ABSTRACT
Background: Seroprevalence of COVID-19 antibody production in a person can be dependent on many physiological and demographic aspects such as previous infection, age, sex, body mass index, and also status of vaccination. It is of immense value to know about demographic aspect of COVID-19 antibody production so as to know about vulnerable population and suggest preventive measures. Aims and Objectives: The present study was aimed to determine effect of demographic variables COVID-19 antibody production in population of urban area. Materials and Methods: In this study, a total of 2454 subjects were screened for COVID-19 neutralizing antibody by ELISA technique. Subjects more than 18-year-old were selected for the study. We used cluster sampling method for data collection. A pre-structured questionnaire was administered after informed consent and 5 mL venous blood was collected in plain bulb for testing. Results: The prevalence of neutralizing antibody was found to be 93.9%. Female had 95% positive antibodies against males (92.34%). Maximum positive antibody status was seen in age group of 20–40 (55.6%). About 77.9% subjects following mixed diet were having positive COVID-19 antibody test as compared to subjects following pure vegetarian (10.2%). About 83.2% subjects who received vaccine showed positive antibody test. The lowest positivity is seen in underweight subjects (8%) followed by obese subjects (12.7%). Maximum inhibition % was seen in subjects using Vitamin C Zinc tablets (92.1%). The lowest inhibition was seen in subjects using Unani Kadha. A one-way ANOVA revealed that there was not a statistically significant difference in prophylactic measures for prevention of COVID-19 infection other than vaccination and COVID-19 neutralizing antibody inhibition %. ([F-1.363], P=0.244). Conclusion: COVID-19 neutralizing antibody prevalence was found to be much higher in the population (96%), which was mostly associated with younger age, gender, diet, and vaccination status of the population. Extensive studies are required to establish any association between prophylactic methods other than vaccination and COVID-19 antibody response. [ FROM AUTHOR] Copyright of Asian Journal of Medical Sciences is the property of Manipal Colleges of Medical Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
ABSTRACT
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.
ABSTRACT
BACKGROUND & OBJECTIVES: To handle the current COVID-19 pandemic in India, multiple strategies have been applied and implemented to slow down the virus transmission. These included clinical management of active cases, rapid development of treatment strategies, vaccines computational modelling and statistical tools to name a few. This article presents a mathematical model for a time series prediction and analyzes the impact of the lockdown. METHODS: Several existing mathematical models were not able to account for asymptomatic patients, with limited testing capability at onset and no data on serosurveillance. In this study, a new model was used which was developed on lines of susceptible-asymptomatic-infected-recovered (SAIR) to assess the impact of the lockdown and make predictions on its future course. Four parameters were used, namely ß, γ, η and ε. ß measures the likelihood of the susceptible person getting infected, and γ denotes recovery rate of patients. The ratio ß/γ is denoted by R0 (basic reproduction number). RESULTS: The disease spread was reduced due to initial lockdown. An increase in γ reflects healthcare and hospital services, medications and protocols put in place. In Delhi, the predictions from the model were corroborated with July and September serosurveys, which showed antibodies in 23.5 and 33 per cent population, respectively. INTERPRETATION & CONCLUSIONS: The SAIR model has helped understand the disease better. If the model is correct, we may have reached herd immunity with about 380 million people already infected. However, personal protective measures remain crucial. If there was no lockdown, the number of active infections would have peaked at close to 14.7 million, resulted in more than 2.6 million deaths, and the peak would have arrived by June 2020. The number of deaths with the current trends may be less than 0.2 million.