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Enregistrement W2125817698 · doi:10.1093/ije/dys090

Profile: The Ouagadougou Health and Demographic Surveillance System

2012· article· en· W2125817698 sur OpenAlexaboutno aff
Clémentine Rossier, Abdramane Soura, B. Baya, Guillaume Compaoré, Bonayi Dabiré, Stéphanie Dos Santos, Géraldine Duthé, Bilampoa Gnoumou, Jean-François Kobiané, Séni Kouanda, Bruno Lankoandé, Thomas Legrand, Cheikh Mbacké, Roch Millogo, Nathalie Mondain, Mark R. Montgomery, A. Nikiéma, Idrissa Ouili, Gilles Pison, Sean Randall, Gabriel Sangli, Bruno Schoumaker, Younoussi Zourkaleini

Notice bibliographique

RevueInternational Journal of Epidemiology · 2012
Typearticle
Langueen
DomaineMedicine
ThématiqueGlobal Maternal and Child Health
Établissements canadiensnon disponible
Organismes subventionnairesWellcome Trust
Mots-clésPovertyPublic healthContext (archaeology)SocioeconomicsEnvironmental healthPopulationGeographyEconomic growthCapital cityMedicineSociologyNursing

Résumé

récupéré en direct d'OpenAlex

The Ouagadougou Health and Demographic Surveillance System (Ouaga HDSS), located in five neighbourhoods at the northern periphery of the capital of Burkina Faso, was established in 2008. Data on vital events (births, deaths, unions, migration events) are collected during household visits that have taken place every 10 months. The areas were selected to contrast informal neighbourhoods (∼40 000 residents) with formal areas (∼40 000 residents), with the aims of understanding the problems of the urban poor, and testing innovative programmes that promote the well-being of this population. People living in informal areas tend to be marginalized in several ways: they are younger, poorer, less educated, farther from public services and more often migrants. Half of the residents live in the Sanitary District of Kossodo and the other half in the District of Sig-Nonghin. The Ouaga HDSS has been used to study health inequalities, conduct a surveillance of typhoid fever, measure water quality in informal areas, study the link between fertility and school investments, test a non-governmental organization (NGO)-led programme of poverty alleviation and test a community-led targeting of the poor eligible for benefits in the urban context. Key informants help maintain a good rapport with the community. The Ouaga HDSS data are available to researchers under certain conditions. Development efforts in Sub-Saharan Africa are focused mainly on rural areas. Although rural citizens are indeed poorer than urban dwellers on average, strong inequalities exist within cities. In fact, the vulnerable fringe of the urban population could experience worse living conditions than rural inhabitants, due to the combined effect of persistent poverty and problems specific to the urban environment (such as criminality, housing density, pollution, road accidents, unhealthy diets, weakening of social control and links, etc.). Moreover, the proportion and the number of urban dwellers is increasing rapidly on the continent. Whereas 15.5% of the Burkina Faso’s population was urban in 1996, this number is expected to rise to 40% by 2030. Whereas Ouagadougou counted 170 000 inhabitants in 1975, this number had soared to 1.5 million by 2006 and is expected to reach 5.8 million by 2030. In order to tackle the problems of the urban poor, the Institut Supérieur des Sciences de la Population (ISSP) at the University of Ouagadougou established a pilot demographic surveillance system in Ouagadougou in 2002. This pilot covered 5000 inhabitants living in one informal and one formal neighbourhood. The pilot showed that collecting data on Pocket PCs rather than on paper questionnaires led to a significant decrease in data production costs. The pilot also showed that despite high in- and out-migration rates, an important proportion of city dwellers enjoy residential stability in Ouagadougou. The Ouaga HDSS joined the INDEPTH network in 2005. In 2008, thanks to a grant from the Wellcome Trust, the ISSP extended the population covered to 80 000 residents. The first research programme of the Ouaga HDSS, to be completed in 2012, uses a mixed-method approach (quantitative, qualitative and spatial analysis) to describe the double burden of disease and health care utilization characterizing the areas, and its unequal distribution according to different dimensions of vulnerability: type of neighbourhood (formal or informal), poverty, lack of education, migrant status and age. Subsequently, other research projects have started in the Ouaga HDSS: a study on fertility and schooling, a surveillance of typhoid fever, a measure of water quality in informal areas and its variation with climate change, the test of a non-governmental organization (NGO)-led programme of poverty alleviation, the test of a community-led targeting process identifying the poorest poor eligible for health benefits in the urban context and a programme of comparative analyses with the Nairobi HDSS. Ouagadougou is the capital city of Burkina Faso and lies at the centre of this country, located in the middle of West Africa (12° North of the Equator and 1° West of the Prime Meridian) (Figure 1). The rainy season lasts from June to October; the rest of the year is dry. Temperatures range from 15°C in December to 42°C in April. Most city dwellers work in the trade sector. Several major national public hospitals are located in the capital along with most private health centres and pharmacies. Location of Ouagadougou in West Africa The Ouaga HDSS sites were chosen to target the most vulnerable populations of the city. We thus paid special attention to areas of unplanned growth. Information given by the municipalities led us to choose three informal areas devoid of formal zoning plans, located at the northern periphery of the city: Nonghin, Polesgo and Nioko 2. To be able to compare these areas with the rest of the city, we added two formal neighbourhoods located close by (Kilwin and Tanghin) (Figure 2). Nonghin and Kilwin belong to the Sanitary District of Sig-Nonghin, whereas Polesgo, Tanghin and Nioko 2 belong to the Sanitary District of Kossodo. A population of 80 000 was defined as a minimum to measure differences in child mortality in a ‘control’ vs an ‘intervention’ area given the 1996 census urban level of mortality in Burkina Faso, and we distributed this total amount equally between formal and informal areas, and between the districts of Kossodo and Sig-Nonghin. The Ouaga HDSS areas cover only part of either district. Location of settlements monitored by the Ouagadougou HDSS In September 2008, we defined the limits of our areas using existing census tracks (census 2006), and creating new ones in places where the city had expanded. Altogether, the areas we followed consist of 55 census tracks divided into 494 blocks. We mapped all the census tracks and blocks using fieldworkers with handheld global positioning system (GPS) receivers and ArcGIS 9. During a first census (October 2008 to March 2009), the demographic surveillance system was explained to every head of household and a consent form was signed; during subsequent censuses, new households are enrolled in the same way. Fieldworkers first enumerated all the Units of Collective Habitation (UCH). A UCH is defined as one or several buildings, of which at least one could be rented or is inhabited, and which are either enclosed, or belong to the same owner. In formal areas, the UCH correspond to city plots, and city numbers are used; in informal areas, an ad hoc identification (ID) number is created and painted on the UCH wall. The geographic coordinates of each UCH were measured, using the GPS function on the Pocket PC. Each UCH contains one or several households; every household belongs to one and only one UCH. A resident is defined as a person who has lived for more than 6 months in a UCH. By living, we mean ‘usually sleeping’ in the UCH, that is, sleeping more frequently in the UCH than anywhere else. A household is defined, within a UCH, as a group of residents (related by family links or not), who put their resources together to collectively satisfy most of their vital needs. Additionally, household members must recognize one member as the head of household. During the third enumeration (mid-point: June 2010), there were 81 717 residents (37 878 in informal areas and 43 839 in formal areas), living in 18 310 households. The average household size was 3.6 in informal areas and 5.7 in formal ones. The male:female ratio was 100.6:100. Among residents, 39% were under 15 years and 16% were under 5 years. The age pyramid differs between formal and informal areas (Figure 3), with a more regular shape in formal areas, albeit with peaks between the ages of 10 and 24 years for women and 15 and 29 years for men, denoting the flux of migrants from rural areas; most residents in informal areas are young adults with small children. Age pyramid, Ouagadougou HDSS, formal and informal areas, 2010 Between October 2008 and April 2012, the fieldworkers conducted four enumerations. They use standard forms to enumerate all UCH, households and residents (the forms are available on http://www.issp.bf/OPO/DATASET/Questionnaire.html). The forms appear on the screen of their Pocket PCs, which have been loaded with the information from the last census concerning the block they are working in. A series of validity checks are built in the programme of the Pocket PC. Each night, the data collected are transferred by Wifi to a server. A validity check is run every 2 weeks on the new data, and errors are corrected. At the end of the enumeration, the new data are merged with the rest of the database, and further errors are detected and corrected. In the initial census, two households refused to participate in the surveillance system, and by February 2011, the number of non-participating households rose to 40. In case of a refusal, the fieldwork supervisor visits the household to try to address any concerns. At the start of the project, local authorities and personalities gathered for several informational sessions; radio programmes and town criers were used to raise awareness about the project. Constant communication is maintained in the informal areas through a network of 12 key informants. In all neighbourhoods, fieldwork supervisors visit local authorities and recognized community representatives for updates. As called for by local custom, following any death, the supervisors visit the household for a greeting and a symbolic donation. At re-enumeration, fieldworkers register any demolished or newly constructed UCH. Within each UCH, fieldworkers enumerate existing households, and register new ones. They interview one member of each household and collect data on the vital events that occurred to any household members since the last census (Table 1). They verify that individuals registered on the household list did indeed sleep in the UCH the previous night, and if not, when they last left. They collect data on residents who have died since the last census (and on residents who have been gone for more than 6 months). Another trained fieldworker returns to bereft households to perform a verbal autopsy using the standard INDEPTH forms (paper questionnaires); a group of eight local medical doctors performs a double diagnosis of each case; discordant cases are discussed and resolved by the group. Fieldworkers ask about births that have occurred since the last census (women aged 12–49 years), paying close attention to births that may have led to deaths. The pregnancy status of each woman is ascertained, as well as the outcome of any previously registered pregnancies. The marital status of residents is updated. Finally, fieldworkers register newcomers, and search for their ID if they have already lived in the area and were recorded. They collect basic information about visitors, and brief histories of migration, marriages and births for new adult residents. Information collected at each re-enumeration round of the Ouagadougou HDSS aThis information is collected every two rounds. Information collected at each re-enumeration round of the Ouagadougou HDSS aThis information is collected every two rounds. At every other enumeration, data are collected on the vaccination history of children under 5 years, on the survival of biological parents and on household goods, economic activities, education, home ownership and housing characteristics (Table 1). These data are stored in 25 relational tables organized around objects, events and episodes, such as individuals, births or episodes of household headships. The most frequently used data are reorganized in eight macro files. SQL Server Pro is the data managing system. In addition, between February and August 2010, we conducted a health survey on a sample of residents under 5 years or over 15 years of age, over-sampling children and the elderly. We drew a sample of 1941 households, of which 1699 responded (a response rate of 87.5%); 3307 individuals (their mothers for children) were interviewed: 950 were under 5 years, 1371 were between 15 and 49 years and 986 were 50 years and over. Weights were calculated taking the non-responses and the stratified sampled procedure into account. The survey was conducted on Pocket PCs. The children’s questionnaire included the following modules: infectious disease symptoms, mosquito net use, accidents and violence, access to health care, anthropometric measures (weight, height and arm circumference). The adult questionnaire included questions on self-reported health, physical and cognitive limitations, depression, behavioural risk factors, accidents and violence, access to health care, anthropometric measures (weight, height, waist circumference and blood pressure). Individuals 50 years and older were asked additional questions on physical limitations, economic independence, pension and support system and cognitive function. Women aged 15–49 years were asked additional questions on sexual activity, the desire for children, current pregnancy status and contraceptive use. We further conducted a qualitative characterization in the neighbourhood in 2008–09, a qualitative investigation of the perception of the September 2009 flooding in Ouagadougou and a qualitative description of poverty in the areas in 2011. A database of health infrastructures in the whole city (including GPS coordinates) was created in 2009–10, and the geographic coordinates of all stagnating water and piles of trash were collected in the Ouaga HDSS areas in 2010. The demographic indicators of the Ouaga HDSS are summarized in Table 2. Informal areas are inhabited mainly by young families with small children.1 Although residents of informal areas go to health centres when their children are sick as often as those who live in formal areas,2 they lack access to public schools and have to resort to expensive private schools despite their greater poverty.3 Informal areas are also the unhappy intersection of a high concentration of young children and particularly unsanitary living conditions,4,5 and as a result, infant mortality is almost twice as high in informal areas as in formal ones.6 Childhood malnutrition is still an important problem for the poor and in informal areas.7 On the other hand, adults living in informal areas do not seem to have a comparative disadvantage in terms of health outcomes.8 They seek formal health services less often when they are sick (because they are more often poor, uneducated and migrants from rural areas)2 but they are also less exposed to certain diseases and risk factors that are more prevalent among the middle class and in formal areas (such as obesity, road accidents and perhaps even HIV).6,8 The picture is similar when considering migration status as a source of vulnerability. With all else constant, migrants and non-migrants seem to have similar health outcomes, although further longitudinal analysis is necessary to exclude the hypothesis of selective out-migration.7 The favourable situation of migrants could be explained by their rapid social integration.3 Indications of social learning effects in the community (people surrounded by more educated individuals use cheaper counterfeit drugs less frequently, everything else being constant),9 predict that the effects of health education programmes are likely to be multiplied by social interaction effects. The lower contraceptive prevalence among poor and migrant couples seems less due to a lack of information, distance or financial constraints, than to persisting ideals of larger family.3,10 Demographic characteristics of the Ouagadougou HDSS All figures are averages for the period January 2009 to December 2011 except those marked with asterisk, which are taken from the third enumeration round with a mid-point date of 23 June 2010. aThe transmigration rate is the rate of moving residence where the starting residence and the finishing residence are both households within Ouaga HDSS. Demographic characteristics of the Ouagadougou HDSS All figures are averages for the period January 2009 to December 2011 except those marked with asterisk, which are taken from the third enumeration round with a mid-point date of 23 June 2010. aThe transmigration rate is the rate of moving residence where the starting residence and the finishing residence are both households within Ouaga HDSS. We also shed some light on some new public health concerns in the African context. Of the adults, 4.5% were estimated to be depressive at the time of the survey, a level that is not negligible; depression appears to be mainly related to identified chronic health conditions and physical limitations.11 The elderly (3% of the Ouaga HDSS population are 60 years and over) either still work or are supported by their spouses or children. Women whose husbands die (at any age) are in especially vulnerable positions when they have no sons to support them.12 In collaboration with researchers at Pennsylvania State, University of Louvain and McGill University, we plan to study the evolution of household poverty and its to family the between migration and child mortality for and the between households and child In collaboration with the of local and research we plan to test two in the Ouaga HDSS an innovative and family programme for young and a family health education programme with a on chronic The of Ouaga HDSS is its an urban where poor individuals are but which is also on urban dwellers and the urban poor is in Another strong is the population of Ouaga HDSS. Although are important in both a population in our areas 1.5 years initial enumeration, which we into and a part of the population their of households in informal areas and in formal areas in and residential In fact, of the residents at the first enumeration were still there at the enumeration that place 1.5 years the Ouaga HDSS also has some is not of the city of Ouagadougou as a not to the centre of the city, which is more by Ouagadougou and older the Ouaga HDSS be used to test some the areas followed do not correspond to the area of the Another is a measure of migrants to and a resident is a selective Although we collect data on no information us to those who may have to among and have We that residents do not often several months a year in their previous migrants are likely to even residents given our Moreover, the procedure to the ID of individuals already lived in our areas often for are thus and within the areas (and returns to the not well Finally, we do not residents to or to health care (and or new residents may have in for similar are also some data quality During the first re-enumeration, we had individuals at home despite three visits and data are for about one household of in the organization of fieldwork in the subsequent seem to have the despite the use of national ID or other to the date of for most individuals, the elderly seem to have Finally, we seem to have been a number of during the first two were for the third data, questionnaires and are available on the Ouaga HDSS data are also to by the Ouaga HDSS for analyses one with an ISSP in the production researchers use the forms on the the of the work and the expected forms be to or This work was by the Wellcome Trust, grant number We the in Nonghin, Polesgo, Tanghin and Nioko 2. We the work of the and their in a good rapport with the in the work of its and We the who have and We to the that was of help during the of the We to and for their support for the project. We are also to the of and the and the pilot have not of The Ouaga HDSS is the only urban demographic surveillance system in West living in informal neighbourhoods are to mortality due to particularly unsanitary living conditions. Health inequalities are lower than expected among adults of a high to chronic diseases and road accidents among the

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,004
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,094
Score d'incertitude au seuil0,193

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0040,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,041
Tête enseignante GPT0,371
Écart entre enseignants0,331 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations87
Publié2012
Routes d'admission1
Résumé présentoui

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Même revueInternational Journal of EpidemiologyMême sujetGlobal Maternal and Child HealthTravaux en français237 207