Year of Publication
Master of Public Health (M.P.H.)
April Young, PhD, MPH
Erin Abner, PhD, MPH
W. Jay Christian, PhD
Wayne T. Sanderson, PhD, MS, CIH
Aim: To explore and visualize the connectivity of suspected Ebola cases and surveillance callers who used cellphone technology in Moyamba District in Sierra Leone for Ebola surveillance, and to examine the demographic differences and characteristics of callers who make more calls as well as more likely to make at least one positive Ebola call.
Methods: Surveillance data for 393 suspected Ebola cases (192 males, 201 females) were collected from October 23, 2014 to June 28, 2015 using cellphone technology. UCINET and NetDraw were used to explore and visualize the social connectivity between callers and suspected Ebola cases. Poisson and logistic regression analyses were used to determine the factors associated with the number of Ebola surveillance calls made and the likelihood of making at least one positive surveillance call respectively.
Result: The entire social network structure was comprised of 393 ties with 745 nodes covering 253 villages. In multivariable analysis, holding other covariates in the model constant, female gender (AOR=0.33, 95% CI [0.14, 0.81]) was associated with decreased odds of making at least one positive Ebola surveillance call compared to male gender. Also, holding other variables in the model constant, female gender (IR= 0.63, 95% CI [0.49, 0.82]) was associated with making fewer Ebola surveillance calls compared to male gender.
Conclusion: Social network visualization can be used to analyze syndromic surveillance data for Ebola collected by cellphone technology and can yield unique insights. This study show that men made more Ebola surveillance calls than women, and were also more likely to make at least one positive Ebola surveillance call than women.
Kangbai, Jia B., "SOCIAL NETWORK ANALYSIS OF CELLPHONE SURVEILLANCE DATA FOR EBOLA IN SIERRA LEONE" (2016). Theses and Dissertations--Public Health (M.P.H. & Dr.P.H.). 87.