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Salmonellosis outbreak archive in China: data collection and assembly

Authors :
Zining Wang
Chenghu Huang
Yuhao Liu
Jiaqi Chen
Rui Yin
Chenghao Jia
Xiamei Kang
Xiao Zhou
Sihao Liao
Xiuyan Jin
Mengyao Feng
Zhijie Jiang
Yan Song
Haiyang Zhou
Yicheng Yao
Lin Teng
Baikui Wang
Yan Li
Min Yue
Source :
Scientific Data, Vol 11, Iss 1, Pp 1-7 (2024)
Publication Year :
2024
Publisher :
Nature Portfolio, 2024.

Abstract

Abstract Infectious disease outbreaks transcend the medical and public health realms, triggering widespread panic and impeding socio-economic development. Considering that self-limiting diarrhoea of sporadic cases is usually underreported, the Salmonella outbreak (SO) study offers a unique opportunity for source tracing, spatiotemporal correlation, and outbreak prediction. To summarize the pattern of SO and estimate observational epidemiological indicators, 1,134 qualitative reports screened from 1949 to 2023 were included in the systematic review dataset, which contained a 506-study meta-analysis dataset. In addition to the dataset comprising over 50 columns with a total of 46,494 entries eligible for inclusion in systematic reviews or input into prediction models, we also provide initial literature collection datasets and datasets containing socio-economic and climate information for relevant regions. This study has a broad impact on advancing knowledge regarding epidemic trends and prevention priorities in diverse salmonellosis outbreaks and guiding rational policy-making or predictive modeling to mitigate the infringement upon the right to life imposed by significant epidemics.

Subjects

Subjects :
Science

Details

Language :
English
ISSN :
20524463
Volume :
11
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Scientific Data
Publication Type :
Academic Journal
Accession number :
edsdoj.5649484883841568f0955917c360c5e
Document Type :
article
Full Text :
https://doi.org/10.1038/s41597-024-03085-7