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Rev. Soc. Bras. Med. Trop ; 53: e20200354, 2020. tab, graf
Article in English | Sec. Est. Saúde SP, Coleciona SUS, LILACS | ID: biblio-1136826

ABSTRACT

Abstract INTRODUCTION: COVID-19 emerged in late 2019 and quickly became a serious public health problem worldwide. This study aim to describe the epidemiological course of cases and deaths due to COVID-19 and their impact on hospital bed occupancy rates in the first 45 days of the epidemic in the state of Ceará, Northeastern Brazil. METHODS: The study used an ecological design with data gathered from multiple government and health care sources. Data were analyzed using Epi Info software. RESULTS: The first cases were confirmed on March 15, 2020. After 45 days, 37,268 cases reported in 85.9% of Ceará's municipalities, with 1,019 deaths. Laboratory test positivity reached 84.8% at the end of April, a period in which more than 700 daily tests were processed. The average age of cases was 67 (<1 - 101) years, most occurred in a hospital environment (91.9%), and 58% required hospitalization in an ICU bed. The average time between the onset of symptoms and death was 18 (1 - 56) days. Patients who died in the hospital had spent an average of six (0 - 40) days hospitalized. Across Ceará, the bed occupancy rate reached 71.3% in the wards and 80.5% in the ICU. CONCLUSIONS: The first 45 days of the COVID-19 epidemic in Ceará revealed a large number of cases and deaths, spreading initially among the population with a high socioeconomic status. Despite the efforts by the health services and social isolation measures the health system still collapsed.


Subject(s)
Humans , Male , Female , Infant , Child, Preschool , Child , Adolescent , Adult , Aged , Aged, 80 and over , Young Adult , Pneumonia, Viral/epidemiology , Bed Occupancy/statistics & numerical data , Betacoronavirus , Health Services Needs and Demand/statistics & numerical data , Pneumonia, Viral/mortality , Time Factors , Brazil/epidemiology , Sex Distribution , Coronavirus Infections , Coronavirus Infections/mortality , Coronavirus Infections/epidemiology , Age Distribution , Health Care Surveys/statistics & numerical data , Pandemics , Data Analysis , Hospital Units/statistics & numerical data , Intensive Care Units/statistics & numerical data , Length of Stay/statistics & numerical data , Middle Aged
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