Salmonellosis Outbreak Archive in China: Data Collection and Assembly

Overview

Journal Sci Data

Specialty Science

Date 2024 Feb 27

PMID 38413596

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

Affiliations

Soon will be listed here.

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.

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