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Measuring elimination of podoconiosis, endemicity classifications, case definition and targets: an international Delphi exercise

Identifieur interne : 001B07 ( Main/Exploration ); précédent : 001B06; suivant : 001B08

Measuring elimination of podoconiosis, endemicity classifications, case definition and targets: an international Delphi exercise

Auteurs : Kebede Deribe [Royaume-Uni, Éthiopie] ; Samuel Wanji [Cameroun] ; Oumer Shafi [Éthiopie] ; Edridah Muheki Tukahebwa [Ouganda] ; Irenee Umulisa [Rwanda] ; Gail Davey [Royaume-Uni]

Source :

RBID : PMC:4550552

Descripteurs français

English descriptors

Abstract

Background

Podoconiosis is one of the major causes of lymphoedema in the tropics. Nonetheless, currently there are no endemicity classifications or elimination targets to monitor the effects of interventions. This study aimed at establishing case definitions and indicators that can be used to assess endemicity, elimination and clinical outcomes of podoconiosis.

Methods

This paper describes the result of a Delphi technique used among 28 experts. A questionnaire outlining possible case definitions, endemicity classifications, elimination targets and clinical outcomes was developed. The questionnaire was distributed to experts working on podoconiosis and other neglected tropical diseases in two rounds. The experts rated the importance of case definitions, endemic classifications, elimination targets and the clinical outcome measures. Median and mode were used to describe the central tendency of expert responses. The coefficient of variation was used to describe the dispersals of expert responses.

Results

Consensus on definitions and indicators for assessing endemicity, elimination and clinical outcomes of podoconiosis directed at policy makers and health workers was achieved following the two rounds of Delphi approach among the experts.

Conclusions

Based on the two Delphi rounds we discuss potential indicators and endemicity classification of this disabling disease, and the ongoing challenges to its elimination in countries with the highest prevalence. Consensus will help to increase effectiveness of podoconiosis elimination efforts and ensure comparability of outcome data.


Url:
DOI: 10.1093/inthealth/ihv043
PubMed: 26185194
PubMed Central: 4550552


Affiliations:


Links toward previous steps (curation, corpus...)


Le document en format XML

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<title>Background</title>
<p>Podoconiosis is one of the major causes of lymphoedema in the tropics. Nonetheless, currently there are no endemicity classifications or elimination targets to monitor the effects of interventions. This study aimed at establishing case definitions and indicators that can be used to assess endemicity, elimination and clinical outcomes of podoconiosis.</p>
</sec>
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<title>Methods</title>
<p>This paper describes the result of a Delphi technique used among 28 experts. A questionnaire outlining possible case definitions, endemicity classifications, elimination targets and clinical outcomes was developed. The questionnaire was distributed to experts working on podoconiosis and other neglected tropical diseases in two rounds. The experts rated the importance of case definitions, endemic classifications, elimination targets and the clinical outcome measures. Median and mode were used to describe the central tendency of expert responses. The coefficient of variation was used to describe the dispersals of expert responses.</p>
</sec>
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<title>Results</title>
<p>Consensus on definitions and indicators for assessing endemicity, elimination and clinical outcomes of podoconiosis directed at policy makers and health workers was achieved following the two rounds of Delphi approach among the experts.</p>
</sec>
<sec>
<title>Conclusions</title>
<p>Based on the two Delphi rounds we discuss potential indicators and endemicity classification of this disabling disease, and the ongoing challenges to its elimination in countries with the highest prevalence. Consensus will help to increase effectiveness of podoconiosis elimination efforts and ensure comparability of outcome data.</p>
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<list>
<country>
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<li>Éthiopie</li>
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