Impact of COVID-19 and comorbidities on health and economics: Focus on developing countries and India

Assessment of Direct Medical Cost of Hospitalized COVID-19 Adult Patients in Kuwait During the First Wave of the Pandemic

Objective

This study aims to estimate the direct medical cost of COVID-19 hospitalizations and to utilize prevalence estimates from Jaber Al-Ahmad Hospital to estimate the direct medical cost of all hospitalized adult patients in Kuwait using a decision tree analysis.

Methods

A cost-of-illness model was developed. The Ministry of Health perspective was considered, direct medical costs were estimated from July 1st to September 30th, using a bottom-up approach. The mean cost per hospitalized patient was estimated using a decision analysis model. Prevalence estimates of ambulance use, use of ER, ICU admission, and mortality were considered in the current study. Patients aged 18 years and above with a confirmed diagnosis of COVID-19 were included. One-way sensitivity analysis and probabilistic sensitivity analysis (PSA) were performed.

Results

Data for 2986 patients were analyzed. The mean age was 61 (SD= 11) years old. Most of the patients were Kuwaiti (2864, 95.91%), and more than half were females (1677, 56.16%). Of the total hospital admissions, 417 patients (14%) were admitted to the ICU. The average length of the hospital stay was 11 (SD= 9) days, and among all hospital admissions, 270 (9.04%) patients died. The total estimated direct medical cost of hospitalized patients at Jaber Al-Ahmad Hospital was $47,213,768 (14,283,203.6 KD). The average cost of hospital stay per patient was estimated at $15,498 (4,688.60 KD). The weighted average cost per hospitalized patient in Kuwait was estimated at $16,373 (4,953.08 KD). The total direct medical cost of hospitalized COVID-19 patients in Kuwait during the study period was estimated at $174,372,450 (52,751,502 KD).

Conclusion

The COVID-19 pandemic constituted a significant burden on the Kuwaiti healthcare system. The findings of this study urge the need for preventive care strategies to reduce adverse health outcomes and the economic impact of the pandemic.

Prospective Study of Incidence and Impact of Comorbidities on Breast Cancer Survival from India

PURPOSE

To report comorbidity burden in newly-diagnosed treatment-naïve breast cancer patients and its effect on survival.

METHODS

Prospective observational study in which demographic, comorbidity and outcome data from a consecutive cohort of patients diagnosed and treated between September 2019 to September 2021 were collected. Charlson Comorbidity Index (CCI) score was calculated for all and proportion of each comorbidity was determined at diagnosis (baseline), at conclusion and six-months post-treatment. Univariate and multivariate analysis was done for impact of various demographic and disease-related factors on the incidence of comorbidities as well as on progression free survival (PFS) and overall survival (OS).

RESULTS

Out of five hundred patients who consented for the study, 416 patients completed planned treatment and only 206 patients had physical follow-up due to COVID-19 pandemic. Incidence of comorbidity at the three time-points was 24%, 32% and 26% respectively. The difference was significant compared to baseline at both the time-points (p<0.05). Hypertension and diabetes were the most common types (incidence 15%-21% and 12-18% respectively) of comorbidities. Advancing age, post-menopauusal status and not being married were significant factors for presence of comorbidities. Median follow-up was 27 months (95% CI 26.25-28.55 months). Presence of multiple comorbidities was a poor prognostic factor for both PFS (2-yr PFS 85% vs 77%) and OS (2-yr OS 89% vs 79%) (both p=0.04) but no such correlation for CCI score.

CONCLUSION

Breast cancer treatment impacted incidence of comorbidities. Presence of multiple comorbidities had an adverse impact on survival. Hence, further research on treatment optimization is required in patients with substantial comorbidities.

Incidence and predictors of development of new onset hypertension post COVID-19 disease

AIMS

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 virus) affects vital organs and causes vascular injury. There are concerns that this injury may have long-term consequences on the cardiovascular system after recovery from COVID-19. We investigated the incidence and predictors of new-onset hypertension at 1-year follow-up post-COVID-19 disease.

METHODS

In this prospective observational study, 393 patients hospitalised and diagnosed with COVID-19 disease at a tertiary cardiac care hospital during 27th March 2021 to 27th May 2021. Eligible 248 patients whose baseline characteristics, laboratory findings, treatment and outcome data were received systematically. Patients were followed up at 1 year of COVID-19 disease recovery.

RESULTS

We found that 32.3% of the population had new onset of hypertension at 1 year follow-up post-COVID-19 disease recovery. More hypertensive patients had severe computed tomography (CT) score severity (28.7 vs 14.9%; P 0.02). More number of patients in the hypertensive group were treated with steroids (73.8% vs 39%; p < 0.0001) during hospital stay. In-hospital complications were higher (12.5 vs 4.2%; P 0.03) in the hypertensive group. Patients who developed new-onset hypertension had statistically significantly higher baseline values of serum ferritin and C-reactive protein (CRP) (P 0.02 and 0.03 respectively). Vascular age was found 12.5 ± 3.96 years more than chronological age in hypertensive patients.

CONCLUSION

New onset of hypertension was detected in 32.3% of patients at one-year follow-up post-COVID-19 disease recovery. Severe inflammation at the time of admission and severe CT severity score were associated with the development of new onset of hypertension on follow-up.

The Rise and Fall of Omicron BA.1 Variant as Seen in Wastewater Supports Epidemiological Model Predictions

The COVID-19 pandemic caused by the SARS-CoV-2 virus has inflicted significant mortality and morbidity worldwide. Continuous virus mutations have led to the emergence of new variants. The Omicron BA.1 sub-lineage prevailed as the dominant variant globally at the beginning of 2022 but was subsequently replaced by BA.2 in numerous countries. Wastewater-based epidemiology (WBE) offers an efficient tool for capturing viral shedding from infected individuals, enabling early detection of potential pandemic outbreaks without relying solely on community cooperation and clinical testing resources. This study integrated RT-qPCR assays for detecting general SARS-CoV-2 and its variants levels in wastewater into a modified triple susceptible-infected-recovered-susceptible (SIRS) model. The emergence of the Omicron BA.1 variant was observed, replacing the presence of its predecessor, the Delta variant. Comparative analysis between the wastewater data and the modified SIRS model effectively described the BA.1 and subsequent BA.2 waves, with the decline of the Delta variant aligning with its diminished presence below the detection threshold in wastewater. This study demonstrates the potential of WBE as a valuable tool for future pandemics. Furthermore, by analyzing the sensitivity of different variants to model parameters, we are able to deduce real-life values of cross-variant immunity probabilities, emphasizing the asymmetry in their strength.

Perspective of healthcare providers on assessing the quality and accessibility of health services for chronic diseases in Jordan during Covid-19: a mixed method study

BACKGROUND

Hospital services in all parts of the world were severely affected by the crisis caused by the Coronavirus pandemic. This was particularly concerning for patients who suffer from chronic diseases.

AIM

This study aimed to: assess the level of quality and accessibility of chronic disease services from the perspectives of healthcare providers, assess the association between healthcare providers' socio-demographic factors and their perspectives on accessibility and quality level, and explore the providers' perspectives on the barriers and facilitators of quality and accessibility to chronic disease health services during the COVID -19 pandemic.

METHOD

Design: An explanatory mixed method design was employed in this study using a questionnaire and focus group discussion approach. The questionnaire consisted of three sections including, demographic, accessibility, and quality.

SAMPLE

A convenience sampling approach was used to collect the quantitative from 412 healthcare providers working at public, private, and teaching hospitals. A purposive sample of 12 healthcare providers were interviewed to collect the qualitative data.

ANALYSIS

The quantitative data were analyzed using SPSS Statistics Version 25. The qualitative data was analyzed using the thematic analysis approach.

RESULTS

This study found that the quality and accessibility of chronic disease services in northern Jordan were affected during COVID-19. Quantitative: The majority of the participants reported moderate level of accessibility and quality. Qualitative: Four main and six subthemes were identified: 1) Accessibility barriers including transportation and fear of infection; 2) Accessibility facilitators including availability of Personal Protective Equipment (PPE) and Covid-19 vaccination; 3) Quality barriers including staff shortage; 4) Quality facilitators including safety protocol.

CONCLUSION

The quality and accessibility of chronic disease services were affected due to the healthcare system restating to address the Covid-19 pandemic. Different barriers and facilitators for chronic disease healthcare services accessibility and quality were identified. The findings of this study lay the ground for healthcare decision and policymakers to develop strategies and formulate polices to ensure these patients receive the needed healthcare services, and hence improve their health outcomes.

Quantitative Framework for Establishing Low-Risk Inter-District Travel Corridors During COVID-19

Aspirations to slow down the spread of novel Coronavirus (COVID-19) resulted in unprecedented restrictions on personal and work-related travels in various nations across the globe in 2020. As a consequence, economic activities within and across the countries were almost halted. As restrictions loosen and cities start to resume public and private transport to revamp the economy, it becomes critical to assess the commuters' travel-related risk in light of the ongoing pandemic. The paper develops a generalizable quantitative framework to evaluate the commute-related risk arising from inter-district and intra-district travel by combining nonparametric data envelopment analysis for vulnerability assessment with transportation network analysis. It demonstrates the application of the proposed model for establishing travel corridors within and across Gujarat and Maharashtra, two Indian states that have reported many COVID-19 cases since early April 2020. The findings suggest that establishing travel corridors between a pair of districts solely based on the health vulnerability indices of the origin and destination discards the en-route travel risks from the prevalent pandemic, underestimating the threat. For example, while the resultant of social and health vulnerabilities of Narmada and Vadodara districts is relatively moderate, the en-route travel risk exacerbates the overall travel risk of travel between them. The study provides a quantitative framework to identify the alternate path with the least risk and hence establish low-risk travel corridors within and across states while accounting for social and health vulnerabilities in addition to transit-time related risks.

The Pattern of COVID-19 in Horn of Africa countries, from March-December 2020

BACKGROUND

Coronavirus-19 (COVID-19) is a novel, highly infectious, and potentially fatal communicable pandemic disease. It has taken longer to reach Africa than the other continents.

OBJECTIVE

To examine the pattern of COVID-19 in the Horn of Africa countries from March to December 2020.

METHODS

A prospective cross-sectional study in which the total number of daily reported cases and deaths were collected from the official website of the World Health Organization (WHO) and Worldometer. Data were standardized based on the total population provided by World Population Prospects 2020 per million. Data sources of WHO reports and governmental reports from March to December 2020 were analyzed in this study. Data extraction was done using the microsoft excel spreadsheet tool, variables relating to the countries were computed in terms of frequencies and percentages.

RESULTS

The findings revealed that as of 31st December 2020, 136,129 (7590 per million) cases were reported from the four countries in the Horn of Africa. The overall case fatality rate (CFR) in the Horn of Africa was 1.14%. The majority of the cases were reported from Djibouti (77.20%), followed by Ethiopia (14.07%), Eritrea (4.87%), and Somalia (3.86%). The highest case fatality rate (0.81%) was from Djibouti, and the lowest (0.01%) was from Eritrea.

CONCLUSIONS

The epidemiological pattern of COVID-19 among the Horn of African countries seems to have slow progress, given the prevalence of the new infections remains low, and the death toll seems stable throughout the study periods, except for Djibouti. Hence, the prevention control measures implemented in the countries should be further strengthened and supported. It is recommended that relevant stakeholders responsible for tackling the COVID-19 pandemic should put up measures to curb the spread of the virus in the region and set up a crisis management system to combat future pandemics.

Health Literacy and Clinic-Epidemiological Profile of Patients with COVID-19-Associated Mucormycosis: A Questionnaire-Based Study

Background The patient partnership is desirable for the optimal management of comorbidities. This became significant more so during the coronavirus disease 2019 (COVID-19) crisis wherein health infrastructure was overburdened.

Objectives The aim of this study was to estimate the clinicoepidemiological profile, health literacy regarding predisposing risk factors, and disease management in patients with COVID-19-associated mucormycosis (CAMCR).

Materials and Methods A structured questionnaire-based study on randomly chosen 100 microbiologically proven patients of CAMCR, consisting of 38 multiple choice questions, was designed with each answer having a patient and assessor response to it.

Results A male predilection was seen (68%) with rhino-orbital (73%) being the commonest anatomic site. Forty-nine percent of the study participants had pre-existing diabetes of which 62% did not carry out regular blood sugar monitoring and in 18%, blood sugars were controlled prior to COVID-19. Thirty-five percent of patients with mild COVID-19 illness were treated with unwarranted steroids and 56% of patients had fluctuating blood sugar levels, during COVID-19 illness.

Seventy-nine percent of patients were not vaccinated against COVID-19, 16% only partially vaccinated. Seventy-one percent of patients were not aware of red flag signs and of mucormycosis with 8% presenting early, on noticing nasal symptoms.

Conclusion This study observed diabetes as the most common comorbidity in patients with CAMCR. A lacuna in the health literacy of diabetics presenting with CAMCR was found. Additionally, knowledge regarding glycemic control during COVID-19 illness with or without the use of steroids and awareness of the “red flag” signs of CAMCR were mostly lacking. Interventions to improve awareness amongst patients with diabetes should help in optimal glycemic control, and avoid potential complications like severe COVID-19 illness, and mucormycosis.

Impact of comorbidity on patients with COVID-19 in India: A nationwide analysis

Background

The emergence of coronavirus disease (COVID-19) as a global pandemic has resulted in the loss of many lives and a significant decline in global economic losses. Thus, for a large country like India, there is a need to comprehend the dynamics of COVID-19 in a clustered way.

Objective

To evaluate the clinical characteristics of patients with COVID-19 according to age, gender, and preexisting comorbidity. Patients with COVID-19 were categorized according to comorbidity, and the data over a 2-year period (1 January 2020 to 31 January 2022) were considered to analyze the impact of comorbidity on severe COVID-19 outcomes.

Methods

For different age/gender groups, the distribution of COVID-19 positive, hospitalized, and mortality cases was estimated. The impact of comorbidity was assessed by computing incidence rate (IR), odds ratio (OR), and proportion analysis.

Results

The results indicated that COVID-19 caused an exponential growth in mortality. In patients over the age of 50, the mortality rate was found to be very high, ~80%. Moreover, based on the estimation of OR, it can be inferred that age and various preexisting comorbidities were found to be predictors of severe COVID-19 outcomes. The strongest risk factors for COVID-19 mortality were preexisting comorbidities like diabetes (OR: 2.39; 95% confidence interval (CI): 2.31-2.47; p < 0.0001), hypertension (OR: 2.31; 95% CI: 2.23-2.39; p < 0.0001), and heart disease (OR: 2.19; 95% CI: 2.08-2.30; p < 0.0001). The proportion of fatal cases among patients positive for COVID-19 increased with the number of comorbidities.

Conclusion

This study concluded that elderly patients with preexisting comorbidities were at an increased risk of COVID-19 mortality. Patients in the elderly age group with underlying medical conditions are recommended for preventive medical care or medical resources and vaccination against COVID-19.

Approaches to engage an aging, rural cohort in southern India during the COVID-19 crisis and the psychological impact of COVID-19 in this cohort

INTRODUCTION

The COVID-19 pandemic produced an unprecedented crisis across the world. Long-term cohort studies were stalled, including our longitudinal aging cohort study in rural India.

METHODS

We describe approaches undertaken to engage with our cohort (n = 1830) through multiple rounds of calls and how we provided useful services to our subjects during the lockdown period. Consenting subjects also underwent telephonic assessments for depression and anxiety using validated, self-report questionnaires.

RESULTS

Subjects reported benefitting from our telephonic engagement strategies, including the COVID-related safety awareness and counselling service. The proportion of subjects with depression increased from 7.42% pre-COVID to 28.97% post-COVID.

DISCUSSION

We envisage that such engagement strategies would improve subject rapport and cohort retention, and thus, could be adopted by similar cohort studies across the world. This marginalized, rural Indian community had severe, adverse psychological impact in this pandemic. Urgent public health measures are needed to mitigate this impact and develop appropriate preventive strategies.

Association of Alleles of Human Leukocyte Antigen Class II Genes and Severity of COVID-19 in Patients of the 'Red Zone' of the Endocrinology Research Center, Moscow, Russia

The aim of this study was to assess the correlations of clinical features of patients with moderate and severe courses of COVID-19, comorbidity (endocrine, autoimmune, cardiovascular, oncological, and pulmonary diseases), and alleles of the HLA class II system genes. One hundred COVID-19 patients hospitalized in the Endocrinology Research Centre, Moscow, Russia, were analyzed for age, gender, smoking, comorbidity, and invasive mechanical ventilation. Computer tomography was used to assess the severity of the disease. HLA-DRB1, HLA-DQA1, and HLA-DQB1 alleles were identified in samples from 100 patients and samples from 327 randomly selected individuals collected in the prepandemic period (control group). There was no association of gender, age, weight, body mass index, smoking, and comorbidity with the severity of COVID-19. Allele DQB1*06:02-8 was more common in patients (p < 0.00005), and DQB1*06:01 and DQB1*05:03 were more common in the control group (p < 0.00005, and p = 0.0011, respectively). DQB1*06:02-8 can probably be considered as predisposing to moderate and severe COVID-19, and DQB1*06:01 can be considered as protective. No association of these alleles with comorbidity was found. Our results suggest that carriers of predisposing alleles, with cardiovascular and non-autoimmune endocrine diseases, should take more stringent preventive measures, and if infected, a more aggressive COVID-19 treatment strategy should be used.

Comparison of clinical characteristics between SARS-CoV-2 Omicron variant and Delta variant infections in China

Background

The continued 'evolution' of Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to the emergence of the Omicron variant after the Delta variant, resulting in a significant increase in the number of people with COVID-19. This increase in the number of cases continues to have a significant impact on lives. Therefore, a more detailed understanding of the clinical characteristics of Omicron infection is essential.

Methods

Using medical charts, we extracted clinical information for 384 patients infected with the Omicron variant in Anyang City, Henan Province, China. Epidemiology and clinical characteristics were compared with a cohort of people infected with the Delta variant in Zhengzhou in 2021.

Findings

Common initial symptoms at onset of illness were cough [240 (63%)], expectoration [112 (29%)], fever [96 (25%)], nasal congestion [96 (25%)] and myalgia or fatigue [30 (6%)]. In patients with the Omicron variant, levels of total cholesterol, low-density lipoprotein and creatinine increased in 52 (14%), 36 (9%) and 58 (15%) patients, respectively, compared with patients with the Delta variant [one (1%), one (1%) and two (2%)]. Levels of triglyceride and high-density lipoprotein also increased. In patients with the Omicron variant, the levels of specific gravity and the erythrocyte sedimentation rate were increased in 115 (30%) and 81 (21%) patients, and serum levels of complement 3 decreased in 93 (41%).

Results

Compared with patients infected with Delta, no major differences in initial clinical symptoms were identified in patients infected with Omicron. However, dyslipidemia and kidney injury were much more severe in patients with the Omicron variant, and the erythrocyte sedimentation rate was increased. Due to decreased levels of complement 3, the immunity of patients with the Omicron variant was weak.

The impact of COVID-related economic shocks on household mental health in Pakistan

We combine data collected just prior to the unfolding of COVID-19 with follow-up data from July 2020 to document the adverse economic effects of the pandemic and resulting impact on parental and child mental well-being in peri-urban Pakistan. 22% of the households in our sample are affected by job loss, with monthly income down 38% on average. Our difference-in-difference results show that job loss is associated with a 0.88 standard deviation (SD) increase in adult mental distress scores (K10), a 0.43 SD reduction in a Hope index of children's aspirations, agency and future pathways, and a 0.39 SD increase in children's depression symptoms. In addition, we observe higher levels of parental stress and anger reported by children, as well as an increase in reported prevalence of domestic violence. Overall, we document that the pandemic has disproportionately and negatively affected the economic and mental well-being of the most vulnerable households in our sample.

Modeling the Transmission Dynamics of COVID-19 Among Five High Burden African Countries

Background

Today, coronavirus disease-19 has left a permanent dark mark on the history of human beings. The ongoing global pandemic outbreak of COVID-19 has spread to 58 African countries, with over 6.07 million confirmed cases and over 151,412 deaths. The five high burden African countries are South Africa, Morocco, Tunisia, Ethiopia, and Libya, with case fatality rates (CFR) of nearly 0.15%, 0.042%, 0.22%, 0.006%, and 0.086%, respectively. This is why the research aims to adequately understand the transmission dynamics of the virus and its variants in five high-burden African countries.

Methods

Our study is a deterministic model, where the population is partitioned into five components on the epidemiological state of the individuals. We presented a year-structured susceptible, infected, mild severs, critical severe, and recover (SIMCR) compartmental model of COVID-19 disease transmission with incidence rate during the pandemic period.

Results

The number of susceptible individuals increased by 30,711,930 in South Africa, 5,919,837 in Morocco, 3,485,020 in Tunisia, 7,833,642 in Ethiopia, and 2,145,404 in Libya in the next 3 decades with compare to the unvaccinated population and the number of infected individuals decreased by 30,479,271 in South Africa, 19,809,751 in Morocco, 3,456,406 in Tunisia, 7,761,993 in Ethiopia, and 2,125,038 in Libya.

Conclusion

SIMCR model is used to describe the transmission of COVID-19 among five high-burden African countries. For the next 30 years, we will have around 86 million infected individuals and millions of death only in those five African countries. To reduce those problems, vaccination is the best and most effective mechanism. So vaccinating half of the populations in those countries helps to control and reduce the transmission rate of COVID-19 in Africa for the next 30 years. This leads to preventing 17,212,405 people from becoming infected and millions of deaths being reduced in those five high-burden African countries.

Cellular heterogeneity in disease severity and clinical outcome: Granular understanding of immune response is key

During an infectious disease progression, it is crucial to understand the cellular heterogeneity underlying the differential immune response landscape that will augment the precise information of the disease severity modulators, leading to differential clinical outcome. Patients with COVID-19 display a complex yet regulated immune profile with a heterogeneous array of clinical manifestation that delineates disease severity sub-phenotypes and worst clinical outcomes. Therefore, it is necessary to elucidate/understand/enumerate the role of cellular heterogeneity during COVID-19 disease to understand the underlying immunological mechanisms regulating the disease severity. This article aims to comprehend the current findings regarding dysregulation and impairment of immune response in COVID-19 disease severity sub-phenotypes and relate them to a wide array of heterogeneous populations of immune cells. On the basis of the findings, it suggests a possible functional correlation between cellular heterogeneity and the COVID-19 disease severity. It highlights the plausible modulators of age, gender, comorbidities, and hosts' genetics that may be considered relevant in regulating the host response and subsequently the COVID-19 disease severity. Finally, it aims to highlight challenges in COVID-19 disease that can be achieved by the application of single-cell genomics, which may aid in delineating the heterogeneity with more granular understanding. This will augment our future pandemic preparedness with possibility to identify the subset of patients with increased diseased severity.

Connecting the dots between inflammatory cascades of obesity and COVID-19 in light of mortal consequences-a review

Obesity is a term that has recently been referred to describe a condition in which a person has become a diseased vessel. Obesity's internal pathology is too mysterious as it has a close resemblance with fatal diseases pathology. Obesity and coronavirus disease 2019 (COVID-19) are simultaneous epidemics declared by many organizations after observing their rampage in the recent world. Oxidative stress, cytokine storm, interleukin, and their contribution to the internal adipocyte environment implicated in the cascades of inflammatory pathology are portrayed here. Major determinants like angiotensin-converting enzyme 2 (ACE2) and renin-angiotensin-aldosterone system (RAAS) axis are highly sensitive molecular factors. Data from various countries suggested a clinical overview of how greater body mass index (BMI) is related to greater COVID-19 risk. It also gives insight into how obese individuals are obligately getting admitted and combating COVID-19 in intensive care unit including children less than 13 years of age under ultimate therapeutic options. There are numerous studies currently taking place for finding a cure for obesity which are mainly focused on natural resources and novel therapies like photobiomodulation (PBM) consisting of laser treatment, infrared treatment, etc. as current pharmacological treatments are reported to have fatal adverse effects. Finally, it is discussed how attenuating obesity will be a solution for future combat strategy. This review gives light on the areas of coagulation, inflammatory parameters, cardiometabolic complications, endothelial dysfunctions, immunological infirmity due to COVID-19 in obese individuals. A conceptual outline about correlation between the inflammatory pathophysiological steps triggering the aggravation of fatal consequences has been drawn in this review.

Perceived risk and perceptions of COVID-19 vaccine: A survey among general public in Pakistan

Background

The coronavirus disease has become a global pandemic, and it continues to wreak havoc on global health and the economy. The development of vaccines may offer a potential eradication of COVID-19. This study evaluated the general knowledge, attitude, and perception of COVID-19 vaccines in the Pakistani population.

Methods

A self-reporting e-survey and questionnaire-based survey from vaccination centers of different cities of Pakistan among 502 participants were conducted. The questionnaire comprised four sections inquiring demographics, vaccination status, and perception or attitude towards the vaccine. Univariate logistic regression was applied to predict the knowledge, attitude and behavior of participants.

Results

The mean age of participants was 50.8±20.3 years. 53% of the participants have both doses of vaccine administered. Pain on the site of injection (49.8%) was the most common symptom, followed by asthenia (43.0%), muscle pain (29.5%), and swelling (24.5%) on the site of vaccine administration. Females complain of more symptoms than males. More severe symptoms were reported after the first dose of vaccine administration; these symptoms subsided within a week for most participants. Overall, the respondents have a positive attitude towards the vaccine. 47.4% are sure about the vaccine’s efficacy, 48.6% said getting vaccinated was their own decision, and 79.9% also recommended others to get vaccinated.

Conclusion

The study concluded that the Pakistani population has a positive attitude but inadequate knowledge towards COVID-19 vaccines. Immediate awareness and vaccination education programs should be conducted by the authorities to complete the mass vaccination schedule.

A critical evaluation of risk to reward ratio of quercetin supplementation for COVID-19 and associated comorbid conditions

The interim results of the large, multinational trials on coronavirus disease 2019 (COVID‐19) using a combination of antiviral drugs appear to have little to no effect on the 28‐day mortality or the in‐hospital course. Therefore, there is a still vivid interest in finding alternate re‐purposed drugs and nutrition supplements, which can halt or slow the disease severity. We review here the multiple preclinical studies, partially supported by clinical evidence showing the quercetin's possible therapeutic/prophylaxis efficacy against severe acute respiratory syndrome coronavirus (SARS‐CoV) as well as comorbidities like chronic obstructive pulmonary disease (COPD), diabetes mellitus, obesity, coagulopathy, and hypertension. Currently, 14 interventional clinical trials are underway assessing the efficacy of quercetin along with other antiviral drugs/nutritional supplements as prophylaxis/treatment option against COVID‐19. The present review is tempting to suggest that, based on circumstantial scientific evidence and preliminary clinical data, the flavonoid quercetin can ameliorate COVID‐19 infection and symptoms acting in concert on two parallel and independent paths: inhibiting key factors responsible for SARS‐CoV‐2 infections and mitigating the clinical manifestations of the disease in patients with comorbid conditions. Despite the broad therapeutic properties of quercetin, further high power randomized clinical trials are needed to firmly establish its clinical efficacy against COVID‐19.

Prevalence and Impact of Preexisting Comorbidities on Overall Clinical Outcomes of Hospitalized COVID-19 Patients

COVID-19 risk increases with comorbidities, and the effect is magnified due to the contribution of individual and combined comorbidities to the overall clinical outcomes. We aimed to explore the influence of demographic factors, clinical manifestations, and underlying comorbidities on mortality, severity, and hospital stay in COVID-19 patients. Therefore, retrospective chart reviews were performed to identify all laboratory-confirmed cases of SARS-CoV-2 infection in Apollo Hospitals, Hyderabad, between March 2020 and August 2020.A total of 369 confirmed SARS-CoV-2 cases were identified: 272 (73.7%) patients were male, and 97 (26.2%) were female. Of the confirmed cases, 218 (59.1%) had comorbidities, and 151 (40.9%) were devoid of comorbidities. This study showed that old age and underlying comorbidities significantly increase mortality, hospital stay, and severity due to COVID-19 infection. The presence of all four comorbidities, diabetes mellitus (DM) + Hypertension (HTN) + coronary artery disease (CAD) + chronic kidney disease (CKD), conferred the most severity (81%). The highest mortality (OR: 44.03, 95% CI: 8.64-224.27) was observed during the hospital stay (12.73 ± 11.38; 95% CI: 5.08-20.38) in the above group. Multivariate analysis revealed that nonsurvivors are highest (81%) in (DM + HTN + CAD + CKD) category with an odds ratio (95% CI) of 44.03 (8.64-224.27). Age, gender, and comorbidities adjusted odds ratio decreased to 20.25 (3.77-108.77). Median survival of 7 days was observed in the (DM + HTN + CAD + CKD) category. In summary, the presence of underlying comorbidities has contributed to a higher mortality rate, greater risk of severe disease, and extended hospitalization periods, hence, resulting in overall poorer clinical outcomes in hospitalized COVID-19 patients.

Early prediction of SARS-CoV-2 reproductive number from environmental, atmospheric and mobility data: A supervised machine learning approach

INTRODUCTION

SARS-CoV-2 was declared a pandemic by the WHO on March 11th, 2020. Public protective measures were enforced in every country to limit the diffusion of SARS-CoV-2. Its transmission, mainly by droplets, has been measured by the effective reproduction number (Rt) that counts the number of secondary cases caused in a population by an average infectious individual at time t. Current strategies to calculate Rt reflect the number of secondary cases after several days, due to a delay from symptoms onset to reporting. We propose a complementary Rt estimation using supervised machine learning techniques to predict short term variations with more timely results.

MATERIAL AND METHODS

Our primary goal was to predict Rt of the current day in the twelve provinces of Lombardy with the highest possible accuracy, and with no influence of the local testing strategies. We gathered data about mobility, weather, and pollution from different public sources as a proxy of human behavior and public health measures. We built four supervised machine learning algorithms with different strategies: the outcome variable was the daily median Rt values per province obtained from officially adopted algorithms.

RESULTS

Data from 243 days for every province were presented to our four models (from February 15th, 2020, to October 14th, 2020). Two models using differential calculation of Rt instead of the raw values showed the highest mean coefficient of determination (0.93 for both) and residuals reported the lowest mean error (-0.03 and 0.01) and standard deviation (0.13 for both) as well. The one with access to the value of Rt of the day before heavily relied on that feature for prediction, while the other one had more distributed weights.

DISCUSSION

The model that had not access to the Rt value of the previous day and used Rt differential value as outcome (FDRt) was considered the most robust according to the metrics. Its forecasts were able to predict the trend that Rt values would have developed over different weeks, but it was not particularly accurate in predicting the precise value of Rt. A correlation among mobility, atmospheric, features, pollution and Rt values is plausible, but further testing should be performed.

COVID-19 Pandemic and Tuberculosis Control: A Narrative Review

Background

The world is currently struggling with the COVID-19pandemic. Measures to control the COVID-19 pandemic have affected other health problems and diseases, including tuberculosis (TB) and its control. The present narrative review aimed at reviewing published literature on the impact of the COVID-19 pandemic on TB control.

Materials and Methods

English language databases, including PubMed, ISI, Scopus, and Google Scholar, were searched using the keywords "Tuberculosis, COVID-19, and Coronavirus" to find relevant articles.

Results

Problems and limitations in financial and human resources, as well as medical and laboratory services caused by the COVID-19 pandemic, contribute to the reduction in the number of newly diagnosed patients with TB. More effort in identifying patients with TB is of great importance, and if the global number of newly diagnosed patients with TB decreases by 25% for three consecutive months due to the COVID-19 pandemic, the TB mortality rate will increase by 13%. An increase in the TB mortality rate means the failure of TB control programs to reach the targets of the Global End TB Strategy.

Conclusion

According to the latest statistics released by the Ministry of Health, the incidence of TB in Iran has not yet reached fewer than 100 cases per million population. On the other hand, being a neighbor with countries with a high risk of TB is a serious threat to Iran. Therefore, further effort to control TB during the COVID-19 pandemic is particularly important.

Differential mortality with COVID-19 and invasive mechanical ventilation between high-income and low-and middle-income countries: a systematic review, meta-analysis, and meta-regression

The COVID-19 pandemic has markedly affected the health care of patients in low- and middle-income countries (LMICs), but no systematic study to corroborate this effect has been undertaken. In addition, the survival outcomes of patients with COVID-19 who received invasive mechanical ventilation (IMV) have not been well established. We pooled evidence from all available studies and did a systematic review and meta-analysis to assess and compare mortality outcomes between LMICs and high-income countries (HICs). We searched MEDLINE and the University of Michigan Library according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines from December 1, 2019, to July 15, 2021, for case-control studies, cohort studies, and brief reports that discussed mortality ratios and survival outcomes among patients with SARS-CoV-2 who received IMV. We excluded studies and case reports without comparison groups, narrative reviews, and preprints. A random-effects estimate of the arcsine square root transformation (PAS) of each outcome was generated with the DerSimonian-Laird method. Seven eligible studies, consisting of 243,835 patients with COVID-19, were included. We identified a significantly higher mortality rate (i.e., a larger PAS) among the patients receiving IMV in LMICs (PAS, 0.754; 95% CI, 0.569-0.900; P<.001) compared to patients in HICs (PAS, 0.588; 95% CI, 0.263-0.876; P<.001). Considerable heterogeneity was present within the individual subgroups possibly because of the extent of the included studies, which had data from specific countries and states but not from individual hospitals or health care centers. Moreover, the sample population in each study was diverse. Meta-regression showed that a higher mortality rate among patients with COVID-19 who received IMV in both HICs (P<.001) and LMICs (P=.04) was associated with chronic pulmonary disease. Our study suggests that chronic pulmonary diseases and poor demographics lead to a worse prognosis among patients with COVID-19 who received IMV. Moreover, the survival outcome is worse in LMICs, where health care systems are usually understaffed and poorly financed.

Post COVID-19 Complications, Adjunct Therapy Explored, And Steroidal After Effects

For survivors of the COVID-19 disease, defeating the virus is just the beginning of a long road to recovery. The virus’s inducibility and catastrophic effects are distributed in multiple organs. The induction of cytokine storms in COVID-19 patients is due to the interaction of the SARS-CoV-2 virus and the host receptor, leading to various immunopathological consequences that might eventually lead to death. So far, it has hit tons of people across the world, but there is still no effective treatment. Patients facing the complications of COVID-19 after recovering have shown extensive clinical symptoms similar to previously circulating coronaviruses. Previous knowledge, and literature have opened up ways to treat this disease and manage post-COVID-19 complications, which poses a severe challenge to health system globally and may exacerbate the fragmentation of diseases. The use of steroids, as a treatment, showed various health problems and side-effects in COVID-19 patients. This review substantially discusses various post-COVID-19 complications observed, adjunctive therapies used along with common COVID-19treatment and spotlighted their side effects and consequences. This review provides latest literature on COVID-19 which emphasizes the subsequent complications in various organs, side-effects of drug, and alternative regimes that were used to treat COVID-19.

Health-related quality of life among COVID-19 individuals: A cross-sectional study in Tamil Nadu, India

Introduction

The EQ-5D-5L questionnaire is a tool that is a very generic and preference-based instrument to describe the health-related quality of life. We have generated the stratified index utility value for the Tamil Nadu population and compared the utility values based on socio-demographic and clinical characteristics.

Methods

We conducted a community-based analytical cross-sectional study using telephonic interviews from November 2020 till December 2020 among individuals aged 18 years and above who were infected by the coronavirus confirmed with an RT-PCR within 30 days in Tamil Nadu State. EQ-5D-5L profile, socio-demographic and clinical characteristics of the study participants were collected and analysed.

Results

We interviewed 372 participants, with 57.5% were males, and their mean age was 44.5 ± 15.3 years. About 40% of participants reported as having comorbidities, such as diabetes (19.4%), hypertension (12.4%), heart disease (2.4%), kidney disease (0.8%) and others. The mean EQ-5D utility score was 0.925 ± 0.150, and the mean EQ-VAS was 90.68 ± 11.81. Overall, men had a higher utility value (0.938 ± 0.130) than women, (0.907 ± 0.170). Individuals with comorbidities, requiring longer hospitalisation were having lower utility scores than their counterparts.

Conclusion

We report the EQ-5D-5L utility values for the COVID-19 illness. These values would help to estimate quality-adjusted life years in health economic evaluation studies.

The modeling and analysis of the COVID-19 pandemic with vaccination and treatment control: a case study of Maharashtra, Delhi, Uttarakhand, Sikkim, and Russia in the light of pharmaceutical and non-pharmaceutical approaches

Nonlinear dynamics is an exciting approach to describe the dynamical practices of COVID-19 disease. Mathematical modeling is a necessary method for investigating the dynamics of epidemic diseases. In the current article, an effort has been made to cultivate a novel COVID-19 compartment mathematical model by incorporating vaccinated populations. Primarily, the fundamental characteristics of the model, such as positivity and boundedness of solutions, are established. Thereafter, equilibrium analysis of steady states has been illustrated through vaccine reproduction number. Further, a nonlinear least square curve fitting technique has been employed to recognize the best fitted model parameters from the COVID-19 mortality data of five regions, namely Maharashtra, Delhi, Uttarakhand, Sikkim, and Russia. The numerical framework of the model has been added to interpret the consequence of various control schemes (pharmaceutical or non-pharmaceutical) on COVID-19 dynamics, and it has been ascertained that all the control protocols have a positive influence on curtailing the COVID-19 transference in the aforementioned regions. In addition, the essence of vaccine efficacy and vaccine-induced immunity are examined by considering different scenarios. Our analysis demonstrates that the disease will be wiped off from the Maharashtra, Delhi, Uttarakhand and Sikkim regions of India, while it shall persist in Russia for some more time. It is also found that, if a vaccine calamity arises, the government should majorly focus on permanent drug treatment of hospitalized individuals rather than vaccination.

Application of a Non-Linear multi-model Ayurveda Intervention in elderly COVID-19 patients- a retrospective case series

The COVID-19 pandemic is ravaging the world, leaving the mainstream medical system handicapped with no proven treatment at one end and the ambiguities regarding the efficacies of vaccines at the other. The elderly population is at greater risk in terms of complications and death. The use of complementary and alternative medicine (CAM) against COVID-19 has already been documented in countries like China with a national participation rate of 90%. In this regard, the practice of CAM especially Ayurveda is relevant in India. The current report is a case series of 64 elderly COVID-19 patients managed through a Non-Linear multi-modal Ayurveda Intervention (NLMAI) via online consultation. NLMAI is a combination of herbal and herbo-mineral drug interventions, lifestyle modifications, and psychological support done in 2 phases. The post-management analysis revealed a mean duration of 11 symptoms of COVID-19 assessed through survival function as 0.577 days [SE=0.39] with a CI of 95% [0.500-0.653] which was considerably low when compared to global statistics. Moreover, none of the cases advanced to complications or death. Hence, novel approaches like NLMAI can be utilized to counter the gravity of the COVID-19 after scientific validation.

Deviation in the Age Structure of Mortality as an Indicator of COVID-19 Pandemic Severity

Objectives. To test whether distortions in the age distribution of deaths can track pandemic activity. Methods. We compared weekly distributions of all-cause deaths by age during the COVID-19 pandemic in the United States from March to December 2020 with corresponding prepandemic weekly baseline distributions derived from data for 2015 to 2019. We measured distortions via Kolmogorov-Smirnov (K-S) and χ2 goodness-of-fit statistics as well as deaths among individuals aged 65 years or older as a percentage of total deaths (PERC65+). We computed bivariate correlations between these measures and the number of recorded COVID-19 deaths for the corresponding weeks. Results. Elevated COVID-19-associated fatalities were accompanied by greater distortions in the age structure of mortality. Distortions in the age distribution of weekly US COVID-19 deaths in 2020 relative to earlier years were highly correlated with COVID fatalities (K-S: r = 0.71, P < .001; χ2: r = 0.90, P < .001; PERC65+: r = 0.85, P < .001). Conclusions. A population-representative sample of age-at-death data can serve as a useful means of pandemic activity surveillance when precise cause-of-death data are incomplete, inaccurate, or unavailable, as is often the case in low-resource environments. (Am J Public Health. 2022;112(1):165-168. https://doi.org/10.2105/AJPH.2021.306567).

Are blood groups related to the distribution and severity of COVID-19? A cross-sectional study in a tertiary care hospital in South India

Background: Blood groups are inherited traits that affect the susceptibility/severity of a disease. A clear relationship between coronavirus disease 2019 (COVID-19) and ABO blood groups is yet to be established in the Indian population. This study aimed to demonstrate an association of the distribution and severity of COVID-19 with ABO blood groups. Methods: A cross-sectional study was conducted after obtaining ethics approval (IEC 207/20) among hospitalized patients using in-patient records and analyzed on SPSS-25. Chi-square tests were used for the analysis of categorical data and independent sample t-test/Mann–Whitney U tests were used for continuous data. Results: The B blood group had the highest prevalence among COVID-19-positive patients. The AB blood group was significantly associated with acute respiratory distress syndrome (ARDS) (p = 0.03), sepsis (p = 0.02), and septic shock (p = 0.02). The O blood group was associated with significantly lower rates of lymphopenia and leucocytosis. However, no significant clinical association was seen in the O blood group. Conclusion: This study has demonstrated that blood groups have a similar distribution among patients hospitalized with COVID-19 in the South Indian population. Additionally, it preludes to a possible association between the AB blood group and ARDS, sepsis, and septic shock. Further studies having a larger representation of AB blood groups, especially in patients hospitalized for critical COVID-19, with adjustment for possible covariates, are warranted to provide a reliable estimate of the risk in the South Indian population.

The overall impact of COVID-19 on healthcare during the pandemic: A multidisciplinary point of view

BACKGROUND AND AIMS

The Coronavirus disease 2019 (COVID-19) pandemic globally changed the priorities of medical and surgical procedures. It has caused many healthcare systems to stop performing their routine screenings. Altering medical clinics to COVID-19 referral centers, lockdowns, and the public fear to refer to medical centers caused a significant reduction in the referral rate; especially in the elderly. This short review article highlights the transform in clinical practice during the post-COVID era and the need for future medical revolutions.

METHODS

A comprehensive literature search was separately performed by both authors. The articles published between 2019 and August 2021 were included in this study and selected according to a quality appraisal method.

RESULTS

We have summarized the possible corresponding changes in the diagnosis and treatment of all fields of medical care including internal medicine, surgical, and minor subcategories after the COVID-19 pandemic. We have also discussed the potential impacts of the pandemic on all these different categories and subcategories of medicine, including the outpatient setting and clinical work. We do believe that the lack of routine check-ups has led to an increase in the stage of disease in patients with a previously diagnosed problem. On the other hand, the dramatic change in the lifestyle of the population including restricted mobility and increased consumption of unhealthy food has caused metabolic syndrome and other new diseases that have not been diagnosed and properly managed.

CONCLUSION

Our findings revealed the urgent need for public health awareness. It indicated the need to carry out both psychological and screening approaches in the post-COVID era to not miss patients with a chronic disease and new cases who were undiagnosed during the COVID pandemic.

Clinical and Demographic Profile of COVID-19 Patients: A Tertiary Level Hospital-Based Study From Northeast India

Background and objective

The coronavirus disease 2019 (COVID-19) outbreak, which was first detected in Wuhan, China, has turned into a rapidly spreading global healthcare crisis. The clinical and laboratory features of COVID-19 are associated with significant regional variations. In this study, we aimed to describe the clinical and demographic profile of COVID-19 patients from a tertiary care hospital in Northeast India.

Materials and methods

This was a hospital-based cross-sectional study that included all laboratory-confirmed COVID-19 cases admitted to the institution from 1st July to 31st October 2020. The information was collected on a predesigned proforma, which included patients' demographic profiles, clinical presentations, and outcomes as per treatment by trained doctors.

Results

The study included 180 laboratory-confirmed COVID-19 cases. A history of contact with laboratory-confirmed COVID-19-affected individuals was found in 92 (51.1%) patients. The median age of the patients was 37.17 years (range: 18-80 years), and there were 104 (57.78%) males in the cohort. Of the total enrolled patients, 102 (56.67%) were asymptomatic from the time of exposure till their admission. The common presenting complaints were fever (n=55, 70.51%), cough (n=42, 53.85%), and shortness of breath (n=32, 42.02%). The case fatality rate among the admitted cases was 15%. Comorbidities were found in 84 (46.67%) patients with the most common one being diabetes mellitus (n=31, 36.9%) followed by hypertension (n=29, 34.52%). Patients with advanced age (more than 60 years) and coexisting comorbidities were at higher risk of progression of disease and death.

Conclusion

The COVID-19 pandemic is not only a huge burden on healthcare facilities but also a significant cause of disruption in societies globally. The majority of the patients with COVID-19 infection presenting to our hospital were young and asymptomatic. Patients of advanced age with comorbidities were found to have more complications. An analysis of the trends related to COVID-19 in different hospital and institutional settings will help to achieve better preparedness and lead to improved patient care to combat the COVID-19 pandemic in a more efficient manner.

Impact Evaluation of Coronavirus Disease 2019 Policy: A Guide to Common Design Issues

Policy responses to COVID-19, particularly those related to non-pharmaceutical interventions, are unprecedented in scale and scope. However, policy impact evaluations require a complex combination of circumstance, study design, data, statistics, and analysis. Beyond the issues that are faced for any policy, evaluation of COVID-19 policies is complicated by additional challenges related to infectious disease dynamics and a multiplicity of interventions. The methods needed for policy-level impact evaluation are not often used or taught in epidemiology, and differ in important ways that may not be obvious. Methodological complications of policy evaluations can make it difficult for decision-makers and researchers to synthesize and evaluate strength of evidence in COVID-19 health policy papers. We (1) introduce the basic suite of policy impact evaluation designs for observational data, including cross-sectional analyses, pre/post, interrupted time-series, and difference-in-differences analysis, (2) demonstrate key ways in which the requirements and assumptions underlying these designs are often violated in the context of COVID-19, and (3) provide decision-makers and reviewers a conceptual and graphical guide to identifying these key violations. The overall goal of this paper is to help epidemiologists, policy-makers, journal editors, journalists, researchers, and other research consumers understand and weigh the strengths and limitations of evidence.

Modeling electricity consumption patterns during the COVID-19 pandemic across six socioeconomic sectors in the State of Qatar

The propagation of the COVID-19 pandemic, and the associated measures taken by many countries to slow down the spread of the disease, has significantly affected all aspects of people's lives, including the global energy sector. This study aims to investigate the impact of the pandemic on the spatial patterns of electricity consumption in six socioeconomic sectors (residential (villa and flat), industrial, commercial, government, and productive farms) in the State of Qatar. The spatiotemporal patterns of electricity consumption have been assessed using various Geographic Information Systems (GIS) and spatial statistical modeling prior and during the pandemic. The results demonstrate variations in electricity consumption within and between the six sectors. The main changes in the electricity consumption within sectors during the pandemic year is during the lockdown phase. Spatially, some sectors are affected by the pandemic, and hence the pattern and the spatial and temporal distribution of electricity consumption has changed during the pandemic year compared to pre-pandemic years. The results also show that there were variations of spatial clustering of electricity consumption among these sectors. Most of the high-high clustering patterns are located in the mid-eastern and northeastern parts of Qatar. The highest variation in electricity consumption between sectors occurred in the productive farms due to its massive development during the pre-pandemic period and were not affected by the pandemic. There is a sharp decline in electricity consumption in both the industrial and commercial sectors during the pandemic year. Other sectors witnessed an increase in electricity consumption during the summer months, which was mainly due to travel restrictions imposed by many countries around the world. This analysis is vital for policymakers to detect the changes in electricity consumption patterns in the context of emergencies such as the pandemic.

Clinical and Laboratory Factors in Predicting Mortality Among COVID-19 RT-PCR Positive Patients: A Retrospective Observational Study From a Tertiary Care Center

BACKGROUND

In coronavirus disease 2019 (COVID-19) patients, risk stratification based on clinical presentation, co-morbid illness, and combined laboratory parameters is essential to provide an adequate, timely intervention based on an individual's conditions to prevent mortality among cases.

METHODS

A retrospective observational study was carried out from June to October 2020, including all reverse transcription-polymerase chain reaction (RT-PCR) positive COVID-19 non-survivors and control group survivors randomly selected after age and sex matching. Clinical and demographic information was collected from the medical records. Categorical variables were expressed by frequency and percentage. To explore the risk factors associated with mortality, univariable and multivariable logistic regression models were used.

RESULTS AND DISCUSSIONS

All non-survivors (n = 100) and 100 survivors (out of 1,018) were analyzed. Male gender (67.4%) was the independent risk factor for COVID-19 infection. Advanced age group, diabetes, cardiovascular, neurological, and hypertensive co-morbidities were statistically associated with mortality. Cardiac arrest and acute kidney injury (AKI) were the most common complications. Mortality is significantly associated with lymphopenia and raised lactate dehydrogenase (LDH), as shown by higher odds. In addition, raised neutrophils, monocytes, aspartate aminotransferase (AST), serum creatinine, interleukin 6 (IL-6), and C-reactive protein (CRP) are also significantly associated with mortality. The most common causes of death were respiratory failure (84%) and acute respiratory distress syndrome (77%). Of the non-survivors, 92% received corticosteroids, 63% were on high-flow nasal cannula oxygen therapy, 29% were mechanically ventilated, and 29% received tocilizumab.

CONCLUSION

Serial monitoring of neutrophils, lymphocytes, D-dimer, procalcitonin, AST, LDH, CRP, IL-6, serum creatinine, and albumin might provide a reliable and convenient method for classifying and predicting the severity and outcomes of patients with COVID-19.

Impact of COVID -19 Pandemic on Plastic Surgery Practices in a Tertiary Care Set Up in Southern India

Background

The COVID-19 pandemic has modified the way, plastic surgeons treat their patients. This article depicts how we as a plastic surgery department in a tertiary care setup handled the pandemic with an emphasis on infection control policy.

Methods

Data was collected from hospital records and quality assurance cell from March 21, 2020 to June 19, 2020 in terms of patient triaging, consultations, perioperative protocols, duty rosters, and academic activities. The changes on these with the impact of COVID-19 were studied with the same period of previous year.

Results

Outpatient clinics were closed and emergency consultations were reduced. Number of consultations reduced from 2591 to 75 and surgeries from 320 to 46 during the same period in 2019 and 2020 respectively. Though tele-consultations were helpful, the overall benefits were subpar. Emergency services continued with the guidelines of institute's infection control committee, such as area specific personal protective equipment, allotment of operating rooms, minimizing the crowd in operating room. There was some compromise in using accessories for microsurgical procedures. Duty rosters were designed to maintain uninterrupted services. Academic activities were continued with virtual platforms.

Conclusion

Adequate preparation of health care setup and nation-wide lockdown has helped to handle emergency cases and in reduction of trauma-surgeries respectively. Though there were obstacles for some patients in accessing health care, our institutional response made us to render maximum possible care. Advancements in virtual platform helped in consultations and academics. Delayed conservative approach was used in most cases at the expense of cosmetic compromise.

A machine-learning scraping tool for data fusion in the analysis of sentiments about pandemics for supporting business decisions with human-centric AI explanations

The COVID-19 pandemic is changing daily routines for many citizens with a high impact on the economy in some sectors. Small-medium enterprises of some sectors need to be aware of both the pandemic evolution and the corresponding sentiments of customers in order to figure out which are the best commercialization techniques. This article proposes an expert system based on the combination of machine learning and sentiment analysis in order to support business decisions with data fusion through web scraping. The system uses human-centric artificial intelligence for automatically generating explanations. The expert system feeds from online content from different sources using a scraping module. It allows users to interact with the expert system providing feedback, and the system uses this feedback to improve its recommendations with supervised learning.

Managing comorbidities in Covid-19 patients: A drug utilization study in a COVID-dedicated hospital in Northern India

INTRODUCTION

In the prevailing COVID-19 pandemic, the Indian healthcare system has worked hard towards restricting the adverse outcomes to the least possible figures. The present study aims to share the experience of a COVID-dedicated tertiary care government hospital in Northern India of managing COVID-19 patients with comorbidities.

METHODOLOGY

A retrospective, observational study was conducted in a COVID-dedicated tertiary health care government hospital in Northern India. Details on sociodemographic data, hospital admission data, and drug utilization pattern of all laboratory-confirmed COVID-19 patients of all age groups, either gender, having comorbidity (s), and admitted between April and September, 2020 were noted and evaluated.

RESULTS

Among the total study participants (N = 406), 2868 drugs were prescribed. Out of these, 2336 were used for the management of symptoms of COVID-19 and 532 were used for the management of coexistent comorbidity (s). For COVID-19 symptoms, the most commonly prescribed class of drugs were antimicrobials (853, 36.52%), followed by nonsteroidal antiinflammatory drugs (374, 16.01%), proton pump inhibitors (299, 12.80%), antihistamines (232, 9.93%), immunosuppressant drugs (103, 4.41%), and others. For comorbidities most commonly prescribed were antihypertensive (310, 58.60%) drugs, followed by antidiabetic drugs (166, 31.38%), bronchodilators (34, 6.43%), thyroid hormones (11, 2.08%), immunosuppressant drugs (7, 1.32%).

CONCLUSION

The most frequently prescribed antihypertensives were calcium channel blockers (CCBs) and least prescribed was beta blocker+CCB. Among the antidiabetic drugs, most frequently prescribed was insulin and least prescribed was DPP-4 inhibitors and Biguanide+DPP-4 inhibitor both.

Clinical and Laboratory Predictors of Mortality in COVID-19 Infection: A Retrospective Observational Study in a Tertiary Care Hospital of Eastern India

Introduction COVID-19 is associated with huge morbidity and mortality in India. Identification of factors associated with mortality would make a difference in the management of COVID-19 infection-related illness. Objective To assess clinical & laboratory parameters associated with adverse outcomes among 984 patients with COVID-19 infection admitted to a tertiary care hospital in eastern India. Materials and methods All patients with real-time polymerase chain reaction (RTPCR) or rapid antigen positive for COVID-19 admitted at our All India Institute of Medical Sciences (AIIMS) Patna between 1st July to 30th Aug 2020 were included for analysis. Statistical analysis was performed using Stata, version 10 (Stata Corp, College Station, USA). Four subgroup regression models have been analyzed to predict the odds of death. Results A total of 984 COVID-19 cases admitted to our hospital during the given period were analyzed. Out of 984 cases, 762 (77.44%) were males and 222 (22.56%) females. The overall case-fatality rate among admitted cases was 254 (25.81%) [males (26.64%) and females (22.96%)]. The final logistic regression model showed that patients presenting with severe COVID-19 disease (adjusted odds ratio [aOR]: 17.81), cough (aOR: 3.83), dyspnea (aOR:2.35), age 60-75 (aOR:1.47), age >75 years (aOR:3.97), presence of chronic kidney disease (CKD) (aOR:2.95), were found to be significantly associated with a high risk of mortality after controlling for the confounders (p<0.05). Among lab variable, total leukocyte count (TLC) (>10,000/mm3) (aOR: 1.74), neutrophil-lymphocyte ratio (NLR) (>3.3) (aOR:2.37), serum albumin (<3.4 g/dl) (aOR : 2.3), blood urea (>43 gm/dl) (aOR:3.72), ferritin (>322) (aOR:2.39), and D-dimer (>0.5) (aOR:5.58) were significantly associated with higher mortality (p<0.05) Conclusion Age 60 years plus, presence of CKD, and severe covid infection carried the highest risk of mortality. Lab markers such as raised TLC, ferritin, D-dimer, and low albumin were associated with worse outcomes in our subset of COVID-19-related illness.

Insights into the Mobility Pattern of Australians during COVID-19

Coronavirus disease 2019 (COVID-19) is an infectious disease characterised by symptoms that are like the common cold. The current pandemic situation in anticipation of a vaccine has posed serious threats to the health and economic sectors of countries worldwide. To overcome the quick transmission of the virus, the government of Australia has also taken drastic measures to prevent its spread. These policies include an international and interstate travel ban, social distancing rules, lockdown, shutdown of educational institutes and work-from-home policies. Such rules have affected people on both behavioural and psychological levels. This study aims to analyse the effect of COVID-19 on Australian citizens, and therefore, the changed behaviour of citizens concerning their mobility patterns, transport preferences and shopping methods under the pandemic have been studied. A detailed literature search was adopted for gathering data related to the study theme, along with real-time evidence of changes in the behaviour of people following the pandemic. The socioeconomic impact of the pandemic on social inequality and thereby the effect on the vulnerable people of the population are also studied. Authentic surveys and statistical data are consulted to figure out how the new lifestyle choices of people will linger in the post-pandemic era. It was found that people in Australia have adopted the work-from-home regime, and new habits suiting the nationwide restrictions have become routine for many people.

Dental Nurses' Mental Health in Germany: A Nationwide Survey during the COVID-19 Pandemic

Several studies have found a rise in the rate of psychological discomfort among healthcare personnel since the COVID-19 pandemic outbreak. In this study, we analyzed the relationship between psychological variables of anxiety, depression, stress, avoidance, intrusion and hyperarousal and several factors among German dental nurses. For this poll, dental nurses were asked nationwide to take part via an online-based survey from July 2020 to January 2021. This survey gathered data on demographics, as well as psychological assessments through the Impact of Events Scale-Revised (IES-R) instrument, and the Depression Anxiety Stress Scales (DASS-21). The correlations between DASS-21/IES-R ratings and sociodemographic data were investigated using univariate analyses (Kruskal-Wallis and Mann-Whitney U tests). Single comparisons were performed using the Dunn-Bonferroni post hoc test if a relevant test result was significant followed by multiple linear regressions. Furthermore, 252 dental nurses took part in the study and showed overall normal or mild results of all psychological variables. Having immune-deficiency or chronic diseases, employment at a dental practice, being married, having no children and seeing the pandemic as a financial threat were presented as significant risk factors (p ≤ 0.05) with higher DASS-21 and IES-R scores. These results emphasize the aspects that must be considered to safeguard German dental nurses' mental wellbeing during the crisis.

A Machine-Generated View of the Role of Blood Glucose Levels in the Severity of COVID-19

SARS-CoV-2 started spreading toward the end of 2019 causing COVID-19, a disease that reached pandemic proportions among the human population within months. The reasons for the spectrum of differences in the severity of the disease across the population, and in particular why the disease affects more severely the aging population and those with specific preconditions are unclear. We developed machine learning models to mine 240,000 scientific articles openly accessible in the CORD-19 database, and constructed knowledge graphs to synthesize the extracted information and navigate the collective knowledge in an attempt to search for a potential common underlying reason for disease severity. The machine-driven framework we developed repeatedly pointed to elevated blood glucose as a key facilitator in the progression of COVID-19. Indeed, when we systematically retraced the steps of the SARS-CoV-2 infection, we found evidence linking elevated glucose to each major step of the life-cycle of the virus, progression of the disease, and presentation of symptoms. Specifically, elevations of glucose provide ideal conditions for the virus to evade and weaken the first level of the immune defense system in the lungs, gain access to deep alveolar cells, bind to the ACE2 receptor and enter the pulmonary cells, accelerate replication of the virus within cells increasing cell death and inducing an pulmonary inflammatory response, which overwhelms an already weakened innate immune system to trigger an avalanche of systemic infections, inflammation and cell damage, a cytokine storm and thrombotic events. We tested the feasibility of the hypothesis by manually reviewing the literature referenced by the machine-generated synthesis, reconstructing atomistically the virus at the surface of the pulmonary airways, and performing quantitative computational modeling of the effects of glucose levels on the infection process. We conclude that elevation in glucose levels can facilitate the progression of the disease through multiple mechanisms and can explain much of the differences in disease severity seen across the population. The study provides diagnostic considerations, new areas of research and potential treatments, and cautions on treatment strategies and critical care conditions that induce elevations in blood glucose levels.

India's pragmatic vaccination strategy against COVID-19: a mathematical modelling-based analysis

OBJECTIVES

To investigate the impact of targeted vaccination strategies on morbidity and mortality due to COVID-19, as well as on the incidence of SARS-CoV-2, in India.

DESIGN

Mathematical modelling.

SETTINGS

Indian epidemic of COVID-19 and vulnerable population.

DATA SOURCES

Country-specific and age-segregated pattern of social contact, case fatality rate and demographic data obtained from peer-reviewed literature and public domain.

MODEL

An age-structured dynamical model describing SARS-CoV-2 transmission in India incorporating uncertainty in natural history parameters was constructed.

INTERVENTIONS

Comparison of different vaccine strategies by targeting priority groups such as keyworkers including healthcare professionals, individuals with comorbidities (24-60 years old) and all above 60.

MAIN OUTCOME MEASURES

Incidence reduction and averted deaths in different scenarios, assuming that the current restrictions are fully lifted as vaccination is implemented.

RESULTS

The priority groups together account for about 18% of India's population. An infection-preventing vaccine with 60% efficacy covering all these groups would reduce peak symptomatic incidence by 20.6% (95% uncertainty intervals (UI) 16.7-25.4) and cumulative mortality by 29.7% (95% CrI 25.8-33.8). A similar vaccine with ability to prevent symptoms (but not infection) will reduce peak incidence of symptomatic cases by 10.4% (95% CrI 8.4-13.0) and cumulative mortality by 32.9% (95% CrI 28.6-37.3). In the event of insufficient vaccine supply to cover all priority groups, model projections suggest that after keyworkers, vaccine strategy should prioritise all who are >60 and subsequently individuals with comorbidities. In settings with weakest transmission, such as sparsely populated rural areas, those with comorbidities should be prioritised after keyworkers.

CONCLUSIONS

An appropriately targeted vaccination strategy would witness substantial mitigation of impact of COVID-19 in a country like India with wide heterogeneity. 'Smart vaccination', based on public health considerations, rather than mass vaccination, appears prudent.

Dental Students in Germany throughout the COVID-19 Pandemic: A Psychological Assessment and Cross-Sectional Survey

Multiple investigations have reported high psychological distress among students since the coronavirus (COVID-19) outbreak started. This survey examined the associations between psychological features, and several demographic and social factors among dental students in German universities. Dental students registered in German universities nationwide were asked to join this survey via a self-directed online questionnaire, from July 2020 to January 2021. This study assembled data on demographic statistics, the depression anxiety stress scales (DASS-21), and the impact of events scale-revised (IES-R) instrument. The relationships between demographic-related variables and mental consequences of depression, anxiety, stress, intrusion, avoidance, and hyperarousal were inspected. Two hundred and eleven students contributed to the questionnaire and conveyed overall normal or mild outcomes of depression, anxiety, stress, intrusion, avoidance, and hyperarousal. In addition, female gender, cardiovascular diseases, smoking habits, and seeing the COVID-19 outbreak as a financial risk were stated as significant related factors (p < 0.05), with increased IES-R and DASS-21 scores. These results highlight the features that should be considered to better protect dental students' mental health in German universities during the crisis.

Patient experiences and perceptions of chronic disease care during the COVID-19 pandemic in India: a qualitative study

OBJECTIVE

People with chronic conditions are known to be vulnerable to the COVID-19 pandemic. This study aims to describe patients' lived experiences, challenges faced by people with chronic conditions, their coping strategies, and the social and economic impacts of the COVID-19 pandemic.

DESIGN, SETTING AND PARTICIPANTS

We conducted a qualitative study using a syndemic framework to understand the patients' experiences of chronic disease care, challenges faced during the lockdown, their coping strategies and mitigators during the COVID-19 pandemic in the context of socioecological and biological factors. A diverse sample of 41 participants with chronic conditions (hypertension, diabetes, stroke and cardiovascular diseases) from four sites (Delhi, Haryana, Vizag and Chennai) in India participated in semistructured interviews. All interviews were audio recorded, transcribed, translated, anonymised and coded using MAXQDA software. We used the framework method to qualitatively analyse the COVID-19 pandemic impacts on health, social and economic well-being.

RESULTS

Participant experiences during the COVID-19 pandemic were categorised into four themes: challenges faced during the lockdown, experiences of the participants diagnosed with COVID-19, preventive measures taken and lessons learnt during the COVID-19 pandemic. A subgroup of participants faced difficulties in accessing healthcare while a few reported using teleconsultations. Most participants reported adverse economic impact of the pandemic which led to higher reporting of anxiety and stress. Participants who tested COVID-19 positive reported experiencing discrimination and stigma from neighbours. All participants reported taking essential preventive measures.

CONCLUSION

People with chronic conditions experienced a confluence (reciprocal effect) of COVID-19 pandemic and chronic diseases in the context of difficulty in accessing healthcare, sedentary lifestyle and increased stress and anxiety. Patients' lived experiences during the pandemic provide important insights to inform effective transition to a mixed realm of online consultations and 'distanced' physical clinic visits.

Experiences and expectations regarding COVID-19 prevention and control measures among the hill tribe population of northern Thailand: a qualitative study

Background

COVID-19 has been a major human threat for a year. A large number of people have been infected and killed globally, including hill tribe people living in remote and border areas between Thailand and Myanmar. Different expectations of and experiences with the implemented disease prevention and control measures by local, national and international organizations have been widely reported. This study aimed to understand the experiences and expectations regarding the disease prevention and control measures that were implemented among hill tribe people in Thailand.

Methods

Qualitative data were collected from participants aged 20 and older who belonged to the hill tribes living on the border of northern Thailand and Myanmar. A semistructured questionnaire was used to guide interviews. Information was extracted for thematic analysis by the NVivo program.

Results

Fifty-seven participants (36 female, 21 male) were interviewed; 27 participants were Thai Yai, 14 participants were Yunnan Chinese, 8 participants were Akha, and 8 participants were from other tribes. The average age was 45.8 years (min = 20 years, max = 90 years). Thirty participants had never attended school, and the other 27 participants had received education at different levels, from primary school to higher education. Forty participants were unemployed, 13 worked as agriculturists, and the other 4 were attending school. Both positive experiences, such as improving personal hygiene practices, maintaining close contact and increasing relationships among family members and demonstrating the leadership of the villager leaders, and negative experiences, including interruption of social interactions, family financial problems, poor access to medical care services, and invisible people to the government, were found. Different expectations were observed regarding organizations at the local, national, and international levels. Expectations at the local level included villagers and community leaders taking action to strongly contribute to prevention and control measures and to prevent unscreened people from entering the village. Obtaining accurate information about the disease and being financially supported were expectations at the national level, while closing borders to protect cases from overflowing into their villages was an international-level expectation.

Conclusion

Although hill tribes reside in very remote rural areas, they experience both positive and negative effects of the disease prevention and control measures implemented by organizations. Their expectations are formally and informally voiced to policy makers at the local, national and international levels.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-11145-5.

Nepal at the edge of sword with two edges: The COVID-19 pandemics and sustainable development goals

Humanity has been threatened by pandemics since several decades with devastating effects on all human activities including the economy, and environment. Currently, the world is reeling from the COVID-19 pandemic. The COVID-19 pandemic has been a major threat to the livelihood of billions of people worldwide. Nepal is not an exception to this and has been seriously threatened by the COVID-19 pandemic. The thousands of the peoples who depend on daily wages to join hand to mouth has been under the brunt of the COVID-19 pandemic because of job loss, disruption in the food supply chain. Also, the COVID-19 pandemic has thwarted Nepal's targets to achieve UN Sustainable Development Goals including an unprecedented state of vulnerability to hunger and poverty in the country. Though some informal shreds of evidence have reported the negative impacts of COVID-19 on Sustainable Development Goals, none of the scientific literature has been available regarding such impacts in Nepal yet. This review aims to synthesize extant literature that reports the effects of COVID-19 on the Nepalese economy and implications for achieving UN Sustainable Development Goals.We found that the COVID-19 pandemic has created unprecedented challenges to achieve the country's committed United Nation's Sustainable Development Goals for Nepal. Further, the COVID-19 pandemic has created a unique "income shock" that is supposed to precipitate household food insecurity in developing economy like Nepal. Our review indicated that the percentage of populations below poverty could rise even more than the present national reported value of 18% in the post-pandemic era. We emphasized generating employment and income-earning opportunities to build a resilient food system. Further, we urged to build international consensus to reset and rethink the course of sustainable development goals.

Expected Impacts of COVID-19: Considering Resource-Limited Countries and Vulnerable Population

Coronavirus disease in 2019 emerged in Wuhan, Hubei Province, China, in December 2019. After a month, it was declared a global threat to public health. The effects of the pandemic could be socio-economic, undermining the health system and risking livelihoods. Vulnerability to this infection has been associated with underlying comorbidities such as hypertension, diabetes, coronary heart disease, chronic respiratory diseases, cancer, and compromised immune systems. Co-morbidity has been common to the elderly, the disabled, and the homeless. In addition, more severe coronavirus disease outcomes have been reported in older males than females. Nonetheless, multiple variables are related to the concept of cultural gender that should be taken into account as women in more affected sectors are economically disadvantageous and over-represented. Similarly, although children are not the face of this pandemic, calamity has a profound effect on their welfare, especially for those living in poor and inconvenient situations. Moreover, the economic influence could be profound and universal when viewed through a migration lens as it is exacerbating xenophobic and discriminatory treatment. Protection measures to mitigate the outbreak of a pandemic, such as social distancing, may reduce social support for certain categories relied on for their day-to-day activities. The mental health of people would definitely be affected by the additional psychosocial burden of the pandemic, particularly in vulnerable groups. Integrated approaches are therefore mandatory to assist these groups and contain the pandemic.

Cyberchondria Amidst COVID-19 Pandemic: Challenges and Management Strategies

The corona-virus disease 2019 (COVID-19), first found in Wuhan, China in December 2019, has posed an inexplicable threat to the global community. After its inception, the virus proliferated rapidly, which led to the cause of millions of deaths, and having a detrimental effect on physical health, social lives, economic uncertainty, and mental health of people. The World Health Organization has reported that there are 111 million confirmed cases of COVID-19 and 2.45 million deaths due to COVID-19 worldwide. Indisputably, the present pandemic has contributed to the extensive psychological and environmental distress together with clinical depression, anxiety and post-traumatic stress disorder (PTSD), domestic violence, and unemployment. Due to the ambiguous nature of the pandemic, educational organizations, and outdoor activities are closed, thus burdening the mental health of younger populations. Children as well as youths are more glued to the Internet for their studies, online gaming, shopping, watching movies, and searching health-related information. Despite the advantages of using the Internet, it has some severe consequences too. Some people are repeatedly searching for physical and mental well-being related information without verifying credible sources, which, in turn, causes distress and anxiety. In such situations, individuals may end up contributing to an illness known as cyberchondria. In this paper, we have tried to highlight the problematic use of Internet for health-related searches and have outlined the management of such illness. We suggest two strategies: firstly, to reduce repeated online searches of health information and, secondly, to manage anxiety-augmenting thoughts that are triggered due to the maladaptive thoughts caused by the abstruse information.

Nanotechnology to the Rescue: Treatment Perspective for the Immune Dysregulation Observed in COVID-19

The study of the use of nanotechnology for drug delivery has been extensive. Nanomedical approaches for therapeutics; drug delivery in particular is superior to conventional methods in that it allows for controlled targeted delivery and release, higher stability, extended circulation time, minimal side-effects, and improved pharmacokinetic clearance (of the drug) form the body, to name a few. The magnitude of COVID-19, the current ongoing pandemic has been severe; it has caused widespread the loss of human life. In individuals with severe COVID-19, immune dysregulation and a rampant state of hyperinflammation is observed. This kind of an immunopathological response is detrimental and results in rapid disease progression, development of secondary infections, sepsis and can be fatal. Several studies have pin-pointed the reason for this immune dysregulation; deviations in the signaling pathways involved in the mediation and control of immune responses. In severe COVID-19 patients, many signaling cascades including JAK/STAT, NF-κB, MAPK/ERK, TGF beta, VEGF, and Notch signaling were found to be either upregulated or inactivated. Targeting these aberrant signaling pathways in conjunction with antiviral therapy will effectuate mitigation of the hyperinflammation, hypercytokinemia, and promote faster recovery. The science of the use of nanocarriers as delivery agents to modulate these signaling pathways is not new; it has already been explored for other inflammatory diseases and in particular, cancer therapy. Numerous studies have evaluated the efficacy and potential of nanomedical approaches to modulate these signaling pathways and have been met with positive results. A treatment regime, that includes nanotherapeutics and antiviral therapies will prove effective and holds great promise for the successful treatment of COVID-19. In this article, we review different nanomedical approaches already studied for targeting aberrant signaling pathways, the host immune response to SARS-CoV-2, immunopathology and the dysregulated signaling pathways observed in severe COVID-19 and the current treatment methods in use for targeting signaling cascades in COVID-19. We then conclude by suggesting that the use of nanomedical drug delivery systems for targeting signaling pathways can be extended to effectively target the aberrant signaling pathways in COVID-19 for best treatment results.

Relationship between physical and mental health comorbidities and COVID-19 positivity, hospitalization, and mortality

BACKGROUND

Understanding the association between separate and combined mental and physical health diagnoses and COVID-19 outcomes is greatly needed to address the severity of illness.

METHODS

Data on 24,034 patients screened for COVID-19 as of July 2020 were extracted from the Froedtert/Medical College of Wisconsin Epic medical record. COVID-19 outcomes were defined as positive screens, proportion hospitalized among positive screens, and proportion that died among positive and hospitalized population. The primary independent variable was a 3-category variable: physical health diagnosis alone, mental health diagnosis alone, and combined mental and physical health diagnoses. Logistic regression and Cox proportional hazard models were used to examine the independent relationship between separate and combined diagnoses and COVID-19 outcomes.

RESULTS

Compared to physical health diagnosis alone, mental health diagnosis alone had lower odds of screening positive (OR=0.68, CI=0.51;0.92) and was not associated with hospitalization or mortality among positive screens. Combined had lower odds of screening positive (OR=0.78, CI=0.69;0.88) and higher odds of hospitalization among positive screens after adjusting for demographics (OR=1.58, CI=1.20;2.08) but lost significance in the fully adjusted model. No category of diagnoses was associated with mortality.

LIMITATIONS

Analysis is cross-sectional and cannot speak to any causal relationships.

CONCLUSIONS

Overall, compared to physical health diagnosis alone, mental health diagnosis and combined had lower odds of positive screens. However, individuals with combined were more likely to be hospitalized, after adjusting for demographics only. These findings add new evidence for risk of COVID-19 and related hospitalization in individuals who have a physical and mental health diagnosis.