Scientometric Research Mapping of OMICRON for Scientific Production: A Global Perception Analysis

Background: South Africa reported a new variant of SARS-CoV-2, named 'Omicron,' to the World Health Or-ganization on November 24, 2021. Scientometric analysis quantify all currently available written communica-tion, the authors of that communication, and their citation analysis. The study's goal was to use the Scopus and Web of Science databases to look at the research metrics of Omicron publications published between Jan-uary 1965 and March 2020. Methods:All scientific research outputs with the word 'Omicron' in the title were retrieved from the Web of Science (January 1965 to March 2022) and Scopus (January 1896 to March 2022) databases on April 10, 2022. The data was analyzed based on year-wise publications; leading authors; predominant journals in publishing, highly cited articles with citations; type of publications; subject classification, frequently used keywords, geo-graphical distribution of publication, language, and more contributed institutions. Results: There were 1229 research outputs for WoS and 655 from Scopus. The number of publications for WoS increased from 22 in 1965 to 265 in 2022, while Scopus increased from 1 in 1896 to 356 in 2022. Both the databases identified the author Yuen KY as the highest contributor; Journal of Virology and Nature as the predominant journals; the Lancet as highly cited journal; majority as original articles; frequently used key-words as 'SARS-CoV-2'; the United States of America as the most productive country; majority publication in English. The publications were mainly on the subjects Chemistry and Medicine by WoS and Scopus, respec-tively. The most productive institute was the ‘University of California Systems’ by WoS and the ‘University of Hong Kong’ by Scopus. Conclusion: The term 'Omicron' first appeared in the domain of Chemistry in the late 18th century. The growth pattern of publication was not consistent. The above research metrics will be helpful to researchers in the coming days.

Exploration of population ecological factors related to the spatial heterogeneity of dengue fever cases diagnosed through a national network of laboratories in India, 2017

Background & objectives: Dengue virus (DENV) transmission is known to be influenced by the environmental conditions. During 2017, the Viral Research and Diagnostic Laboratories (VRDLs) tested 78,744 suspected dengue fever (DF) patients, of whom, 21,260 were laboratory confirmed. The objectives of the study were to evaluate the hypothesis that spatial heterogeneity existed for DF patients and to identify significant determinants of DENV transmission in various districts across the Indian States during 2017. Methods: Laboratory confirmed DF cases were analysed from 402 districts spread across the Indian States. The determinants for DF transmission included in the model were population density, proportion of population living in rural areas, proportion o f forest cover area to the total geographical area, proportion of persons not able to read and write and who were aged greater than seven years; the climatic variables considered were minimum, maximum and average temperature, precipitation and cumulative rainfall. The spatial heterogeneity was assessed using spatial regression analysis. Results: DF cases showed strong spatial dependency, with Moran's I=4.44 (P <0.001). The robust measure for spatial lag (6.55; P=0.01) was found to be the best model fit for the data set. Minimum temperature and cumulative rainfall were significant predictors. Interpretation & conclusions: A significant increase in the number of dengue cases has occurred when the minimum temperature was 23.0-25.8癈 and the cumulative rainfall 118.14-611.64 mm across the Indian districts. Further in-depth investigations incorporating more number of demographic, ecological and socio-economic factors would be needed for robust conclusions.

Magnitude of recall bias in the estimation of immunization coverage and its determinants.

OBJECTIVE: To study the magnitude of recall bias in the estimation of immunization coverage and to identify its determinants. DESIGN: A follow-up study of cohort of children for one year; followed by a cross-sectional recall survey. SUBJECTS: All live births in two contiguous PHC areas in Villupuram district, Tamil Nadu. METHODS: The prospective data collected from mothers of 774 children was considered as 'Gold Standard' and the retrospective recall data from them was compared with it. This was carried out for individual immunization schedules, namely, DPT, OPV, BCG and measles and for the combined immunization status. Measures such as sensitivity, specificity, positive and negative predictive values were computed. Logistic Regression technique was employed for evaluating the determinants of agreement. RESULTS: Less than 50% of mothers has immunization cards with them and more than 70% of the cards did not have complete information. The sensitivity of the recall method was 41.3% and the specificity was 79.5% when the complete immunization status was considered. For individual immunization schedules, the sensitivity ranged from 95% for BCG to 53% for measles vaccination and the specificity ranged from 30% for BCG to 68% for measles vaccination. Mother's age emerged out as a significant determinant in the agreement of two methods. Maintenance of immunization cards were very poor. CONCLUSIONS: Method of obtaining immunization status through recall survey is not sensitive. Proper maintenance of immunization cards and ensuring the availability of them with mothers for inspection are recommended for obtaining accurate estimation of vaccine coverages.

Lot quality assurance sampling for monitoring immunization coverage in Madras City.

OBJECTIVE: To explore the usefulness of Lot Quality Assurance Sampling (LQAS) to identify divisions in a city that had immunization coverage levels of 80% for any of the four EPI vaccines. METHODS: Only 43 divisions were considered for the study, the stratification factor being the death rate. The hypothesis that 80% coverage is 'unacceptable' was stipulated. Critical value (the number of unimmunized children) was chosen as 3. A simple random sample of 36 children in the age-group 12-23 months was taken from each selected division. Since sampling frames of children were not available, a simple random sample of 36 households was selected. Immunization status of each child was assessed by interviewing the child's mother/guardian. If the number of unimmunized children exceeded 3, then the division was regarded having coverage level 80% and rejected. RESULTS: The coverage was classified as unacceptable(i. e., below 80%) in 19 divisions for Polio and DPT vaccines, in 26 divisions for Measles vaccine and in 4 divisions for BCG vaccine. The average time spent for undertaking the LQAS survey was 6 man-days per division. CONCLUSION: This study demonstrated the utility of the LQAS technique in identifying 'unsatisfactory' pockets in Madras City, when the overall coverage was satisfactory. The technique will have greater application with an increase in the number of large units (cities/districts) having an overall coverage of 90% or more.