Skip to main content
 

Capacity building, collaboration, and measuring the impact of FIC’s Division of International Epidemiology & Population Studies: A bibliometric analysis

Thursday, September 15, 2016 — Poster Session II

12:00 p.m. – 1:30 p.m.
FAES Terrace
OD
RSCHSUPP-19

Authors

  • AA Livinski
  • C Viboud

Abstract

The Division of International Epidemiology & Population Studies (DIEPS) acts as the informal intramural research program for FIC. Its major research programs (completed or on-going) include: Multinational Influenza Seasonal Mortality Study (MISMS), Research and Policy for Infectious Disease Dynamics (RAPIDD), and MAL-ED (MALnutrition and Enteric Diseases), focused on research in epidemiology and mathematical modeling of infectious diseases. A bibliometric analysis was conducted in April 2016 to analyze publications authored by FIC/DIEPS staff from 2009–2015. The analysis attempted to identify authors, institutions, and countries that publish with FIC/DIEPS staff, provide a snapshot of DIEPS’s international collaborations and capacity building efforts, and ascertain contributions to epidemiology and modeling. PubMed/MEDLINE and Web of Science databases were searched resulting in 927 retrieved publications, which were cited 21,330 times. Of these 927, results were limited to publications that have at least one non-USA author (n=665). World Bank Country and Lending categories were used to organize results and visualize country co-authorship. Excluding the USA, the countries FIC/DIEPS-affiliated authors were from included middle (10), lower-middle (15), and low income economies (10) ranging from China to Nicaragua to Ethiopia. Of the top 30 non-USA institutions of affiliated authors, Ministries of Health, Institut Pasteur, ICDDR,b, Autonomous National University Mexico, Witwatersrand University, Venda University, and Aga Khan University were from lower-middle and low income economies. The range of co-author countries and institutions demonstrates FIC/DIEPS’s fostering of linkages, training reach, and global capacity building to promote and improve use of disease modeling tools for evidence-based policy and decision-making.

Category: Research Support Services