PAOLO BOCCHINI professor of civil and environmental engineering, is one of the study’s leaders. R E S E A R C H Predicting the Next Ebola Outbreak Study shows individual risk-factor data could help predict an outbreak West Africa was human interaction with bats. Now members of the team have examined how social and economic factors, such as a person’s level of education and general knowledge of Ebola, might contribute to “high-risk behaviors” 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 ofcials better target prevention and education resources, the researchers say. “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 environmenA team of scientists at Lehigh developed a predictive model several years ago to accurately forecast Ebola outbreaks based on climate-driven bat migration. Ebola, a serious and sometimes-deadly infectious disease, is zoonotic, or enters a human population via interaction with animals. It is widely believed that the source of the 2014 Ebola outbreak in tal engineering at “WE CONFIRMED A RELATIONSHIP Lehigh and one of the study’s lead- BETWEEN SOCIAL, ECONOMIC AND DEMOers. “Our results GRAPHIC FACTORS AND THE PROPENSITY show that it is indeed possible to FOR INDIVIDUALS TO ENGAGE IN BEHAVIORS calibrate a model to predict, with a THAT EXPOSE THEM TO EBOLA SPILLOVER.” reasonable level of accuracy, the propensity of an individual to engage in high-risk behaviors.” For example, the team’s data and analyses suggested Kailahun, a town in eastern Sierra Leone, and Kambia in the northern part of the country, as the rural districts in the country with the highest likelihood of infection spillover, based on individual risk factors accurately identifying the location, Kailahun, where the 2014 Ebola epidemic is believed to have originated. The results are detailed in “Estimation of Ebola’s spillover infection exposure in Sierra Leone based on sociodemographic and economic factors,” published in PLOS ONE. Additional authors include Lehigh graduate student Sena Mursel; undergraduate students Nathaniel Alter, Lindsay Slavit and Anna Smith; and Javier Buceta, a facultymember at the Institute for Integrative Systems Biology in Valencia, Spain. Among the fndings: Young adults (ages between 18-34) and adults (ages between 34-50) were most at risk in the population they studied. This group constituted 77% of the investigated sample, but 86% of the respondents were at risk. In addition, those with agricultural jobs were among the most at risk: 50% of the study respondents have an agriculture-related occupation but represent 79% of respondents at risk. “We confrmed a relationship between social, economic and demographic factors and the propensity for individuals to engage in behaviors that expose them to Ebola spillover,” says Bocchini. “We also calibrated a preliminary model that quantifes this relationship.” Residents of the town of Kailahun gather along a river at dusk. The authors say these results point to the need for a holistic approach for any model seeking to accurately predict disease outbreaks. Their fndingsmay also be useful to population health ofcials, whomay be able to use suchmodels to better focus scarce resources. “One has to look at the big picture,” says Bocchini. “We collected satel- —PAOLO BOCCHINI lite images that showed the evolution of enviro-climatic data and combined them with ecological models and random feld models to capture the spatial and temporal fuctuations of natural resources and the resulting continentwide migrations of infected animal carriers. We also studied the human population’s social, economic, demographic and behavioral characteristics, integrating everything to obtain our predictions. “Only this broad perspective and interdisciplinary approach can truly capture these dynamics, and with this line of research, we are proving that it works,” he adds. Buceta says, “In the end, the conclusions of our study are not that surprising: 1 6 | L E H I G H B U L L E T I N
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