| 11. |
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| 12. |
- Filippi, Véronique, et al.
(författare)
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Effects of severe obstetric complications on women's health and infant mortality in Benin
- 2010
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Ingår i: Tropical medicine & international health. - : Wiley. - 1360-2276 .- 1365-3156. ; 15:6, s. 733-742
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Tidskriftsartikel (refereegranskat)abstract
- Women in developing countries face a high risk of severe complications during pregnancy and delivery. These can lead to adverse consequences for their own health and that of their offspring. Resources are needed to ensure that pregnant women receive adequate care before, during and after discharge from hospital. Near-miss women with a perinatal death appear a particularly high-risk group.
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| 13. |
- Fottrell, Edward, et al.
(författare)
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A probabilistic method to estimate the burden of maternal morbidity in resource-poor settings : preliminary development and evaluation
- 2014
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Ingår i: Emerging Themes in Epidemiology. - : BioMed Central (BMC). - 1742-7622. ; 11:1, s. 3-
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Maternal morbidity is more common than maternal death, and population-based estimates of the burden of maternal morbidity could provide important indicators for monitoring trends, priority setting and evaluating the health impact of interventions. Methods based on lay reporting of obstetric events have been shown to lack specificity and there is a need for new approaches to measure the population burden of maternal morbidity. A computer-based probabilistic tool was developed to estimate the likelihood of maternal morbidity and its causes based on self-reported symptoms and pregnancy/delivery experiences. Development involved the use of training datasets of signs, symptoms and causes of morbidity from 1734 facility-based deliveries in Benin and Burkina Faso, as well as expert review. Preliminary evaluation of the method compared the burden of maternal morbidity and specific causes from the probabilistic tool with clinical classifications of 489 recently-delivered women from Benin, Bangladesh and India.RESULTS: Using training datasets, it was possible to create a probabilistic tool that handled uncertainty of women's self reports of pregnancy and delivery experiences in a unique way to estimate population-level burdens of maternal morbidity and specific causes that compared well with clinical classifications of the same data. When applied to test datasets, the method overestimated the burden of morbidity compared with clinical review, although possible conceptual and methodological reasons for this were identified.CONCLUSION: The probabilistic method shows promise and may offer opportunities for standardised measurement of maternal morbidity that allows for the uncertainty of women's self-reported symptoms in retrospective interviews. However, important discrepancies with clinical classifications were observed and the method requires further development, refinement and evaluation in a range of settings.
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| 14. |
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| 15. |
- Fottrell, Edward, et al.
(författare)
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Demonstrating the robustness of population surveillance data : implications of error rates on demographic and mortality estimates
- 2008
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Ingår i: BMC Medical Research Methodology. - : BioMed Central. - 1471-2288. ; 8, s. Article nr 13-
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: As in any measurement process, a certain amount of error may be expected in routine population surveillance operations such as those in demographic surveillance sites (DSSs). Vital events are likely to be missed and errors made no matter what method of data capture is used or what quality control procedures are in place. The extent to which random errors in large, longitudinal datasets affect overall health and demographic profiles has important implications for the role of DSSs as platforms for public health research and clinical trials. Such knowledge is also of particular importance if the outputs of DSSs are to be extrapolated and aggregated with realistic margins of error and validity.METHODS: This study uses the first 10-year dataset from the Butajira Rural Health Project (BRHP) DSS, Ethiopia, covering approximately 336,000 person-years of data. Simple programmes were written to introduce random errors and omissions into new versions of the definitive 10-year Butajira dataset. Key parameters of sex, age, death, literacy and roof material (an indicator of poverty) were selected for the introduction of errors based on their obvious importance in demographic and health surveillance and their established significant associations with mortality. Defining the original 10-year dataset as the 'gold standard' for the purposes of this investigation, population, age and sex compositions and Poisson regression models of mortality rate ratios were compared between each of the intentionally erroneous datasets and the original 'gold standard' 10-year data.RESULTS: The composition of the Butajira population was well represented despite introducing random errors, and differences between population pyramids based on the derived datasets were subtle. Regression analyses of well-established mortality risk factors were largely unaffected even by relatively high levels of random errors in the data.CONCLUSION: The low sensitivity of parameter estimates and regression analyses to significant amounts of randomly introduced errors indicates a high level of robustness of the dataset. This apparent inertia of population parameter estimates to simulated errors is largely due to the size of the dataset. Tolerable margins of random error in DSS data may exceed 20%. While this is not an argument in favour of poor quality data, reducing the time and valuable resources spent on detecting and correcting random errors in routine DSS operations may be justifiable as the returns from such procedures diminish with increasing overall accuracy. The money and effort currently spent on endlessly correcting DSS datasets would perhaps be better spent on increasing the surveillance population size and geographic spread of DSSs and analysing and disseminating research findings.
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| 16. |
- Fottrell, Edward
(författare)
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Dying to count : mortality surveillance in resource-poor settings
- 2009
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Ingår i: Global Health Action. - : CoAction Publishing. - 1654-9716 .- 1654-9880. ; 2
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Tidskriftsartikel (refereegranskat)abstract
- Reliable cause-specific mortality data constitute a crucial resource for health monitoring, service planning and prioritisation. However, in the majority of the world's poorest settings, systematic health and vital event surveillance systems are weak or non-existent. As such, deaths are not counted and causes of death remain unregistered for more than two-thirds of the world's population.For researchers, health workers and policy makers in resource-poor settings, therefore, attempts to measure mortality have to be implemented from first principles. As a result, there is wide variation in mortality surveillance methodologies in different settings, and lack of standardisation and rigorous validation of these methods hinder meaningful comparison of mortality data between settings and over time.With a particular focus on Health and Demographic Surveillance Systems (HDSSs), this paper summarises recent research and conceptual development of certain methodological aspects of mortality surveillance stemming from a series of empirical investigations. The paper describes the advantages and limitations of various methods in particular contexts, and argues that there is no single methodology to satisfy all data needs. Rather, methodological decisions about mortality measurement should be a synthesis of all available knowledge relating to clearly defined concepts of why data are being collected, how they can be used and when they are of good enough quality to inform public health action.
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| 17. |
- Fottrell, Edward F, 1980-
(författare)
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Dying to count : mortality surveillance methods in resource-poor settings
- 2008
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- 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.
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| 18. |
- Fottrell, Edward, et al.
(författare)
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Identifying humanitarian crises in population surveillance field sites : simple procedures and ethical imperatives.
- 2009
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Ingår i: Public Health. - : Elsevier BV. - 0033-3506 .- 1476-5616. ; 123:2, s. 151-155
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVES: Effective early warning systems of humanitarian crises may help to avert substantial increases in mortality and morbidity, and prevent major population movements. The Butajira Rural Health Programme (BRHP) in Ethiopia has maintained a programme of epidemiological surveillance since 1987. Inspection of the BRHP data revealed large peaks of mortality in 1998 and 1999, well in excess of the normally observed year-to-year variation. Further investigation and enquiry revealed that these peaks related to a measles epidemic, and a serious episode of drought and consequent food insecurity that went undetected by the BRHP. This paper applies international humanitarian crisis threshold definitions to the BRHP data in an attempt to identify suitable mortality thresholds that may be used for the prospective detection of humanitarian crises in population surveillance sites in developing countries. STUDY DESIGN: Empirical investigation using secondary analysis of longitudinal population-based cohort data. METHODS: The daily, weekly and monthly thresholds for crises in Butajira were applied to mortality data for the 5-year period incorporating the crisis periods of 1998-1999. Days, weeks and months in which mortality exceeded each threshold level were identified. Each threshold level was assessed in terms of prospectively identifying the true crisis periods in a timely manner whilst avoiding false alarms. RESULTS: The daily threshold definition is too sensitive to accurately detect impending or real crises in the population surveillance setting of the BRHP. However, the weekly threshold level is useful in identifying important increases in mortality in a timely manner without the excessive sensitivity of the daily threshold. The weekly threshold level detects the crisis periods approximately 2 weeks before the monthly threshold level. CONCLUSION: Mortality measures are highly specific indicators of the health status of populations, and simple procedures can be used to apply international crisis threshold definitions in population surveillance settings for the prospective detection of important changes in mortality rate. Standards for the timely use of surveillance data and ethical responsibilities of those responsible for the data should be made explicit to improve the public health functioning of current sentinel surveillance methodologies.
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| 19. |
- Fottrell, Edward, et al.
(författare)
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Mortality measurement in transition : proof of principle for standardised multi-country comparisons
- 2010
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Ingår i: Tropical medicine & international health. - : Wiley. - 1360-2276 .- 1365-3156. ; 15:10, s. 1256-1265
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Tidskriftsartikel (refereegranskat)abstract
- Given the standardised method of VA interpretation, the observed differences in mortality cannot be because of local differences in assigning cause of death. Standardised, fit-for-purpose methods are needed to measure population health and changes in mortality patterns so that appropriate health policy and programmes can be designed, implemented and evaluated over time and place. The InterVA approach overcomes several longstanding limitations of existing methods and represents a valuable tool for health planners and researchers in resource-poor settings.
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| 20. |
- Fottrell, Edward, et al.
(författare)
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Population survey sampling methods in a rural African setting : measuring mortality
- 2008
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Ingår i: Population Health Metrics. - : BioMed Central (BMC). - 1478-7954. ; 6, s. Article nr 2-
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Population-based sample surveys and sentinel surveillance methods are commonly used as substitutes for more widespread health and demographic monitoring and intervention studies in resource-poor settings. Such methods have been criticised as only being worthwhile if the results can be extrapolated to the surrounding 100-fold population. With an emphasis on measuring mortality, this study explores the extent to which choice of sampling method affects the representativeness of 1% sample data in relation to various demographic and health parameters in a rural, developing-country setting.METHODS: Data from a large community based census and health survey conducted in rural Burkina Faso were used as a basis for modelling. Twenty 1% samples incorporating a range of health and demographic parameters were drawn at random from the overall dataset for each of seven different sampling procedures at two different levels of local administrative units. Each sample was compared with the overall 'gold standard' survey results, thus enabling comparisons between the different sampling procedures.RESULTS: All sampling methods and parameters tested performed reasonably well in representing the overall population. Nevertheless, a degree of variation could be observed both between sampling approaches and between different parameters, relating to their overall distribution in the total population.CONCLUSION: Sample surveys are able to provide useful demographic and health profiles of local populations. However, various parameters being measured and their distribution within the sampling unit of interest may not all be best represented by a particular sampling method. It is likely therefore that compromises may have to be made in choosing a sampling strategy, with costs, logistics the intended use of the data being important considerations.
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