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Refining a probabilistic model for interpreting verbal autopsy data.
Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Epidemiology and Public Health Sciences. Epidemiologi och folkhälsovetenskap.ORCID iD: 0000-0001-5474-4361
Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Epidemiology and Public Health Sciences. Epidemiologi och folkhälsovetenskap.
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2006 (English)In: Scandinavian journal of public health, ISSN 1403-4948, Vol. 34, no 1, 26-31 p.Article in journal (Refereed) Published
Place, publisher, year, edition, pages
2006. Vol. 34, no 1, 26-31 p.
Keyword [en]
Autopsy/methods, Bayes Theorem, Cause of Death, Coroners and Medical Examiners, Data Collection/methods, Data Interpretation; Statistical, Developing Countries, Humans, Models; Statistical, Reproducibility of Results, Speech, Vietnam
URN: urn:nbn:se:umu:diva-14119DOI: 10.1080/14034940510032202PubMedID: 16449041OAI: diva2:153790
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]


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.


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.


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.


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.
Umeå University medical dissertations, ISSN 0346-6612 ; 1152
mortality, surveillance, verbal autopsy, survey methods
National Category
Public Health, Global Health, Social Medicine and Epidemiology
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)
Available from: 2008-02-14 Created: 2008-02-14 Last updated: 2010-01-11Bibliographically approved

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