Dataset Information

Estimation and prediction of COVID-19 cases in Brazilian metropolises.

ABSTRACT: 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 Florianópolis 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.

SUBMITTER: Sousa GJB

PROVIDER: S-EPMC7319758 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Estimation and prediction of COVID-19 cases in Brazilian metropolises.

Sousa George Jó Bezerra GJB Garces Thiago Santos TS Cestari Virna Ribeiro Feitosa VRF Moreira Thereza Maria Magalhães TMM Florêncio Raquel Sampaio RS Pereira Maria Lúcia Duarte MLD

Revista latino-americana de enfermagem 20200626

<h4>Objective</h4>to estimate the transmission rate, the epidemiological peak, and the number of deaths by the new coronavirus.<h4>Method</h4>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 val ...[more]

PMID: 32609282

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Project description:Background:A novel human coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was identified in China in December 2019. There is limited support for many of its key epidemiologic features, including the incubation period for clinical disease (coronavirus disease 2019 [COVID-19]), which has important implications for surveillance and control activities. Objective:To estimate the length of the incubation period of COVID-19 and describe its public health implications. Design:Pooled analysis of confirmed COVID-19 cases reported between 4 January 2020 and 24 February 2020. Setting:News reports and press releases from 50 provinces, regions, and countries outside Wuhan, Hubei province, China. Participants:Persons with confirmed SARS-CoV-2 infection outside Hubei province, China. Measurements:Patient demographic characteristics and dates and times of possible exposure, symptom onset, fever onset, and hospitalization. Results:There were 181 confirmed cases with identifiable exposure and symptom onset windows to estimate the incubation period of COVID-19. The median incubation period was estimated to be 5.1 days (95% CI, 4.5 to 5.8 days), and 97.5% of those who develop symptoms will do so within 11.5 days (CI, 8.2 to 15.6 days) of infection. These estimates imply that, under conservative assumptions, 101 out of every 10 000 cases (99th percentile, 482) will develop symptoms after 14 days of active monitoring or quarantine. Limitation:Publicly reported cases may overrepresent severe cases, the incubation period for which may differ from that of mild cases. Conclusion:This work provides additional evidence for a median incubation period for COVID-19 of approximately 5 days, similar to SARS. Our results support current proposals for the length of quarantine or active monitoring of persons potentially exposed to SARS-CoV-2, although longer monitoring periods might be justified in extreme cases. Primary Funding Source:U.S. Centers for Disease Control and Prevention, National Institute of Allergy and Infectious Diseases, National Institute of General Medical Sciences, and Alexander von Humboldt Foundation.

Dataset Information

Estimation and prediction of COVID-19 cases in Brazilian metropolises.

Publications

Estimation and prediction of COVID-19 cases in Brazilian metropolises.

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