A Canadian researcher is one of four scientists raising the issue that Ebola may be silently immunizing large numbers of people, who never fall ill or infect others yet become protected from future infection. Their letter was published in the medical journal The Lancet.

If true, this finding could have significant ramifications for both projections of how widespread the disease will be, and strategies policy makers and health workers should use to contain the disease, say the authors.

McMaster University's Jonathan Dushoff, an associate professor of biology and an investigator with the Michael G. DeGroote Institute for Infectious Disease Research, is one of the authors with principal author Steve Bellan of The University of Texas at Austin and others from UT Austin and the University of Florida. They call on public health authorities to determine how commonplace it is for people to be infected by Ebola without ever developing symptoms or spreading the disease and whether these individuals are then protected from future infection.

"Although resources on the ground are scarce, now is the best time to learn more about immunity to Ebola, and the sooner we know the sooner the knowledge can be used to stop the epidemic," said Dushoff.

Bellan said: "Ultimately, knowing whether a large segment of the population in the afflicted regions is immune to Ebola could save lives. If we can reliably identify who they are, they could become people who help with disease-control tasks, and that would prevent exposing others who aren't immune. We might not have to wait until we have a vaccine to use immune individuals to reduce the spread of disease."

The letter notes that researchers have found evidence of asymptomatic Ebola infection in the aftermath of earlier Ebola outbreaks, but it is yet unknown whether such infection provides immunity. The authors conclude that resolving this question and identifying naturally immunized individuals could prove critical in public health efforts to contain the disease, as well as in accurately estimating the likely spread of the disease.