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

Hannah McClymont; Stephen B Lambert; Ian Barr; Sotiris Vardoulakis; Hilary Bambrick; Wenbiao Hu

doi:10.1007/s44197-024-00272-y

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

J Epidemiol Glob Health. 2024 Sep;14(3):645-657. doi: 10.1007/s44197-024-00272-y. Epub 2024 Aug 14.

Authors

Hannah McClymont¹, Stephen B Lambert^{2

3}, Ian Barr^{4

5}, Sotiris Vardoulakis^{6

7}, Hilary Bambrick⁸, Wenbiao Hu^{9

10}

Affiliations

¹ Ecosystem Change and Population Health (ECAPH) Research Group, School of Public Health and Social Work, Queensland University of Technology (QUT), Brisbane, Australia.
² Communicable Diseases Branch, Queensland Health, Brisbane, Australia.
³ National Centre for Immunisation Research and Surveillance, Sydney Children's Hospitals Network, Westmead, Australia.
⁴ WHO Collaborating Centre for Reference and Research on Influenza, The Peter Doherty Institute for Infection and Immunity, Melbourne, Australia.
⁵ Department of Microbiology and Immunology, University of Melbourne, Melbourne, Australia.
⁶ Health Research Institute, University of Canberra, Canberra, Australia.
⁷ Healthy Environments and Lives (HEAL) National Research Network, Canberra, Australia.
⁸ National Centre for Epidemiology and Population Health, College of Health and Medicine, The Australian National University, Canberra, Australia.
⁹ Ecosystem Change and Population Health (ECAPH) Research Group, School of Public Health and Social Work, Queensland University of Technology (QUT), Brisbane, Australia. w2.hu@qut.edu.au.
¹⁰ Healthy Environments and Lives (HEAL) National Research Network, Canberra, Australia. w2.hu@qut.edu.au.

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.

Keywords: COVID-19; Dengue; Early Warning Systems; Influenza; Internet-based Surveillance; mHealth.

Publication types

Systematic Review

MeSH terms

COVID-19* / epidemiology
COVID-19* / prevention & control
Communicable Diseases / epidemiology
Dengue / diagnosis
Dengue / epidemiology
Epidemiological Monitoring*
Humans
Influenza, Human / diagnosis
Influenza, Human / epidemiology
Internet*
Pandemics
SARS-CoV-2