Nutrition surveillance using a small open cohort: experience from Burkina Faso.

Mark Myatt,Mathias Altmann,Boshen Jiao,Martin Loada,Christophe Fermanian,Chiara Altare

doi:10.1186/s12982-016-0052-0

Abstract

BackgroundNutritional surveillance remains generally weak and early warning systems are needed in areas with high burden of acute under-nutrition. In order to enhance insight into nutritional surveillance, a community-based sentinel sites approach, known as the Listening Posts (LP) Project, was piloted in Burkina Faso by Action Contre la Faim (ACF). This paper presents ACF’s experience with the LP approach and investigates potential selection and observational biases.MethodsSix primary sampling units (PSUs) were selected in each livelihood zone using the centric systematic area sampling methodology. In each PSU, 22 children aged between 6 and 24 months were selected by proximity sampling. The prevalence of GAM for each month from January 2011 to December 2013 was estimated using a Bayesian normal–normal conjugate analysis followed by PROBIT estimation. To validate the LP approach in detecting changes over time, the time trends of MUAC from LP and from five cross-sectional surveys were modelled using polynomial regression and compared by using a Wald test. The differences between prevalence estimates from the two data sources were used to assess selection and observational biases.ResultsThe 95 % credible interval around GAM prevalence estimates using LP approach ranged between +6.5 %/−6.0 % on a prevalence of 36.1 % and +3.5 %/−2.9 % on a prevalence of 10.8 %. LP and cross-sectional surveys time trend models were well correlated (p = 0.6337). Although LP showed a slight but significant trend for GAM to decrease over time at a rate of −0.26 %/visit, the prevalence estimates from the two data sources showed good agreement over a 3-year period.ConclusionsThe LP methodology has proved to be valid in following trends of GAM prevalence for a period of 3 years without selection bias. However, a slight observational bias was observed, requiring a periodical reselection of the sentinel sites. This kind of surveillance project is suited to use in areas with high burden of acute under-nutrition where early warning systems are strongly needed. Advocacy is necessary to develop sustainable nutrition surveillance system and to support the use of surveillance data in guiding nutritional programs.

Highlights

Nutritional surveillance remains generally weak and early warning systems are needed in areas with high burden of acute under-nutrition
This paper presents the experience of the international non-governmental organization Action Contre la Faim (ACF) with nutrition surveillance using a communitybased sentinel sites approach, known as the Listening
This paper presents the methodology for nutrition surveillance that was tested by ACF in a rural area of Burkina Faso, using a small open cohort in community-based sentinel sites

Summary

Introduction

Nutritional surveillance remains generally weak and early warning systems are needed in areas with high burden of acute under-nutrition. Nutrition surveillance refers to a continuous process and focuses on monitoring trends over time, rather than providing one-time estimates of (e.g.) absolute levels of the prevalence of they have been recognized as an important component in fighting malnutrition, nutritional surveillance systems remain weak in most developing countries [3] Reasons for this include (1) no common agreement on the best methods to implement nutrition surveillance, (2) a lack of confidence in surveillance data, and (3) little comparable data on the costs of different potentially effective systems that would justify investments in such a system [2, 4]. Unless active case-finding is used, beneficiaries may tend to come to the facilities only when the disease is severe This means that indicators may lag behind incidence, making surveillance data inappropriate for an early warning system. Unless they are repeated frequently enough, surveys may miss seasonal effect and cannot provide timely information on changes over time [9]

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Conclusion