Using health surveillance systems data to assess the impact of AIDS and antiretroviral treatment on adult morbidity and mortality in Botswana

Introduction: Botswana's AIDS response included free antiretroviral treatment (ART) since 2002, achieving 80% coverage of persons with CD450% and >30% through 2011, while continuing to increase in older women. Conclusions: Adult mortality in Botswana fell markedly as ART coverage increased. HIV prevalence declines may reflect ART-associated reductions in sexual transmission. Triangulation of surveillance system data offers a reasonable approach to evaluate impact of HIV/AIDS interventions, complementing cohort approaches that monitor individual-level health outcomes

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

<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Methods</p> <p>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.</p> <p>Results</p> <p>Triangulation can be limited by the quality of the original data, the potentials for ecological fallacy and "data dredging" and reproducibility of results.</p> <p>Conclusions</p> <p>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.</p

Outcomes and Impact of HIV Prevention, ART and TB Programs in Swaziland - Early Evidence from Public Health Triangulation

<p>Introduction: Swaziland's severe HIV epidemic inspired an early national response since the late 1980s, and regular reporting of program outcomes since the onset of a national antiretroviral treatment (ART) program in 2004. We assessed effectiveness outcomes and mortality trends in relation to ART, HIV testing and counseling (HTC), tuberculosis (TB) and prevention of mother to child transmission (PMTCT).</p><p>Methods: Data triangulated include intervention coverage and outcomes according to program registries (2001-2010), hospital admissions and deaths disaggregated by age and sex (2001-2010) and population mortality estimates from the 1997 and 2007 censuses and the 2007 demographic and health survey.</p><p>Results: By 2010, ART reached 70% of the estimated number of people living with HIV/AIDS with CD4</p><p>Conclusion: Against a background of high, but stable HIV prevalence and decreasing HIV incidence, we documented early evidence of a mortality decline associated with the expanded national HIV response since 2004. Attribution of impact to specific interventions (versus natural epidemic dynamics) will require additional data from future household surveys, and improved routine (program, surveillance, and hospital) data at district level.</p>