Genetic and social network analysis to target interventions for malaria elimination

This proposed award will support the career development of Dr. Jennifer Smith, an Assistant Adjunct Professor in the Department of Epidemiology and Biostatistics at the University of California, San Francisco (UCSF). Dr. Smith’s career goal is to become an independent researcher with combined expertise in parasite genotyping and human network analyses to optimize interventions for infectious disease elimination. To support her career development, this application proposes a study that leverages data collected as part of ongoing research in malaria high-risk populations and uses novel genetic and social network analyses to address an urgent challenge preventing achievement of malaria elimination targets. As malaria transmission declines, an increasingly large proportion of the parasite reservoir is clustered in specific sub-populations with high exposure to infection and who often face significant barriers to accessing and utilizing malaria interventions. While normative bodies like the World Health Organization recommend a targeted response in known malaria high-risk populations, there is limited evidence on the extent to which these populations drive transmission, the impact of targeted interventions or how to optimize coverage. Through cross-sectional and temporal analysis of genetic and social network data collected as part of an existing, separately funded population-based evaluation of targeted malaria interventions in high-risk populations, this project proposes to investigate genetic connectivity between infections in migrant and resident populations and the role social networks play in uptake of malaria interventions.

This study will provide crucial knowledge on how malaria high-risk populations contribute to transmission dynamics, inform how social networks can be leveraged to improve intervention uptake, and quantify the impact of targeted interventions on overall transmission. The proposed research will build on Dr. Smith’s foundation in epidemiologic methods and include a 5-year training plan including mentorship from leaders in genetic and malaria epidemiology, social network analysis and mathematical modelling at UCSF, University of Southern California and UC Berkeley. 

This study will apply novel genetic and social network analyses to survey data from malaria high-risk populations in Namibia to understand parasite and human connectivity and infer small scale malaria transmission patterns, intervention uptake, and potential impact of targeted intervention approaches. Results of this research will provide critical information whether targeted interventions in malaria high-risk populations hold promise for malaria elimination in this context and provide a template for tailoring interventions to optimize coverage and impact

Grant details

Enabling Technologies & Assays
Measurement of Transmission

Jul 2020 — Jun 2025

$144,939

Namibia
United States