by Priya Singh, Aditya Anand, Shweta Rana, Amit Kumar, Sujeet Kumar, Prabudh Goel, Krushna Chandra Gouda, Harpreet Singh
Introduction: The COVID-19 pandemic has caused widespread morbidity, mortality, and socio-economic disruptions worldwide. Vaccination has proven to be a crucial strategy in controlling the spread of the virus and mitigating its impact.
Objective: The study focuses on assessing the effectiveness of COVID-19 vaccination in reducing the incidence of positive cases, hospitalizations, and ICU admissions. The presented study is focused on the COVID-19 fully vaccinated population by considering the data from the first positive case reported until 20 September 2021.
Methods: Using data from multiple countries, time series analysis is deployed to investigate the variations in the COVID-19 positivity rates, hospitalization rates, and ICU requirements after successful vaccination campaigns at the country scale.
Results: Analysis of the COVID-19 positivity rates revealed a substantial decline in countries with high pre-vaccination rates. Within 1–3 months of vaccination campaigns, these rates decreased by 20–44%. However, certain countries experienced an increase in positivity rates with the emergence of the new Delta variant, emphasizing the importance of ongoing monitoring and adaptable vaccination strategies. Similarly, the analysis of hospitalization rates demonstrated a steady decline as vaccination drive rates rose in various countries. Within 90 days of vaccination, several countries achieved hospitalization rates below 200 per million. However, a slight increase in hospitalizations was observed in some countries after 180 days of vaccination, underscoring the need for continued vigilance. Furthermore, the ICU patient rates decreased as vaccination rates increased across most countries. Within 120 days, several countries achieved an ICU patient rate of 20 per million, highlighting the effectiveness of vaccination in preventing severe cases requiring intensive care.
Conclusion: COVID-19 vaccination has proven to be very much effective in reducing the incidence of cases, hospitalizations, and ICU admissions. However, ongoing surveillance, variant monitoring, and adaptive vaccination strategies are crucial for maximizing the benefits of vaccination and effectively controlling the spread of the virus.
Source: https://doi.org/10.3389/fpubh.2023.1272961
by Iranna Gogeri, K. C. Gouda & T. Sumathy
Atmospheric carbon dioxide (CO2) is considered as most significant greenhouse gas (GHG) in terms of its global warming potential and human-caused emissions. In Indian context, CSIR Fourth Paradigm Institute has established continuous monitoring of GHG stations at Hosakote nearer to Bengaluru, India. In the present study, seasonal autoregressive integrated moving average (SARIMA) model has been developed based on evaluation criteria, considering its statistical performance and ability to capture the trend and patterns in CO2 concentration at station scale which will be useful in regional studies. The present work addresses to find an optimized SARIMA configuration for the accurate prediction of the CO2 concentration and to provide a projection of the same in the near future i.e., till 2027. The proposed model is being trained with data from October 2016 to December 2020 and the performance is validated by comparing simulated results with the observed data for recent 2 years (2021 and 2022). The statistical measures for the model’s performance has been evaluated by computing the important error parameters and correlation analysis.The study demonstrated that the SARIMA model is very much suitable for forecasting the CO2 concentrations, as it provided accurate predictions by showing good agreement with the observed values.The predicted data align well with observations and capture the seasonal variations, suggesting that model developed in this study has captured the patterns and trends in the CO2 concentration data effectively and can be considered a reliable tool for predicting future CO2 concentrations. Also, the projection made till 2027 using the optimised model and it is predicted that there is slight increase in the CO2 concentrations over the Bengaluru region in the near future time i.e., 2023–2027. These inferences will contribute for understanding the CO2 concentration trends in at station scale and provide valuable insights for policymakers, researchers, and stakeholders involved in climate change mitigation and environmental planning.
Source: https://doi.org/10.1007/s00477-023-02629-4
