Dataset Information

Modeling health impact of global health programs implemented by Population Services International.

ABSTRACT:

Background

Global health implementing organizations benefit most from health impact estimation models that isolate the individual effects of distributed products and services - a feature not typically found in intervention impact models, but which allow comparisons across interventions and intervention settings. Population Services International (PSI), a social marketing organization, has developed a set of impact models covering seven health program areas, which translate product/service distribution data into impact estimates. Each model's primary output is the number of disability-adjusted life-years (DALYs) averted by an intervention within a specific country and population context. This paper aims to describe the structure and inputs for two types of DALYs averted models, considering the benefits and limitations of this methodology.

Methods

PSI employs two modeling approaches for estimating health impact: a macro approach for most interventions and a micro approach for HIV, tuberculosis (TB), and behavior change communication (BCC) interventions. Within each intervention country context, the macro approach determines the coverage that one product/service unit provides a population in person-years, whereas the micro approach estimates an individual's risk of infection with and without the product/service unit. The models use these estimations to generate per unit DALYs averted coefficients for each intervention. When multiplied by program output data, these coefficients predict the total number of DALYs averted by an intervention in a country.

Results

Model outputs are presented by country for two examples: Water Chlorination DALYs Averted Model, a macro model, and the HIV Condom DALYs Averted Model for heterosexual transmission, a micro model. Health impact estimates measured in DALYs averted for PSI interventions on a global level are also presented.

Conclusions

The DALYs averted models offer implementing organizations practical measurement solutions for understanding an intervention's contribution to improving health. These models calculate health impact estimates that reflect the scale and diversity of program operations and intervention settings, and that enable comparisons across health areas and countries. Challenges remain in accounting for intervention synergies, attributing impact to a single organization, and sourcing and updating model inputs. Nevertheless, these models demonstrate how DALYs averted can be viably used by the global health community as a metric for predicting intervention impact using standard program output data.

SUBMITTER: Yang H

PROVIDER: S-EPMC3684543 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Modeling health impact of global health programs implemented by Population Services International.

Yang Hongmei H Duvall Susan S Ratcliffe Amy A Jeffries David D Stevens Warren W

BMC public health 20130617

<h4>Background</h4>Global health implementing organizations benefit most from health impact estimation models that isolate the individual effects of distributed products and services - a feature not typically found in intervention impact models, but which allow comparisons across interventions and intervention settings. Population Services International (PSI), a social marketing organization, has developed a set of impact models covering seven health program areas, which translate product/servic ...[more]

PMID: 23902668

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Project description:Background"Decolonizing global health" (DGH) may help global health trainees understand and remediate the effects of historical colonialism on global health, but little is known regarding how trainees perceive DGH. Understanding their perspectives is critical for designing educational interventions tailored to their needs.ObjectivesTo understand how trainees perceive DGH research and to determine if perspectives differ between trainees from high- (HICs) versus low- and middle-income countries (LMICs).MethodsAn online survey of all 2017-2022 pre-doctoral and post-doctoral trainees (n = 111) and mentors (n = 91) within a multi-university program that supports US and international investigators in one-year mentored global health research. The survey evaluated individuals' self-reported knowledge and attitudes toward DGH and their perceptions of historical colonialism's impact on eight aspects of global health.FindingsThe response rate to trainee surveys was 56%. Trainees from LMICs were less aware of the concept of DGH; 5/25 (20%) had never heard of DGH and 16/25 (64%) reported that they "know a little," whereas all HIC trainees had heard of DGH and 29/36 (81%) reported that they "know a little" (p = 0.019). For three aspects of global health (i.e., which research questions get asked; development of collaborative relationships; and data/statistical analyses), trainees from LMICs were more likely to report positive effects of colonialism. However, in open-ended responses, no thematic differences existed between how LMIC and HIC trainees defined DGH (i.e., actively eliminating power imbalances; prioritizing local needs; promoting local leadership; providing equitable opportunities; and ensuring programs are culturally appropriate).ConclusionsDifferent perspectives surrounding what DGH means suggest a shared understanding may be needed and is arguably prerequisite to designing educational interventions to help global health trainees recognize, understand, and act in global health. Future research is needed to understand perspectives on decolonization across diverse contexts with attention to constructs such as race, ethnicity, and gender.

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Dataset Information

Modeling health impact of global health programs implemented by Population Services International.

Background

Methods

Results

Conclusions

Publications

Modeling health impact of global health programs implemented by Population Services International.

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