巴西COVID-19危机期间的住院、死亡和公共医疗支出：弱势群体焦点

数据集获取（Figshare）

• 源站标题：Hospitalization, mortality and public healthcare expenditure in Brazil during the COVID-19 crisis: vulnerabilities in the spotlight
• DOI：10.6084/m9.figshare.20008991.v1
• 发布日期：2022-06-06
• 文件数：4 个
• 文件总体积：241.58 KB
• 源站页面：https://scielo.figshare.com/articles/dataset/Hospitalization_mortality_and_public_healthcare_expenditure_in_Brazil_during_the_COVID-19_crisis_vulnerabilities_in_the_spotlight/20008991

命令行下载

curl -L -o "1b82049960ddc3f30fbae1bc2cd50ede680dbf0c.png" "https://ndownloader.figshare.com/files/35623748"
curl -L -o "cba9244d722964da627e85b9d9a687e47fe59c4f.jpg" "https://ndownloader.figshare.com/files/35623751"
curl -L -o "Table_1.xls" "https://ndownloader.figshare.com/files/35623754"
curl -L -o "Table_2.xls" "https://ndownloader.figshare.com/files/35623757"

文件清单

• 1b82049960ddc3f30fbae1bc2cd50ede680dbf0c.png（219.05 KB）
• cba9244d722964da627e85b9d9a687e47fe59c4f.jpg（7.17 KB）
• Table_1.xls（9.73 KB）
• Table_2.xls（5.63 KB）

文件总体积 241.58 KB（源站 API 实测）。

数据加载示例（图像类）

from PIL import Image
import glob, os

files = (glob.glob(os.path.join(path, "**", "*.png"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.jpg"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.tif"), recursive=True))
print("图像文件数:", len(files))
img = Image.open(files[0]); print("尺寸/模式:", img.size, img.mode)

# torchvision Dataset 方式:
# from torchvision import datasets
# ds = datasets.ImageFolder(path)  # 要求 子目录=类别

目录组织与标注格式以源站说明和下载后实际文件为准。

数据说明

ABSTRACT BACKGROUND: Multiple opinion-based communications have highlighted the actions of the Brazilian government during the pandemic. Nevertheless, none have appraised public data to identify factors associated with worsening of the healthcare system. OBJECTIVE: To analyze and collate data from public health and treasury information systems in order to understand the escalating process of weakening of Brazilian healthcare and welfare since the beginning of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. DESIGN AND SETTING: Secondary data study conducted using multiple public databases administered by the Brazilian federal government. METHODS: We processed information from multiple national databases and appraised health and economic-related data. RESULTS: Based on our analyses, there were substantial reductions in inpatient hospital admissions and in the numbers of patients seeking primary care services, along with a decrease in immunization coverage. Moreover, we observed a considerable decline in government transfers to hospital services (reduction of 82.0%) and a diminution of public outlays in several healthcare-related subfunctions (“hospital and outpatient care”, “primary care”, “prophylactic and therapeutic support” and “epidemiological surveillance”). We observed an increase in the overall mortality rate over the period analyzed, especially regarding all group-based diseases. Notably, there were remarkable differences among geographic, racial, gender and other parameters, thus revealing the impact of vulnerabilities on COVID-19 outcomes. CONCLUSION: This assessment of documentation of public expenditure and the shrinkage of investment in sensitive areas of the healthcare system in Brazil emphasized areas that still require collective attention in order to guarantee national welfare.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.6084/m9.figshare.20008991.v1（source: https://scielo.figshare.com/articles/dataset/Hospitalization_mortality_and_public_healthcare_expenditure_in_Brazil_during_the_COVID-19_crisis_vulnerabilities_in_the_spotlight/20008991）。