Time series data on typhoid fever incidence during outbreaks from 2000 to 2022

Area of Science:

• Epidemiology
• Infectious Disease Modeling
• Public Health

Background:

• Typhoid fever remains a significant global health concern, necessitating robust data for effective control.
• Accurate and comprehensive epidemiological data are crucial for understanding disease dynamics and planning interventions.

Purpose of the Study:

• To present a comprehensive, time-series dataset of culture-confirmed typhoid fever outbreaks from 2000-2022.
• To provide a foundational resource for researchers and policymakers to develop typhoid fever control strategies.
• To facilitate the optimization of vaccination campaigns and public health planning.

Main Methods:

• Systematic literature search of PubMed, OVID-Medline, and OVID-Embase for peer-reviewed studies.
• Extraction of daily, weekly, and monthly time-series incidence data using WebPlotDigitizer.
• Data verification through subset validation to ensure accuracy and reliability.

Main Results:

• A curated dataset of typhoid fever outbreaks spanning 2000-2022, categorized into daily, weekly, and monthly time series.
• Detailed methodology for data compilation and quality assurance is described.
• The dataset offers potential for diverse applications in infectious disease modeling and public health.

Conclusions:

• The compiled dataset represents a valuable resource for advancing typhoid fever research and control efforts.
• This data can inform evidence-based strategies for vaccination, public health planning, and targeted interventions.
• The study contributes to enhancing global typhoid fever control measures through improved data availability and accessibility.