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Several digital contact tracing smartphone applications have been developed worldwide in the effort to combat COVID-19 that warn users of potential exposure to infectious patients and generate big data that helps in early identification of hotspots, complementing the manual tracing operations. In most democracies, concerns over a breach in data privacy have resulted in severe opposition toward their mandatory adoption. This paper examines India as a noticeable exception, where the compulsory installation of such a government-backed application, the "Aarogya Setu" has been deemed mandatory in certain situations. We argue that the mandatory app requirement constitutes a legitimate public health intervention during a public health emergency. [ABSTRACT FROM AUTHOR]

In 2020 editor-in-chief (Andrew Malekoff) issued a special call for papers for group work stories on pandemic 2020. Among the 28 stories accepted for the series there were 16 from India, 9 from the United States, 2 from Canada and 1 from Israel. General submissions from the U.S., Canada and Israel were typical for the journal. Atypical are submissions from India. Rather than publish the stories in one special issue of the Journal, he decided to spread them out over several issues through 2022. In the course of organizing the special series (with a December 2021 deadline) he continued communication with a few of the authors from India, with particular interest and concern in the deteriorating situation as 2021 unfolded. Although the present commentary is not about group work per se, it is an update by Ajay Saini, Nancy and Andrew Malekoff on the current state of affairs in India, with some contrast to the situation in the U.S., that offers continuing context for the stories in the series. [ABSTRACT FROM AUTHOR]

Background: COVID-19 has become a global pandemic, prompting lockdowns in practically every country. To prevent the spread of the disease, India has enforced a rigorous nationwide lockdown that commenced in March 2020. The lockdown imposed amid the pandemic ensured that most commercial activities and vehicle transportation ceased, resulting in a significant reduction in air pollution levels. Material and Methods: The value of air pollutants PM10, PM2.5, NO2, and SO2 from January to May 2020 was obtained from the Indian Central Pollution Control Board. Before lockdown and during lockdown, relative fluctuations in ambient concentrations of four air contaminants were investigated. The Box-Jenkins approach was used to estimate future air pollution data points using time series data analysis. Results: The PM10 level reduced by 61%, 30%, 68%, 37%, and 43% in the selected cities, respectively. Comparison of other pollutant concentrations before and after the lockdown also found a reduction in ambient pollutant concentrations, resulting in improved air quality. Inference of predicted model values to observed values revealed a significant increase in the concentrations of all pollutants. The percentage increases in AQImean from predicted to observed values were 206% in Ghaziabad, 148% in Delhi, 59% in Hyderabad, and 160% in Cochin. Conclusion: The strict lockdown has resulted in a significant drop in air pollutant levels. Upgrading present technologies could help keep pollution to a minimum of 37% under control. The findings would prompt the government to consider how to strictly reduce vehicle and industrial pollution to improve air quality and maintain improved public health. [ABSTRACT FROM AUTHOR]

Introduction: Maharashtra, India, remained a hotspot during the COVID-19 pandemic. After the initial complete lockdown, the state slowly relaxed restrictions. We aim to estimate the lockdown's impact on COVID-19 cases and associated healthcare costs. Methods: Using daily case data for 84 days (9 March–31 May 2020), we modeled the epidemic's trajectory and predicted new cases for different phases of lockdown. We fitted log-linear models to estimate the growth rate, basic (R0), daily reproduction number (Re), and case doubling time. Based on pre-restriction and Phase 1 R0, we predicted new cases for the rest of the restriction phases, and we compared them with the actual number of cases during each phase. Furthermore, using the published and gray literature, we estimated the costs and savings of implementing these restrictions for the projected period, and we performed a sensitivity analysis. Results: The estimated median R0 during the different phases was 1.14 (95% CI: 0.85, 1.45) for pre-lockdown, 1.67 (95% CI: 1.50, 1.82) for phase 1 (strict mobility restrictions), 1.24 (95% CI: 1.12, 1.35) for phase 2 (extension of phase 1 with no restrictions on agricultural and essential services), 1.12 (95% CI: 1.01, 1.23) for phase 3 (extension of phase 2 with mobility relaxations in areas with few infections), and 1.05 (95% CI: 0.99, 1.123) for phase 4 (implementation of localized lockdowns in high-case-load areas with fewer restrictions on other areas), respectively. The corresponding doubling time rate for cases (in days) was 17.78 (95% CI: 5.61, −15.19), 3.87 (95% CI: 3.15, 5.00), 10.37 (95% CI: 7.10, 19.30), 20.31 (95% CI: 10.70, 212.50), and 45.56 (95% CI: 20.50, –204.52). For the projected period, the cases could have reached 631,819 without the lockdown, as the actual reported number of cases was 64,975. From a healthcare perspective, the estimated total value of averted cases was INR 194.73 billion (USD 2.60 billion), resulting in net cost savings of 84.05%. The Incremental Cost-Effectiveness Ratio (ICER) per Quality Adjusted Life Year (QALY) for implementing the lockdown, rather than observing the natural course of the pandemic, was INR 33,812.15 (USD 450.83). Conclusion: Maharashtra's early public health response delayed the pandemic and averted new cases and deaths during the first wave of the pandemic. However, we recommend that such restrictions be carefully used while considering the local socio-economic realities in countries like India. [ABSTRACT FROM AUTHOR]

Mucormycosis emerged as a major public health challenge during the second wave of the COVID-19 pandemic in India in mid-2021. The disease, colloquially known as the Black fungus, was declared epidemic by the government. This review describes the epidemiological pattern and the determinants of mucormycosis. The review also proposes evidence based public health strategies for the prevention and control of mucormycosis. The rationale use of steroids in clinical management, formulation of evidence-based standard treatment guidelines and adherence to those guidelines by physicians, the strengthening of primary healthcare services to facilitate early care; compliance with infection prevention and control measures at all the health facilities; and early diagnosis and case management are the key strategies to prevent future emergence of mucormycosis. The article concludes that it is not enough that we tackle a health challenge at hand, in crisis mode. It is equally important that we derive learnings and take measures prevent any future. Effective control of mucormycosis and prevention of future outbreaks of disease is possible through coordinated actions of health policy makers, public health experts and clinicians. The entire episode is also a reminder for strengthening India's health systems at all levels – primary, secondary and tertiary – as well as in both public and private sector. [ABSTRACT FROM AUTHOR]

Objective: Coronavirus disease (COVID-19) has emerged as a global pandemic for public health due to the large scale outbreak, therefore there is an urgent need to detect the infected cases quickly and isolate them in order to suppress the further spread of the disease. This study tries to identify a suitable pool testing method and algorithm for COVID-19. Methods: This study tries to derive a general equation for the number of tests required for a pooled sample to detect every infected individual in the specific pool. The gain in pool testing over the normal procedure is quantified by the percentage of tests required compared to individual testing. Results: The percentage of tests required by the pool testing strategy varies according to the different splitting procedures, the size of the pooled sample, and the probability of an individual being infected in the population. If the probability of infection is 0.05, then for a pool size of 32, only 14 tests are sufficient to detect every infected individual. Conclusion: The number of tests required to detect infected individuals by using the pooling method is much lower than individual testing. This may help us with increasing our testing capacity for COVID-19 by testing a large number of individuals in less time with limited resources. [ABSTRACT FROM AUTHOR]

Coronavirus disease 2019 (COVID-19) is caused by SARS-CoV-2, which is known for the multiple mutations and forms that have rapidly spread across the world. With the imminent challenges faced by low- and middle-income countries in curbing the public health fallbacks due to limited resources, mucormycosis emerged as a fungal infection associated with high mortality. In this rapid review, we explored MEDLINE, Cochrane, Web of Science, WHO Global Database, and the search engine—Google Scholar for articles listed until July 2021 and presented a narrative synthesis of findings from 39 articles. The epidemiology, causative factors, incidence parameters, pharmacological treatment, and recommendations for low- and middle-income countries are enlisted. This study concludes that a majority of the globally reported COVID-19 associated mucormycosis cases stemmed from India. Individuals receiving systemic corticosteroids or who have a history of diabetes mellitus are more prone to contracting the disease. Public health authorities in LMIC are recommended to strengthen antifungal therapies for COVID-19 associated mucormycosis and to strategize reduction in diabetes mellitus prevalence. [ABSTRACT FROM AUTHOR]

The World Health Organization (WHO) declared the Coronavirus Disease (COVID‐19) a pandemic due to the huge upsurge in the number of reported cases worldwide. The COVID‐19 pandemic in India has become a public health threat, and if we go by the number of confirmed cases then the situation seems to be a matter of grave concern. According to real‐time data, the numbers of confirmed cases are growing exponentially. No doubt, substantial public health interventions both at the national and state levels are implemented immediately by the Government of India; there is a need for improved preparedness plans and mitigation strategies along with accurate forecasting. The present study aims to forecast the COVID‐19 outbreak infected cases in India. The data have been obtained from https://www.covid19india.org, https://www.worldometers.info/coronavirus, and ICMR reported publicly available information about COVID‐19 confirmation cases. We have used the double exponential smoothing method for forecasting the trends in terms of confirmed, active, recovered and death cases from COVID‐19 for emergency preparedness and future predictions. Findings reveal that the estimated value of point forecast is just 8.22% of the total number of confirmed cases reported on a daily basis across the country. It was observed that the deaths were lower for the states and union territories with a higher detection rate. It is suggested that by keeping in view the limited healthcare resources in the country, accurate forecasting, early detection, and avoidance of acute care for the majority of infected cases is indispensable. [ABSTRACT FROM AUTHOR]

aimed to make a comparative analysis of the public health containment measures between China and India, explore the causes of the serious COVID-19 epidemic in India, and eventually to improve global infectious disease control. Methods: We extracted publicly available data from official websites, summarized the containment measures implemented in China and India, and assessed their effectiveness. Results: China has responded to the COVID-19 outbreak with strict public health containment measures, including lockdown of Wuhan city, active case tracing, and large-scale testing, ultimately preventing a large increase in daily new cases and maintaining a low mortality rate per million population (as of May 5, 2021, daily new cases were 11 and mortality rate per million population was 3.37). India, although imposing a national lockdown to control the pandemic, has not implemented strict testing, tracking, and quarantine measures due to the overburdened healthcare system. Combined with massive lockdown, it has accelerated human mobility and exacerbated the epidemic, resulting in a rapid increase in daily new cases and a high mortality rate per million population (as of May 5, 2021, daily new cases were 412,431 and mortality rate per million population was 166.79). Conclusion: China and India implemented public health containment measures to contain the spread of the COVID-19 pandemic based on their national situations. Meanwhile, daily new cases and mortality of COVID-19 also were affected by environmental and socioeconomic. Countries make a comprehensive strategy not only in terms of the biological, pharmaceutical, health, and sanitation sectors but also based on sustainability science and environmental science. [ABSTRACT FROM AUTHOR]

Background- Coronavirus disease (COVID-19), which is caused by deadly novel corona virus has devastated the world causing a morbidity rate of more than 64 million and mortality rate of 1.5 million. India, being a Lower Middle-Income Country (LMIC) with a GNI per capita of nearly $2000, has proactively instituted various containment strategies. India has witnessed the effectiveness of primary prevention strategies in fighting various health problems in the years gone. The most worrying factor was about community spread of the pandemic, which would cause the spread of illness uncontrollable. Economic analysts had forecasted if appropriate strategy on containment of coronavirus is not initiated, the country would regress back to 20 years, in terms of economy and healthcare. This scoping review throws light into the efficacious preventive strategies adopted by India to fight COVID-19 pandemic and attempting to reduce mortality and morbidity rate, to flatten the illness curve. Methods- We used a wide range of scientific database and news reports to conduct an extensive review on India's fight against COVID-19. Articles which has been published from January to November 2020 were reviewed and pooled the data to write this review. Conclusion- Containment strategies are the key for prevention of any contagious illness. COVID-19 being highly contagious, and infecting millions of populations, is successfully being controlled in India to reduce the cases. The Case Fatality Ratio (CFR) of COVID-19 is very low in India, compared to other countries. [ABSTRACT FROM AUTHOR]