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10.1002/pra2.426 http://scihub22266oqcxt.onion/10.1002/pra2.426 33173831!7645914!33173831     free     free     free Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Proc+Assoc+Inf+Sci+Technol 2020 ; 57 (1): e426 Nephropedia Template TP {{tp|p=33173831|t=2020. A case report: Challenges in COVID-19 modeling at a public health department |pdf=|usr=}}{{33173831}} gab.com Text A case report: Challenges in COVID-19 modeling at a public health department JO: Proc Assoc Inf Sci Technol http://www.kidney.de/pget.php?&tw=1&pmid=33173831 #FOAvip In response to the COVID-19 public health emergency, the Tulsa Health Department created local models. This was an iterative process, with the focus predicting all infections (including asymptomatic and mild cases that would not meet testing criteria,) and deaths for the Tulsa area. SEIR-type models were utilized. Developing infectious disease models is challenging due to data issues related to validity, and complex interrelated assumptions, and this was exacerbated with the COVID-19 crisis. Directly related to these data challenges were challenges with communicating without spreading misinformation, and being clear about the model limitations. Twit Text FOAVip A case report: Challenges in COVID-19 modeling at a public health department ????Proc Assoc Inf Sci Technol http://www.kidney.de/pget.php?&tw=1&pmid=33173831 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33173831 #FOAvip English Wikipedia <ref>{{Cite pmid|33173831}}</ref> A case report: Challenges in COVID-19 modeling at a public health department #MMPMID33173831 Rogers M Proc Assoc Inf Sci Technol 2020[]; 57 (1): e426 PMID33173831show ga In response to the COVID-19 public health emergency, the Tulsa Health Department created local models. This was an iterative process, with the focus predicting all infections (including asymptomatic and mild cases that would not meet testing criteria,) and deaths for the Tulsa area. SEIR-type models were utilized. Developing infectious disease models is challenging due to data issues related to validity, and complex interrelated assumptions, and this was exacerbated with the COVID-19 crisis. Directly related to these data challenges were challenges with communicating without spreading misinformation, and being clear about the model limitations. äA case report: Challenges in COVID-19 modeling at a public health depa(epmc).pdf DeepDyve Pubget Overpricing