An Analysis of the COVID-19 Situation in India in Terms of Testing, Treatment, Vaccine Acceptance and National Economic Performance

Patel, Ritu Bhaumik; Patel, Bhaumik Bipinchandra

doi:10.3389/ijph.2022.1604975

Cited by 8 publications

(5 citation statements)

References 24 publications

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“…The testing coverage of 33.7% observed in our survey was lower than in other highincome countries [39][40][41] although these reference data were reported considerably earlier than the ISSP survey. However, the Hungarian testing coverage was higher than that in Brazil [42] and India [43]. Unfortunately, Hungary ceased reporting testing frequency on 1 January 2021.…”

Section: Main Findingsmentioning

confidence: 95%

Effectiveness of and Inequalities in COVID-19 Epidemic Control Strategies in Hungary: A Nationwide Cross-Sectional Study

et al. 2023

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Introduction: Before the mass vaccination, epidemiological control measures were the only means of containing the COVID-19 epidemic. Their effectiveness determined the consequences of the COVID-19 epidemic. Our study evaluated the impact of sociodemographic, lifestyle, and clinical factors on patient-reported epidemiological control measures. Methods: A nationwide representative sample of 1008 randomly selected adults were interviewed in person between 15 March and 30 May 2021. The prevalence of test-confirmed SARS-CoV-2 infection was 12.1%, of testing was 33.7%, and of contact tracing among test-confirmed infected subjects was 67.9%. The vaccination coverage was 52.4%. Results: According to the multivariable logistic regression models, the occurrence of infection was not influenced by sociodemographic and lifestyle factors or by the presence of chronic disease. Testing was more frequent among middle-aged adults (aOR = 1.53, 95% CI 1.10–2.13) and employed adults (aOR = 2.06, 95% CI 1.42–3.00), and was more frequent among adults with a higher education (aORsecondary = 1.93, 95% CI 1.20–3.13; aORtertiary = 3.19, 95% CI 1.81–5.63). Contact tracing was more frequently implemented among middle-aged (aOR41-7y = 3.33, 95% CI 1.17–9.45) and employed (aOR = 4.58, 95% CI 1.38–15.22), and those with chronic diseases (aOR = 5.92, 95% CI 1.56–22.47). Positive correlation was observed between age groups and vaccination frequency (aOR41-70y = 2.94, 95% CI 2.09–4.15; aOR71+y = 14.52, 95% CI 7.33–28.77). Higher than primary education (aORsecondary = 1.69, 95% CI 1.08–2.63; aORtertiary = 4.36, 95% CI 2.46–7.73) and the presence of a chronic disease (aOR = 2.58, 95% CI 1.75–3.80) positively impacted vaccination. Regular smoking was inversely correlated with vaccination (aOR = 0.60; 95% CI 0.44–0.83). Conclusions: The survey indicated that testing, contact tracing, and vaccination were seriously influenced by socioeconomic position; less so by chronic disease prevalence and very minimally by lifestyle. The etiological role of socioeconomic inequalities in epidemic measure implementation likely generated socioeconomic inequality in COVID-19-related complication and death rates.

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Section: Main Findingsmentioning

confidence: 95%

Effectiveness of and Inequalities in COVID-19 Epidemic Control Strategies in Hungary: A Nationwide Cross-Sectional Study

et al. 2023

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“…The novel virus is rapidly spreading across China and has been transmitted to 213 other countries/territories across the globe. Researchers have reported that the virus is constantly evolving and spreading through asymptomatic carriers, further suggesting a high global health threat [20].…”

Section: Considering the Emergence Of Coronavirus Through Evolutionmentioning

confidence: 99%

Viruses Follow an Evolutionary Pathway

Chouhan,

Pandey,

Patel

2024

J Viro Res Rep

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“…Different countries have implemented various measures to mitigate the transmission of the disease, resulting in varying infection situations [17]. For instance, COVID-19 growth in China has already stabilized [18], whereas India is still experiencing an upward trend [19]. Hence, the initial task is to determine whether the virus is still undergoing rapid growth or has transitioned beyond the exponential growth phase, approaching the maximum number of cases.…”

Section: Parameter Estimationmentioning

confidence: 99%

Using logistic function to predict epidemic trend of COVID-19 in China

2023

TNS

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As the novel coronavirus continues to spread and mutate, there has been growing concern over public health. Multiple measures have been enacted to mitigate the transmission of the disease, resulting in varying infection scenarios across different countries. To achieve timely and effective control of the epidemic, we note that predicting the future course of an epidemic plays an important role. The logistic function, a continuous-time demographic model, may be a suitable mathematical tool for estimating the trend of the epidemic. This paper aims to evaluate the accuracy of the logistic map in estimating the future trend of the COVID-19. We collect the most recent COVID-19 epidemiological data prior to January 30, 2023, and subsequently integrate figures into the curve fitting tool in MATLAB to generate an epidemic curve. By comparing the actual numbers and the predicted figures, the accuracy of logistic map can be properly assessed.

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An Analysis of the COVID-19 Situation in India in Terms of Testing, Treatment, Vaccine Acceptance and National Economic Performance

Cited by 8 publications

References 24 publications

Effectiveness of and Inequalities in COVID-19 Epidemic Control Strategies in Hungary: A Nationwide Cross-Sectional Study

Effectiveness of and Inequalities in COVID-19 Epidemic Control Strategies in Hungary: A Nationwide Cross-Sectional Study

Viruses Follow an Evolutionary Pathway

Using logistic function to predict epidemic trend of COVID-19 in China

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