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10.3346/jkms.2020.35.e227 http://scihub22266oqcxt.onion/10.3346/jkms.2020.35.e227 32567261!7308140!32567261     free     free     free Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       J+Korean+Med+Sci 2020 ; 35 (24): e227 Nephropedia Template TP {{tp|p=32567261|t=2020. Epidemiological Characteristics and Forecast of COVID-19 Outbreak in the Republic of Kazakhstan |pdf=|usr=}}{{32567261}} gab.com Text Epidemiological Characteristics and Forecast of COVID-19 Outbreak in the Republic of Kazakhstan JO: J Korean Med Sci http://www.kidney.de/pget.php?&tw=1&pmid=32567261 #FOAvip BACKGROUND: Coronavirus disease 2019 (COVID-19) pandemic entered Kazakhstan on 13 March 2020 and quickly spread over its territory. This study aimed at reporting on the rates of COVID-19 in the country and at making prognoses on cases, deaths, and recoveries through predictive modeling. Also, we attempted to forecast the needs in professional workforce depending on implementation of quarantine measures. METHODS: We calculated both national and local incidence, mortality and case-fatality rates, and made forecast modeling via classic susceptible-exposed-infected-removed (SEIR) model. The Health Workforce Estimator tool was utilized for forecast modeling of health care workers capacity. RESULTS: The vast majority of symptomatic patients had mild disease manifestations and the proportion of moderate disease was around 10%. According to the SEIR model, there will be 156 thousand hospitalized patients due to severe illness and 15.47 thousand deaths at the peak of an outbreak if no measures are implemented. Besides, this will substantially increase the need in professional medical workforce. Still, 50% compliance with quarantine may possibly reduce the deaths up to 3.75 thousand cases and the number of hospitalized up to 9.31 thousand cases at the peak. CONCLUSION: The outcomes of our study could be of interest for policymakers as they help to forecast the trends of COVID-19 outbreak, the demands for professional workforce, and to estimate the consequences of quarantine measures. Twit Text FOAVip Epidemiological Characteristics and Forecast of COVID-19 Outbreak in the Republic of Kazakhstan ????J Korean Med Sci http://www.kidney.de/pget.php?&tw=1&pmid=32567261 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32567261 #FOAvip English Wikipedia <ref>{{Cite pmid|32567261}}</ref> Epidemiological Characteristics and Forecast of COVID-19 Outbreak in the Republic of Kazakhstan #MMPMID32567261 Semenova Y; Glushkova N; Pivina L; Khismetova Z; Zhunussov Y; Sandybaev M; Ivankov A J Korean Med Sci 2020[Jun]; 35 (24): e227 PMID32567261show ga BACKGROUND: Coronavirus disease 2019 (COVID-19) pandemic entered Kazakhstan on 13 March 2020 and quickly spread over its territory. This study aimed at reporting on the rates of COVID-19 in the country and at making prognoses on cases, deaths, and recoveries through predictive modeling. Also, we attempted to forecast the needs in professional workforce depending on implementation of quarantine measures. METHODS: We calculated both national and local incidence, mortality and case-fatality rates, and made forecast modeling via classic susceptible-exposed-infected-removed (SEIR) model. The Health Workforce Estimator tool was utilized for forecast modeling of health care workers capacity. RESULTS: The vast majority of symptomatic patients had mild disease manifestations and the proportion of moderate disease was around 10%. According to the SEIR model, there will be 156 thousand hospitalized patients due to severe illness and 15.47 thousand deaths at the peak of an outbreak if no measures are implemented. Besides, this will substantially increase the need in professional medical workforce. Still, 50% compliance with quarantine may possibly reduce the deaths up to 3.75 thousand cases and the number of hospitalized up to 9.31 thousand cases at the peak. CONCLUSION: The outcomes of our study could be of interest for policymakers as they help to forecast the trends of COVID-19 outbreak, the demands for professional workforce, and to estimate the consequences of quarantine measures. |Adolescent[MESH] |Adult[MESH] |Aged[MESH] |Aged, 80 and over[MESH] |Betacoronavirus[MESH] |COVID-19[MESH] |Child[MESH] |Child, Preschool[MESH] |Coronavirus Infections/*epidemiology/*mortality[MESH] |Female[MESH] |Forecasting[MESH] |Hospitalization/*statistics & numerical data/*trends[MESH] |Humans[MESH] |Incidence[MESH] |Infant[MESH] |Infant, Newborn[MESH] |Kazakhstan/epidemiology[MESH] |Male[MESH] |Middle Aged[MESH] |Models, Statistical[MESH] |Pandemics[MESH] |Pneumonia, Viral/*epidemiology/*mortality[MESH] |Prognosis[MESH] |SARS-CoV-2[MESH] |Severity of Illness Index[MESH]Epidemiological Characteristics and Forecast of COVID-19 Outbreak in t(epmc).pdf DeepDyve Pubget Overpricing