New Delhi, Dec 18 (IANS): Earlier this month, Uganda announced that the last known patient of the Ebola outbreak that surfaced there in mid-September had recovered, giving hope that the sudden spread of the virus has slowed dramatically, if not stopped altogether.

The Ebola spillover risk, however, is still high.

It is widely believed that the source of the 2014 Ebola outbreak in West Africa, which killed more than 11,000 people, was human interaction with bats, and the sudden Ebola outbreak worried the world, as it still navigates through the pandemic.

According to Science magazine, when the new Ebola cases surfaced, several vaccines for the Sudan ebolavirus were in development, and Ugandan health officials on December 2 approved testing three candidates. But at the start of the outbreak, no manufacturer had enough doses in vials to ship.

The Uganda outbreak highlights the need for a more streamlined outbreak response system.

Several years ago, a team of scientists at Lehigh University in the US developed a predictive model to accurately forecast Ebola outbreaks based on climate-driven bat migration.

Ebola is a serious and sometimes deadly infectious disease that is zoonotic, or enters a human population via interaction with animals.

Now, members of the team have examined how social and economic factors, such as level of education and general knowledge of Ebola, might contribute to "high-risk behaviours" that may bring individuals into contact with potentially infected animals.

A focus on geographical locations with high concentrations of individuals at high-risk could help public health officials better target prevention and education resources.

"We created a survey that combined the collection of social, demographic and economic data with questions related to general knowledge of Ebola transmission and potentially high-risk behaviors," says Paolo Bocchini, professor of civil and environmental engineering at Lehigh and one of the study's leaders.

The results are detailed in a paper which will soon be published in PLOS ONE. Young adults (ages between 18-34) and adults (ages between 34-50) were most at risk in the population they studied.

"We confirmed a relationship between social, economic and demographic factors and the propensity for individuals to engage in behaviours that expose them to Ebola spillover," says Bocchini. "We also calibrated a preliminary model that quantifies this relationship."

The authors say these results point to the need for a holistic approach for any model seeking to accurately predict disease outbreaks.

Their findings may also be useful for population health officials, who may be able to use such models to better focus scarce resources.