Doffing Corridor: Establishing Expedited High-Volume Doffing With Exposure Reduction to Contaminated Personal Protective Equipment (PPE) in a COVID-19 Hospital in India.

Background Considering the virulent nature of the COVID-19, the safety of healthcare workers (HCW) became a challenge for hospital administrators. Wearing a personal protective equipment (PPE) kit, called donning, which can be easily done by the help of another staff. But correctly removing the infectious PPE kit (doffing) was a challenge. The increased number of HCWs for COVID-19 patient care raised the opportunity to develop an innovative method for the smooth doffing of PPEs. Objective We aimed to design and establish an innovative PPE doffing corridor in a tertiary care COVID-19 hospital during the pandemic in India with a heavy doffing rate and minimize the COVID-19 virus spread among healthcare workers. Methodology A prospective, observational cohort study at the COVID-19 hospital, Postgraduate Institute of Medical Education and Research (PGIMER), Chandigarh, India, was conducted from July 19, 2020, to March 30, 2021. The time taken for PPE doffing process of HCWs was observed and compared between the doffing room and doffing corridor. The data was collected by a public health nursing officer using Epicollect5 mobile software and Google forms. The following parameters, like grade of satisfaction, time and volume of doffing, the errors in the steps of doffing, rate of infection, were compared between the doffing corridor and the doffing room. The statistical analysis was done by the use of SPSS software. Result 'Doffing corridor' decreased the overall doffing time by 50% compared to the initial doffing room. The doffing corridor solved the purpose of accommodating more HCWs for PPE doffing and an overall saving of 50% time. Fifty-one percent of HCWs rated the satisfaction rate as Good in the grading scale. The errors in the steps of doffing that occurred in the doffing process were comparatively lesser in the doffing corridor. The HCWs who doffed in the doffing corridor were three times less likely to get self-infection than the conventional doffing room. Conclusion Since COVID-19 was a new pandemic, the healthcare organizations focused on innovations to combat the spread of virus. One of these was an innovative doffing corridor to expedite the doffing process and decrease the exposure time to the contaminated items. The doffing corridor process can be considered at a high-interest rate to any hospital dealing with infectious disease, with high working satisfaction, less exposure to the contagion, and less risk of infection.

Does Oxford Government Response Tracker Explain the SARS-CoV-2 Morbidity and Mortality: An Ecological Time Series Study.

BACKGROUND: Many nations swiftly designed and executed government policies to contain the rapid rise of SARS-CoV-2 cases. The government actions can be broadly segmented as movement and mass gathering restrictions (such as travel and lockdown), public awareness (such as facial covering and hand washing), emergency healthcare investment and social welfare provisions (such as poor welfare schemes to distribute food and shelter). The Blavatnik School of Government-Oxford university tracked various policy initiatives by governments across the globe and released them as composite indices. We assessed the overall government response using Oxford Comprehensive Health Index (CHI) and Stringency Index (SI) to combat the SARS-CoV-2 pandemic. OBJECTIVE: This study aims to demonstrate the utility of CHI and SI to gauge and evaluate the government responses for containing the spread of SARS-CoV-2. We expect a significant inverse relationship between policy indices (CHI and SI) and SARS-CoV-2 severity indices (morbidity and mortality). METHODS: In this ecological study, we analysed data from two publicly available data sources released between March 2020, to October 2021: Oxford Covid-19 Government Response Tracker (OxCGRT) and World Health Organization (WHO). We applied Auto-Regressive Integrated Moving Average (ARIMA) and Seasonal ARIMA (SARIMA) to model the data. The performance of different models was assessed using a combination of evaluation criteria: Adj-R2, Root Mean Square of Error (RMSE) and Bayesian Information Criteria (BIC). RESULTS: The strict implementation of policies by the government to contain the crises of SARS-CoV-2 resulted in higher CHI and SI in the beginning. Although the value of CHI and SI gradually fell--the same was consistently higher at values of more than 80% points. During the initial investigation, we found that Cases Per Million (CPM) and Deaths Per Million (DPM) followed the same trend. However, the final CPM and DPM model were SARIMA (3,2,1)(1,0,1) and ARIMA (1,1,1), respectively. The current study does not support the hypotheses that SARS-CoV-2 severity (CPM and DPM) is associated with stringent policy measures (CHI and SI). CONCLUSIONS: Our study concludes that the policy measures (CHI and SI) do not explain the change in epidemiological indicators (CPM and DPM). The study reiterates our understanding that strict policies do not necessarily lead to better compliance but may overwhelm the overstretched physical health systems. The 21st-century problems, thus, demand 21st-century solutions. The digital ecosystem was instrumental in the timely collection, curation, cloud storage and data communication. Thus, digital epidemiology can--and--should be successfully integrated into existing surveillance systems for better disease monitoring, management and evaluation.

Exploring the Utility of Google Mobility Data During the COVID-19 Pandemic in India: Digital Epidemiological Analysis.

BACKGROUND: Association between human mobility and disease transmission has been established for COVID-19, but quantifying the levels of mobility over large geographical areas is difficult. Google has released Community Mobility Reports (CMRs) containing data about the movement of people, collated from mobile devices. OBJECTIVE: The aim of this study is to explore the use of CMRs to assess the role of mobility in spreading COVID-19 infection in India. METHODS: In this ecological study, we analyzed CMRs to determine human mobility between March and October 2020. The data were compared for the phases before the lockdown (between March 14 and 25, 2020), during lockdown (March 25-June 7, 2020), and after the lockdown (June 8-October 15, 2020) with the reference periods (ie, January 3-February 6, 2020). Another data set depicting the burden of COVID-19 as per various disease severity indicators was derived from a crowdsourced API. The relationship between the two data sets was investigated using the Kendall tau correlation to depict the correlation between mobility and disease severity. RESULTS: At the national level, mobility decreased from -38% to -77% for all areas but residential (which showed an increase of 24.6%) during the lockdown compared to the reference period. At the beginning of the unlock phase, the state of Sikkim (minimum cases: 7) with a -60% reduction in mobility depicted more mobility compared to -82% in Maharashtra (maximum cases: 1.59 million). Residential mobility was negatively correlated (-0.05 to -0.91) with all other measures of mobility. The magnitude of the correlations for intramobility indicators was comparatively low for the lockdown phase (correlation ≥0.5 for 12 indicators) compared to the other phases (correlation ≥0.5 for 45 and 18 indicators in the prelockdown and unlock phases, respectively). A high correlation coefficient between epidemiological and mobility indicators was observed for the lockdown and unlock phases compared to the prelockdown phase. CONCLUSIONS: Mobile-based open-source mobility data can be used to assess the effectiveness of social distancing in mitigating disease spread. CMR data depicted an association between mobility and disease severity, and we suggest using this technique to supplement future COVID-19 surveillance.

Comparison of Imaging Severity Between Vaccinated and Unvaccinated COVID-19 Patients: Perspective of an Indian District.

BACKGROUND: Extensive vaccination drives undertaken globally helped in the fight against the coronavirus disease 2019 (COVID-19) pandemic, but different nations adopted different vaccination policies to tackle the disease. The vaccination drive in India began with the administration of two different vaccines: Covishield and Covaxin. We assessed the effect of vaccination status on imaging severity in patients with positive COVID-19 reverse transcription-polymerase chain reaction (RT-PCR)/antigen tests. METHOD: This was a single-center retrospective observation analysis carried out over three months between March 1, 2021, to May 31, 2021. Data access was provided by the District Hospital Review Board (DHRB) and the Department of Health (DOH), District Ambala, Haryana. Appropriate statistical tools were used to analyze the data. Statistical Package for Social Sciences (SPSS) 26.0 and Python 3.9 were used for statistical analysis and visualization, and a p-value of less than 0.05 was considered statistically significant. RESULTS: The total sample size of the study was 1,316, out of which 371 (28.2%) were vaccinated and 945 (71.8%) were not vaccinated. The mean age of the study participants was 49.6 ± 15.7 years. Seven hundred ninety-seven (60.6%) participants were male, while 519 (39.4%) participants were female. A statistically significant reduction was observed in the computed tomography severity score (CTSS) of the vaccinated population compared to the non-vaccinated group (χ2 = 74.3, p < 0.001). Vaccination led to a statistically significant decrease in mean CTSS across all lung lobes. CONCLUSION: Emerging COVID-19 variants challenge the effect of available vaccines, with different nations adopting different vaccination strategies to deal with the ongoing health problem. CTSS was employed as an objective marker to study the disease severity and effect of vaccination. Vaccination resulted in a significant reduction in CTSS seen on high-resolution computed tomography (HRCT) chest scans. There was a significant decrease in the incidence of severe COVID-19 pneumonia among vaccinated individuals. We need more observational data to corroborate the efficacy of vaccines presented in the randomized trials. Sharing such data between different nations can help us adopt a unifying vaccination strategy and decrease the impact of COVID-19 in subsequent disease waves.

Surface contamination by SARS-CoV2 RNA in dedicated COVID care area of a tertiary care hospital in North India.

Environmental surfaces are potential source of SARS-CoV2 transmission. The study assessed the efficacy of hospital disinfection policy and contamination of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV2) RNA in COVID management Hospital. Inanimate surfaces from both patient areas (n = 70) and non-patient areas (n = 39) were sampled through surface swabbing and subjected to Reverse transcriptase PCR. Out of the 70 samples collected from the COVID hospital, SARS-CoV2 RNA positivity of 17.5% (7/40) and 6.7% (2/30) was seen in high risk and moderate risk area respectively. Samples from Non COVID related patient area such as CD ward and administrative block were assessed and the SARS CoV-2 RNA positivity was 0% and 10% respectively. Among the total 8 environmental surface samples positive for SARS-CoV2 RNA detected from the area surrounding the SARS-CoV2 infected patients, maximum positivity of 31.8% (7/22) was found among the environmental samples collected around the patients with < 20 Ct value in nasopharyngeal swab samples followed by 3.3% positivity (1/30) around patients with Ct value ranging from 20 to 25 whereas no SARS-CoV2 RNA (0/5) was detected around the patient with > 25 Ct value. Nearly 50% (2/4) of the surface samples came positive from the resident PPE and mobile of the treating doctors which largely elaborates the need for stringent doffing measurement and hand hygiene policy post doffing. The study emphasizes the necessity of frequent and aggressive disinfection policy to prevent nosocomial infection in such high risk areas within close vicinity of the patients.

Bacterial coinfections and secondary infections in COVID-19 patients from a tertiary care hospital of northern India: Time to adhere to culture-based practices.

OBJECTIVE: Bacterial co-pathogens are common in various viral respiratory tract infections, leading to increased disease severity and mortality. Still, they are understudied during large outbreaks and pandemics. This study was conducted to highlight the overall burden of these infections in COVID-19 patients admitted to our tertiary care hospital, along with their antibiotic susceptibility patterns. MATERIAL AND METHODS: During the six-month study period, clinical samples (blood samples, respiratory samples, and sterile body fluids, including cerebrospinal fluid [CSF]) of COVID-19 patients with suspected bacterial coinfections (at presentation) or secondary infections (after 48 hours of hospitalization) were received and processed for the same. RESULTS: Clinical samples of 814 COVID-19 patients were received for bacterial culture and susceptibility. Out of the total patient sample, 75% had already received empirical antibiotics before the samples were sent for analysis. Overall, 17.9% of cultures were positive for bacterial infections. Out of the total patients with bacterial infection, 74% (108/146) of patients had secondary bacterial infections (after 48 hours of hospitalization) and 26% (38/146) had bacterial coinfections (at the time of admission). Out of the 143 total isolates obtained, the majority (86%) were gram-negative organisms, of which Acinetobacter species was the commonest organism (35.6%), followed by Klebsiella pneumoniae (18.1%). The majority (50.7%) of the pathogenic organisms reported were multidrug resistant. CONCLUSION: The overall rate of secondary bacterial infections (SBIs) in our study was lower (7.9%) than reported by other studies. A rational approach would be to adhere to the practice of initiating culture-based guidance for antibiotics and to restrict unnecessary empirical antimicrobial therapy.

Psychological impact of COVID-19 on Mental Health Professionals working in different tertiary level healthcare setups of India

Background: The exponential increase of mental health issues associated with COVID-19 increased the pressure on mental health professionals. Hence, this study was conducted to assess the psychological consequences of Covid-19 on mental health professionals working in the country. Methods: This multi-centric study was conducted on mental health professionals of the country. The data collection was done online by using a survey form created through the Google Forms platform. Socio-demographic data sheet, Coronavirus Anxiety Scale and Depression, Anxiety and Stress Scale - 21 Items (DASS-21) were used for data collection. The data analysis was done by using Statistical Package of Social Sciences (SPSS) Windows version 25. Descriptive statistics, Independent Samples t Test and Pearson's Correlation (Two Tailed) were used for data analysis. Results: The mean age of the selected mental health professionals was noted to be 33.89 ± 7.79 years. In all the domains of the Depression, Anxiety and Stress Scale - 21 Items (DASS-21) females scored significantly higher than males (p =0.0001). The psychiatric nurses reported significantly higher level of anxiety and stress in the DASS-21 items. Significant positive correlations were noted between the corona virus anxiety and the three domains of the DASS-21. Conclusion: A considerable psychological impact of the Covid-19 pandemic was observed on the mental health professionals of our country. Increased anxiety about the corona virus was associated with increased likelihood of depression, stress and anxiety among the mental health professionals.

Multidimensional dynamic healthcare personnel (HCP)-centric model from a low-income and middle-income country to support and protect COVID-19 warriors: a large prospective cohort study.

OBJECTIVES: Healthcare personnel (HCP) are at an increased risk of acquiring COVID-19 infection especially in resource-restricted healthcare settings, and return to homes unfit for self-isolation, making them apprehensive about COVID-19 duty and transmission risk to their families. We aimed at implementing a novel multidimensional HCP-centric evidence-based, dynamic policy with the objectives to reduce risk of HCP infection, ensure welfare and safety of the HCP and to improve willingness to accept and return to duty. SETTING: Our tertiary care university hospital, with 12 600 HCP, was divided into high-risk, medium-risk and low-risk zones. In the high-risk and medium-risk zones, we organised training, logistic support, postduty HCP welfare and collected feedback, and sent them home after they tested negative for COVID-19. We supervised use of appropriate personal protective equipment (PPE) and kept communication paperless. PARTICIPANTS: We recruited willing low-risk HCP, aged <50 years, with no comorbidities to work in COVID-19 zones. Social distancing, hand hygiene and universal masking were advocated in the low-risk zone. RESULTS: Between 31 March and 20 July 2020, we clinically screened 5553 outpatients, of whom 3012 (54.2%) were COVID-19 suspects managed in the medium-risk zone. Among them, 346 (11.4%) tested COVID-19 positive (57.2% male) and were managed in the high-risk zone with 19 (5.4%) deaths. One (0.08%) of the 1224 HCP in high-risk zone, 6 (0.62%) of 960 HCP in medium-risk zone and 23 (0.18%) of the 12 600 HCP in the low-risk zone tested positive at the end of shift. All the 30 COVID-19-positive HCP have since recovered. This HCP-centric policy resulted in low transmission rates (<1%), ensured satisfaction with training (92%), PPE (90.8%), medical and psychosocial support (79%) and improved acceptance of COVID-19 duty with 54.7% volunteering for re-deployment. CONCLUSION: A multidimensional HCP-centric policy was effective in ensuring safety, satisfaction and welfare of HCP in a resource-poor setting and resulted in a willing workforce to fight the pandemic.

Demographic & clinical profile of patients with COVID-19 at a tertiary care hospital in north India.

BACKGROUND & OBJECTIVES: The COVID-19 pandemic emerged as a major public health emergency affecting the healthcare services all over the world. It is essential to analyze the epidemiological and clinical characteristics of patients with COVID-19 in different parts of our country. This study highlights clinical experience in managing patients with COVID-19 at a tertiary care centre in northern India. METHODS: Clinical characteristics and outcomes of consecutive adults patients admitted to a tertiary care hospital at Chandigarh, India, from April 1 to May 25, 2020 were studied. The diagnosis of SARS-CoV-2 infection was confirmed by real-time reverse transcriptase polymerase chain reaction (RT-PCR) on throat and/or nasopharyngeal swabs. All patients were managed according to the institute's consensus protocol and in accordance with Indian Council of Medical Research guidelines. RESULTS: During the study period, 114 patients with SARS-CoV-2 infection were admitted. The history of contact with COVID-19-affected individuals was available in 75 (65.8%) patients. The median age of the patients was 33.5 yr (13-79 yr), and there were 66 (58%) males. Of the total enrolled patients, 48 (42%) were symptomatic. The common presenting complaints were fever (37, 77%), cough (26, 54%) and shortness of breath (10, 20.8%). Nineteen (17%) patients had hypoxia (SpO2<94%) at presentation and 36 (31%) had tachypnoea (RR >24). Thirty four (29.8%) patients had an accompanying comorbid illness. Age more than 60 yr and presence of diabetes and hypertension were significantly associated with severe COVID-19 disease. Admission to the intensive care unit (ICU) was needed in 18 patients (52%), with three (2.6%) patients requiring assisted ventilation. Mortality of 2.6 per cent (3 patients) was observed. INTERPRETATION & CONCLUSIONS: Majority of the patients with COVID-19 infection presenting to our hospital were young and asymptomatic. Fever was noted only in three-fourth of the patients and respiratory symptoms in half of them. Patients with comorbidities were more vulnerable to complications. Triaged classification of patients and protocol-based treatment resulted in good outcomes and low case fatality.