医院网络与患者转移导致的医院获得性病原体传播

数据集获取（Figshare）

• 源站标题：Hospital Networks and the Dispersal of Hospital-Acquired Pathogens by Patient Transfer
• DOI：10.1371/journal.pone.0035002
• 发布日期：2012-04-25
• 文件数：7 个
• 文件总体积：10.72 MB
• 源站页面：https://plos.figshare.com/articles/dataset/Hospital_Networks_and_the_Dispersal_of_Hospital_Acquired_Pathogens_by_Patient_Transfer/125903

命令行下载

curl -L -o "Figure_S1.pdf" "https://ndownloader.figshare.com/files/333610"
curl -L -o "Figure_S2.pdf" "https://ndownloader.figshare.com/files/333671"
curl -L -o "Figure_S3.pdf" "https://ndownloader.figshare.com/files/333720"
curl -L -o "Movie_S1.avi" "https://ndownloader.figshare.com/files/333769"
curl -L -o "Table_S1.pdf" "https://ndownloader.figshare.com/files/333865"
curl -L -o "Table_S2.pdf" "https://ndownloader.figshare.com/files/333899"
curl -L -o "Text_S1.pdf" "https://ndownloader.figshare.com/files/334012"

文件清单

• Figure_S1.pdf（231.81 KB）
• Figure_S2.pdf（107.39 KB）
• Figure_S3.pdf（592.18 KB）
• Movie_S1.avi（9.61 MB）
• Table_S1.pdf（65.30 KB）
• Table_S2.pdf（51.70 KB）
• Text_S1.pdf（70.96 KB）

文件总体积 10.72 MB（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

Hospital-acquired infections (HAI) are often seen as preventable incidents that result from unsafe practices or poor hospital hygiene. This however ignores the fact that transmissibility is not only a property of the causative organisms but also of the hosts who can translocate bacteria when moving between hospitals. In an epidemiological sense, hospitals become connected through the patients they share. We here postulate that the degree of hospital connectedness crucially influences the rates of infections caused by hospital-acquired bacteria. To test this hypothesis, we mapped the movement of patients based on the UK-NHS Hospital Episode Statistics and observed that the proportion of patients admitted to a hospital after a recent episode in another hospital correlates with the hospital-specific incidence rate of MRSA bacteraemia as recorded by mandatory reporting. We observed a positive correlation between hospital connectedness and MRSA bacteraemia incidence rate that is significant for all financial years since 2001 except for 2008–09. All years combined, this correlation is positive and significantly different from zero (partial correlation coefficient r = 0.33 (0.28 to 0.38)). When comparing the referral pattern for English hospitals with referral patterns observed in the Netherlands, we predict that English hospitals more likely see a swifter and more sustained spread of HAIs. Our results indicate that hospitals cannot be viewed as individual units but rather should be viewed as connected elements of larger modular networks. Our findings stress the importance of cooperative effects that will have a bearing on the planning of health care systems, patient management and hospital infection control.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.1371/journal.pone.0035002（source: https://plos.figshare.com/articles/dataset/Hospital_Networks_and_the_Dispersal_of_Hospital_Acquired_Pathogens_by_Patient_Transfer/125903）。