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Using geospatial social media data for infectious disease studies: a systematic review

  • Fengrui Jing
  • , Zhenlong Li
  • , Shan Qiao
  • , Jiajia Zhang
  • , Banky Olatosi
  • , Xiaoming Li

Research output: Contribution to journalReview articlepeer-review

Abstract

Geospatial social media (GSM) data has been increasingly used in public health due to its rich, timely, and accessible spatial information, particularly in infectious disease research. This review synthesized 86 research articles that use GSM data in infectious diseases published between December 2013 and March 2022. These articles cover 12 infectious disease types ranging from respiratory infectious diseases to sexually transmitted diseases with spatial levels varying from the neighborhood, county, state, and country. We categorized these studies into three major infectious disease research domains: surveillance, explanation, and prediction. With the assistance of advanced computing, statistical and spatial methods, GSM data has been widely and deeply applied to these domains, particularly in surveillance and explanation domains. We further identified four knowledge gaps in terms of contextual information use, application scopes, spatiotemporal dimension, and data limitations and proposed innovation opportunities for future research. Our findings will contribute to a better understanding of using GSM data in infectious diseases studies and provide insights into strategies for using GSM data more effectively in future research.

Original languageEnglish (US)
Pages (from-to)130-157
Number of pages28
JournalInternational Journal of Digital Earth
Volume16
Issue number1
DOIs
StatePublished - 2023

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Science Applications
  • General Earth and Planetary Sciences

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