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. 2024 Feb 27;11(1):244.
doi: 10.1038/s41597-024-03085-7.

Salmonellosis outbreak archive in China: data collection and assembly

Affiliations

Salmonellosis outbreak archive in China: data collection and assembly

Zining Wang et al. Sci Data. .

Erratum in

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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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Analysis process and dataset characteristics of systematic review and meta-analysis. (a) Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram of search strategy and selection of articles. (b) The number of Chinese and English publications included in the systematic review dataset by year period. (c) The number of new cases recorded in Chinese and English publications included in the systematic review dataset by year period.
Fig. 2
Fig. 2
Dataset composition and structure. The complete outbreak datasets are divided into four parts: temporal-spatial data, patient cohort information, pathogen diagnosis and treatment, and objective environmental factors.
Fig. 3
Fig. 3
The annual trend and geographical distribution of Salmonella outbreaks. (a) The variation in the number of Salmonella outbreaks with the growth of years is depicted by the black line representing linear regression fit, with the blue semi-transparent area indicating the 95% confidence interval. (b) Geographic distribution of Salmonella outbreaks in China based on administrative divisions.

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