Integration of Spatial and Social Network Analysis in Vaccine Trials

This project develops and tests spatial analytical and social network analysis methods for vaccine trials and disease transmission modeling. Existing methods limit the extrapolation of results and are sometimes of questionable validity. This project builds on earlier work by the investigators that developed theory and methods for incorporating neighborhood-level variables into ecological vaccine trials (Ali et al., 2005, 2008; Emch et al., 2006, 2007). In 1985, a community-based individually randomized oral cholera vaccine trial was conducted in Matlab, Bangladesh. This study is reanalyzing the cholera vaccine trial data using new measures of social and environmental connectivity developed with social network analysis software, a geographic information system (GIS), and satellite remote sensing technologies. These new measures will help determine: (1) how placebo incidence and protective efficacy (PE) vary within social networks; (2) how placebo incidence and PE vary spatially by different environmental contexts; and (3) how spatial, environmental, and social network information can be used simultaneously to assess the effectiveness of vaccines and disease risk. We will use four data sets, already collected by the investigators, including: (1) a large cholera vaccine trial database, (2) a comprehensive longitudinal demographic database from which the vaccine trial participants were selected, (3) an accurate household-level GIS database, and (4) high resolution Quickbird satellite imagery. We are measuring kinship ties between all households using a complete network design as well as environmental connectivity using satellite imagery and GIS techniques. These GIS and satellite databases, in conjunction with the demographic, social network, and vaccine datasets, will facilitate adding integrated spatial, environmental, and social components to this vaccine evaluation study. Reanalyzing the Matlab oral cholera vaccine trial using a spatial analytical framework and social and environmental connectivity measures can give new insight into vaccine effectiveness evaluation and disease transmission modeling. As a result, the theoretical and methodological issues addressed in this project will have important implications for future vaccine trials.

Principal Investigator: Michael E. Emch

Other Investigators: Mohammed Ali (International Vaccine Institute), John Clemens (International Vaccine Institute)

Funding Source: NIH NIAID

Grant Number: R03 AI076748

Funding Period: 9/1/2009 - 9/30/2013

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