Study on Age-specific Population at Risk of Developing Dementia,Anxiety and Depression Following Exposure to COVID-19

Abstract

Background

Memory, learning, language and decision-making are just some of the cognitive abilities that may be negatively impacted by neurological illnesses such as dementia, anxiety and depression.

Purpose

This research aims to examine the influence of demographic variables on the prevalence of dementia, anxiety and depression in patients recovering from COVID-19.

Methods

This research looks at those who are at risk of developing dementia, anxiety or depression after being exposed to COVID-19. The hospital EC (Ethics Committee-Unique Hospital, Surat, India) granted consent, as did the Dehradun Institute of Technology University’s research ethics committee (DITU/UREC/2022/04/6). Participants actively partook and gave informed consent. Patient data were collected with the assistance of medical personnel, and participants had to fulfil the inclusion and exclusion criteria. A questionnaire was distributed, and data were examined based on participant replies.

Results

The COVID-19 pandemic has had widespread effects on both physical and mental health, leading to increased risks of dementia, anxiety and depression. Elderly individuals are most susceptible to dementia, likely due to pre-existing vulnerabilities and the significant neurological impact of COVID-19 on this age group. Young adults exhibited a notable increase in anxiety, possibly linked to factors such as social isolation, economic uncertainty and disruptions to daily life. Additionally, depression prevalence has significantly risen among younger individuals following the pandemic.

Conclusion

The study provides important insights into the age-related impact of COVID-19 on mental health. Older adults are more prone to dementia and anxiety, while younger individuals show a higher prevalence of depression. These findings underscore the varying mental health effects across age groups, highlighting the need for targeted mental health interventions for both the elderly and young adults post-COVID-19.

Keywords

Anxiety depression dementia diabetes hypertension

Introduction

Coronavirus disease (COVID-19) is an infectious ailment induced by the SARS-CoV-2 virus. The majority of those infected with the virus will exhibit mild to moderate respiratory symptoms and will recover without the need for specialised treatment. Nevertheless, some individuals may have severe illness and require medical intervention. Individuals of advanced age and those with pre-existing medical disorders such as cardiovascular disease, diabetes, hypertension, asthma, chronic respiratory ailments or cancer are at an elevated risk of experiencing severe sickness. The COVID-19 pandemic in India is a segment of the global pandemic of COVID-19 induced by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The first instances of COVID-19 in India was documented on 30 January 2020.¹ A worldwide pandemic known as COVID-19 has emerged as a result of the virus’s fast spread across human populations.^{1, 2} Those with cardiovascular disease, and those 65 and older are at a higher risk of developing acute respiratory syndrome, multiple organ failure, pneumonia and mortality.^3–5 Because vaccines were scarce and situation management was challenging, physical separation, quarantine and isolation were the only realistic options for controlling the epidemic.^{1, 6}

The significant death and sickness rates associated with the COVID-19 infection made the urgent need for vaccinations apparent.^7–9 People with dementia may have a worsening of symptoms and an overall decline in quality of life as a result of this. SARS-CoV-2, the virus responsible for COVID-19 has the ability to directly infiltrate the central nervous system. The virus can gain access to the brain either by the olfactory nerve or by breaching the blood–brain barrier, which may lead to inflammation and harm to neurons.⁸

The immunological reaction of the body to COVID-19 can lead to substantial inflammation in the brain. Increased amounts of cytokines, known as the ‘cytokine storm’, can cause long-term inflammation in the brain, which is linked to the development of dementia. Severe cases of COVID-19 can result in respiratory distress and hypoxia, leading to insufficient oxygen flow to the brain. This can induce neuronal injury and contribute to cognitive impairment. COVID-19 patients, particularly those with severe cases have had cognitive impairments such as memory loss, impaired concentration and disorientation during their recovery.^{8, 9}

Public health measures regarding COVID-19, including wearing masks, keeping one’s distance from others and regularly washing one’s hands may be difficult for people with dementia to follow.^10–18 Dementia symptoms and the rate of cognitive deterioration can both be accelerated by this. Chronic fatigue, headaches and cognitive decline are some of the long-term neurological effects of COVID-19. These conditions can make dementia symptoms worse and have a negative impact on overall health. Concern, unease and heightened dread are hallmarks of anxiety during the COVID-19 pandemic as people face the unknowns and possible risks associated with the outbreak. Everyone involved, from family members and caregivers to those living with the condition, faces challenges when dealing with Alzheimer’s disease. Among the world’s ageing population, it is a major cause of disability and reliance. There can be no more neglected dementia unless it is part of every country’s public health agenda.^19–24

The primary purpose of the research is to determine the ways in which the COVID-19 pandemic has impacted dementia sufferers, including the ways in which it has altered the accessibility of healthcare, the ways in which it has exacerbated symptoms and the ways in which it has raised the danger of infection. The goal is to learn how COVID-19 affects the brain and neurological system in people who already have dementia and how it might affect these people in the long run.^25–30 Social isolation, comorbidities and the accessibility of services and assistance are some of the factors that may amplify the impact of COVID-19 on dementia patients. It is necessary to have a comprehensive understanding of the wider societal consequences that the COVID-19 pandemic on persons who have dementia and those who provide care for them. These ramifications include changes to healthcare systems, social policies and economic concerns.^31–34

Methods

The objective of the research was to investigate persons at risk of developing dementia, anxiety and depression after exposure to COVID-19. The data of COVID-19 subjects were gathered (Figure 1) from Unique Hospital Multispecialty and Research Institute in Surat, India. Subjects voluntarily took part in the trial and completed the informed consent form (ICF). The data were analysed according to the patients replies. The research used the CDR scale to gather data in alignment with the CDL scale.

Figure 1.

Workflow of Work Done.

Enrolment

The research included patients classified as very unwell who required prolonged hospitalisation (≥4 days or transfer to the intensive care unit [ICU]).

Research Design and Methodology

The objective of the research was to examine and evaluate persons who were exposed to COVID-19 and ascertain the likelihood that they may develop dementia, anxiety and sadness. The research included a total of 1000 participants. The data of COVID-19 patients were collected from the COVID-19 hospital with the aid of hospital staff. Patients who satisfied the designated inclusion and exclusion criteria were recruited in the study. Subjects hospitalised in the ICU for 4 or more days. The study included people who had no previous history of dementia but had a neurological ailment or another medical condition. Patients with mild or symptomless COVID-19 cases who have been hospitalised for a minimum of 4 days or have been moved to the ICU will be included in the research. Patients meeting the required criteria were instructed to voluntarily complete the questionnaire (Table 1). The research used the CDL for data collection. The questionnaire consists of 11 questions filled by the subjects. The data were analysed according to the subject’s replies.

Table 1.

Post-COVID Treatment Questionnaire.

	Subject Questionnaire	Strict Confidentiality
		Page 1
Post-COVID Treatment Questionnaire
Subject Name:		Answered Name:
Birthday:		Age:
Date of Discharge:		Relationship:
Answer the following questions by circling the right option.
Sr. No	Subject Survey	Yes	No
1.	On a consistent basis, he or she asks questions regarding the same problem.	Yes	No
2.	A point where they are unable to appreciate the context of the facts.	Yes	No
3.	The individual has developed a lack of regard about dress and other aspects of their personal life.	Yes	No
4.	It has come to their notice that they have started to forget to turn off the faucet, shut the door and/or have grown incapable of cleaning in an efficient way.	Yes	No
5.	When engaging in dual tasks, an individual neglects.	Yes	No
6.	Individual has been incapable of adhering to medicine under appropriate care.	Yes	No
7.	Individual has started to need more time to complete tasks (e.g., household duties) that were previously accomplished swiftly.	Yes	No
8.	He/She has grown incapable of formulating plans.	Yes	No
9.	He/She is unable to comprehend intricate subjects.	Yes	No
10.	He/She became more disinterested and reluctant, ultimately ceasing hobbies and other activities.	Yes	No
11.	He/She has grown more irritable and distrustful compared with prior behaviour.	Yes	No
Total SED = 11Q score
Subject With Depression: Yes/No Subject With Anxiety: Yes/No

Sr. No	Subject Self-declaration	Initials of Subject
1.	I so attest that I was able to examine and comprehend the information sheet dated TBD for the research indicated above, and that I was also given the chance to ask questions.	[ ]
2.	I accept that my participation in the study is optional and that I may withdraw at any time, without reason, without affecting my medical treatment or legal rights.	[ ]
3.	I agree not to impose limitations on the use of any data or outcomes derived from this research, as long as such usage is exclusively for scientific reasons.	[ ]
4.	Considering the academic nature of the research, I offer my agreement to take part in the aforementioned study without the expectation of receiving any kind of monetary remuneration.	[ ]

Approvals

Prior to conducting the study, the following endorsements were obtained.

University Research Ethics Committee from Dehradun Institute of Technology University, Dehradun, India (DITU/UREC/2022/04/6).

Ethics Committee Approval from the hospital (Ethics Committee-Unique Hospital, Surat, India).

Activities

The actions listed below were carried out over the course of the study.

ICF.

Age, gender, weight and Body Mass Index.

Clinical Evaluation, patient history and vitals.

All patients were instructed to adhere to the protocol guidelines provided.

Administration Method for Study Tools

The data on the subjects were obtained from the database of the hospital, which was located in Surat, India. These data were used in order to select patients in accordance with a distinct set of inclusion and exclusion criteria.

In addition to facilitating the delivery of the Informed Consent Form, Case Report Form and questionnaires to the subjects, the research assistants also helped the completion of these documents by the patients.

While the patients were filling out the questionnaire, the Principal Investigator was responsible for administering the ICF. For the purpose of future research, the results from the questionnaire were examined and converted.

Data Acquisition and Administration

Data were gathered using physical forms and then put into Microsoft Excel. Data analysis was carried out utilising statistical methods as needed.

ANOVA.

Eligibility Criteria (I/E).

Case Report Forms.

ICFs.

CDL Questionnaire.

Numerical Analysis

After extracting the data from the source database, the data were analysed using the ANOVA test. The sociodemographic characteristics were documented and organised using a table. A number of computations were performed to establish the mean and standard deviation.

Analysis of Qualitative Data

The SAS Program was utilised to conduct an analysis of data collected from post-COVID-19 participants. Using the responses that indicated ‘YES’ for each item in the questionnaire, a ratio was calculated using the data. A research of the statistical features of a sample of 1000 patients who had recovered from COVID-19 was conducted.

Results

Elderly individuals are highly susceptible to dementia post-COVID-19 due to neurological effects, while young adults face increased anxiety and depression from social and economic disruptions. The pandemic worsened mental health conditions, especially in those with pre-existing cognitive or psychiatric disorders. Hospitalised COVID-19 patients showed a higher risk of psychiatric issues. These findings highlight the need for targeted mental health interventions post-pandemic.

Dementia Age Statistical Analysis

The analysis of dementia scores across different age groups reveals that the mean dementia scores fluctuate with age (Table 2). The highest mean score is observed at age 59 (Mean = 6.53, Std Dev = 2.61), indicating a potentially increased risk of dementia symptoms in this age group. Most age groups exhibit a Pr > |t| value of <.0001, signifying strong statistical significance, suggesting a meaningful relationship between age and dementia severity.

Table 2.

Dementia Age Numerical Analysis.

Age	Score	N Obs	Mean	Std Dev	Pr > \|t\|
19	69	16	4.31	2.80	<.0001
20	131	31	4.23	2.38	<.0001
25	242	46	5.26	2.97	<.0001
28	81	15	5.40	1.99	<.0001
29	77	15	5.13	2.70	<.0001
30	381	88	4.33	2.29	<.0001
31	56	13	4.31	2.06	<.0001
32	74	15	4.93	1.83	<.0001
33	64	15	4.27	2.74	<.0001
34	171	30	5.70	3.02	<.0001
35	174	40	4.35	2.11	<.0001
38	109	26	4.19	2.70	<.0001
39	126	28	4.50	2.33	<.0001
40	298	58	5.14	2.55	<.0001
42	60	16	3.75	2.27	<.0001
43	88	17	5.18	2.43	<.0001
44	71	14	5.07	1.98	<.0001
45	137	29	4.72	2.14	<.0001
47	53	16	3.31	1.78	<.0001
48	69	14	4.93	2.56	<.0001
50	65	13	5.00	3.03	<.0001
55	236	44	5.36	2.71	<.0001
59	982	15	6.53	2.61	<.0001
60	211	44	4.80	2.64	<.0001
65	287	60	4.78	2.28	<.0001
66	80	16	5.00	2.76	<.0001
70	152	31	4.90	1.78	<.0001
72	72	16	4.50	2.61	<.0001
75	123	31	3.97	1.97	<.0001
77	129	31	4.16	2.05	<.0001
78	63	13	4.85	1.72	<.0001
80	310	60	5.17	2.48	<.0001
81	70	13	5.38	2.10	<.0001
85	215	43	5.00	2.54	<.0001
86	65	13	5.00	1.68	<.0001
89	53	13	4.08	0.86	<.0001

Anxiety Age Numerical Analysis

The analysis of anxiety scores across different age groups highlights that individuals aged 59 have the highest mean anxiety score (Mean = 6.29, Std Dev = 2.69; Table 3). The p values for most age groups are <.0001, indicating that the observed differences in anxiety levels across ages are statistically significant. This suggests that age plays a crucial role in anxiety severity, with some age groups experiencing heightened anxiety.

Table 3.

Anxiety Age Numerical Analysis.

Age	Score	N Obs	Mean	Std Dev	Pr > \|t\|
19	33	8	4.1250000	3.7201190	.0165
20	56	16	3.5000000	2.1291626	<.0001
25	118	23	5.1304348	3.2516338	<.0001
28	44	8	5.5000000	1.8516402	<.0001
29	22	6	3.6666667	1.2110601	.0007
30	174	42	4.1428571	2.3013403	<.0001
31	21	5	4.2000000	1.9235384	.0081
32	35	7	5.0000000	1.5275252	.0001
33	39	7	5.5714286	2.8199966	.0020
34	87	15	5.8000000	3.2557641	<.0001
35	69	17	4.0588235	2.2491829	<.0001
38	51	10	5.1000000	2.8848262	.0003
39	58	12	4.8333333	2.6227443	<.0001
40	122	25	4.8800000	2.3860707	<.0001
42	35	9	3.8888889	2.0883273	.0005
43	48	9	5.3333333	2.7838822	.0004
44	29	6	4.8333333	2.2286020	.0032
45	69	13	5.3076923	1.7974341	<.0001
47	31	8	3.8750000	1.8850919	.0007
48	30	7	4.2857143	1.6035675	.0004
50	25	5	5.0000000	2.8284271	.0168
55	105	20	5.2500000	2.5930068	<.0001
59	44	7	6.2857143	2.6903708	.0008
60	81	19	4.2631579	1.9956092	<.0001
65	129	29	4.4482759	2.2612608	<.0001
66	43	8	5.3750000	2.6692696	.0007
70	77	15	5.1333333	1.5055453	<.0001
72	42	9	4.6666667	2.5980762	.0007
75	72	17	4.2352941	1.7863864	<.0001
77	64	15	4.2666667	2.5485757	<.0001
78	31	6	5.1666667	1.8348479	.0010
80	163	29	5.6206897	2.4700173	<.0001
81	19	5	3.8000000	0.8366600	.0005
85	104	19	5.4736842	2.7155605	<.0001
86	23	5	4.6000000	1.5165751	.0025
89	17	4	4.2500000	0.5000000	.0004

Depression Age Numerical Analysis

The depression scores show an increasing trend, peaking at age 59 (Mean = 6.75, Std Dev = 2.71; Table 4).

Table 4.

Depression Age Numerical Analysis.

Age	Score	N Obs	Mean	Std Dev	Pr > \|t\|
19	36	8	4.5000000	1.6903085	.0001
20	75	15	5.0000000	2.4494897	<.0001
25	124	23	5.3913043	2.7259549	<.0001
28	37	7	5.2857143	2.2886885	.0009
29	55	9	6.1111111	3.0184617	.0003
30	207	46	4.5000000	2.2973415	<.0001
31	35	8	4.3750000	2.2638463	.0009
32	39	8	4.8750000	2.1671245	.0004
33	25	8	3.1250000	2.2320714	.0055
34	84	15	5.6000000	2.8735245	<.0001
35	105	23	4.5652174	2.0186874	<.0001
38	58	16	3.6250000	2.5000000	<.0001
39	68	16	4.2500000	2.1447611	<.0001
40	176	33	5.3333333	2.6887110	<.0001
42	25	7	3.5714286	2.6367368	.0116
43	40	8	5.0000000	2.1380899	.0003
44	42	8	5.2500000	1.9086270	.0001
45	68	16	4.2500000	2.3237900	<.0001
47	22	8	2.7500000	1.5811388	.0017
48	39	7	5.5714286	3.2586880	.0040
50	40	8	5.0000000	3.3380918	.0039
55	131	24	5.4583333	2.8586888	<.0001
59	54	8	6.7500000	2.7124054	.0002
60	130	25	5.2000000	3.0138569	<.0001
65	158	31	5.0967742	2.2855319	<.0001
66	37	8	4.6250000	2.9730936	.0032
70	75	16	4.6875000	2.0238165	<.0001
72	30	7	4.2857143	2.8115408	.0069
75	51	14	3.6428571	2.2051389	<.0001
77	65	16	4.0625000	1.5261608	<.0001
78	32	7	4.5714286	1.7182494	.0004
80	147	31	4.7419355	2.4626238	<.0001
81	51	8	6.3750000	2.0658793	<.0001
85	111	24	4.6250000	2.3922429	<.0001
86	42	8	5.2500000	1.8322508	<.0001
89	36	9	4.0000000	1.0000000	<.0001

This suggests that depression severity is more pronounced in middle-aged and older adults. The p values remain <.0001 for most observations, indicating a significant association between age and depression severity. The standard deviation values also suggest that there is considerable variability in depression scores across different age groups.

Dementia and Depression Age Numerical Analysis

When analysing individuals experiencing both dementia and depression, the mean scores remain high, particularly at ages 25 (Mean = 7.50, p = .0109) and 40 (Mean = 7.83, p = .0001; Table 5). These findings suggest that individuals at these ages may be at a heightened risk of co-occurring dementia and depression. The p values indicate that most of these observations are statistically significant.

Table 5.

Dementia and Depression Age Statistical Analysis.

Age	Score	N Obs	Mean	Std. Dev.	Pr > \|t\|
19	12	2	6.00	1.41	.1051
20	14	2	7.00	2.83	.1772
25	30	4	7.50	2.65	.0109
29	14	2	7.00	2.83	.1772
30	49	7	7.00	1.53	<.0001
32	16	2	8.00	1.41	.0792
34	15	2	7.50	2.12	.1257
35	12	2	6.00	2.83	.2048
38	13	3	4.33	0.58	.0059
39	19	3	6.33	0.58	.0028
40	47	6	7.83	1.72	.0001
43	12	2	6.00	1.41	.1051
45	11	2	5.50	0.71	.0577
55	19	3	6.33	0.58	.0028

Dementia and Anxiety Age Numerical Analysis

This analysis indicates that individuals aged 25 and 34 exhibit the highest mean scores (9.33 and 9.50, respectively), implying that these age groups may be at a greater risk for experiencing both dementia and anxiety (Table 6). The p values further support the statistical significance of these findings, with most values being <.05, indicating strong evidence for a relationship between these conditions.

Table 6.

Dementia and Anxiety Age Numerical Analysis.

Age	Score	N Obs	Mean	Std. Dev.	Pr > \|t\|
20	12	2	6.00	4.24	.2952
25	28	3	9.33	1.53	.0088
30	41	6	6.83	1.33	<.0001
34	19	2	9.50	0.71	.0335
35	14	3	4.67	1.53	.0339
39	15	2	7.50	2.12	.1257
40	35	4	8.75	0.50	<.0001

Other Diseases Among Survivors with Anxiety and Depression

Table 7 presents the prevalence of other diseases among individuals experiencing both anxiety and depression. Diabetes is observed in 20 individuals with both conditions, while hypertension is more prevalent, affecting 45 individuals. Asthma appears to have the highest co-occurrence, with 75 individuals affected. The presence of these comorbidities suggests a potential link between mental health conditions and chronic physical illnesses, emphasising the need for integrated healthcare approaches.

Table 7.

Other Diseases Among Survivors Who Have Anxiety and Depression.

Disease	Anxiety and Depression	Anxiety and Depression
Diabetes	20	35
Hypertension	45	30
Asthma	75	55

Discussion

Age has a crucial role in the onset and advancement of dementia. Dementia is not a typical component of the ageing process; however, it is more prevalent among both younger and older individuals.^{31, 32} Various age cohorts may exhibit differing levels of susceptibility to mental health issues following exposure to COVID-19.³⁴ Elderly individuals may have a higher vulnerability to developing dementia as a result of potential neuroinflammatory mechanisms activated by the virus. On the other hand, younger persons may be more susceptible to experiencing anxiety and sadness as a result of disturbances in their social and economic circumstances.^{20, 33, 34}

Age-specific psychosocial factors are also highly influential. Elderly individuals may encounter heightened feelings of isolation and reduced assistance from their social networks as a result of limitations on social engagements, perhaps intensifying indications of sadness and anxiety. On the other hand, younger people may experience stress due to factors such as job insecurity, interruptions in their education and an unclear outlook for the future.³⁷ Pre-existing health conditions, such as cardiovascular disease, diabetes or cognitive impairment, can have varying effects on the risk of developing dementia, anxiety and depression in different age groups when exposed to COVID-19. Gaining a comprehensive understanding of these interactions is crucial for implementing focused interventions and providing necessary support.^33–35

Elderly individuals face a higher risk of severe COVID-19 consequences due to pre-existing weaknesses in brain health and a greater likelihood of experiencing such results. The combination of age-related cognitive loss with the neurological effects of COVID-19 amplifies the chance of developing dementia.^{20, 34} Individuals with Pre-existing Mental Health Conditions Individuals who have pre-existing mental health concerns, such as anxiety or depression, are more prone to experiencing a worsening of their conditions after contracting COVID-19. This is because the stress caused by the sickness and the potential neuropsychiatric effects of the virus can exacerbate their mental health issues.³⁶ The findings have major long-term consequences for healthcare systems globally. There is a requirement for Enhanced Surveillance and Screening, Consistent observation of cognitive and psychological symptoms in individuals who have recovered from COVID-19, especially those in high-risk categories.

Integrated care models the integration of neurological, psychiatric and primary care services to offer comprehensive management of post-COVID disorders. Public Health Strategies Tackling the mental health crisis caused by the pandemic by implementing public health measures such as providing mental health support services and community programs. Research and Education Continual investigation to enhance comprehension of the underlying physiological processes connecting COVID-19 to dementia, anxiety and depression, and instruction of healthcare practitioners to identify and manage these diseases proficiently.^{36, 37}

For the purpose of developing targeted treatments and support systems, it is essential to acquire an understanding of the differences in mental health issues that are associated with different ages. This study delivers valuable insights that can be beneficial to healthcare professionals, representatives and researchers in customising strategies to challenge psychological health challenges according to the specific needs of different age groups. Age-stratified investigations into the psychological consequences of COVID-19 exposure are crucial for comprehending the intricate ramifications of the pandemic and guiding focused therapies and policies to assist individuals who are vulnerable to acquiring dementia, anxiety and depression.^31–33 The convergence between COVID-19 exposure and subsequent mental health conditions, such as dementia, anxiety and depression, has emerged as a notable focus in medical studies and public health.³⁷ This could worsen current disorders or lead to the start of new ones. The pandemic has caused considerable distress as a result of variables such as the apprehension of contracting the virus, the lack of social interaction, financial insecurity and the unpredictability of what lies ahead.^{34, 35}

Depression can last for a prolonged period even after the initial phase of the illness, and some people may go through persistent episodes of depression.^14–19 Consider including the data in a research study or survey that delves into the co-occurrence of mental health issues and other physical disorders. These data can be valuable for comprehending any connections or coexisting illnesses between different ailments, which can assist healthcare practitioners in delivering enhanced care and assistance for people with multiple health issues.^35–38

The data show that there are age differences in the prevalence of these diseases. This could be due to various factors, including genetic, hormonal and lifestyle differences. The data might be part of a study or survey that investigates the co-occurrence of mental health conditions and other medical conditions among survivors.^{21, 36} Such data can be useful for understanding potential associations or comorbidities between these conditions, which can help healthcare professionals in providing better care and support for patients with multiple health concerns.^36–38

Multiple research studies and observations have identified numerous elements that contribute to this increased risk.^33–35 The pandemic has instilled a pervasive sense of fear and uncertainty over health, wealth and the future. This ambiguity has the potential to induce anxiety and worsen pre-existing mental health issues. Humans possess an innate inclination towards social interaction, and extended periods of isolation can lead to experiences of solitude, melancholy and unease.³⁴

The epidemic has resulted in a significant mortality rate, leading to the demise of several persons and the subsequent grief experienced by their loved ones. Grief significantly contributes to the development of depression and anxiety. The interruption of daily rituals, deprivation of regularity and annulment of significant occasions (such as marriages, graduations, etc.) have resulted in a feeling of bereavement and psychological anguish. Healthcare professionals face an elevated susceptibility to anxiety and depression as a result of the demanding nature of their work during the pandemic, which includes extended shifts, heavy patient caseloads and exposure to severe disease and mortality. Moral harm can be observed among healthcare professionals when they are compelled to make choices that contradict their ethical principles, such as allocating limited care resources or witnessing avoidable fatalities. Disruptions caused by the epidemic have hindered people’s ability to receive mental health treatments.^32–34

Many people are facing challenges in accessing care because clinics have closed, resources have been redirected, or they are afraid to seek in-person treatment. Telehealth has increased healthcare accessibility for certain individuals, but it remains inaccessible to people without dependable internet access or the necessary technological skills to utilise virtual platforms. The neurological effects of COVID-19 are becoming increasingly apparent, indicating that the virus can directly disrupt the brain, perhaps leading to changes in brain function and the development of psychiatric disorders. The virus has the potential to initiate inflammation or disturb the balance of neurotransmitters, resulting in mood problems. The pandemic can exacerbate pre-existing mental health issues, leading to a worsening of symptoms owing to increased stress and disruption.^19–24 The obstacles presented by COVID-19 can intensify the feelings of anxiety and sadness. To effectively support individuals in recovering and sustaining their mental health after COVID-19, it is crucial to comprehend and treat the intricate interaction of various elements that contribute to anxiety and sadness.^{37, 38}

Conclusion

The study highlights the significant impact of COVID-19 on mental health, linking exposure to the virus with increased risks of dementia, anxiety and depression. Elderly individuals are more vulnerable to dementia due to neurological effects, while younger adults experience heightened anxiety and depression from social and economic disruptions. The pandemic has worsened mental health conditions, particularly in those with pre-existing cognitive or psychiatric disorders, emphasising the need for targeted interventions. Economic instability, social isolation and healthcare challenges further contribute to stress and anxiety. Addressing these concerns through improved healthcare accessibility, mental health support and socioeconomic assistance is crucial for post-pandemic recovery and long-term well-being.

Footnotes

Acknowledgement

We like to convey our appreciation to all the writers, co-authors and supportive personnel for their tremendous aid in this endeavour.

Authors’ Contribution

Data gathering, manuscript preparation and revisions were all done by Jigar S. Padhiar. The identification of important intellectual content was the responsibility of Dr Uddipak Rai, who also contributed to the article’s creation, editing and critical evaluation. The writers have reviewed and approved the final manuscript, and they both commit to being fully responsible for the work, including making sure it is true and honest. No possible conflicts of interest involving either writer’s work have been reported.

Data Availability Statement

Includes original data generated.

Statement of Ethics

Prior to the beginning of the investigation, permission from the Hospital and University Research Ethics Committee (UREC) was obtained from the ethics committee. The participants gave their consent after being fully informed.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

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

ICMJE Statement

This research (CTRI Ref No.: REF/2025/01/098554) was largely the brainchild of both writers, who also helped with its design and implementation.

ORCID iD

Jigar Sanjiv Padhiar

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