Use my Search Websuite to scan PubMed, PMCentral, Journal Hosts and Journal Archives, FullText. Kick-your-searchterm to multiple Engines kick-your-query now !>

A dictionary by aggregated review articles of nephrology, medicine and the life sciences Your one-stop-run pathway from word to the immediate pdf of peer-reviewed on-topic knowledge.

10.1017/dmp.2021.151 http://scihub22266oqcxt.onion/10.1017/dmp.2021.151 34006346!8314068!34006346     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=34006346&cmd=llinks): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 215 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Disaster+Med+Public+Health+Prep 2021 ; 17 (ä): e19 Nephropedia Template TP {{tp|p=34006346|t=2021. Mathematical Modeling and COVID-19 Forecast in Texas, USA: A Prediction Model Analysis and the Probability of Disease Outbreak |pdf=|usr=}}{{34006346}} gab.com Text Mathematical Modeling and COVID-19 Forecast in Texas, USA: A Prediction Model Analysis and the Probability of Disease Outbreak JO: Disaster Med Public Health Prep http://www.kidney.de/pget.php?&tw=1&pmid=34006346 #FOAvip BACKGROUND: Response to the unprecedented coronavirus disease 2019 (COVID-19) outbreak needs to be augmented in Texas, United States, where the first 5 cases were reported on March 6, 2020, and were rapidly followed by an exponential rise within the next few weeks. This study aimed to determine the ongoing trend and upcoming infection status of COVID-19 in county levels of Texas. METHODS: Data were extracted from the following sources: published literature, surveillance, unpublished reports, and websites of Texas Department of State Health Services (DSHS), Natality report of Texas, and WHO Coronavirus Disease (COVID-19) Dashboard. The 4-compartment Susceptible-Exposed-Infectious-Removal (SEIR) mathematical model was used to estimate the current trend and future prediction of basic reproduction number and infection cases in Texas. Because the basic reproduction number is not sufficient to predict the outbreak, we applied the Continuous-Time Markov Chain (CTMC) model to calculate the probability of the COVID-19 outbreak. RESULTS: The estimated mean basic reproduction number of COVID-19 in Texas is predicted to be 2.65 by January 31, 2021. Our model indicated that the third wave might occur at the beginning of May 2021, which will peak at the end of June 2021. This prediction may come true if the current spreading situation/level persists, i.e., no clinically effective vaccine is available, or this vaccination program fails for some reason in this area. CONCLUSION: Our analysis indicates an alarming ongoing and upcoming infection rate of COVID-19 at county levels in Texas, thereby emphasizing the promotion of more coordinated and disciplined actions by policy-makers and the population to contain its devastating impact. Twit Text FOAVip Mathematical Modeling and COVID-19 Forecast in Texas, USA: A Prediction Model Analysis and the Probability of Disease Outbreak ????Disaster Med Public Health Prep http://www.kidney.de/pget.php?&tw=1&pmid=34006346 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34006346 #FOAvip English Wikipedia <ref>{{Cite pmid|34006346}}</ref> Mathematical Modeling and COVID-19 Forecast in Texas, USA: A Prediction Model Analysis and the Probability of Disease Outbreak #MMPMID34006346 Hassan MN; Mahmud MS; Nipa KF; Kamrujjaman M Disaster Med Public Health Prep 2021[May]; 17 (ä): e19 PMID34006346show ga BACKGROUND: Response to the unprecedented coronavirus disease 2019 (COVID-19) outbreak needs to be augmented in Texas, United States, where the first 5 cases were reported on March 6, 2020, and were rapidly followed by an exponential rise within the next few weeks. This study aimed to determine the ongoing trend and upcoming infection status of COVID-19 in county levels of Texas. METHODS: Data were extracted from the following sources: published literature, surveillance, unpublished reports, and websites of Texas Department of State Health Services (DSHS), Natality report of Texas, and WHO Coronavirus Disease (COVID-19) Dashboard. The 4-compartment Susceptible-Exposed-Infectious-Removal (SEIR) mathematical model was used to estimate the current trend and future prediction of basic reproduction number and infection cases in Texas. Because the basic reproduction number is not sufficient to predict the outbreak, we applied the Continuous-Time Markov Chain (CTMC) model to calculate the probability of the COVID-19 outbreak. RESULTS: The estimated mean basic reproduction number of COVID-19 in Texas is predicted to be 2.65 by January 31, 2021. Our model indicated that the third wave might occur at the beginning of May 2021, which will peak at the end of June 2021. This prediction may come true if the current spreading situation/level persists, i.e., no clinically effective vaccine is available, or this vaccination program fails for some reason in this area. CONCLUSION: Our analysis indicates an alarming ongoing and upcoming infection rate of COVID-19 at county levels in Texas, thereby emphasizing the promotion of more coordinated and disciplined actions by policy-makers and the population to contain its devastating impact. äMathematical Modeling and COVID-19 Forecast in Texas, USA: A Predictio(epmc).pdf DeepDyve Pubget Overpricing