A Review and Bibliometric Analysis on COVID-19 and its Effect

Epidemic handling is one of the foremost tasks for any country globally as it affects the population directly, creating a situation of chaos and disruption in humanity in every way possible. In the current world, where we find a new virus or bacteria daily in different parts of the world, it is very difficult for the medical industry and researchers worldwide to combat these situations as quickly as needed. However, with the emergence of AI and machine learning in the past 15-20 years, it is a blessing for these industries. It gives them a way to combat these deadly situations more quickly and effectively. COVID-19 is a highly communicable virus and affects the respiratory system to reach fatality and has created panic due to its worldwide spread recently. This study postulates how COVID-19 has spread across the globe, and its impact on various factors like economy, health, and employment, and how the studies have been carried out after the outbreak has been reported. We also present a bibliometric and systematic analysis of how much contribution from various segments has come to understand and handle this pandemic and how the researches have taken place in what direction. The study concludes by identifying the gaps in those research directions and finding the same future scope. © 2023 American Institute of Physics Inc.. All rights reserved.

Five-year trends in pediatric vision screening and access in the United States.

Analyses of the National Survey of Children's Health (2016-2020) demonstrated a 9.4% decrease in the proportion of children receiving eye screening from a specialist with an 85.7% increase in unmet vision care after the SARS-CoV-2 pandemic.

Comparative analysis of time series prediction model for forecasting COVID-19 trend

The outbreak of the COVID-19 pandemic occurred some time ago, making the world a pandemic. Based on this condition is important to predict early to prevent the COVID-19 disease if someday pandemic occurs. The aim of the study is to compare the analysis result of cumulative cases of COVID-19 using multiple linear regression (MLR), ridge regression (RR), and long short term memory (LSTM) models for cases study Java and Bali islands. We chose both islands as a case study because they have very dense populations. These three models are the most widely used time series-based prediction models and have relatively high accuracy values. The predictive variables used are the number of cumulative cases, the daily cases, and population density. The research data was taken from Kaggle and processed using google collabs. Data was taken from January 20, 2020, to August 8, 2020, and data training was carried out for 12 days. The results show the accuracy of LSTM is better than other models. it can be seen in the accuracy value (99.8%) of the model test result. The testing model uses R2, mean square error (MSE), and root mean square error (RMSE). © 2022 Institute of Advanced Engineering and Science. All rights reserved.

The effect of COVID-19 on prostate cancer testing in Australia.

AIM: The effects of the COVID-19 pandemic on healthcare in Australia have yet to be fully determined. There are well documented decreases in the rates of screening and diagnostic testing for many cancers in 2020, with commensurate stage migration of cancers when they are eventually detected. We aimed to determine whether there was a decrease in the rate of prostate cancer (PC) screening and testing in Australia in 2020. METHOD: Data was extracted from the Department of Human Services (DHS) website for Medicare Benefits Schedule (MBS) item numbers for tests pertinent to detection of Prostate Cancer. This data is de-identified and publicly available. Data was analysed at both a national, and a state level. RESULTS: For 2020 nationwide the percentage change for prostate cancer testing was minor with 97% as many PSA tests, 99% as many prostate MRIs, and 105% as many prostate biopsies as the average for the preceding years. The differences were not significant (PSA tests p = 0.059 and prostate biopsies p = 0.109). The predicted values are fairly similar to both the average values for the preceding 5 years and the actual number of tests done in 2020. With exception of PSA tests in Victoria the actual number of tests performed was within the 95% Prediction Interval (performed: 167,426; predicted 171,194-196,699; p = 0.015). CONCLUSION: The current pandemic has had a widespread reach across Australia, with varying impact across each state and territory. Contrary to the trends across the world, our data suggest that during 2020 in Australia most areas remained unaffected in terms of prostate cancer testing excluding Victoria, which had statistically significant decrease in the number of PSA tests correlating with the extended lockdown that occurred in the state.

SARS-CoV-2 pandemic in New York metropolitan area: the view from a major urgent care provider.

PURPOSE: Tracking severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing and positivity trends is crucial for understanding the trajectory of the pandemic. We describe demographic and clinical characteristics, testing, and positivity rates for SARS-CoV-2 among 2.8 million patients evaluated at an urgent care provider. METHODS: We conducted a retrospective study of patients receiving a diagnostic or serologic test for SARS-CoV-2 between March 1, 2020 and July 20, 2021 at 115 CityMD locations in the New York metropolitan area. Temporal trends in SARS-CoV-2 positivity by diagnostic and serologic tests stratified by age, sex, race/ethnicity, and borough of residence were assessed. RESULTS: During the study period, 6.1 million COVID diagnostic and serological tests were performed on 2.8 million individuals. Testing levels were higher among 20-29-year-old, non-Hispanic White, and female patients compared with other groups. About 35% were repeat testers. Reverse transcriptase polymerase chain reaction positivity was higher in non-Hispanic Black (7.9%), Hispanic (8.2%), and Native American (8.2%) compared to non-Hispanic White (5.7%) patients. Overall seropositivity was estimated to be 22.1% (95% confidence interval: 22.0-22.2) and was highest among 10-14 year olds (27.9%), and non-Hispanic Black (26.0%) and Hispanic (31.0%) testers. CONCLUSION: Urgent care centers can provide broad access to diagnostic testing and critical evaluation for ambulatory patients during pandemics, especially in population-dense, urban epicenters.  Urgent care center electronic medical records data can provide in-depth surveillance during pandemics complementary to citywide health department data sources.