Introduction.To address suboptimal influenza vaccination rates among health care workers, the Healthcare Infection Control Practices Advisory Committee and the Advisory Committee on Immunization Practices recently issued recommendations designed to increase the number of health care workers vaccinated against influenza. The purpose of the present study was to determine how widely these recommendations have been implemented and to identify important elements of successful influenza vaccine programs.Methods. The Infectious Diseases Society of America Emerging Infections Network surveyed 991 infectious diseases consultants. Infectious diseases consultants were asked about vaccination programs and vaccination rates at their respective institutions. Multinomial logistic regression models based on proportional odds were used to determine predictors of vaccination-rate categories. All program elements were significant univariable factors in predicting vaccination rates. Because the program elements were highly associated with one another, principal components analysis was used to find combinations of the covariates that would serve as optimal predictors of higher vaccination rates.Results. Most infectious diseases consultants indicated that the vaccination rate for all health care workers in their institution had a range of 41%-60%. Vaccination rates were significantly higher in institutions that required signed declination statements (). In the model based on principal components analysis for predicting P p .004 institutional vaccination rates, only the first principal component warranted retention ( ). In this component, P ! .001 the program elements weighted the most heavily were (1) offering the influenza vaccine free of charge, (2) providing adequate staff and resources, and (3) educating targeted groups of health care workers. Requiring signed declinations was not heavily weighted.Conclusion. Influenza vaccination rates remain suboptimal, and hospitals have not completely implemented the Healthcare Infection Control Practices Advisory Committee-Advisory Committee on Immunization Practices recommendations to maximize vaccination rates.
million for as early as Feb 22, a rate matched by the UK two weeks later. Germany also steeply increased its testing rate starting Mar 10. The total number of samples tested in Germany was 918,460, as of Mar 29 and the case doubling time was 9 days. S. Korea had tested 443, 273 (1% of the total population) cases as of Apr 3 and the case doubling time was 33 days. In contrast, test numbers in India were negligible, and doubling time was 4 days 1,2 . Importantly, testing capacity globally is currently limited. S. Korea, at number three after US and China in terms of testing kit production, can only support a capacity of 1,35,000 tests per day at present 3 . Additionally, ICMR guidelines such as "Laboratory test should only be offered when prescribed by a qualified physician" and 48 hours of turnaround time for test results further delay case identification and isolation 4 . Conclusions: If India was to mirror the testing rate of S. Korea, w15 million individuals may have to be tested within coming few weeks to be able to bend the curve of the COVID-19 cases. A balance of both the strategies -exponentially increasing testing and social distancing will be crucial. Sources: 1. https://ourworldindata.org/coronavirus" l "testing-for-covid-19, accessed on Apr 6, 2020 2. Statista, https://www.statista.com/statistics/1104809/days-for-covid19-cases-todouble-select-countries-worldwide/, accessed on Apr 6, 2020 3. News: http://www.arirang.com/News/News_View.asp?nSeq=254993 4. MoHFW website, https://www.mohfw.gov.in/pdf/NotificationofICMguidelinesfor COVID19testinginprivatelaboratoriesiIndia.pdf, accessed on Ap 7, 2020
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