Comparative study of COVID- 19 pneumonia in first and second waves

Background: The main aim of the study was to evaluate the different parameters of the COVID-19 pneumonia in India during the first and second waves. Method: Five hundred RT-PCR positive and HRCT documented COVID-19 pneumonia patients each from first wave (June 2020-December 2020) and second wave (March 2021-May 2021) were selected. The results were evaluated in terms of age groups affected, gender wise distribution, and CT severity score on HRCT. The final conclusion was done by comparing these variables from first wave with the ones during the second wave and inferences drawn upon thereof. Results: During the first wave, majority of the population involved belonged to more than 45 years category whereas during the second wave majority belonged to the 18-45 years category. Further, the severity of the disease was more during the second wave than the first wave with more males being affected than females in both the waves. Conclusion: Second COVID-19 wave in India was more severe than the first wave in terms of the number of patients affected as well as the severity of the pneumonia in the involved patients, likely due to continuously mutating variants of the virus & lifting up of the restrictions.

Extended reality for patient recovery and wellness

The healthcare sector is undergoing rapid change using information and communication technologies (E-Health). E-Health enables faster access to patient records and effective diagnosis and opens new areas of technology curated treatments. The unprecedented situation of the COVID pandemic faced by the world population has shifted greater focus toward healthcare and remote care systems, which have given rise to technological innovations in healthcare systems, including advancements in immersive extended reality (XR). Virtual reality, augmented reality, and mixed reality are together referred to as XR or immersive XR. Immersive XR also refers to all real-and-virtual collaborative environments and human–machine interactions. The characteristics of XR, such as integrating real and virtual environments and user interaction facilitation by utilizing past data, have promoted the application of immersive XR in many healthcare domains, including psychotherapy, patient recovery, wellness, etc. Poststroke motor recovery and neurorehabilitation are some examples that utilize XR-enabled platforms. Thus, this chapter will focus on mapping current research and development of immersive XR in patient recovery and wellness in the context of trivial and emerging nontrivial applications. This chapter will also involve systematic exploration of the available academic manuscripts, global patent grants, and emerging technical standards to compare the current academic and commercial developments to extend immersive XR in the field of patient recovery and wellness. © 2023 Elsevier Inc. All rights reserved.

Challenges in Accessing and Delivering Maternal and Child Health Services during the COVID-19 Pandemic: A Cross-Sectional Rapid Survey from Six States of India.

BACKGROUND/OBJECTIVES: Globally, the COVID-19 pandemic and its prevention and control policies have impacted maternal and child health (MCH) services. This study documents the challenges faced by patients in accessing MCH services, and the experiences of health care providers in delivering those services during the COVID-19 outbreak, explicitly focusing on the lockdown period in India. METHODS: A cross-sectional study (rapid survey) was conducted in 18 districts from 6 states of India during March to June, 2020. The sample size included 540 MCH patients, 18 gynaecologists, 18 paediatricians, 18 district immunisation officers and 108 frontline health workers. Bivariate analysis and multivariable analysis were used to assess the association between sociodemographic characteristics, and challenges faced by the patients. RESULTS: More than one-third of patients (n = 212; 39%) reported that accessing MCH services was a challenge during the lockdown period, with major challenges being transportation-related difficulties (n = 99; 46%) unavailability of hospital-based services (n = 54; 23%) and interrupted outreach health services (n = 39; 18.4%). The supply-side challenges mainly included lack of infrastructural preparedness for outbreak situations, and a shortage of human resources. CONCLUSIONS/RECOMMENDATIONS: A holistic approach is required that focuses on both preparedness and response to the outbreak, as well reassignment and reinforcement of health care professionals to continue catering to and maintaining essential MCH services during the pandemic.

Comparative Study of COVID- 19 Pneumonia in First and Second Waves

[...]COVID-19 wave in India was more severe than the first wave in terms of the number of patients affected as well as the severity of the pneumonia in the involved patients, likely due to continuously mutating variants ofthe virus & lifting up of the restrictions. [1] The diagnosis of this disease depends upon the real-time reverse transcriptase polymerase chain reaction . The CT manifestations of the COVID-19 pneumonia include multifocal ground glass and consolidative opacities in a peripheral distribution with predominantly apicobasal gradient . [6,7] Material and Methods A cross sectional study was conducted among the patients who had documented RT-PCR positive and CT documented COVID-19 pneumonia admitted in Chest Diseases Hospital of GMC, Jammu.

Covid-19 Analysis using Chest X-Rays and CT-Scan

COVID-19 is commonly known as a novel coronavirus disease, which is a highly contagious disease that emerged in China in late 2019. This disease is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It is a virus belonging to the large family of coronaviruses. The disease first emerged in Wuhan, China in 2019 and then quickly developed into a global pandemic, spreading to more than 213 countries. The well-known symptoms of COVID-19 are fever, shortness of breath, dry cough, and other symptoms. Pain or difficulty breathing may occur. Most of these symptoms point to signs of respiratory infections and lung abnormalities that can be detected by radiologists. So, chest xray and computed tomography images can be used with machine learning algorithms to find the disease.

Medical Chatbot using AI and NLP

The use of chatbots has grown rapidly across industries, including marketing, assistive systems, education, healthcare, cultural heritage, and entertainment. This paper discusses the incentives for using chatbots and explains how useful chatbots are in various contexts. As intelligent software and hardware, also known as intelligent agents, are developed and analyzed, Artificial Intelligence (AI) is becoming more and more integrated into daily lives. From manual labor to complex procedures, intelligent agents are capable of performing a wide range of tasks. One of the simplest and most common forms of intelligent human-computer interaction is the chatbot, which is a classic example of an artificial intelligence Human-Computer Interaction (HCI) system. A chatbot is described as "a computer program designed to simulate interaction with human users, particularly over the Internet." In addition to chatbots, it also called smart bots, interactive agents, digital assistants, and intelligent conversational objects. In the midst of the COVID-19 pandemic, going to the doctor is no longer an indulgence. A chatbot is a Natural Language Processing (NLP) based chatbot to help with basic medical questions. Only the best knowledge of a chatbot can be used to answer medical questions.

Unconditional and conditional analysis between COVID-19 cases, temperature, exchange rate and stock markets using wavelet coherence and wavelet partial coherence approaches

This paper examines the time-frequency relationship between the number of confirmed COVID-19 cases, temperature, exchange rates and stock market return in the top-15 most affected countries by the COVID-19 pandemic. We employ Wavelet Coherence and Partial Wavelet Coherence on the daily data from 1st February, 2020 to 13th May, 2020. This study adds to the literature by implementing the Wavelet Coherence technique to explore the unexpected outbreak effects of the global pandemic on temperature, exchange rates and stock market returns. Our results reveal (i) there is evidence of cyclicality between temperature and COVID-19 cases, implying that average daily temperature has a significant impact on the spread of the COVID-19 disease in most of the countries;(ii) strong connectedness at low frequencies display that COVID-19 cases have a significant long-term impact on the exchange rate returns and stock markets returns of the most affected countries under study;(iii) after controlling for the effect of stock market returns and temperature, the co-movements between the confirmed COVID-19 cases and exchange rate returns becomes stronger;(iv) after controlling for the effect of exchange rate returns and temperature, the co-movements between the confirmed COVID-19 cases and stock market returns become stronger. Apart from theoretical contribution, this paper offers value to investors and policymakers as they attempt to combat the coronavirus risk and shape the economy and stock market behavior.

COVID-19 and environmental concerns: A rapid review.

COVID-19 has slowed global economic growth and consequently impacted the environment as well. Parallelly, the environment also influences the transmission of this novel coronavirus through various factors. Every nation deals with varied population density and size; air quality and pollutants; the nature of land and water, which significantly impact the transmission of coronavirus. The WHO (Ziaeepour et al., 2008) [1] has recommended rapid reviews to provide timely evidence to the policymakers to respond to the emergency. The present study follows a rapid review along with a brief bibliometric analysis of 328 research papers, which synthesizes the evidence regarding the environmental concerns of COVID-19. The novel contribution of this rapid review is threefold. One, we take stock of the diverse findings as regards the transmission of the novel coronavirus in different types of environments for providing conclusive directions to the ongoing debate regarding the transmission of the virus. Two, our findings provide topical insights as well as methodological guidance for future researchers in the field. Three, we inform the policymakers on the efficacy of environmental measures for controlling the spread of COVID-19.

MCP-1: Function, regulation, and involvement in disease.

MCP-1 (Monocyte chemoattractant protein-1), also known as Chemokine (CC-motif) ligand 2 (CCL2), is from family of CC chemokines. It has a vital role in the process of inflammation, where it attracts or enhances the expression of other inflammatory factors/cells. It leads to the advancement of many disorders by this main mechanism of migration and infiltration of inflammatory cells like monocytes/macrophages and other cytokines at the site of inflammation. MCP-1 has been inculpated in the pathogenesis of numerous disease conditions either directly or indirectly like novel corona virus, cancers, neuroinflammatory diseases, rheumatoid arthritis, cardiovascular diseases. The elevated MCP-1 level has been observed in COVID-19 patients and proven to be a biomarker associated with the extremity of disease along with IP-10. This review will focus on involvement and role of MCP-1 in various pathological conditions.

Meteorological factors, COVID-19 cases, and deaths in top 10 most affected countries: an econometric investigation.

This paper examines the nexus between the Covid-19 confirmed cases, deaths, meteorological factors, including an air pollutant among the world's top 10 infected countries, from 1 February 2020 through 30 June 2020, using advanced econometric techniques to address heterogeneity across the nations. The findings of the study suggest that there exists a strong cross-sectional dependence between Covid-19 cases, deaths, and all the meteorological factors for the countries under study. The findings also reveal that a long-term relationship exists between all the meteorological factors. There exists a bi-directional causality running between the Covid-19 cases and all the meteorological factors. With Covid-19 death cases as the dependent variable, there exists bi-directional causality running between the Covid-19 death cases and Covid-19 confirmed cases, air pressure, humidity, and temperature. Temperature and air pressure exhibit a statistically significant and negative impact on the Covid-19 confirmed cases. Air pollutant PM2.5 also exhibits a significant but positive impact on the Covid-19 confirmed cases. Temperature indicates a statistically significant and negative impact on the Covid-19 death cases. At the same time, Covid-19 confirmed cases and air pollutant PM2.5 exhibit a statistically significant and positive impact on the Covid-19 death cases across the ten countries under study. Hence, it is possible to postulate that cool and dry weather conditions with lower temperatures may promote indoor activities and human gatherings (assembling), leading to virus transmission. This study contributes both practically and theoretically to the concerned field of pandemic management. Our results assist in taking appropriate measures in implementing intersectoral policies and actions as necessary in a timely and efficient manner. Causal relations of Meteorological factors and Covid-19 (2 models used in the study).

COVID-19 prevalence and mortality in patients with cancer and the effect of primary tumour subtype and patient demographics: a prospective cohort study.

BACKGROUND: Patients with cancer are purported to have poor COVID-19 outcomes. However, cancer is a heterogeneous group of diseases, encompassing a spectrum of tumour subtypes. The aim of this study was to investigate COVID-19 risk according to tumour subtype and patient demographics in patients with cancer in the UK. METHODS: We compared adult patients with cancer enrolled in the UK Coronavirus Cancer Monitoring Project (UKCCMP) cohort between March 18 and May 8, 2020, with a parallel non-COVID-19 UK cancer control population from the UK Office for National Statistics (2017 data). The primary outcome of the study was the effect of primary tumour subtype, age, and sex and on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) prevalence and the case-fatality rate during hospital admission. We analysed the effect of tumour subtype and patient demographics (age and sex) on prevalence and mortality from COVID-19 using univariable and multivariable models. FINDINGS: 319 (30·6%) of 1044 patients in the UKCCMP cohort died, 295 (92·5%) of whom had a cause of death recorded as due to COVID-19. The all-cause case-fatality rate in patients with cancer after SARS-CoV-2 infection was significantly associated with increasing age, rising from 0·10 in patients aged 40-49 years to 0·48 in those aged 80 years and older. Patients with haematological malignancies (leukaemia, lymphoma, and myeloma) had a more severe COVID-19 trajectory compared with patients with solid organ tumours (odds ratio [OR] 1·57, 95% CI 1·15-2·15; p<0·0043). Compared with the rest of the UKCCMP cohort, patients with leukaemia showed a significantly increased case-fatality rate (2·25, 1·13-4·57; p=0·023). After correction for age and sex, patients with haematological malignancies who had recent chemotherapy had an increased risk of death during COVID-19-associated hospital admission (OR 2·09, 95% CI 1·09-4·08; p=0·028). INTERPRETATION: Patients with cancer with different tumour types have differing susceptibility to SARS-CoV-2 infection and COVID-19 phenotypes. We generated individualised risk tables for patients with cancer, considering age, sex, and tumour subtype. Our results could be useful to assist physicians in informed risk-benefit discussions to explain COVID-19 risk and enable an evidenced-based approach to national social isolation policies. FUNDING: University of Birmingham and University of Oxford.

A qualitative enquiry into strategic and operational responses to Covid-19 challenges in South Asia.

The Covid-19 epidemic is a public health emergency of international concern. It poses a massive risk for the human race across the planet, calling for the need to take measures at the local, regional, national, and global levels. South Asian countries stand more vulnerable to the pandemic due to their dense population, poor infrastructure, and low surveillance system. This paper aims to understand the challenges from the Covid-19 pandemic for South Asia; and investigates the strategic and operational responses to this pandemic by policymakers and healthcare professionals, respectively, in South Asia. The study uses interviews and opinions of policymakers and doctors, from the South Asian region, involved in tackling the Covid-19 crisis. The qualitative analysis is performed on these interviews and opinions by using NVivo 12 software. The findings indicate that policymakers and healthcare providers across South Asia have been showing efficient teamwork while dealing with this pandemic. The healthcare administrators being at the operational level, convey the challenges they face to the policymakers who then respond to them at a strategic level.

COVID-19 mortality in patients with cancer on chemotherapy or other anticancer treatments: a prospective cohort study.

BACKGROUND: Individuals with cancer, particularly those who are receiving systemic anticancer treatments, have been postulated to be at increased risk of mortality from COVID-19. This conjecture has considerable effect on the treatment of patients with cancer and data from large, multicentre studies to support this assumption are scarce because of the contingencies of the pandemic. We aimed to describe the clinical and demographic characteristics and COVID-19 outcomes in patients with cancer. METHODS: In this prospective observational study, all patients with active cancer and presenting to our network of cancer centres were eligible for enrolment into the UK Coronavirus Cancer Monitoring Project (UKCCMP). The UKCCMP is the first COVID-19 clinical registry that enables near real-time reports to frontline doctors about the effects of COVID-19 on patients with cancer. Eligible patients tested positive for severe acute respiratory syndrome coronavirus 2 on RT-PCR assay from a nose or throat swab. We excluded patients with a radiological or clinical diagnosis of COVID-19, without a positive RT-PCR test. The primary endpoint was all-cause mortality, or discharge from hospital, as assessed by the reporting sites during the patient hospital admission. FINDINGS: From March 18, to April 26, 2020, we analysed 800 patients with a diagnosis of cancer and symptomatic COVID-19. 412 (52%) patients had a mild COVID-19 disease course. 226 (28%) patients died and risk of death was significantly associated with advancing patient age (odds ratio 9·42 [95% CI 6·56-10·02]; p<0·0001), being male (1·67 [1·19-2·34]; p=0·003), and the presence of other comorbidities such as hypertension (1·95 [1·36-2·80]; p<0·001) and cardiovascular disease (2·32 [1·47-3·64]). 281 (35%) patients had received cytotoxic chemotherapy within 4 weeks before testing positive for COVID-19. After adjusting for age, gender, and comorbidities, chemotherapy in the past 4 weeks had no significant effect on mortality from COVID-19 disease, when compared with patients with cancer who had not received recent chemotherapy (1·18 [0·81-1·72]; p=0·380). We found no significant effect on mortality for patients with immunotherapy, hormonal therapy, targeted therapy, radiotherapy use within the past 4 weeks. INTERPRETATION: Mortality from COVID-19 in cancer patients appears to be principally driven by age, gender, and comorbidities. We are not able to identify evidence that cancer patients on cytotoxic chemotherapy or other anticancer treatment are at an increased risk of mortality from COVID-19 disease compared with those not on active treatment. FUNDING: University of Birmingham, University of Oxford.