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Revealing the burden of maternal mortality: a probabilistic model for determining pregnancy-related causes of death from verbal autopsies
Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Epidemiology and Global Health.
Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Epidemiology and Global Health.ORCID iD: 0000-0001-5474-4361
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2007 (English)In: Population Health Metrics, ISSN 1478-7954, Vol. 5, no 1Article in journal (Refereed) Published
Abstract [en]

Background: Substantial reductions in maternal mortality are called for in Millennium Development Goal 5 (MDG-5), thus assuming that maternal mortality is measurable. A key difficulty is attributing causes of death for the many women who die unaided in developing countries. Verbal autopsy (VA) can elicit circumstances of death, but data need to be interpreted reliably and consistently to serve as global indicators. Recent developments in probabilistic modelling of VA interpretation are adapted and assessed here for the specific circumstances of pregnancy-related death.

Methods: A preliminary version of the InterVA-M probabilistic VA interpretation model was developed and refined with adult female VA data from several sources, and then assessed against 258 additional VA interviews from Burkina Faso. Likely causes of death produced by the model were compared with causes previously determined by local physicians. Distinction was made between free-text and closed-question data in the VA interviews, to assess the added value of free-text material on the model's output.

Results: Following rationalisation between the model and physician interpretations, cause-specific mortality fractions were broadly similar. Case-by-case agreement between the model and any of the reviewing physicians reached approximately 60%, rising to approximately 80% when cases with a discrepancy were reviewed by an additional physician. Cardiovascular disease and malaria showed the largest differences between the methods, and the attribution of infections related to pregnancy also varied. The model estimated 30% of deaths to be pregnancy-related, of which half were due to direct causes. Data derived from free-text made no appreciable difference.

Conclusion: InterVA-M represents a potentially valuable new tool for measuring maternal mortality in an efficient, consistent and standardised way. Further development, refinement and validation are planned. It could become a routine tool in research and service settings where levels and changes in pregnancy-related deaths need to be measured, for example in assessing progress towards MDG-5.

Place, publisher, year, edition, pages
BioMed Central, 2007. Vol. 5, no 1
National Category
Public Health, Global Health, Social Medicine and Epidemiology Obstetrics, Gynecology and Reproductive Medicine
Identifiers
URN: urn:nbn:se:umu:diva-14131DOI: 10.1186/1478-7954-5-1PubMedID: 17288607OAI: oai:DiVA.org:umu-14131DiVA: diva2:153802
Available from: 2008-09-08 Created: 2008-09-08 Last updated: 2015-04-29Bibliographically approved
In thesis
1. Dying to count: mortality surveillance methods in resource-poor settings
Open this publication in new window or tab >>Dying to count: mortality surveillance methods in resource-poor settings
2008 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Background

Mortality data are critical to understanding and monitoring changes in population health status over time. Nevertheless, the majority of people living in the world’s poorest countries, where the burden of disease is highest, remain outside any kind of systematic health surveillance. This lack of routine registration of vital events, such as births and deaths, constitutes a major and longstanding constraint on the understanding of patterns of health and disease and the effectiveness of interventions. Localised sentinel demographic and health surveillance strategies are a useful surrogate for more widespread surveillance in such settings, but rigorous, evidence-based methodologies for sample-based surveillance are weak and by no means standardised. This thesis aims to describe, evaluate and refine methodological approaches to mortality measurement in resource-poor settings.

Methods

Through close collaboration with existing community surveillance operations in a range of settings, this work uses existing data from demographic surveillance sites and community-based surveys using various innovative approaches in order to evaluate and refine methodological approaches to mortality measurement and cause-of-death determination. In doing so, this work explores the application of innovative techniques and procedures for mortality surveillance in relation to the differing needs of those who use mortality data, ranging from global health organisations to local health planners.

Results

Empirical modelling of sampling procedures in community-based surveys in rural Africa and of random errors in longitudinal data collection sheds light on the effects of various data-capture and quality-control procedures and demonstrates the representativeness and robustness of population surveillance datasets. The development, application and refinement of a probabilistic approach to determining causes of death at the population level in developing countries has shown promise in overcoming the longstanding limitations and issues of standardisation of existing methods. Further adaptation and application of this approach to measure maternal deaths has also been successful. Application of international guidelines on humanitarian crisis detection to mortality surveillance in Ethiopia demonstrates that simple procedures can and, from an ethical perspective, should be applied to sentinel surveillance methods for the prospective detection of important mortality changes in vulnerable populations.

Conclusion

Mortality surveillance in sentinel surveillance systems in resource-poor settings is a valuable and worthwhile task. This work contributes to the understanding of the effects of different methods of surveillance and demonstrates that, ultimately, the choice of methods for collecting data, assuring data quality and determining causes of death depends on the specific needs and requirements of end users. Surveillance systems have the potential to contribute substantially to developing health care systems in resource-poor countries and should not only be considered as research-oriented enterprises.

Place, publisher, year, edition, pages
Umeå: Epidemiologi och folkhälsovetenskap, 2008. 66 p.
Series
Umeå University medical dissertations, ISSN 0346-6612 ; 1152
Keyword
mortality, surveillance, verbal autopsy, survey methods
National Category
Public Health, Global Health, Social Medicine and Epidemiology
Identifiers
urn:nbn:se:umu:diva-1544 (URN)978-91-7264-500-4 (ISBN)
Public defence
2008-02-29, sal 135, 9A, Norrlands Universitetssjukhus, Umeå, 13:00 (English)
Opponent
Supervisors
Available from: 2008-02-14 Created: 2008-02-14 Last updated: 2010-01-11Bibliographically approved

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Fottrell, EdwardByass, PeterHögberg, Ulf

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