Internet-based Surveillance Systems and Infectious Diseases Prediction: An Updated Review of the Last 10 Years and Lessons from the COVID-19 Pandemic

The last decade has seen major advances and growth in internet-based surveillance for infectious diseases through advanced computational capacity, growing adoption of smart devices, increased availability of Artificial Intelligence (AI), alongside environmental pressures including climate and land u...

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Published inJournal of Epidemiology and Global Health Vol. 14; no. 3; pp. 645 - 657
Main Authors McClymont, Hannah, Lambert, Stephen B., Barr, Ian, Vardoulakis, Sotiris, Bambrick, Hilary, Hu, Wenbiao
Format Journal Article
LanguageEnglish
Published Dordrecht Springer Netherlands 01.09.2024
Springer
Subjects
Communicable Diseases - epidemiology
COVID-19
COVID-19 - epidemiology
COVID-19 - prevention & control
Dengue
Dengue - diagnosis
Dengue - epidemiology
Early Warning Systems
Humans
Influenza
Influenza, Human - diagnosis
Influenza, Human - epidemiology
Internet
Internet-based Surveillance
Medicine
Medicine & Public Health
mHealth
Pandemics
Population Surveillance - methods
Review
Review Article
SARS-CoV-2
COVID-19
mHealth
Early Warning Systems
Influenza
Dengue
Internet-based Surveillance
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Abstract The last decade has seen major advances and growth in internet-based surveillance for infectious diseases through advanced computational capacity, growing adoption of smart devices, increased availability of Artificial Intelligence (AI), alongside environmental pressures including climate and land use change contributing to increased threat and spread of pandemics and emerging infectious diseases. With the increasing burden of infectious diseases and the COVID-19 pandemic, the need for developing novel technologies and integrating internet-based data approaches to improving infectious disease surveillance is greater than ever. In this systematic review, we searched the scientific literature for research on internet-based or digital surveillance for influenza, dengue fever and COVID-19 from 2013 to 2023. We have provided an overview of recent internet-based surveillance research for emerging infectious diseases (EID), describing changes in the digital landscape, with recommendations for future research directed at public health policymakers, healthcare providers, and government health departments to enhance traditional surveillance for detecting, monitoring, reporting, and responding to influenza, dengue, and COVID-19.
AbstractList Abstract The last decade has seen major advances and growth in internet-based surveillance for infectious diseases through advanced computational capacity, growing adoption of smart devices, increased availability of Artificial Intelligence (AI), alongside environmental pressures including climate and land use change contributing to increased threat and spread of pandemics and emerging infectious diseases. With the increasing burden of infectious diseases and the COVID-19 pandemic, the need for developing novel technologies and integrating internet-based data approaches to improving infectious disease surveillance is greater than ever. In this systematic review, we searched the scientific literature for research on internet-based or digital surveillance for influenza, dengue fever and COVID-19 from 2013 to 2023. We have provided an overview of recent internet-based surveillance research for emerging infectious diseases (EID), describing changes in the digital landscape, with recommendations for future research directed at public health policymakers, healthcare providers, and government health departments to enhance traditional surveillance for detecting, monitoring, reporting, and responding to influenza, dengue, and COVID-19.
The last decade has seen major advances and growth in internet-based surveillance for infectious diseases through advanced computational capacity, growing adoption of smart devices, increased availability of Artificial Intelligence (AI), alongside environmental pressures including climate and land use change contributing to increased threat and spread of pandemics and emerging infectious diseases. With the increasing burden of infectious diseases and the COVID-19 pandemic, the need for developing novel technologies and integrating internet-based data approaches to improving infectious disease surveillance is greater than ever. In this systematic review, we searched the scientific literature for research on internet-based or digital surveillance for influenza, dengue fever and COVID-19 from 2013 to 2023. We have provided an overview of recent internet-based surveillance research for emerging infectious diseases (EID), describing changes in the digital landscape, with recommendations for future research directed at public health policymakers, healthcare providers, and government health departments to enhance traditional surveillance for detecting, monitoring, reporting, and responding to influenza, dengue, and COVID-19.
Author Vardoulakis, Sotiris
Barr, Ian
McClymont, Hannah
Hu, Wenbiao
Lambert, Stephen B.
Bambrick, Hilary
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Keywords COVID-19
mHealth
Early Warning Systems
Influenza
Dengue
Internet-based Surveillance
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Snippet The last decade has seen major advances and growth in internet-based surveillance for infectious diseases through advanced computational capacity, growing...
Abstract The last decade has seen major advances and growth in internet-based surveillance for infectious diseases through advanced computational capacity,...
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SubjectTerms Communicable Diseases - epidemiology
COVID-19
COVID-19 - epidemiology
COVID-19 - prevention & control
Dengue
Dengue - diagnosis
Dengue - epidemiology
Early Warning Systems
Humans
Influenza
Influenza, Human - diagnosis
Influenza, Human - epidemiology
Internet
Internet-based Surveillance
Medicine
Medicine & Public Health
mHealth
Pandemics
Population Surveillance - methods
Review
Review Article
SARS-CoV-2
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Title Internet-based Surveillance Systems and Infectious Diseases Prediction: An Updated Review of the Last 10 Years and Lessons from the COVID-19 Pandemic
URI https://link.springer.com/article/10.1007/s44197-024-00272-y
https://www.ncbi.nlm.nih.gov/pubmed/39141074
https://pubmed.ncbi.nlm.nih.gov/PMC11442909
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Volume 14
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