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10.1590/1518-8345.4501.3345 http://scihub22266oqcxt.onion/10.1590/1518-8345.4501.3345 32609282!7319758!32609282     free     free     free Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Rev+Lat+Am+Enfermagem 2020 ; 28 (ä): e3345 Nephropedia Template TP {{tp|p=32609282|t=2020. Estimation and prediction of COVID-19 cases in Brazilian metropolises |pdf=|usr=}}{{32609282}} gab.com Text Estimation and prediction of COVID-19 cases in Brazilian metropolises JO: Rev Lat Am Enfermagem http://www.kidney.de/pget.php?&tw=1&pmid=32609282 #FOAvip OBJECTIVE: to estimate the transmission rate, the epidemiological peak, and the number of deaths by the new coronavirus. METHOD: a mathematical and epidemiological model of susceptible, infected, and recovered cases was applied to the nine Brazilian capitals with the highest number of cases of the infection. The number of cases for the 80 days following the first case was estimated by solving the differential equations. The results were logarithmized and compared with the actual values to observe the model fit. In all scenarios, it was considered that no preventive measures had been taken. RESULTS: the nine metropolises studied showed an upward curve of confirmed cases of COVID-19. The prediction data point to the peak of the infection between late April and early May. Fortaleza and Manaus had the highest transmission rates (>/=2.0 and >/=1.8, respectively). Rio de Janeiro may have the largest number of infected people (692,957) and Florianopolis the smallest (24,750). CONCLUSION: the estimates of the transmission rate, epidemiological peak, and number of deaths from coronavirus in Brazilian metropolises presented expressive and important numbers the Brazilian Ministry of Health needs to consider. The results confirm the rapid spread of the virus and its high mortality in the country. Twit Text FOAVip Estimation and prediction of COVID-19 cases in Brazilian metropolises ????Rev Lat Am Enfermagem http://www.kidney.de/pget.php?&tw=1&pmid=32609282 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32609282 #FOAvip English Wikipedia <ref>{{Cite pmid|32609282}}</ref> Estimation and prediction of COVID-19 cases in Brazilian metropolises #MMPMID32609282 Sousa GJB; Garces TS; Cestari VRF; Moreira TMM; Florencio RS; Pereira MLD Rev Lat Am Enfermagem 2020[]; 28 (ä): e3345 PMID32609282show ga OBJECTIVE: to estimate the transmission rate, the epidemiological peak, and the number of deaths by the new coronavirus. METHOD: a mathematical and epidemiological model of susceptible, infected, and recovered cases was applied to the nine Brazilian capitals with the highest number of cases of the infection. The number of cases for the 80 days following the first case was estimated by solving the differential equations. The results were logarithmized and compared with the actual values to observe the model fit. In all scenarios, it was considered that no preventive measures had been taken. RESULTS: the nine metropolises studied showed an upward curve of confirmed cases of COVID-19. The prediction data point to the peak of the infection between late April and early May. Fortaleza and Manaus had the highest transmission rates (>/=2.0 and >/=1.8, respectively). Rio de Janeiro may have the largest number of infected people (692,957) and Florianopolis the smallest (24,750). CONCLUSION: the estimates of the transmission rate, epidemiological peak, and number of deaths from coronavirus in Brazilian metropolises presented expressive and important numbers the Brazilian Ministry of Health needs to consider. The results confirm the rapid spread of the virus and its high mortality in the country. |*Betacoronavirus[MESH] |*Pandemics/statistics & numerical data[MESH] |Algorithms[MESH] |Brazil/epidemiology[MESH] |COVID-19[MESH] |Cities/epidemiology[MESH] |Coronavirus Infections/*epidemiology/mortality/transmission[MESH] |Humans[MESH] |Models, Statistical[MESH] |Models, Theoretical[MESH] |Pneumonia, Viral/*epidemiology/mortality/transmission[MESH] |SARS-CoV-2[MESH]Estimation and prediction of COVID-19 cases in Brazilian metropolises (epmc).pdf DeepDyve Pubget Overpricing