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A High-throughput Platform for the Screening of Salmonella spp./Shigella spp.
Published on: November 7, 2018
Salmonellosis outbreak archive in China: data collection and assembly
Zining Wang1,2,3, Chenghu Huang1,2,3, Yuhao Liu1,2,3
1Department of Veterinary Medicine, Zhejiang University College of Animal Sciences, Hangzhou, 310058, China.
Scientific Data
|February 27, 2024
Summary
This study analyzes Salmonella outbreaks (SO) to understand epidemic patterns and improve prediction. It provides valuable data for public health policy and outbreak mitigation strategies.
Area of Science:
- Epidemiology
- Public Health
- Infectious Disease Dynamics
Background:
- Infectious disease outbreaks cause significant public health and socio-economic disruption.
- Salmonella outbreaks (SO) are crucial for understanding disease patterns due to underreported sporadic cases.
- Effective source tracing and prediction are vital for managing SO.
Purpose of the Study:
- To systematically review and summarize the patterns of Salmonella outbreaks (SO) globally.
- To estimate epidemiological indicators for SO and provide data for predictive modeling.
- To inform public health policy and guide rational decision-making for epidemic prevention.
Main Methods:
- Conducted a systematic review of 1,134 qualitative reports on SO from 1949 to 2023.
- Included a meta-analysis dataset of 506 studies.
- Compiled datasets with over 50 columns and 46,494 entries, including socio-economic and climate data.
Main Results:
- Established a comprehensive dataset for SO analysis, suitable for systematic reviews and predictive modeling.
- Identified key epidemiological indicators and patterns in Salmonella outbreaks.
- Provided foundational data for understanding epidemic trends and prevention priorities.
Conclusions:
- The study advances knowledge on epidemic trends and prevention priorities for Salmonella outbreaks.
- The findings support the development of predictive models for SO.
- Data generated can guide policy-making to mitigate the impact of epidemics.
