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10.1016/j.cegh.2020.06.012 http://scihub22266oqcxt.onion/10.1016/j.cegh.2020.06.012 C7324346!7324346!32838059     free     free     free Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Clin+Epidemiol+Glob+Health 2021 ; 9 (ä): 57-61 Nephropedia Template TP {{tp|p=32838059|t=2021. Modelling of reproduction number for COVID-19 in India and high incidence states |pdf=|usr=}}{{32838059}} gab.com Text Modelling of reproduction number for COVID-19 in India and high incidence states JO: Clin Epidemiol Glob Health http://www.kidney.de/pget.php?&tw=1&pmid=32838059 #FOAvip Background: Since the onset of the COVID-19 in China, forecasting and projections of the epidemic based on epidemiological models have been in the centre stage. Researchers have used various models to predict the maximum extent of the number of cases and the time of peak. This yielded varying numbers. This paper aims to estimate the effective reproduction number (R) for COVID-19 over time using incident number of cases that are reported by the government. Methods: Exponential Growth method to estimate basic reproduction rate R0, and Time dependent method to calculate the effective reproduction number (dynamic) were used. ?R0? package in R software was used to estimate these statistics. Results: The basic reproduction number (R0) for India was estimated at 1.379 (95% CI: 1.375, 1.384). This was 1.450 (1.441, 1.460) for Maharashtra, 1.444 (1.430, 1.460) for Gujarat, 1.297 (1.284, 1.310) for Delhi and 1.405 (1.389, 1.421) for Tamil Nadu. In India, the R at the first week from March 2?8, 2020 was 3.2. It remained around 2 units for three weeks, from March 9?29, 2020. After March 2020, it started declining and reached around 1.3 in the following week suggesting a stabilisation of the transmissibility rate. Conclusion: The study estimated a baseline R0 of 1.379 for India. It also showed that the R was getting stabilised from first week of April (with an average R of 1.29), despite the increase in March. This suggested that in due course there will be a reversal of epidemic. However, these analyses should be revised periodically. Twit Text FOAVip Modelling of reproduction number for COVID-19 in India and high incidence states ????Clin Epidemiol Glob Health http://www.kidney.de/pget.php?&tw=1&pmid=32838059 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32838059 #FOAvip English Wikipedia <ref>{{Cite pmid|32838059}}</ref> Modelling of reproduction number for COVID-19 in India and high incidence states #MMPMID32838059 Marimuthu S; Joy M; Malavika B; Nadaraj A; Asirvatham ES; Jeyaseelan L Clin Epidemiol Glob Health 2021[Jan]; 9 (ä): 57-61 PMID32838059show ga Background: Since the onset of the COVID-19 in China, forecasting and projections of the epidemic based on epidemiological models have been in the centre stage. Researchers have used various models to predict the maximum extent of the number of cases and the time of peak. This yielded varying numbers. This paper aims to estimate the effective reproduction number (R) for COVID-19 over time using incident number of cases that are reported by the government. Methods: Exponential Growth method to estimate basic reproduction rate R0, and Time dependent method to calculate the effective reproduction number (dynamic) were used. ?R0? package in R software was used to estimate these statistics. Results: The basic reproduction number (R0) for India was estimated at 1.379 (95% CI: 1.375, 1.384). This was 1.450 (1.441, 1.460) for Maharashtra, 1.444 (1.430, 1.460) for Gujarat, 1.297 (1.284, 1.310) for Delhi and 1.405 (1.389, 1.421) for Tamil Nadu. In India, the R at the first week from March 2?8, 2020 was 3.2. It remained around 2 units for three weeks, from March 9?29, 2020. After March 2020, it started declining and reached around 1.3 in the following week suggesting a stabilisation of the transmissibility rate. Conclusion: The study estimated a baseline R0 of 1.379 for India. It also showed that the R was getting stabilised from first week of April (with an average R of 1.29), despite the increase in March. This suggested that in due course there will be a reversal of epidemic. However, these analyses should be revised periodically. äModelling of reproduction number for COVID-19 in India and high incide(epmc).pdf DeepDyve Pubget Overpricing