RESUMO
COVID-19 epidemic doubling time by Chinese province was increasing from January 20 through February 9, 2020. The harmonic mean of the arithmetic mean doubling time estimates ranged from 1.4 (Hunan, 95% CI, 1.2-2.0) to 3.1 (Xinjiang, 95% CI, 2.1-4.8), with an estimate of 2.5 days (95% CI, 2.4-2.6) for Hubei.
RESUMO
In China, the doubling time of the coronavirus disease epidemic by province increased during January 20-February 9, 2020. Doubling time estimates ranged from 1.4 (95% CI 1.2-2.0) days for Hunan Province to 3.1 (95% CI 2.1-4.8) days for Xinjiang Province. The estimate for Hubei Province was 2.5 (95% CI 2.4-2.6) days.
Assuntos
Betacoronavirus/crescimento & desenvolvimento , Infecções por Coronavirus/epidemiologia , Infecções por Coronavirus/transmissão , Pandemias , Pneumonia Viral/epidemiologia , Pneumonia Viral/transmissão , Betacoronavirus/patogenicidade , COVID-19 , Teste para COVID-19 , China/epidemiologia , Técnicas de Laboratório Clínico/métodos , Infecções por Coronavirus/diagnóstico , Infecções por Coronavirus/virologia , Geografia , Humanos , Incidência , Pneumonia Viral/diagnóstico , Pneumonia Viral/virologia , SARS-CoV-2 , Fatores de TempoRESUMO
Background: The ongoing coronavirus disease 2019 pandemic has severely affected the United States. During infectious disease outbreaks, forecasting models are often developed to inform resource utilization. Pregnancy and delivery pose unique challenges, given the altered maternal immune system and the fact that most American women choose to deliver in the hospital setting. Objective: This study aimed to forecast the first pandemic wave of coronavirus disease 2019 in the general population and the incidence of severe, critical, and fatal coronavirus disease 2019 cases during delivery hospitalization in the United States. Study Design: We used a phenomenological model to forecast the incidence of the first wave of coronavirus disease 2019 in the United States. Incidence data from March 1, 2020, to April 14, 2020, were used to calibrate the generalized logistic growth model. Subsequently, Monte Carlo simulation was performed for each week from March 1, 2020, to estimate the incidence of coronavirus disease 2019 for delivery hospitalizations during the first pandemic wave using the available data estimate. Results: From March 1, 2020, our model forecasted a total of 860,475 cases of coronavirus disease 2019 in the general population across the United States for the first pandemic wave. The cumulative incidence of coronavirus disease 2019 during delivery hospitalization is anticipated to be 16,601 (95% confidence interval, 9711-23,491) cases, 3308 (95% confidence interval, 1755-4861) cases of which are expected to be severe, 681 (95% confidence interval, 1324-1038) critical, and 52 (95% confidence interval, 23-81) fatal. Assuming similar baseline maternal mortality rate as the year 2018, we projected an increase in maternal mortality rate in the United States to at least 18.7 (95% confidence interval, 18.0-19.5) deaths per 100,000 live births as a direct result of coronavirus disease 2019. Conclusion: Coronavirus disease 2019 in pregnant women is expected to severely affect obstetrical care. From March 1, 2020, we forecast 3308 severe and 681 critical cases with about 52 coronavirus disease 2019-related maternal mortalities during delivery hospitalization for the first pandemic wave in the United States. These results are significant for informing counseling and resource allocation.
