Time series data on typhoid fever incidence during outbreaks from 2000 to 2022
Abstract This article presents a comprehensive dataset compiling reported cases of typhoid fever from culture-confirmed outbreaks across various geographical locations from 2000 through 2022, categorized into daily, weekly, and monthly time series. The dataset was curated by identifying peer-reviewe...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-01-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-024-04289-7 |
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| author | Dae-Hyup Koh Monica Duong Nodar Kipshidze Virginia E. Pitzer Jong-Hoon Kim |
| author_facet | Dae-Hyup Koh Monica Duong Nodar Kipshidze Virginia E. Pitzer Jong-Hoon Kim |
| author_sort | Dae-Hyup Koh |
| collection | DOAJ |
| description | Abstract This article presents a comprehensive dataset compiling reported cases of typhoid fever from culture-confirmed outbreaks across various geographical locations from 2000 through 2022, categorized into daily, weekly, and monthly time series. The dataset was curated by identifying peer-reviewed epidemiological studies available in PubMed, OVID-Medline, and OVID-Embase. Time-series incidence data were extracted from plots using WebPlotDigitizer, followed by verification of a subset of the dataset. The primary aim of this dataset is to serve as a foundational tool for researchers and policymakers, enabling the development of robust, model-based strategies for the control of typhoid fever outbreaks. The article describes the method by which the dataset has been compiled and how the quality of the data has been verified. Furthermore, it discusses the dataset’s potential applications in optimizing vaccination campaigns, improving public health planning, and tailoring interventions to specific epidemiologic contexts. This article contributes significantly to the field of infectious disease modeling, offering a valuable resource for enhancing typhoid fever control measures globally. |
| format | Article |
| id | doaj-art-3b6879fdb92c47d79cc4ba6e2020aaf3 |
| institution | Kabale University |
| issn | 2052-4463 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj-art-3b6879fdb92c47d79cc4ba6e2020aaf32025-01-19T12:09:46ZengNature PortfolioScientific Data2052-44632025-01-0112111010.1038/s41597-024-04289-7Time series data on typhoid fever incidence during outbreaks from 2000 to 2022Dae-Hyup Koh0Monica Duong1Nodar Kipshidze2Virginia E. Pitzer3Jong-Hoon Kim4Epidemiology, Public Health, Impact, International Vaccine InstituteEpidemiology, Public Health, Impact, International Vaccine InstituteDepartment of Epidemiology of Microbial Diseases, Yale School of Public HealthDepartment of Epidemiology of Microbial Diseases, Yale School of Public HealthEpidemiology, Public Health, Impact, International Vaccine InstituteAbstract This article presents a comprehensive dataset compiling reported cases of typhoid fever from culture-confirmed outbreaks across various geographical locations from 2000 through 2022, categorized into daily, weekly, and monthly time series. The dataset was curated by identifying peer-reviewed epidemiological studies available in PubMed, OVID-Medline, and OVID-Embase. Time-series incidence data were extracted from plots using WebPlotDigitizer, followed by verification of a subset of the dataset. The primary aim of this dataset is to serve as a foundational tool for researchers and policymakers, enabling the development of robust, model-based strategies for the control of typhoid fever outbreaks. The article describes the method by which the dataset has been compiled and how the quality of the data has been verified. Furthermore, it discusses the dataset’s potential applications in optimizing vaccination campaigns, improving public health planning, and tailoring interventions to specific epidemiologic contexts. This article contributes significantly to the field of infectious disease modeling, offering a valuable resource for enhancing typhoid fever control measures globally.https://doi.org/10.1038/s41597-024-04289-7 |
| spellingShingle | Dae-Hyup Koh Monica Duong Nodar Kipshidze Virginia E. Pitzer Jong-Hoon Kim Time series data on typhoid fever incidence during outbreaks from 2000 to 2022 Scientific Data |
| title | Time series data on typhoid fever incidence during outbreaks from 2000 to 2022 |
| title_full | Time series data on typhoid fever incidence during outbreaks from 2000 to 2022 |
| title_fullStr | Time series data on typhoid fever incidence during outbreaks from 2000 to 2022 |
| title_full_unstemmed | Time series data on typhoid fever incidence during outbreaks from 2000 to 2022 |
| title_short | Time series data on typhoid fever incidence during outbreaks from 2000 to 2022 |
| title_sort | time series data on typhoid fever incidence during outbreaks from 2000 to 2022 |
| url | https://doi.org/10.1038/s41597-024-04289-7 |
| work_keys_str_mv | AT daehyupkoh timeseriesdataontyphoidfeverincidenceduringoutbreaksfrom2000to2022 AT monicaduong timeseriesdataontyphoidfeverincidenceduringoutbreaksfrom2000to2022 AT nodarkipshidze timeseriesdataontyphoidfeverincidenceduringoutbreaksfrom2000to2022 AT virginiaepitzer timeseriesdataontyphoidfeverincidenceduringoutbreaksfrom2000to2022 AT jonghoonkim timeseriesdataontyphoidfeverincidenceduringoutbreaksfrom2000to2022 |