The Indian perspective of COVID-19 outbreak

Impact of COVID-19 outbreak on healthcare workers in a Tertiary Healthcare Center in India: a cross sectional study

Numerous speculations have continually emerged, trying to explore the association between COVID-19 infection and a varied range of demographic and clinical factors. Frontline healthcare workers have been the primary group exposed to this infection, and there have been limited global research that examine this cohort. However, while there are a few large studies conducted on Indian healthcare professionals to investigate their potential risk and predisposing factors to COVID-19 infection, to our knowledge there are no studies evaluating the development of long COVID in this population. This cross-sectional study systematically utilized the demographic and clinical data of 3329 healthcare workers (HCW) from a tertiary hospital in India to gain significant insights into the associations between disease prevalence, severity of SARS-Cov-2 infection and long COVID. Most of the study population was found to be vaccinated (2,615, 78.5%), while 654 (19.65%) HCWs were found to be SARS-CoV-2 positive at least once. Of the infected HCWs, 75.1% (491) did not require hospitalization, whereas the rest were hospitalized for an average duration of 9 days. A total of 206 (6.19%) individuals were found to be suffering from long COVID. Persistent weakness/tiredness was the most experienced long-COVID symptom, while females (1.79, 1.25-2.57), individuals who consumed alcohol (1.85, 1.3-2.64) or had blood group B (1.9, 1.33-2.7) were at a significantly higher risk for developing long COVID.

An in-depth appraisal of clinico-biochemical and radiological findings of COVID-19 patients during the COVID-19 pandemic in a dedicated COVID Care Hospital in Eastern India and its outcome in relation to the COVAXIN vaccination status: A 2-year study

Introduction

COVID-19 pandemic hit Odisha province from April 2020 to December 2020, then from April 2021 to August 2021 and from February 2022 to April 2022 as the first, second, and third waves, respectively, with the most severe form witnessed during the second wave. Kalinga Institute of Medical Sciences hospital in Odisha was declared a Dedicated COVID Hospital (DCH) during those three waves and witnessed 9485 cases of admissions among which there were 1214 deaths. COVAXIN vaccination of the vulnerable population was launched in February 2021 onwards. This study has been done to know the clinic-biochemical profiles, radiologic findings of COVID-19 admitted patients, the predictors of mortality in the second wave, and clinical outcomes in the three waves in relation to COVAXIN vaccination status.

Material and Methods

This was a serial three-round retrospective study from the electronic medical records using multistage random sampling where we collected and critically analyzed the demographic, and all the relevant possible health data of the cases that consist of 514 cases admitted in three waves. The data from death certificates among the 555 cases in the second wave have been analyzed to conclude predictors of mortality.

Results

Mortality increased with age, male gender, comorbidities, and raised C-reactive protein level. High NL ratio, extent of pulmonary involvement. There was a wide variation in incidence and spectrum of illness starting from 79% incidence of mild symptomatic in the initial and third wave, but remained in the range of 35-65% in the second wave, respectively, and the most noticeable symptomatic illness was that of the upper respiratory tract. In fulminant cases, the mode of presentations was severe pneumonia and acute respiratory distress syndrome. Males were more sufferers than females. Children had better outcomes compared to adults. COVID-associated coagulopathy had a normal platelet count. Subsequently, in 2021 year onwards vaccination of the vulnerable population was launched in a phased manner that changed the dynamics of the disease outcome by better survival chances despite intercurrent COVID infection by induction of herd immunity. On the contrary, there was a higher prevalence of serious illness among non-vaccinated individuals. While the cases continued during the second wave of the pandemic, long COVID became a clinical entity of symptomatic that persisted or recurred among the COVID illness recovered cases after reverse transcriptase polymerase chain reaction results for COVID-19 became negative. The symptoms consisted of fatigue, cough, dyspnea as pulmonary manifestations and extra-pulmonary involvement of the cardiac, renal, and central nervous systems and the pulmonary imaging features consisted of interstitial pneumonia, consolidation, cavity pattern, and prone to microbial infection. These events lead to morbidity and admission. Coinciding with the vaccination of all population of Odisha province with the first dose of the vaccine by around the period of the first quarter of 2022, there was a new variant named Omicron responsible in the third wave, in which the majority of the admitted cases had.mild upper respiratory illness. This was not as lethal as its predecessors due to its lower propensity to invade the lungs and blood vessels.

Conclusion

Immune dysregulation plays a central role in the pathogenesis of the manifestations. Vaccine-induced protection and the induction of herd immunity played a proactive role in the waning of the severity of clinical presentations.

Zika virus as an emerging arbovirus of international public health concern

Zika virus (ZIKV) was identified in 1947 in a rhesus monkey during an investigation of the yellow fever virus in the Zika Forest of Uganda; it was also isolated later from humans in Nigeria. The main distribution areas of ZIKV were the African mainland and South-East Asia in the 1980s, Micronesia in 2007, and more recently the Americas in 2014. ZIKV belongs to the Flaviviridae family and Flavivirus genus. ZIKV infection, which is transmitted by Aedes mosquitoes, is an emerging arbovirus disease. The clinical symptoms of ZIKV infection are fever, headache, rashes, arthralgia, and conjunctivitis, which clinically resemble dengue fever syndrome. Sometimes, ZIKV infection has been associated with Guillain-Barré syndrome and microcephaly. At the end of 2015, following an increase in cases of ZIKV infection associated with Guillain-Barré syndrome and microcephaly in newborns in Brazil, the World Health Organization declared a global emergency. Therefore, considering the global distribution and pathogenic nature of this virus, the current study aimed at reviewing the virologic features, transmission patterns, clinical manifestations, diagnosis, treatment, and prevention of ZIKV infection.

Assessment of Community Behavior and COVID-19 Transmission during Festivities in India: A Qualitative Synthesis through a Media Scanning Technique

In India during the first wave of COVID-19 infection, the authorities were concerned about the advent of the festive season, which could lead to a surge in cases of SARS-CoV-2 infection. The present study attempted to assess the socio-behavioral aspects of COVID-appropriate behavior (CAB) at individual and community levels, and their impact on the transmission of COVID-19 during festivities in India. Media scanning was conducted to qualitatively assess CAB by analyzing 284 news reports from across India; quantitative data on COVID-19 daily cases from March 2020 to December 2020 were used to determine the trends of the adjusted test positivity (ATP) ratio for six cities. Peaks in ATP were observed in Chandigarh, Delhi-NCR in North India during and after Dussehra and Deepavali, and in Mumbai, in the west, after Navratri. Additionally, a surge in ATP was observed in Trivandrum after Onam and in Chennai around Deepavali in the south; meanwhile, in the eastern city of Kolkata, cases increased following Durga Puja. The major challenges were adherence to CAB viz. social distancing, hygiene, and compliance with the mask mandate. Microlevel CAB indicated relatively higher laxity in maintaining hand hygiene in all cities. Observations from the current study indicate that innovative community-driven initiatives during festivals in each geographical zone are key to the large-scale implementation of disease prevention measures.

Women's political leadership and efficiency in reducing COVID-19 death rate: An application of technical inefficiency effects model across Indian states

Evidence from earlier studies on COVID-19 suggests that the countries led by female leaders were more successful in handling the COVID-19. India being a patrilocal society evident that women's political autonomy in the Gram Panchayat does miracles concerning development. With this backdrop, the present paper aims to explore the role of women's political participation and leadership on the efficiency in reducing the COVID-19 death rate for Indian states. This predominantly empirical paper is entirely based on secondary data compiled from different sources. The empirical analysis of the paper is facilitated by the utilization of the Technical Inefficiency Effects model within the framework of Stochastic Production Frontier. The empirical results accredit us to conclude that the efficiency of the Indian states in reducing the COVID-19 death rate is highly influenced by female political participation and leadership, digitalization, urbanization, and literacy rate. The study ends with suitable policy prescriptions.

Urtica dioica Agglutinin: A plant protein candidate for inhibition of SARS-COV-2 receptor-binding domain for control of Covid19 Infection

Despite using effective drugs and vaccines for Covid 19, due to some limitations of current strategies and the high rate of coronavirus mutation, the development of medicines with effective inhibitory activity against this infection is essential. The SARS-CoV-2 enters the cell by attaching its receptor-binding domain (RBD) of Spike to angiotensin-converting enzyme-2 (ACE2). According to previous studies, the natural peptide Urtica dioica agglutinin (UDA) exhibited an antiviral effect on SARS-CoV, but its mechanism has not precisely been elucidated. Here, we studied the interaction between UDA and RBD of Spike protein of SARS-CoV-2. So, protein-protein docking of RBD-UDA was performed using Cluspro 2.0. To further confirm the stability of the complex, the RBD-UDA docked complex with higher binding affinity was studied using Molecular Dynamic simulation (via Gromacs 2020.2), and MM-PBSA calculated the binding free energy of the system. In addition, ELISA assay was used to examine the binding of UDA with RBD protein. Results were compared to ELISA of RBD-bound samples of convalescent serum IgG (from donors who recovered from Covid 19). Finally, the toxicity of UDA is assessed by using MTT assay. The docking results show UDA binds to the RBD binding site. MD simulation illustrates the UDA-RBD complex is stable during 100 ns of simulation, and the average binding energy was calculated to be -47.505 kJ/mol. ELISA and, MTT results show that UDA binds to RBD like IgG-RBD binding and may be safe in human cells. Data presented here indicate UDA interaction with S-protein inhibits the binding sites of RBD, it can prevent the virus from attaching to ACE2 and entering the host cell.

A novel hybrid fuzzy time series model for prediction of COVID-19 infected cases and deaths in India

World is facing stress due to unpredicted pandemic of novel COVID-19. Daily growing magnitude of confirmed cases of COVID-19 put the whole world humanity at high risk and it has made a pressure on health professionals to get rid of it as soon as possible. So, it becomes necessary to predict the number of upcoming cases in future for the preparation of future plan-of-action and medical set-ups. The present manuscript proposed a hybrid fuzzy time series model for the prediction of upcoming COVID-19 infected cases and deaths in India by using modified fuzzy C-means clustering technique. Proposed model has two phases. In phase-I, modified fuzzy C-means clustering technique is used to form basic intervals with the help of clusters centroid while in phase-II, these intervals are upgraded to form sub-intervals. The proposed model is tested against available COVID-19 data for the measurement of its performance based on mean square error, root mean square error and average forecasting error rate. The novelty of the proposed model lies in the prediction of COVID-19 infected cases and deaths for next coming 31 days. Beside of this, estimation for the approximate number of isolation beds and ICU required has been carried out. The projection of the present model is to provide a base for the decision makers for making protection plan during COVID-19 pandemic.

Stress, Depression, Anxiety, and Burnout among Healthcare Workers during the COVID-19 Pandemic: A Cross-sectional Study in a Tertiary Centre

Background:

Healthcare workers have been known to suffer from depression, anxiety, and other mental health issues as a result of their profession. Healthcare professionals were already vulnerable to mental health issues prior to the COVID-19 pandemic, but now they are even more prone to stress and frustration.

Objective:

The study aimed to assess stress, depression, anxiety, and burnout among healthcare workers during the COVID-19 pandemic. Moreover, it assessed the relationship between stress, depression, anxiety, burnout, and COVID-19 related stress.

Methods:

A cross-sectional, descriptive, and correlative design was adopted to assess stress, depression, anxiety, and burnout among healthcare workers and determine the relationship among these variables during the COVID-19 pandemic.

Results:

The response rate was 87.6% (831 out of 949), the majority of the participants were nurses (87.4%), and 38.4% were working in inpatient settings. The means of COVID-19 related anxiety (17.38 ± 4.95) and burnout (20.16 ± 6.33) were high and tended to be in the upper portion of the total scores. Participants reported moderate to extremely severe levels of stress (26.5%), anxiety (55.8%), and depression (37.2%). Males reported a higher level of stress (16.59 ± 10.21 vs. 13.42 ± 9.98, p = 0.002) and depression (14.97 ± 10.98 vs. 11.42 ± 10.56, p = 0.001). COVID-19 related anxiety was significantly correlated with participants’ professions (p = 0.004). Burnout (p = 0.003) and depression (p = 0.044) were significantly correlated with the participants’ working area. Significant positive correlations were found between stress, depression, anxiety, burnout, and COVID-19 related stress.

Conclusion:

Healthcare workers may experience considerable psychologic distress as a result of the COVID-19 pandemic due to providing direct patient care, quarantine, or self-isolation. Healthcare workers who were at high risk of contracting COVID-19 appeared to have psychological distress, burnout, and probably, chronic psychopathology. Frontline staff, especially nurses, were at higher risk of showing higher levels of psychological and mental health issues in the long term.

Lessons Learnt From a Greenfield Hangar-Based 1,000-Bedded Temporary Hospital in India

During the COVID-19 pandemic, the total number of hospital beds in the National Capital Region (NCR) of Delhi was 54,321 (roughly 300 beds per one lakh population), which was inadequate for the patients. Therefore, the Indian government initiated the construction of a 1,000-bedded greenfield hangar-based hospital to bridge the healthcare gap. As a result, Intensive Care Unit (ICU) beds in the facility augmented the COVID-19 care ICU beds in the city by 11%. The authors were involved in the planning, developing, and initiating the functioning of 1,000-bedded Dedicated COVID-19 Hospital (DCH). The hospital was conceptualized, built, and operationalized in 12 days only. Lessons learned from this experience would be of benefit should similar situations arise in future. Coordinating structural designing early with the entire project team-from facility administrators and medical practitioners to architects, consultants, and contractors-can result in a structure that better matches the facility's long-term needs and often saves construction time and costs. This article enumerates various challenges faced and the way they were addressed. This hangar-based hospital can be rapidly constructed and deployed on a massive scale. While structural integrity is essential, the planning team was particularly aware of the patient-centric modality of healthcare. Many modifications were carried out in the structure based on patient inputs. Informal discussions with discharged patients and relatives revealed that the human-centric approach was the mainstay of the therapy.

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.

Forecast of the COVID-19 trend in India: A simple modelling approach

By February 2021, the overall impact of the COVID-19 pandemic in India had been relatively mild in terms of total reported cases and deaths. Surprisingly, the second wave in early April becomes devastating and attracts worldwide attention. Multiple factors (e.g., Delta variants with increased transmissibility) could have driven the rapid growth of the epidemic in India and led to a large number of deaths within a short period. We aim to reconstruct the transmission rate, estimate the infection fatality rate and forecast the epidemic size. We download the reported COVID-19 mortality data in India and formulate a simple mathematical model with a flexible transmission rate. We use iterated filtering to fit our model to deaths data. We forecast the infection attack rate in a month ahead. Our model simulation matched the reported deaths well and is reasonably close to the results of the serological study. We forecast that the infection attack rate (IAR) could have reached 43% by July 24, 2021, under the current trend. Our estimated infection fatality rate is about 0.07%. Under the current trend, the IAR will likely reach a level of 43% by July 24, 2021. Our estimated infection fatality rate appears unusually low, which could be due to a low case to infection ratio reported in previous study. Our approach is readily applicable in other countries and with other types of data (e.g., excess deaths).

The Cat Que Virus: a resurfacing orthobunyavirus could lead to epidemics

The newly emerging and re-emerging of viral contagion in the present scenario are of more extensive health concern. After a long calm of many years, an unexpected eruption of the Cat Que Virus in China is a source of our concern. Cat Que Virus is an Arbovirus and belongs to the Simbu serogroup of the Orthobunyavirus genus of the Bunyaviridae family. The Simbu serogroup is an extremely diverse group of Arbovirus. The arboviruses are causing the infection in multiple hosts including humans and various livestock. They can cause mild to life-threatening infections. Arboviruses expand their spectrum and are more observable in recent times. Human actions have the most significant geophysical impact on the environment. Changes in rainfall patterns, floods, and the risk of extreme weather events are all consequences of climate change. These events may be connected to the extension of permissive vectors, geographic ranges, and therefore provide more chance of growth and spread of potential vector. Arboviruses are responsible for the health hazard to millions of people globally. It is critical to concentrate research and surveillance on these emerging and re-emerging viruses, particularly arthropod-borne viral infections. The appropriate research and surveillance on them will help us for the development of effective control and treatment strategies and also reduce health problems. The present review summarizes the current broad outline of discovery, evolution and dispersal of this unknown virus.

Ayurveda Rasayana as antivirals and immunomodulators: potential applications in COVID-19

Coronavirus disease (COVID-19) has been declared as a pandemic by the World Health Organization with rapid spread across 216 countries. COVID-19 pandemic has left its imprints on various health systems globally and caused immense social and economic disruptions. The scientific community across the globe is in a quest for digging the effective treatment for COVID-19 and exploring potential leads from traditional systems of healthcare across the world too. Ayurveda (Indian traditional system of medicine) has a comprehensive aspect of immunity through Rasayana which is a rejuvenation therapy. Here we attempt to generate the potential leads based on the classical text from Ayurveda in general and Rasayana in particular to develop effective antiviral and/or immunomodulator for potential or adjunct therapy in SARS-CoV-2. The Rasayana acts not only by resisting body to restrain or withstand the strength, severity or progression of a disease but also by promoting power of the body to prevent the manifestation of a disease. These Rasayana herbs are common in practice as immunomodulator, antiviral and protectives. The studies on Rasayana can provide an insight into the future course of research for the plausible development of effective management of COVID-19 by the utilization and development of various traditional systems of healthcare. Keeping in view the current pandemic situation, there is an urgent need of developing potential medicines. This study proposes certain prominent medicinal plants which may be further studied for drug development process and also in clinical setup under repurposing of these herbs.

Anti-dengue activity of super critical extract and isolated oleanolic acid of Leucas cephalotes using in vitro and in silico approach

Backgrounds

Leucas cephalotes is a common ethnomedicinal plant widely used by traditional healers for the treatment of Malaria and other types of fever. Oleanolic acid and its derivatives have been reported for various types of pharmacological activities, such as anti-inflammatory, antioxidant, anticancer, hepatoprotective, anti-HIV and anti-HCV activity.

Methods

L.cephalotes plant extracts were prepared by supercritical fluid extraction (SFE) method and oleanolic acid was isolated by preparatory thin-layer chromatography. The compound was identified and characterize by using ultraviolet-visible spectroscopy (UV-VIS), Fourier transform infra-Red spectroscopy (FT-IR) and high-performance thin-layer chromatography (HPTLC). The structure of the compound was elucidated by proton nuclear magnetic resonance (¹HNMR) and carbon nuclear magnetic resonance (¹CNMR) and the purity checked by differential scanning calorimetry (DSC). The MTT assay was used to determine the toxicity of plant extract and oleanolic acid using a microplate reader at 595 nm. The anti-dengue activity of plant extract and oleanolic acid was tested in vitro and in silico using real-time RT-PCR.

Results

The optimum yield of the extract was obtained at 40 °C temperature and 15Mpa pressure. The maximum non-toxic dose (MNTD) of plant extract and oleanolic acid were found as 46.87 μg/ml and 93.75 μg/ml, respectively in C6/36 cell lines. UV spectrophotometer curve of the isolated compound was overlapped with standard oleanolic acid at 232 nm. Superimposed FT-IR structure of the isolated compound was indicated the same spectra at 3433, 2939, 2871, 1690, 1500,1463, 1387, 1250, 1209, 1137 and 656 position as per marker compound. HPTLC analysis showed the retention factor of L. cephalotes extract was 0.19 + 0.06 as similar to the standard oleanolic acid chromatogram. The NMR structure of the isolated compound was identified as similar to the marker oleanolic acid structure. DSC analysis revealed the purity of isolated oleanolic acid was 98.27% with a melting point of 311.16 °C. Real-time RT PCR results revealed that L. cephalotes supercritical extract and isolated oleanolic acid showed 100 and 99.17% inhibition against the dengue − 2 virus when treated with MNTD value of plant extract (46.87 μg/ml) and the test compound (93.75 μg/ml), respectively. The molecular study demonstrated the binding energy of oleanolic acid with NS1and NS5 (non-structural protein) were − 9.42 & -8.32Kcal/mol, respectively.

Conclusions

The SFE extract L. cephalotes and its active compound, oleanolic acid inhibiting the activity of dengue-2 serotype in the in vitro and in silico assays. Thus, the L.cephalotes plant could be an excellent source for drug design for the treatment of dengue infection.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12906-021-03402-2.

Epidemiological, Clinical, and Laboratory Predictors of In-Hospital Mortality Among COVID-19 Patients Admitted in a Tertiary COVID Dedicated Hospital, Northern India: A Retrospective Observational Study

Introduction

COVID-19 pandemic still poses a serious challenge to health system worldwide. This study was planned to determine exposure characteristics, in-hospital mortality, and predictors of in hospital mortality among COVID-19 patients.

Material and methods

We retrospectively investigated epidemiological, clinical, and laboratory profile of confirmed COVID-19 patients admitted from 25th March to 31st August 2020. COVID-19 patient profiles were collected from Medical Record Section of the hospital.

Results

In hospital mortality occurred in 159 (11%) cases. Increasing respiratory rate, higher temperature, higher total leukocyte count, and high blood urea levels were found to be independent risk factors for in hospital mortality whereas higher hemoglobin and higher oxygen saturation at the time of hospital admission were found to be protective against in hospital mortality.

Conclusion

In hospital mortality among COVID-19 patients is almost 1 in 10 in tertiary care hospital. Patients with advancing age (AOR: 1.048; 95% CI: 1.021-1.076), higher respiratory rate (AOR: 1.248; 95% CI: 1.047-1.489), higher temperature (AOR: 1.758; 95% CI: 1.025-3.016), higher leukocyte count (AOR: 1.147; 95% CI: 1.035-1.270), and higher urea levels (AOR: 1.034; 95% CI: 1.005-1.064) at the time of admission are important predictors of COVID-19 in-hospital mortality.

The Effect of COVID-19 and Related Lockdown Phases on Young Peoples' Worries and Emotions: Novel Data From India

The COVID-19 pandemic has posed unprecedented stress to young people. Despite recent speculative suggestions of poorer mental health in young people in India since the start of the pandemic, there have been no systematic efforts to measure these. Here we report on the content of worries of Indian adolescents and identify groups of young people who may be particularly vulnerable to negative emotions along with reporting on the impact of coronavirus on their lives. Three-hundred-and-ten young people from North India (51% male, 12-18 years) reported on their personal experiences of being infected by the coronavirus, the impact of the pandemic and its' restrictions across life domains, their top worries, social restrictions, and levels of negative affect and anhedonia. Findings showed that most participants had no personal experience (97.41%) or knew anyone (82.58%) with COVID-19, yet endorsed moderate-to-severe impact of COVID-19 on their academics, social life, and work. These impacts in turn associated with negative affect. Participants' top worries focused on academic attainments, social and recreational activities, and physical health. More females than males worried about academic attainment and physical health while more males worried about social and recreational activities. Thus, Indian adolescents report significant impact of the pandemic on various aspects of their life and are particularly worried about academic attainments, social and recreational activities and physical health. These findings call for a need to ensure provisions and access to digital education and medical care.

In-vitro and in-silico evaluation of the anti-chikungunya potential of Psidium guajava leaf extract and their synthesized silver nanoparticles

Chikungunya is a notorious viral infection, which affects a large segment of world populations in absence of vaccines and antivirals. The current study evaluates of anti-chikungunya activities of Psidium guajava leaves extract and their green synthesized silver nanoparticles. Green synthesized nanoparticles were well characterized for their size and stability by dynamic light scattering (DLS), zeta potential, scanning electron microscopy (SEM) and their functional groups were analyzed by FTIR. Maximum non-toxic doses (MNTD) of extracts and nanoparticles were analysed by using Vero cell-lines. Anti-chikungunya activities of extracts and nano-particles were determined on Vero cells and their effects on cell viability were measured by MTT assay. The P. guajava nano-particles and extracts revealed the anti-chikungunya activities in the Vero cell. The cells viability was increased by 40% and 60% as compared to the virus control, when these cells were treated with MNTD of P. guajava nano-particles and extracts, respectively. To know the reason for antiviral activity, molecular docking of phytochemicals was done against a replication essential cysteine protease (nsP2) of Chikungunya. It was found that phytochemicals; Longifollen and Quercetin showed the minimum binding energy with nsP2. P. guajava extracts can be exploited to develop an effective anti-chikungunya agent. In the absence of CHIKV vaccines and antivirals, P. guajava may be used to develop rapid, responsive, specific, and cost-effective anti-chikungunya agents.

Convolution neural network based infection transmission analysis on Covid-19 using GIS and Covid data materials

Towards the improvement of predicting and analyzing the infection transmission, a novel CNN (Convolution Neural Network) based Covid Infection Transmission Analysis (CNN-CITA) is presented in this article. The method works based on both GIS data set and the Covid data set. The method reads all the data from the data sets. From the remote sensing data, the method extracts different climate conditions like temperature, humidity, and rainfall. Similarly from Global Information System data set, the locations of the peoples are fetched and merged. The merged data has been split into number of time frame, at each condition, the data sets are merged. Such merged data has been trained with deep learning networks which support the search of person location and mobility. Based on the result and the data set maintained by the governments, the infection transmission rate has been measured on region basis. In each region of movement performed by any person, the method computes the infection Transmission Rate (ITR) in two time window as before and after. According to the infection rate and ITR value of different region, a subset of sources are selected as vulnerable sources. The method produces higher performance in predicting the vulnerable sources and supports the reduction of infection rate.

Perspectives About Modulating Host Immune System in Targeting SARS-CoV-2 in India

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the causative agent of coronavirus induced disease-2019 (COVID-19), is a type of common cold virus responsible for a global pandemic which requires immediate measures for its containment. India has the world's largest population aged between 10 and 40 years. At the same time, India has a large number of individuals with diabetes, hypertension and kidney diseases, who are at a high risk of developing COVID-19. A vaccine against the SARS-CoV-2, may offer immediate protection from the causative agent of COVID-19, however, the protective memory may be short-lived. Even if vaccination is broadly successful in the world, India has a large and diverse population with over one-third being below the poverty line. Therefore, the success of a vaccine, even when one becomes available, is uncertain, making it necessary to focus on alternate approaches of tackling the disease. In this review, we discuss the differences in COVID-19 death/infection ratio between urban and rural India; and the probable role of the immune system, co-morbidities and associated nutritional status in dictating the death rate of COVID-19 patients in rural and urban India. Also, we focus on strategies for developing masks, vaccines, diagnostics and the role of drugs targeting host-virus protein-protein interactions in enhancing host immunity. We also discuss India's strengths including the resources of medicinal plants, good food habits and the role of information technology in combating COVID-19. We focus on the Government of India's measures and strategies for creating awareness in the containment of COVID-19 infection across the country.

Challenges faced in establishing a dedicated 250 bed COVID-19 intensive care unit in a temporary structure

An Intensive Care Unit (ICU) is an organized system for the provision of care to critically ill patients that provides intensive and specialized medical and nursing care, an enhanced capacity for monitoring, and multiple modalities of physiologic organ support to sustain life during a period of life-threatening organ system insufficiency. While this availability of trained manpower and specialized equipment makes it possible to care for critically ill patients, it also presents singular challenges in the form of man and material management, design concerns, budgetary concerns, and protocolization of treatment. Consequently, the establishment of an ICU requires rigorous design and planning, a process that can take months to years. However, the Coronavirus disease-19 (COVID-19) epidemic has required the significant capacity building to accommodate the increased number of critically ill patients. At the peak of the pandemic, many countries were forced to resort to the building of temporary structures to house critically ill patients, to help tide over the crisis. This narrative review describes the challenges and lessons learned while establishing a 250 bedded ICU in a temporary structure and achieving functionality within a period of a fortnight.

Has loneliness and poor resilient coping influenced the magnitude of psychological distress among apparently healthy Indian adults during the lockdown? Evidence from a rapid online nation-wide cross-sectional survey

BACKGROUND

The burden of psychological distress is increasing with the spread of the pandemic and also with the enforcement of its containment measures. The aim of this research was to determine the proportion of self-reported psychological distress, loneliness and degrees of resilient coping, and to also investigate the relationship of loneliness, coping and other variables with psychological distress among apparently healthy Indians during nation-wide lockdown period.

METHODS

A cross-sectional, region-stratified survey using pre-designed pre-tested Google form disseminated via different social media platforms was conducted. A total of 1249 responses were analysed all over India. The form enquired about Socio-demographic profile, awareness on COVID pandemic and cases in the surroundings. UCLA Loneliness scale, Brief resilience and coping scale (BRCS) and Psychological distress scale (K6) assessed self-reported loneliness, coping and psychological distress, respectively. Special regressor technique adjusting for endogeneity and heteroskedasticity was used to extract the average marginal effects.

RESULTS

Majority of the respondents were 18-35 years old, male, single and urban residents. News media, social media mostly acted as sources of information regarding COVID related news. Overall, 54.47% (95% CI: 51.39-57.53%) and 38.39% (95% CI: 35.57-41.29%) were reported to be lonely and had low resilient coping ability respectively. Around 44.68% had high risk of developing psychological distress. Being a student (average marginal effect coefficient (AMECoef).: -0.07, 95% CI: [-0.12, -0.01]) and perceiving lockdown as an effective measure (AMECoef: -0.11, 95% CI: [-0.19, -0.03]) were protective against psychological distress. Psychological distress was associated with male respondents (AMECoef 0.07, 95% CI: [0.02, 0.11]), low or medium resilient copers (AMECoef 0.89, 95% CI: [0.17, 1.61]), and perceiving a serious impact of social distancing measures (AMECoef 0.17, 95% CI: [0.09, 0.26]).

CONCLUSIONS

Psychological distress among Indian population during lockdown was prevalent. Poor coping ability and perceiving social distancing to have a serious impact was found to be significantly contributing to psychological distress. Appropriate measures to address these issues would be beneficial for the community mental health.

Interspecies transmission of coronaviruses and immunization: An Indian perspective

The milder form of infection and higher rates of recovery witnessed among COVID-19 patients in India is indicative of the potential intervention of other “unconventional” biological mechanisms. The recently established similarity between beta-coronavirus strains in animals and humans led us to hypothesize that previous contact with infected dogs or cattle could shield humans from the circulating SARS-CoV-2 virus. We further believe that our hypothesis, if confirmed by further studies, could be used as a potential vaccine strategy.

The Main Molecular and Serological Methods for Diagnosing COVID-19: An Overview Based on the Literature

Diagnostic tests have been considered as the main alternative for the control of coronavirus disease (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), as a correct diagnosis allows for decision making when facing the disease, particularly as there is a lack of effective therapeutic protocols and vaccines. Thus, in this review, we summarized the main diagnostic approaches currently available for the diagnosis of SARS-CoV-2 infection in humans based on studies available in article databases. The tests can be organized into two main categories: nucleic acid-based tests, recommended for the initial detection of the virus, and serological tests, recommended for assessing the disease progression. The studies have shown that the performance of diagnostic methods depends on different factors, such as the type of samples and the characteristics of each assay. It was identified that the positivity of the tests is mainly related to the onset of symptoms. We also observed that point-of-care diagnoses are considered as one of the main trends in this area, due to the low-cost and simplicity of the assay; however, the analytical performance must be critically analyzed. Thus, the COVID-19 pandemic has highlighted the critical role of diagnostic technologies in the control of infectious diseases.

In-vitro and in silico activity of Cyamopsis tetragonoloba (Gaur) L. supercritical extract against the dengue-2 virus

Our health and wealth are highly influenced by a number of viruses. Dengue is one of them having a global influence in absence of vaccines and antiviral. WHO suggested that the morbidity of dengue is increasing more than 6 times from 0.5 million in 2010 to over 3.34 million in 2016, following a sharp increase in 2019. The aim of the present study is to check the in vitro and in silico anti-dengue activity of Cyamopsis tetragonoloba supercritical extract in cell lines. The optimum yield of supercritical extract was obtained 0.13 g/10 g (1.3% w/w) at 40 °C temp and 15 MPa pressure and further characterized by GC-MS. The antiviral assay was performed on C6/36 cell lines with 100 copies of dengue-2 virus and maximum non-toxic dose (31.25 µg/ml) of supercritical extract and their effect was detected by real-time RT-PCR. This study revealed that C. tetragonoloba supercritical extract inhibited the dengue-2 virus (99.9%). GC-MS analysis of C. tetragonoloba supercritical extract showed the presence of 10 compounds. The major compounds identified were Hexadecanoic acid, 15-methyl-methyl ester (24.498%); 9,12-octadecadienoyl chloride, (z,z)- (23.718%); methyl dodecanoic acid (13.228%); methyl-stearate (8.696%); Tridecanoic acid, 12-methyl-, methyl-ester (8.426%), dodecanoic acid (6.102%). The study reveals that C. tetragonoloba can be exploited to develop an effective, inexpensive, and specific anti-dengue. The molecular docking study demonstrated the binding energy of 1,2-benzenedicarboxylic acid, bis(2-methylpropyl) ester (- 4.1 kcal/mol), 9,12-octadecadienoyl chloride (z,z) (- 4.0 kcal/mol) ligands were higher than others. It is concluded that C. tetragonoloba can play a major role to inhibit dengue-2 virus.

Nexus between population density and novel coronavirus (COVID-19) pandemic in the south Indian states: A geo-statistical approach

The unprecedented growth of the novel coronavirus (SARS-CoV-2) as a severe acute respiratory syndrome escalated to the coronavirus disease 2019 (COVID-19) pandemic. It has created an unanticipated global public health crisis that is spreading rapidly in India as well, posing a serious threat to 1350 million persons. Among the factors, population density is foremost in posing a challenge in controlling the COVID-19 contagion. In such extraordinary times, evidence-based knowledge is the prime requisite for pacifying the effect. In this piece, we have studied the district wise transmissions of the novel coronavirus in five south Indian states until 20th July 2020 and its relationship with their respective population density. The five states are purposefully selected for their records in better healthcare infrastructure vis-à-vis other states in India. The study uses Pearson's correlation coefficient to account for the direct impact of population density on COVID-19 transmission rate. Response surface methodology approach is used to validate the correlation between density and transmission rate and spatiotemporal dynamics is highlighted using Thiessen polygon method. The analysis has found that COVID-19 transmission in four states (Kerala, Tamil Nadu, Karnataka and Telangana) strongly hinges upon the spatial distribution of population density. In addition, the results indicate that the long-term impacts of the COVID-19 crisis are likely to differ with demographic density. In conclusion, those at the helm of affairs must take cognizance of the vulnerability clusters together across districts.

Partial derivative Nonlinear Global Pandemic Machine Learning prediction of COVID 19

The recent worldwide outbreak of the novel coronavirus disease 2019 (COVID-19) opened new challenges for the research community. Machine learning (ML)-guided methods can be useful for feature prediction, involved risk, and the causes of an analogous epidemic. Such predictions can be useful for managing and intercepting the outbreak of such diseases. The foremost advantages of applying ML methods are handling a wide variety of data and easy identification of trends and patterns of an undetermined nature.In this study, we propose a partial derivative regression and nonlinear machine learning (PDR-NML) method for global pandemic prediction of COVID-19. We used a Progressive Partial Derivative Linear Regression model to search for the best parameters in the dataset in a computationally efficient manner. Next, a Nonlinear Global Pandemic Machine Learning model was applied to the normalized features for making accurate predictions. The results show that the proposed ML method outperformed state-of-the-art methods in the Indian population and can also be a convenient tool for making predictions for other countries.

The Enigma of Low COVID-19 Fatality Rate in India

Coronavirus disease 2019 (COVID-19), an acute onset pneumonia caused by a novel Betacoronavirus Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has rapidly evolved into a pandemic. Though its origin has been linked to the Wuhan City of China's Hubei Province in December 2019, recent reports claim that the original animal-to-human transmission of the virus probably happened sometime between September and October 2019 in Guangdong Province, rather than Hubei. As of July 3, 2020, India has reported a case positivity rate of 6.5% and a fatality rate of 2.8%, which are among the lowest in the world. Also, the severity of the disease is much less among Indians as evidenced by the low rate of ICU admission (15.3%) and the need for mechanical ventilation (4.16%). As per the World Health Organization (WHO) situation report 165 on July 3, 2020, India has one of the lowest deaths per 100,000 population (1.32 deaths against a global average of 6.04). Several factors related to the pathogen, host and environment might have some role in reducing the susceptibility of Indians to COVID-19. These include some ongoing mutations that can alter the virulence of the circulating SARS-CoV-2 strains, host factors like innate immunity, genetic diversity in immune responses, epigenetic factors, genetic polymorphisms of ACE2 receptors, micro RNAs and universal BCG vaccination, and environmental factors like high temperature and humidity which may alter the viability and transmissibility of the strain. This perspective -highlights the potential factors that might be responsible for the observed low COVID-19 fatality rate in Indian population. It puts forward several hypotheses which can be a ground for future studies determining individual and population susceptibility to COVID-19 and thus, may offer a new dimension to our current understanding of the disease.