Open Access Highly Accessed Correspondence

Public health triangulation: approach and application to synthesizing data to understand national and local HIV epidemics

George W Rutherford16*, William McFarland12, Hilary Spindler1, Karen White1, Sadhna V Patel3, John Aberle-Grasse3, Keith Sabin35, Nathan Smith14, Stephanie Taché1, Jesus M Calleja-Garcia5 and Rand L Stoneburner1

Author Affiliations

1 Global Health Sciences, University of California, San Francisco, California, USA

2 the San Francisco Department of Public Health, San Francisco, California, USA

3 the Global AIDS Program, Centers for Disease Control and Prevention, Atlanta, Georgia, USA

4 the Public Health Prevention Service, Epidemiology Program Office, Centers for Disease Control and Prevention, Atlanta, Georgia, USA

5 the HIV/AIDS Division, World Health Organization, Geneva, Switzerland

6 ST: Institut für Allgemein-, Familien- und Präventivmedizin, Paracelsus Medizinishce Privatuniversität, Salzburg, Austria, and RLS: the Joint United Nations Programme on HIV/AIDS in Geneva, Switzerland

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BMC Public Health 2010, 10:447  doi:10.1186/1471-2458-10-447

Published: 29 July 2010



Public health triangulation is a process for reviewing, synthesising and interpreting secondary data from multiple sources that bear on the same question to make public health decisions. It can be used to understand the dynamics of HIV transmission and to measure the impact of public health programs. While traditional intervention research and metaanalysis would be ideal sources of information for public health decision making, they are infrequently available, and often decisions can be based only on surveillance and survey data.


The process involves examination of a wide variety of data sources and both biological, behavioral and program data and seeks input from stakeholders to formulate meaningful public health questions. Finally and most importantly, it uses the results to inform public health decision-making. There are 12 discrete steps in the triangulation process, which included identification and assessment of key questions, identification of data sources, refining questions, gathering data and reports, assessing the quality of those data and reports, formulating hypotheses to explain trends in the data, corroborating or refining working hypotheses, drawing conclusions, communicating results and recommendations and taking public health action.


Triangulation can be limited by the quality of the original data, the potentials for ecological fallacy and "data dredging" and reproducibility of results.


Nonetheless, we believe that public health triangulation allows for the interpretation of data sets that cannot be analyzed using meta-analysis and can be a helpful adjunct to surveillance, to formal public health intervention research and to monitoring and evaluation, which in turn lead to improved national strategic planning and resource allocation.