Using substitute workers for sick staff spreads disease, study finds
US research shows replacement workers are at higher risk of illness
Infectious diseases would spread faster due to placing a healthy person in a situation where he or she could become infected as well. Photograph: Getty Images/iStockphoto
The common policy of replacing a teacher or a health worker with a substitute when they are sick could help to increase the spread of disease, a new study has found.
While this result may appear counterintuitive, the authors back up their analysis of mathematical models of the spread of disease with data from past outbreaks. The study was led by Prof Samuel Scarpino from Santa Fe Institute in the US*.
“The findings show that a common-sense response during outbreaks could in fact be adding to the problem,” said Prof Lina Zgaga, Associate Professor of Epidemiology at Trinity College Dublin Centre for Health Sciences.
The results could help develop better public health policies during outbreaks, the authors say. For example, vaccinating key workers could significantly decrease the danger of disease spreading faster.
Replacement workers are shown by the results to be clearly at higher risk of illness, and this should also be addressed accordingly.
“I have no doubt this study has important implications for future planning around disease outbreaks,” said Prof Zgaga.
The results are published this week in the scientific journal Nature Physics.
The researchers used a mathematical model of how disease spreads, comparing a situation where a sick key worker - such as a teacher or a health worker - is replaced by a healthy substitute and one where this does not happen.
The model evaluating the replacement situation resulted in faster spreading of disease and increased epidemic size.
Comparing their mathematical model to recorded data from past outbreaks of two different diseases, the authors of the study found a similar pattern.
“I think in the scientific community whenever you mention the word model people become immediately suspicious,” said Prof Zgaga. However, she pointed out that in this case the results from the model were supported by observational data gathered over long periods of time.
*This article was edited on Monday, August 2nd to include the reference to Prof Samuel Scarpino from Santa Fe Institute in the US who led the study.