ArticlePathogens and global health2020
Forecasting tuberculosis using diabetes-related google trends data.
Article in Pathogens and global health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Machine Learning Used in Communicable Disease Control: A Scoping Review.Public health reviews · 2026Pooled it
- Highly Fluorescent ZnO Composite of N-doped Carbon Dots From Dregea Volubilis for Fluorometric Determination of Glucose in Biological Samples.Journal of fluorescence · 2025Article
- Decreased online hepatitis information seeking during the COVID-19 pandemic: an Infodemiology study.Journal of preventive medicine and hygiene · 2022Article
- A Co-Doped Carbon Dot/Silver Nanoparticle Nanocomposite-Based Fluorescence Sensor for Metformin Hydrochloride Detection.Nanomaterials (Basel, Switzerland) · 2022Article
- Article
- Impact of the World Inflammatory Bowel Disease Day and Crohn's and Colitis Awareness Week on Population Interest Between 2016 and 2020: Google Trends Analysis.JMIR infodemiologyArticle
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Online activity-based data can be used to aid infectious disease forecasting. Our aim was to exploit the converging nature of the tuberculosis (TB) and diabetes epidemics to forecast TB case numbers. Thus, we extended TB prediction models based on traditional data with diabetes-related Google searches. We obtained data on the weekly case numbers of TB in Germany from June 8
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.