Joseph Larmarange

Décrire les épidémies, Comprendre les populations : une démographie du VIH en Afrique subsaharienne

Joseph LARMARANGE — 2022-10-14T06:38:12Z

Habilitation à Diriger des Recherches soutenue le 12 octobre 2012 par Joseph Larmarange à l'Université Paris Cité.
Décrire les épidémies, Comprendre les populations : une démographie du VIH en Afrique subsaharienne
Joseph Larmarange Démographie. Université Paris Cité, 2022 HDR tel-03814024

- Publications / Afrique subsaharienne, ATLAS, CAP-CoV-Soignants-BF, DOD-CI (ANRS 12287 / 12323), ELIHoS (ANRS 12139), PrEP CI (ANRS 12361), Prévalences du VIH (ANRS 12114), prevR, PRINCESSE, TasP (ANRS 12249), Afrique du Sud, Burkina Faso, Côte d'Ivoire, Mali, Sénégal, Accès aux soins, Analyse de séquences, Approches biographiques, Approches communautaires, Autotests VIH, Cartographie, Cascade des soins, Comparaison de cohortes, Comportements sexuels, Démographie, Dépistage, EDS (Enquêtes Démographiques et de Santé), Enquêtes par téléphone, Enseignement académique, Lien vers les soins, Épidémiologie, Essais cliniques, Estimateurs à noyau (kernel density estimation), Femmes enceintes, Financement des programmes, Hépatites virales, Homo / Bisexualités, Identités sexuelles, Incidence du VIH, Interpolation spatiale, IST (Infections Sexuellement Transmissibles), Itinéraires thérapeutiques, Masculinités, Ménages, Mesure d'impact, Mesure des indicateurs, Méthodologie, Migrations, Observatoire de population, Partenaires sexuel(le)s, PrEP, Prévalence du VIH, Prévention, Prise en charge, Recherche interventionnelle, Recherche participative/communautaire, Recrutement « boules de neige », Représentations / Perceptions, Représentativité et Biais, Santé publique, Santé sexuelle, Structure des populations, Structures de santé, Surveillance sentinelle, Téléphones mobiles, Temporalités, Traitement antirétroviral (ARV), Travail du sexe, Treatment as Prevention (TasP), Universal Test & Treat (UTT), Usageres de drogue, VIH / SIDA

Evaluation of geospatial methods to generate subnational HIV prevalence estimates for local level planning

Joseph LARMARANGE — 2016-05-14T14:35:02Z

Author

The Subnational Estimates Working Group of the HIV Modelling Consortium

Abstract

Objective: There is evidence of substantial subnational variation in the HIV epidemic. However, robust spatial HIV data are often only available at high levels of geographic aggregation and not at the finer resolution needed for decision making. Therefore, spatial analysis methods that leverage available data to provide local estimates of HIV prevalence may be useful. Such methods exist but have not been formally compared when applied to HIV.

Design/methods: Six candidate methods – including those used by the Joint United Nations Programme on HIV/AIDS to generate maps and a Bayesian geostatistical approach applied to other diseases – were used to generate maps and subnational estimates of HIV prevalence across three countries using cluster level data from household surveys. Two approaches were used to assess the accuracy of predictions: internal validation, whereby a proportion of input data is held back (test dataset) to challenge predictions; and comparison with location-specific data from household surveys in earlier years.

Results: Each of the methods can generate usefully accurate predictions of prevalence at unsampled locations, with the magnitude of the error in predictions similar across approaches. However, the Bayesian geostatistical approach consistently gave marginally the strongest statistical performance across countries and validation procedures.

Conclusions: Available methods may be able to furnish estimates of HIV prevalence at finer spatial scales than the data currently allow. The subnational variation revealed can be integrated into planning to ensure responsiveness to the spatial features of the epidemic. The Bayesian geostatistical approach is a promising strategy for integrating HIV data to generate robust local estimates.

Reference

Subnational Estimates Working Group of the HIV Modelling Consortium (2016) “Evaluation of geospatial methods to generate subnational HIV prevalence estimates for local level planning”, AIDS (London, England), 30 (9) (June 1), p. 1467-1474. DOI : 10.1097/QAD.0000000000001075.

Developing subnational estimates of HIV prevalence and the number of people living with HIV

Joseph LARMARANGE — 2014-12-16T12:00:47Z

A series of reports developed for UNAIDS and presenting HIV estimates at sub-national level computed from Demographic and Health Surveys.

The method has been fully described in HIV estimates at second subnational level from national population-based surveys (AIDS 2014).

Reports are available on UNAIDS webiste, under the Subnational estimates from survey data heading.

References

Larmarange Joseph (2014) Zimbabwe: Developing subnational estimates of HIV prevalence and the number of people living with HIV (JC2665E), Geneva : UNAIDS, 18 p. http://www.unaids.org/en/resources/documents/2014/2014_subnationalestimatessurvey_Zimbabwe.

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Larmarange Joseph (2014) United Republic of Tanzania: Developing subnational estimates of HIV prevalence and the number of people living with HIV (JC2665E), Geneva : UNAIDS, 24 p. http://www.unaids.org/en/resources/documents/2014/2014_subnationalestimatessurvey_Tanzania.

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Larmarange Joseph (2014) Malawi: Developing subnational estimates of HIV prevalence and the number of people living with HIV (JC2665E), Geneva : UNAIDS, 15 p. http://www.unaids.org/en/resources/documents/2014/2014_subnationalestimatessurvey_Malawi.

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Larmarange Joseph (2014) Guinea: Developing subnational estimates of HIV prevalence and the number of people living with HIV (JC2665E), Geneva : UNAIDS, 17 p. http://www.unaids.org/en/resources/documents/2014/2014_subnationalestimatessurvey_Guinea.

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Larmarange Joseph (2014) Côte d'Ivoire: Developing subnational estimates of HIV prevalence and the number of people living with HIV (JC2665E), Geneva : UNAIDS, 21 p. http://www.unaids.org/en/resources/documents/2014/2014_subnationalestimatessurvey_CotedIvoire.

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Larmarange Joseph (2014) Cameroon: Developing subnational estimates of HIV prevalence and the number of people living with HIV (JC2665E), Geneva : UNAIDS, 21 p. http://www.unaids.org/en/resources/documents/2014/2014_subnationalestimatessurvey_cameroon.

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Larmarange Joseph (2014) Burundi: Developing subnational estimates of HIV prevalence and the number of people living with HIV (JC2665E), Geneva : UNAIDS, 17 p. http://www.unaids.org/en/resources/documents/2014/2014_subnationalestimatessurvey_Burundi.

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Larmarange Joseph (2014) Burkina Faso: Developing subnational estimates of HIV prevalence and the number of people living with HIV (JC2665E), Geneva : UNAIDS, 17 p. http://www.unaids.org/en/resources/documents/2014/2014_subnationalestimatessurvey_BurkinaFaso.

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Larmarange Joseph (2014) Uganda: Developing subnational estimates of HIV prevalence and the number of people living with HIV (JC2665E), Geneva : UNAIDS, 22 p. http://www.unaids.org/en/resources/documents/2014/2014_subnationalestimatessurvey_Uganda.

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Larmarange Joseph (2014) Rwanda: Developing subnational estimates of HIV prevalence and the number of people living with HIV (JC2665E), Geneva : UNAIDS, 17 p. http://www.unaids.org/en/resources/documents/2014/2014_subnationalestimatessurvey_Rwanda.

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Larmarange Joseph (2014) Lesotho: Developing subnational estimates of HIV prevalence and the number of people living with HIV (JC2665E), Geneva : UNAIDS, 16 p. http://www.unaids.org/en/resources/documents/2014/2014_subnationalestimatessurvey_Lesotho.

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Larmarange Joseph (2014) Haiti: Developing subnational estimates of HIV prevalence and the number of people living with HIV (JC2665E), Geneva : UNAIDS, 17 p. http://www.unaids.org/en/resources/documents/2014/2014_subnationalestimatessurvey_Haiti.

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Subnational Estimates Working Group of the HIV Modelling Consortium (2016) “Evaluation of geospatial methods to generate subnational HIV prevalence estimates for local level planning”, AIDS (London, England), 30 (9) (June 1), p. 1467-1474. DOI : 10.1097/QAD.0000000000001075.

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Abstract: OBJECTIVE: There is evidence of substantial subnational variation in the HIV epidemic. However, robust spatial HIV data are often only available at high levels of geographic aggregation and not at the finer resolution needed for decision making. Therefore, spatial analysis methods that leverage available data to provide local estimates of HIV prevalence may be useful. Such methods exist but have not been formally compared when applied to HIV. DESIGN/METHODS: Six candidate methods - including those used by the Joint United Nations Programme on HIV/AIDS to generate maps and a Bayesian geostatistical approach applied to other diseases - were used to generate maps and subnational estimates of HIV prevalence across three countries using cluster level data from household surveys. Two approaches were used to assess the accuracy of predictions: internal validation, whereby a proportion of input data is held back (test dataset) to challenge predictions; and comparison with location-specific data from household surveys in earlier years. RESULTS: Each of the methods can generate usefully accurate predictions of prevalence at unsampled locations, with the magnitude of the error in predictions similar across approaches. However, the Bayesian geostatistical approach consistently gave marginally the strongest statistical performance across countries and validation procedures. CONCLUSIONS: Available methods may be able to furnish estimates of HIV prevalence at finer spatial scales than the data currently allow. The subnational variation revealed can be integrated into planning to ensure responsiveness to the spatial features of the epidemic. The Bayesian geostatistical approach is a promising strategy for integrating HIV data to generate robust local estimates.

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HIV estimates at second subnational level from national population-based surveys

Joseph LARMARANGE — 2014-11-21T09:43:37Z

Published in AIDS in November 2014.

Authors

Larmarange Joseph¹ and Bendaud Victoria²

Ceped (UMR 196 Paris Descartes Ined IRD), IRD, Paris, France
Strategic Information and Monitoring Division, UNAIDS, Geneva, Switzerland

Abstract

Objectives:

A better understanding of the subnational variations could be paramount to the efficiency and effectiveness of the response to the HIV epidemic. The purpose of this study is to describe the methodology used to produce the first estimates at second subnational level released by UNAIDS.

Methods:

We selected national population-based surveys with HIV testing and survey clusters geolocation, conducted in 2008 or later. A kernel density estimation approach (prevR) with adaptive bandwidths was used to generate a surface of HIV prevalence. This surface was combined with LandScan global population distribution grid to estimate the spatial distribution of people living with HIV (PLWHIV). Finally, results were adjusted to national UNAIDS's published estimates and merged per second subnational administrative unit. An indicator of the quality of the estimates was computed for each administrative unit.

Results:

These estimates combine two complementary approaches: the prevR method, focusing on spatial variations of HIV prevalence, as well as national estimates published by UNAIDS, taking into account trends of HIV prevalence over time. Seventeen country reports have been produced. However, quality of the estimates at second subnational level is highly heterogonous between countries, depending on the number of units and the survey sampling size. In some countries, estimates at second subnational level are very uncertain and should be interpreted with caution.

Conclusion:

These estimates at second subnational level constitute a first step to help countries to better understand their HIV epidemic and to inform programming at lower geographical levels. Further developments are needed to better match local needs.

Citation

Larmarange Joseph and Bendaud Victoria (2014) “HIV estimates at second subnational level from national population-based surveys:”, AIDS, 28, p. S469-S476. DOI : 10.1097/QAD.0000000000000480. http://content.wkhealth.com/linkback/openurl?sid=WKPTLP:landingpage&an=00002030-201411004-00008.

Mapping Demographic and Health Surveys (DHS): a method to estimate regional trends of a proportion

Joseph LARMARANGE — 2013-09-01T03:25:16Z

Poster presented at XXVII IUSSP International Population Conference in Busan (August 2013).

Author

Joseph Larmarange

Abstract

For many countries, in particular in sub-Saharan Africa, Demographic and Health Surveys (DHS) are the main national source of data (depending on the subject). Several DHS collect latitude and longitude of surveyed clusters but the sampling method is not appropriate to derive local estimates: sample size is not large enough for a direct spatial interpolation. We develop a methodological approach for estimating a proportion by using kernel density estimators with adaptive bandwidths of equal number of persons surveyed. The method was tested by creating a fictitious country from which survey datasets were produced. We compared the prevalence surface estimated from survey data with the model's original prevalence surface. This method makes it possible to achieve a smoothing effect that adapts to the high irregularity of spatial distribution among the survey clusters. The surfaces thus generated are relatively accurate for densely populated areas and strongly smoothed in sparsely surveyed areas. Although local variations were filtered out, the regional component in the spatial variation of prevalence was reproduced, and the estimated prevalence surfaces could be interpreted as regional trend surfaces. Furthermore, this approach could be easily applied using prevR, a dedicated package for the statistical software R.

Reference

Larmarange Joseph (2013) “Mapping Demographic and Health Surveys (DHS): a method to estimate regional trends of a proportion (prevR)” (poster, session 176), presented at the XXVII IUSSP International Population Conference, Busan.

Méthodes pour cartographier les tendances régionales de la prévalence du VIH à partir des Enquêtes Démographiques et de Santé (EDS)

Joseph LARMARANGE — 2011-06-16T16:16:00Z

Larmarange Joseph, Vallo Roselyne, Yaro Seydou, Msellati Philippe, Méda Nicolas (2011). “Méthodes pour cartographier les tendances régionales de la prévalence du VIH à partir des Enquêtes Démographiques et de Santé (EDS)”, Cybergeo : European Journal of Geography, 539 (http://cybergeo.revues.org/23782 doi=10.4000/cybergeo.23782), RIS, BibTeX.

Larmarange Joseph, Vallo Roselyne, Yaro Seydou, Msellati Philippe, Méda Nicolas (2011). “Methods for mapping regional trends of HIV prevalence from Demographic and Health Surveys (DHS)”, Cybergeo : European Journal of Geography, 558, doi: 10.4000/cybergeo.24606 (http://cybergeo.revues.org/24606), RIS, BibTeX.

Auteurs

Joseph Larmarange
CEPED (UMR 196 Paris Descartes INED IRD), IRD, France.
Roselyne Vallo
Université de Montpellier I / INSERM U 1058 / Départements d'information médicale et d'anatomie cytologie pathologiques, CHU Montpellier, France.
Seydou Yaro
Centre Muraz, Burkina Faso.
Philippe Msellati
UMI 233 IRD/Université de Montpellier I, France.
Nicolas Méda
Centre Muraz, Burkina Faso.

Résumé

Pour de nombreux pays, en particulier en Afrique subsaharienne, les Enquêtes Démographiques et de Santé (EDS) constituent la principale estimation de la prévalence du VIH au niveau national et en population générale. Plusieurs EDS collectent la longitude et la latitude des grappes enquêtées.

Dans cet article, nous présentons trois approches méthodologiques pour cartographier les variations spatiales de la prévalence du VIH à partir des EDS. Ces approches sont appliquées à des simulations d'EDS échantillonnées à partir d'un pays modèle. Les surfaces estimées sont alors comparées à la surface initiale du modèle.

Nous montrons qu'une méthode utilisant des estimateurs à noyau à fenêtres adaptatives de même effectif permet d'estimer les principales tendances régionales des épidémies. Son application aux données de l'EDS 2003 du Burkina Faso fournit une image plausible de la situation épidémiologique dans ce pays.

Mots-clés

Interpolation, interpolation par noyaux, tendances régionales, méthodologie, enquêtes démographiques et de santé, pays en développement, VIH.

Title

Methods for mapping regional trends of HIV prevalence from Demographic and Health Surveys (DHS)

Abstract

For many countries, in particular in sub-Saharan Africa, Demographic and Health Surveys (DHS) are the main estimates of HIV prevalence at national level in general population. Several DHS collect longitude and latitude of surveyed clusters.

In this paper, we present three methodological approaches for mapping spatial variations of HIV prevalence from DHS. These approaches are applied to DHS simulation sampled from a model country. The estimated surfaces are then compared with the initial surface of the model.

We show that a method using kernel estimators with adaptive bandwidths of the same number of observed people allows estimating main regional trends of the epidemics. Its application to data from 2003 DHS of Burkina Faso give a plausible picture of the epidemiological situation in this country.

Key-words

Interpolation, kernel interpolation, regional trends, methodology, demographic and health surveys, developing countries, HIV.

Remerciements

Ce travail a bénéficié du support financier de l'Agence Nationale de Recherche sur le VIH/Sida et les hépatites virales (projet ANRS 12114).

Voir en ligne / See online

prevR 2

Joseph LARMARANGE — 2007-03-02T18:00:00Z

See below for a presentation in English.

Présentation

prevR se présente sous la forme d'un package additionnel pour le logiciel de statistiques libre et gratuit R (http://www.r-project.org/). Il permet d'importer les données, de les formater, puis de cartographier les tendances régionales d'une prévalence. Les résultats peuvent ensuite être exportés vers d'autres logiciels de statistiques ou des logiciels de cartographie.

prevR a été développé par Joseph Larmarange avec l'appui financier de l'ANRS (Agence Nationale de Recherche sur le Sida et les hépatites virales) et de l'IRD (Institut de Recherche pour le Développement, en collaboration avec le Centre Muraz au Burkina Faso et l'appui technique de LYSIS.

prevR est distribué sous la licence CeCILL-C.

Les méthodologies implémentées dans prevR ont été décrites dans Larmarange Joseph, Vallo Roselyne, Yaro Seydou, Msellati Philippe, Méda Nicolas (2011). “Méthodes pour cartographier les tendances régionales de la prévalence du VIH à partir des Enquêtes Démographiques et de Santé (EDS)”, Cybergeo : European Journal of Geography, 539 (http://cybergeo.revues.org/23782), RIS, BibTeX. .

Téléchargement et installation

prevR a été entièrement réécrit afin de produire une version 2 plus facile d'utilisation et offrant plus de possibilités.

prevR est désormais disponible sur CRAN. Pour l'installer, il vous suffit d'utiliser la commande Packages > Installer le(s) package(s)... sous R. prevR et ses dépendances seront alors directement téléchargés et installés.

Sur la page de prevR sur CRAN, vous trouverez le manuel de référence des fonctions de prevR à la fois en anglais et en français.

Utilisez la commande require(prevR) pour charger prevR. demo(prevR) vous permet d'afficher une démonstration rapide des possibilités du package, ?prevR vous donne accès à l'aide en ligne en anglais et vignette('prevR-FR') vous permet d'afficher l'aide en français.

Des exemples et fonctions supplémentaires sont disponibles sur GitHub : https://github.com/larmarange/prevR-extra.

Support

Si vous avez des questions sur prevR 2, vous pouvez laisser un commentaire ci-dessous.

Presentation in English

prevR is a package for the free and open-source statistical software R (http://www.r-project.org/). prevR allows spatial estimation of a prevalence surface or a relative risks surface, using data from a Demographic and Health Survey (DHS) or an analog survey. Data can be easily imported and exported from and to other statistical or cartographic software.

prevR 2 has been developed by Joseph Larmarange, in a partnership with Centre Muraz in Burkina Faso, with fundings from the French National Agency for Research on AIDS and Viral Hepatitis (ANRS) and the French Research Institute for Development
(IRD), and technical support from LYSIS.

prevR 2 is available under the licence CeCILL-C.

Methodologies implemented in prevR 2 has been published in Larmarange Joseph, Vallo Roselyne, Yaro Seydou, Msellati Philippe, Méda Nicolas (2011). “Methods for mapping regional trends of HIV prevalence from Demographic and Health Surveys (DHS)”, Cybergeo : European Journal of Geography, 558, doi: 10.4000/cybergeo.24606 (http://cybergeo.revues.org/24606), RIS, BibTeX.

Download and install

prevR has been completely rewritten for version 2, easier to use and including new method (kernel density estimation).

prevR is now available on CRAN. To install it, simple use the command Packages > Install package(s)... in R. prevR and all its dependencies will be downloaded and installed.

On prevR's page on CRAN, you can download the reference manual both in English and French.

Use the command require(prevR) to load prevR, demo(prevR) for a demo, ?prevR for help.

Some examples and additional functions could be find on GitHub: https://github.com/larmarange/prevR-extra.

Assistance

If you have any question about prevR 2, simply write a comment bellow.