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Vision et Ambition

Notre vision Contribuer à l’amélioration de la santé de la reproduction, notamment celle de la mère et de l’enfant au Burkina Faso et dans la sous–région ouest Africaine. Nos missions Servir de guide opérationnel pour l’action aux structures, instituts, organisations intervenant dans le domaine de la santé de la reproduction ; Servir de cadre (...)

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RESEARCH ARTICLE : A probabilistic method to estimate the burden of maternal morbidity in resource-poor settings : preliminary development and evaluation

 

Edward Fottrell1,2*, Ulf Högberg3, Carine Ronsmans4, David Osrin1, Kishwar Azad5, Nirmala Nair6, Nicolas Meda7,Rasmane Ganaba7, Sourou Goufodji8, Peter Byass2 and Veronique Filippi4

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.
Keywords : Maternal health, Morbidity, Developing countries, Pregnancy, Childbirth, Bayesian analysis, Africa, Asia

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RESEARCH ARTICLE Prevalence of and Factors Associated with Human Cysticercosis in 60 Villages in Three Provinces of Burkina Faso


Hélène Carabin1*, Athanase Millogo2, Assana Cissé3, Sarah Gabriël4, Ida Sahlu5,6, Pierre Dorny4, Cici Bauer7, Zekiba Tarnagda8, Linda D Cowan1†, (...)

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RESEARCH ARTICLE :The obstetric care subsidy policy in Burkina Faso : what are the effects after five years of implementation ? Findings of a complex evaluation


Rasmané Ganaba1*, Patrick G. C. Ilboudo1, Jenny A. Cresswell2, Maurice Yaogo1, Cheick Omar Diallo3, Fabienne Richard4, Nadia Cunden5, Veronique (...)

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