vaccination in following COVID-19 waves resulted from mutation of the SARS-CoV-2 virus.

Credit authorship contribution statement

All the authors have participated and have made substantial contributor for this paper.

Role of funding source

The authors received no financial support for the research, authorship, and/or publication of this article.

Ethical statement

Ethical approval was obtained from the Local Research Ethics Committee.

Declaration of competing interest

The authors have no conflicts of interest concerning the subject of the study.

Acknowledgments

We thank the patients and workers for participating in the study. We also thank Fundación Pública Andaluza para la Integración Social de Personas con Enfermedad Mental (FAISEM) and Hospital Universitario Virgen del Rocío for their support.

MCR works as Clinical Psychologist at Virgen del Rocío University Hospital (Seville, Spain) via Consejería de Salud y Familias (Junta de Andalucía) 2020 grant which covers his salary (RH-0081-2020).

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