Evidence of mental health-related morbidities and its association with socio-economic status among previously hospitalized patients with symptoms of COVID-19 in Bangladesh

Introduction The long-term impact of COVID-19 on mental health, particularly in relation to socio-economic vulnerabilities, has received little attention. This study reports the prevalence of mental health-related symptoms among previously hospitalized patients after recovery from COVID-19, and its association with socio-economic status (SES). Methods Data collection of this cross-sectional study was conducted during February–April 2021, among previously hospitalized patients with COVID-19 like symptoms, on average six months after their discharge from the hospital. Using DASS-21, a validated scale to document symptoms of depression, anxiety, and stress, information on mental health-related symptoms were recorded from 481 respondents along with sociodemographic and economic information through telephone interviews. Chi-square tests were performed to identify significant group differences. Multinomial logistic regression analyzed the association between the changes in socioeconomic characteristics and mental health-related symptoms. Relative index of inequality (RII), slope index of inequality (SII), and concentration index (CIX) were applied to capture relevant inequalities in relation to mental health-related symptoms. Results Eleven percent of the respondents reported changes in employment status, nearly half changes in income and expenditure. Forty-five percent reported symptoms of depression, anxiety and/or stress, and 12% reported coexistence of all three symptoms. Women [Adjusted Odds Ratio, AOR: 2.95;95% Confidence Interval, CI: 1.39–5.68], and those who reported changes in occupation [AOR: 3.04;95% CI: 1.01–9.08] and expenditure [AOR: 2.46;95% CI: 1.12–5.37] were more likely to report all three mental health-related symptoms compared to men and those without changes in occupation and expenditure. The older age group was less likely [AOR: 0.96;95%CI: 0.93–0.99] to report coexistence of all three symptoms compared to their younger counterparts. Negative values of concentration index (CIX) indicate that any one mental health-related symptom was significantly concentrated among those with lower expenditure and poor SES. Conclusion This study will help in addressing mental health-related challenges after recovery from COVID-19 among the identified vulnerable groups through relevant community-based and clinical response, including counseling services, in Bangladesh and similar LMIC contexts.

Evidence of mental health-related morbidities and its association with socio-economic status among previously hospitalized patients with symptoms of COVID-19 in Bangladesh.

Introduction: The long-term impact of COVID-19 on mental health, particularly in relation to socio-economic vulnerabilities, has received little attention. This study reports the prevalence of mental health-related symptoms among previously hospitalized patients after recovery from COVID-19, and its association with socio-economic status (SES). Methods: Data collection of this cross-sectional study was conducted during February-April 2021, among previously hospitalized patients with COVID-19 like symptoms, on average six months after their discharge from the hospital. Using DASS-21, a validated scale to document symptoms of depression, anxiety, and stress, information on mental health-related symptoms were recorded from 481 respondents along with sociodemographic and economic information through telephone interviews. Chi-square tests were performed to identify significant group differences. Multinomial logistic regression analyzed the association between the changes in socioeconomic characteristics and mental health-related symptoms. Relative index of inequality (RII), slope index of inequality (SII), and concentration index (CIX) were applied to capture relevant inequalities in relation to mental health-related symptoms. Results: Eleven percent of the respondents reported changes in employment status, nearly half changes in income and expenditure. Forty-five percent reported symptoms of depression, anxiety and/or stress, and 12% reported coexistence of all three symptoms. Women [Adjusted Odds Ratio, AOR: 2.95; 95% Confidence Interval, CI: 1.39-5.68], and those who reported changes in occupation [AOR: 3.04; 95% CI: 1.01-9.08] and expenditure [AOR: 2.46; 95% CI: 1.12-5.37] were more likely to report all three mental health-related symptoms compared to men and those without changes in occupation and expenditure. The older age group was less likely [AOR: 0.96; 95%CI: 0.93-0.99] to report coexistence of all three symptoms compared to their younger counterparts. Negative values of concentration index (CIX) indicate that any one mental health-related symptom was significantly concentrated among those with lower expenditure and poor SES. Conclusion: This study will help in addressing mental health-related challenges after recovery from COVID-19 among the identified vulnerable groups through relevant community-based and clinical response, including counseling services, in Bangladesh and similar LMIC contexts.

Natural therapeutics and nutraceuticals for lung diseases: Traditional significance, phytochemistry, and pharmacology.

BACKGROUND: Lung diseases including chronic obstructive pulmonary disease (COPD), infections like influenza, acute respiratory distress syndrome (ARDS), asthma and pneumonia lung cancer (LC) are common causes of sickness and death worldwide due to their remoteness, cold and harsh climatic conditions, and inaccessible health care facilities. PURPOSE: Many drugs have already been proposed for the treatment of lung diseases. Few of them are in clinical trials and have the potential to cure infectious diseases. Plant extracts or herbal products have been extensively used as Traditional Chinese Medicine (TCM) and Indian Ayurveda. Moreover, it has been involved in the inhibition of certain genes/protiens effects to promote regulation of signaling pathways. Natural remedies have been scientifically proven with remarkable bioactivities and are considered a cheap and safe source for lung disease. METHODS: This comprehensive review highlighted the literature about traditional plants and their metabolites with their applications for the treatment of lung diseases through experimental models in humans. Natural drugs information and mode of mechanism have been studied through the literature retrieved by Google Scholar, ScienceDirect, SciFinder, Scopus and Medline PubMed resources against lung diseases. RESULTS: In vitro, in vivo and computational studies have been explained for natural metabolites derived from plants (like flavonoids, alkaloids, and terpenoids) against different types of lung diseases. Probiotics have also been biologically active therapeutics against cancer, anti-inflammation, antiplatelet, antiviral, and antioxidants associated with lung diseases. CONCLUSION: The results of the mentioned natural metabolites repurposed for different lung diseases especially for SARS-CoV-2 should be evaluated more by advance computational applications, experimental models in the biological system, also need to be validated by clinical trials so that we may be able to retrieve potential drugs for most challenging lung diseases especially SARS-CoV-2.

Mucormycosis and COVID-19 pandemic: Clinical and diagnostic approach.

The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is yet to be controlled worldwide, especially in India. The second wave of coronavirus disease 2019 (COVID-19) led to panic and confusion in India, owing to the overwhelming number of the population that fell prey to this highly infectious virus of recent times. In the second wave of COVID-19, the patients had to fight both the virus and opportunistic infections triggered by fungi and bacteria. Repeated use of steroids, antibiotics, and oxygen masks during the management of severely and critically ill COVID-19 patients nurtured opportunistic infections such as mucormycosis. Despite mucormycosis being a decades-old disease, it has gained notice of its widespread occurrence in COVID-19 patients throughout India. Instances of mucormycosis are usually unearthed in immunocompromised individuals and are caused by the inhalation of filamentous fungi, either from the natural environment or through supportive care units. In the recent outbreak during the second wave of COVID-19 in India, it has been seen to cause secondary infection as it grows along with the treatment of COVID-19. Furthermore, COVID-19 patients with comorbidities such as diabetes were more likely to have the mucormycosis co-infection because of their challenged immune systems' inability to fight it. Despite the hype, mucormycosis still remains neglected and least studied, which is predominantly due to all focus on diagnostics, vaccine, and therapeutic research. In this review, we emphasize mainly on the association of mucormycosis in COVID-19 patients. We also present the molecular mechanism of mucormycosis for a better understanding of the fungal infections in patients who have recently been infected with SARS-CoV-2. Better understanding of fungal pathogens, immediate diagnosis, and management of the infections are crucial in COVID-19 patients, as high mortalities have been recorded in co-infected patients despite recovery from COVID-19.

Comparing COVID-19 physical distancing policies: results from a physical distancing intensity coding framework for Botswana, India, Jamaica, Mozambique, Namibia, Ukraine, and the United States.

BACKGROUND: Understanding the differences in timing and composition of physical distancing policies is important to evaluate the early global response to COVID-19. A physical distancing intensity monitoring framework comprising 16 domains was recently published to compare physical distancing approaches across 12 U.S. States. We applied this framework to a diverse set of low and middle-income countries (LMICs) (Botswana, India, Jamaica, Mozambique, Namibia, and Ukraine) to test the appropriateness of this framework in the global context and to compare the policy responses in these LMICs with a sample of U.S. States during the first 100-days of the pandemic. RESULTS: The LMICs in our sample adopted wide ranging physical distancing policies. The highest peak daily physical distancing intensity during this period was: Botswana (4.60); India (4.40); Ukraine (4.40); Namibia (4.20); Mozambique (3.87), and Jamaica (3.80). The number of days each country stayed at peak policy intensity ranged from 12-days (Jamaica) to more than 67-days (Mozambique). We found some key similarities and differences, including substantial differences in whether and how countries expressly required certain groups to stay at home. Despite the much higher number of cases in the US, the physical distancing responses in our LMIC sample were generally more intense than in the U.S. States, but results vary depending on the U.S. State. The peak policy intensity for the U.S. 12-state average was 3.84, which would place it lower than every LMIC in this sample except Jamaica. The LMIC sample countries also reached peak physical distancing intensity earlier in outbreak progression compared to the U.S. states sample. The easing of physical distancing policies in the LMIC sample did not discernably correlate with change in COVID-19 incidence. CONCLUSIONS: This physical distancing intensity framework was appropriate for the LMIC context with only minor adaptations. This framework may be useful for ongoing monitoring of physical distancing policy approaches and for use in effectiveness analyses. This analysis helps to highlight the differing paths taken by the countries in this sample and may provide lessons to other countries regarding options for structuring physical distancing policies in response to COVID-19 and future outbreaks.