Google trends predicts present and future plague cases during the plague outbreak in Madagascar: Infodemiological study

Nicola Luigi Bragazzi*, Naim Mahroum

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

20 Scopus citations


Background: Plague is a highly infectious zoonotic disease caused by the bacillus Yersinia pestis. Three major forms of the disease are known: bubonic, septicemic, and pneumonic plague. Though highly related to the past, plague still represents a global public health concern. Cases of plague continue to be reported worldwide. In recent months, pneumonic plague cases have been reported in Madagascar. However, despite such a long-standing and rich history, it is rather difficult to get a comprehensive overview of the general situation. Within the framework of electronic health (eHealth), in which people increasingly search the internet looking for health-related material, new information and communication technologies could enable researchers to get a wealth of data, which could complement traditional surveillance of infectious diseases. Objective: In this study, we aimed to assess public reaction regarding the recent plague outbreak in Madagascar by quantitatively characterizing the public's interest. Methods: We captured public interest using Google Trends (GT) and correlated it to epidemiological real-world data in terms of incidence rate and spread pattern. Results: Statistically significant positive correlations were found between GT search data and confirmed (R2=0.549), suspected (R2=0.265), and probable (R2=0.518) cases. From a geospatial standpoint, plague-related GT queries were concentrated in Toamasina (100%), Toliara (68%), and Antananarivo (65%). Concerning the forecasting models, the 1-day lag model was selected as the best regression model. Conclusions: An earlier digital Web search reaction could potentially contribute to better management of outbreaks, for example, by designing ad hoc interventions that could contain the infection both locally and at the international level, reducing its spread.

Original languageEnglish
Article numbere13142
JournalJMIR Public Health and Surveillance
Issue number1
StatePublished - Jan 2019


  • Digital surveillance
  • Google trends
  • Infectious outbreaks
  • Infodemiology
  • Infoveillance
  • Nowcasting and forecasting models
  • Plague


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