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Epidemiological and digital syndromic surveillance data on dengue, chikungunya, and SARI in Brazil
by
Codeço, Cláudia T.
, Almeida, Alexandra
, Borges, Marcelo E.
, Machado, Dalila
in
692/699/1785
/ 692/699/255
/ Arthritis
/ Behavior
/ Brazil - epidemiology
/ Chikungunya Fever - epidemiology
/ Chikungunya virus
/ COVID-19
/ COVID-19 - epidemiology
/ Data Descriptor
/ Datasets
/ Datasets as Topic
/ Decision making
/ Dengue - epidemiology
/ Dengue fever
/ Disease Outbreaks
/ Disease transmission
/ Epidemics
/ Epidemiological Monitoring
/ Epidemiology
/ Exploratory behavior
/ Health surveillance
/ Humanities and Social Sciences
/ Humans
/ Infections
/ Influenza
/ Information systems
/ Leukopenia
/ multidisciplinary
/ Nausea
/ Outbreaks
/ Pain
/ Pandemics
/ Public health
/ Respiratory diseases
/ Respiratory tract infection
/ Science
/ Science (multidisciplinary)
/ Trends
/ Vector-borne diseases
2026
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Epidemiological and digital syndromic surveillance data on dengue, chikungunya, and SARI in Brazil
by
Codeço, Cláudia T.
, Almeida, Alexandra
, Borges, Marcelo E.
, Machado, Dalila
in
692/699/1785
/ 692/699/255
/ Arthritis
/ Behavior
/ Brazil - epidemiology
/ Chikungunya Fever - epidemiology
/ Chikungunya virus
/ COVID-19
/ COVID-19 - epidemiology
/ Data Descriptor
/ Datasets
/ Datasets as Topic
/ Decision making
/ Dengue - epidemiology
/ Dengue fever
/ Disease Outbreaks
/ Disease transmission
/ Epidemics
/ Epidemiological Monitoring
/ Epidemiology
/ Exploratory behavior
/ Health surveillance
/ Humanities and Social Sciences
/ Humans
/ Infections
/ Influenza
/ Information systems
/ Leukopenia
/ multidisciplinary
/ Nausea
/ Outbreaks
/ Pain
/ Pandemics
/ Public health
/ Respiratory diseases
/ Respiratory tract infection
/ Science
/ Science (multidisciplinary)
/ Trends
/ Vector-borne diseases
2026
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Epidemiological and digital syndromic surveillance data on dengue, chikungunya, and SARI in Brazil
by
Codeço, Cláudia T.
, Almeida, Alexandra
, Borges, Marcelo E.
, Machado, Dalila
in
692/699/1785
/ 692/699/255
/ Arthritis
/ Behavior
/ Brazil - epidemiology
/ Chikungunya Fever - epidemiology
/ Chikungunya virus
/ COVID-19
/ COVID-19 - epidemiology
/ Data Descriptor
/ Datasets
/ Datasets as Topic
/ Decision making
/ Dengue - epidemiology
/ Dengue fever
/ Disease Outbreaks
/ Disease transmission
/ Epidemics
/ Epidemiological Monitoring
/ Epidemiology
/ Exploratory behavior
/ Health surveillance
/ Humanities and Social Sciences
/ Humans
/ Infections
/ Influenza
/ Information systems
/ Leukopenia
/ multidisciplinary
/ Nausea
/ Outbreaks
/ Pain
/ Pandemics
/ Public health
/ Respiratory diseases
/ Respiratory tract infection
/ Science
/ Science (multidisciplinary)
/ Trends
/ Vector-borne diseases
2026
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Epidemiological and digital syndromic surveillance data on dengue, chikungunya, and SARI in Brazil
Journal Article
Epidemiological and digital syndromic surveillance data on dengue, chikungunya, and SARI in Brazil
2026
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Overview
Vector-borne diseases, such as dengue and chikungunya, along with air-borne diseases like influenza and COVID-19, are prone to epidemics, which increases the demand for real-time outbreak monitoring. Developing such systems requires harmonized datasets for calibration and validation. In this study, we created a dataset containing official disease notifications for dengue, chikungunya, and severe acute respiratory infections (SARI) across Brazilian states for over a decade. The dataset integrates Google Trends search data for each disease and all associated symptoms, organized by the corresponding epidemiological week. By providing this integrated resource, we aim to encourage the use of alternative online data to explore associations between digital search behavior and official disease incidence, thereby supporting the development of nowcasting models for early outbreak detection to inform timely public health responses and decision-making.
Publisher
Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
Subject
/ Behavior
/ Chikungunya Fever - epidemiology
/ COVID-19
/ Datasets
/ Humanities and Social Sciences
/ Humans
/ Nausea
/ Pain
/ Science
/ Trends
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