A new ESR study has found that internet searches, Healthline calls and school absenteeism data could alert health officials to a disease outbreak days ahead of other systems.
The ESR researchers used the 2016 Havelock North Campylobacter outbreak to investigate whether these alternative data sources could have provided an earlier indication of the campylobacter cases in the community – and the results were conclusive.
The 2016 campylobacter outbreak began on August 8, but the full extent of the outbreak was not known until August 14. Researchers’ modelling found that they could have detected an increase in cases up to five days before the outbreak was detected via traditional pathways.
Lead author, ESR’s Dr Mehnaz Adnan says the data may have allowed for an earlier intervention to curb transmission in the community.
“Early outbreak detection and magnitude prediction is critical to outbreak control, but with any disease surveillance system, there are unavoidable delays before an outbreak can be detected and the community protected. It can take a number of days between someone becoming infected, developing symptoms, seeking healthcare and a case being diagnosed and notified to health authorities. During this time people might use Google searches of their symptoms or call Healthline – and we can use that information.
“As previous studies have suggested, we wanted to see if we could utilise this data as an early signal to alert health officials earlier, enabling them to investigate potential outbreak sources ahead of traditional methods.”
Dr Adnan says they are not advocating to replace traditional methods, but rather to complement them.
“These model predictions could fill a critical time-gap in existing surveillance based on notification of cases of disease. ESR are stewards of the national notifiable disease surveillance system, EpiSurv, so we are best placed to investigate how we could support and enhance this system in the future. In this case we have done this by investigating alternative data sources and evaluated their potential for recognising 2016 Havelock North Campylobacter outbreak at an earlier time.”
The researchers warn that further work is required to assess the place of such surveillance data sources and methods in routine public health practice.
“A number of key questions will need to be systematically investigated to establish the practical role of these methods and how they could be most effectively integrated into routine public health practice,” Dr Adnan says. “There are a number of hurdles, this type of non-traditional surveillance carries with it the workload required to interpret and respond to signals, which can be extensive.”
The paper Potential Early Identification of a Large Campylobacter Outbreak Using Alternative Surveillance Data Sources: Autoregressive Modelling and Spatiotemporal Clustering was published in JMIR Public Health and Surveillance.
The Health Research Council funded study included authors from Victoria University of Wellington, the Hawkes Bay District Health Board and the University of Otago.