denguedatasets¶
Licence GNU General Public Licence v3.0 (GPL-3.0)
denguedatasets is free software distribuited under the terms of the GNU General Public Licence v3.0
Datasets included in denguedatasets¶
This file documents the origin and license of each dataset included in the denguedatasets Python package.
dengue_bangladesh¶
Source: Kaggle URL: https://www.kaggle.com/datasets/kawsarahmad/dengue-dataset-bangladesh Title: Dengue Dataset of Bangladesh. Unraveling Dengue: Analyzing and Mapping Affected Areas in Bangladesh for Target License: CC BY 4.0 Original Name: dataset.csv Final Name: dengue_bangladesh.csv Description: This dataset presents real-world data collected through surveys conducted in the Dhaka region of Bangladesh. It focuses on understanding the prevalence and characteristics of the Dengue fever phenomenon, a significant public health concern in the area. The dataset is updated monthly to reflect the evolving nature of the Dengue outbreak.
dengue_bangladesh_mortality¶
Source: Kaggle URL: https://www.kaggle.com/datasets/gazijahin/climatic-influence-on-dengue-mortality-2000-2024 Title: Climatic Influence on Dengue Mortality (2000-2024). Effects of climatic factors for increasing the risk of Dengue cases License: MIT Original Name: Climatic_Influence_on_Dengue_Mortality.csv Final Name: dengue_bangladesh_mortality.csv Description: This dataset explores the spatio-temporal interaction between climate variability and dengue outbreaks across six divisions of Bangladesh from 2000 to 2024. It connects meteorological parameters with epidemiological indicators (cases, deaths, and case-fatality rate) to uncover how changing weather patterns influence dengue mortality.
dengue_philippines¶
Source: Kaggle URL: https://www.kaggle.com/datasets/vincentgupo/dengue-cases-in-the-philippines Title: Philippines Dengue Cases 2016-2020 License: CC0: Public Domain Original Name: ph_dengue_cases2016-2020.csv Final Name: dengue_philippines.csv Description: Data set contains the recorded number of dengue cases per region of the Philippines from year 2016 to 2020. It can be used to find trends about the disease as well as spatiotemporal analysis that can result into data-driven solution about the trends of the desease for the past 5 years.
dengue_taiwan¶
Source: Kaggle URL: https://www.kaggle.com/datasets/taweilo/taiwan-dengue-daily-confirmed-cases-1998-2024 Title: Taiwan Dengue Cases 1998-2024. Daily and Regional Confirmed Cases of Dengue from 1998 to 2024 License: CC0: Public Domain Original Name: Dengue_Daily_EN.csv Final Name: dengue_taiwan.csv Description: The dataset contains detailed information on dengue fever cases since 1998, encompassing various aspects such as dates, geographical locations, and serotype details. This data can be leveraged to analyze temporal trends, spatial distribution, and the serotype of dengue cases. It is valuable for understanding the disease's progression, its impact across different regions, and the effectiveness of intervention measures over time.
dengue_sri_lanka¶
Source: Kaggle URL: https://www.kaggle.com/datasets/sadaruwan/sri-lanka-dengue-cases-2010-2020 Title: Sri Lanka Dengue Cases 2010-2020 License: Data files © Original Authors Original Name: Dengue_Data(2010-2020).csv Final Name: dengue_sri_lanka.csv Description: This Dataset Include Data About Sri Lanka Dengue Cases From 2010 to 2020
dengue_brazil¶
Source: Kaggle URL: https://www.kaggle.com/datasets/raomuhammadsaeedali/brazil-dengue-dataset-2000-2019 Title: Brazil Dengue Dataset 2000-2019. Brazil Dengue Dataset offers insights into geography, environment, and disease. License: GPL 2 Original Name: data_2000_2019.csv Final Name: dengue_brazil.csv Description: The dataset supplied comprises a comprehensive collection of information pertaining to numerous geographical and environmental characteristics across microregions in Brazil from 2000 to 2019. Microregion codes and names, mesoregion codes and names, state codes and names, region codes and names, biome codes and names, ecozone codes and names, climate regimes, months, years, times, dengue cases, population estimates, population density, maximum and minimum temperatures, Palmer's drought severity index, urban population percentages, access to water network percentages, and reported water shortage frequency are all included in the dataset. This information is linked to individual microregions and provides insights into population dynamics, climatic patterns, urbanization trends, water resources, and disease occurrences.
dengue_brazil_labels¶
Source: Kaggle URL: https://www.kaggle.com/datasets/raomuhammadsaeedali/brazil-dengue-dataset-2000-2019 Title: Brazil Dengue Dataset 2000-2019 — Data Dictionary License: GPL 2 Original Name: data_desc.csv Final Name: dengue_brazil_labels.csv Description: Data dictionary/variable-label reference table accompanying the Brazil Dengue Dataset 2000-2019, documenting field names, codes, and descriptions used across microregion, mesoregion, state, region, biome, and ecozone identifiers, as well as climatic and demographic variables in the main dataset.
dengue_colombia_medellin¶
Source: Kaggle URL: https://www.kaggle.com/datasets/davidrestrepo/dengue Title: Dengue Tabular Data of Medellin License: Unknown Original Name: Dengue_Dataset(Medellin).csv Final Name: dengue_colombia_medellin.csv Description: Dengue challenge 2- Make Health LATAM 2022. En este reto se proveerá de un dataset para cada municipio de Colombia, compuesto por los casos de dengue semana a semana entre 2007 y 2019, acompañado de otras variables sociales y climatológicas. Encontrarás además un dataset especial que hemos preparado para el municipio de Medellín, con variables climatológicas preprocesadas y una versión comprimida de imágenes satelitales para incluir en los modelos
dengue_colombia¶
Source: Kaggle URL: https://www.kaggle.com/datasets/davidrestrepo/dengue Title: Dengue Tabular Data of Colombia License: Unknown Original Name: dengue_data_all_municipalities.csv Final Name: dengue_colombia.csv Description: Dengue challenge 2- Make Health LATAM 2022. En este reto se proveerá de un dataset para cada municipio de Colombia, compuesto por los casos de dengue semana a semana entre 2007 y 2019, acompañado de otras variables sociales y climatológicas. Encontrarás además un dataset especial que hemos preparado para el municipio de Medellín, con variables climatológicas preprocesadas y una versión comprimida de imágenes satelitales para incluir en los modelos
dengue_sri_lanka_2019¶
Source: Kaggle URL: https://www.kaggle.com/datasets/kanchana1990/sri-lanka-dengue-data-2019-2021-insights Title: Sri Lanka Dengue Data: 2019-2021 Insights License: CC0: Public Domain Original Name: dengue_2019.csv Final Name: dengue_sri_lanka_2019.csv Description: A comprehensive record of dengue cases across all districts and provinces in Sri Lanka, detailing monthly occurrences from January to December for the years 2019-2021. Data serves as a critical resource for understanding the epidemiological trends of dengue, facilitating public health responses and preventive strategies. Though compact, this dataset offers rich opportunities for data science applications including trend analysis, hotspot detection, and predictive modeling for future outbreaks. Data was meticulously compiled and made available by the National Dengue Control Unit (NDCU) of Sri Lanka. For more details, visit the NDCU Dengue Information Portal.
dengue_sri_lanka_2020¶
Source: Kaggle URL: https://www.kaggle.com/datasets/kanchana1990/sri-lanka-dengue-data-2019-2021-insights Title: Sri Lanka Dengue Data: 2019-2021 Insights License: CC0: Public Domain Original Name: dengue_2020.csv Final Name: dengue_sri_lanka_2020.csv Description: A comprehensive record of dengue cases across all districts and provinces in Sri Lanka, detailing monthly occurrences from January to December for the years 2019-2021. Data serves as a critical resource for understanding the epidemiological trends of dengue, facilitating public health responses and preventive strategies. Though compact, this dataset offers rich opportunities for data science applications including trend analysis, hot spot detection, and predictive modeling for future outbreaks. Data was meticulously compiled and made available by the National Dengue Control Unit (NDCU) of Sri Lanka. For more details, visit the NDCU Dengue Information Portal.
dengue_sri_lanka_2021¶
Source: Kaggle URL: https://www.kaggle.com/datasets/kanchana1990/sri-lanka-dengue-data-2019-2021-insights Title: Sri Lanka Dengue Data: 2019-2021 Insights License: CC0: Public Domain Original Name: dengue_2021.csv Final Name: dengue_sri_lanka_2021.csv Description: A comprehensive record of dengue cases across all districts and provinces in Sri Lanka, detailing monthly occurrences from January to December for the years 2019-2021. Data serves as a critical resource for understanding the epidemiological trends of dengue, facilitating public health responses and preventive strategies. Though compact, this dataset offers rich opportunities for data science applications including trend analysis, hot spot detection, and predictive modeling for future outbreaks. Data was meticulously compiled and made available by the National Dengue Control Unit (NDCU) of Sri Lanka. For more details, visit the NDCU Dengue Information Portal.
dengue_pakistan¶
Source: Kaggle URL: https://www.kaggle.com/datasets/aamir28/pakistan-dengue-surveillance-data-2016-2020 Title: Pakistan Dengue Surveillance Data (2016-2020) License: CC BY-SA 4.0 Original Name: dengue_data.csv Final Name: dengue_pakistan.csv Description: This dataset contains monthly dengue fever surveillance data from Pakistan covering the period 2016-2020. It provides comprehensive information on dengue cases and deaths across all provinces and territories, making it valuable for epidemiological research, public health policy development, and disease outbreak analysis. Time Period: January 2016 to December 2020 (5 years). Geographic Coverage: All provinces and territories of Pakistan. Frequency: Monthly aggregated data. Total Records: 420 monthly observations. Geographic Regions Included Punjab: Most populous province, Sindh: Second largest province including Karachi, KPK (Khyber Pakhtunkhwa): Northwestern province, Balochistan: Largest province by area, ICT (Islamabad Capital Territory): Federal capital territory, AJK (Azad Jammu & Kashmir): Administered territory, GB (Gilgit-Baltistan): Northern territory.
dengue_india¶
Source: Kaggle URL: https://www.kaggle.com/datasets/jadhavpranav/dengue-cases-in-india Title: Dengue Cases in India License: CC0: Public Domain Original Name: dengue_cases_in_india.csv Final Name: dengue_india.csv Description: This data is scrapped from the National Center for Vector Borne Diseases Control. It's a website managed by the Ministry of Health & Family Welfare, Government of India. This data contains dengue cases and deaths happening in each state of India over the years.
dengue_peru¶
Source: Kaggle URL: https://www.kaggle.com/datasets/fazzzzzzzzzz/datos-dengue-en-el-per-2019-2022-en-csv Title: Datos Dengue en el Perú 2019-2022 en CSV License: Apache 2.0 Original Name: datos_dengue_TF.csv Final Name: dengue_peru.csv Description: No description available
dengue_jakarta¶
Source: Kaggle URL: https://www.kaggle.com/datasets/yutakatarokusumah/jakarta-dengue-weather-2021-2024 Title: Jakarta Dengue Cases and Weather Data, 2021-2024. License: Unknown Original Name: jakarta-dengue-weather_2021-2024.csv Final Name: dengue_jakarta.csv Description: No description available
dengue_sierra_leone¶
Source: Kaggle URL: https://www.kaggle.com/datasets/michaalmarkosesay/sierra-leone-freetown-dengueai-dataset-20152024 Title: Sierra Leone Freetown DengueAI Dataset (2015–2024). License: CC BY 4.0 Original Name: SierraLeone_Freetown_DengueAI_Data.csv Final Name: dengue_sierra_leone.csv Description: The Sierra Leone Freetown DengueAI Dataset (2015–2024) offers an integrated collection of epidemiological and climatic variables, specifically designed for AI-based dengue outbreak prediction and time-series modeling. The dataset captures monthly variations in temperature, humidity, and precipitation, as well as confirmed dengue cases in Freetown, Sierra Leone. Data sources include OpenDengue and NOAA GSOD.