Using Community-Level Prevalence of Loa loa Infection to Predict the Proportion of Highly-Infected Individuals: Statistical Modelling to Support Lymphatic Filariasis and Onchocerciasis Elimination Programs.
Identifieur interne : 000945 ( Main/Exploration ); précédent : 000944; suivant : 000946Using Community-Level Prevalence of Loa loa Infection to Predict the Proportion of Highly-Infected Individuals: Statistical Modelling to Support Lymphatic Filariasis and Onchocerciasis Elimination Programs.
Auteurs : Daniela K. Schlüter [Royaume-Uni] ; Martial L. Ndeffo-Mbah [États-Unis] ; Innocent Takougang [Cameroun] ; Tony Ukety [Suisse] ; Samuel Wanji [Cameroun] ; Alison P. Galvani [États-Unis] ; Peter J. Diggle [Royaume-Uni]Source :
- PLoS neglected tropical diseases [ 1935-2735 ] ; 2016.
Descripteurs français
- KwdFr :
- Animaux, Cameroun (épidémiologie), Caractéristiques de l'habitat, Congo (épidémiologie), Filariose lymphatique (), Filariose lymphatique (épidémiologie), Humains, Loa (physiologie), Loase (épidémiologie), Modèles statistiques, Onchocercose (), Onchocercose (épidémiologie), Population rurale, République démocratique du Congo (épidémiologie).
- MESH :
- physiologie : Loa.
- épidémiologie : Cameroun, Congo, Filariose lymphatique, Loase, Onchocercose, République démocratique du Congo.
- Animaux, Caractéristiques de l'habitat, Filariose lymphatique, Humains, Modèles statistiques, Onchocercose, Population rurale.
English descriptors
- KwdEn :
- Animals, Cameroon (epidemiology), Congo (epidemiology), Democratic Republic of the Congo (epidemiology), Elephantiasis, Filarial (epidemiology), Elephantiasis, Filarial (prevention & control), Humans, Loa (physiology), Loiasis (epidemiology), Models, Statistical, Onchocerciasis (epidemiology), Onchocerciasis (prevention & control), Residence Characteristics, Rural Population.
- MESH :
- epidemiology : Cameroon, Congo, Democratic Republic of the Congo, Elephantiasis, Filarial, Loiasis, Onchocerciasis.
- physiology : Loa.
- prevention & control : Elephantiasis, Filarial, Onchocerciasis.
- Animals, Humans, Models, Statistical, Residence Characteristics, Rural Population.
Abstract
Lymphatic Filariasis and Onchocerciasis (river blindness) constitute pressing public health issues in tropical regions. Global elimination programs, involving mass drug administration (MDA), have been launched by the World Health Organisation. Although the drugs used are generally well tolerated, individuals who are highly co-infected with Loa loa are at risk of experiencing serious adverse events. Highly infected individuals are more likely to be found in communities with high prevalence. An understanding of the relationship between individual infection and population-level prevalence can therefore inform decisions on whether MDA can be safely administered in an endemic community. Based on Loa loa infection intensity data from individuals in Cameroon, the Republic of the Congo and the Democratic Republic of the Congo we develop a statistical model for the distribution of infection levels in communities. We then use this model to make predictive inferences regarding the proportion of individuals whose parasite count exceeds policy-relevant levels. In particular we show how to exploit the positive correlation between community-level prevalence and intensity of infection in order to predict the proportion of highly infected individuals in a community given only prevalence data from the community in question. The resulting prediction intervals are not substantially wider, and in some cases narrower, than the corresponding binomial confidence intervals obtained from data that include measurements of individual infection levels. Therefore the model developed here facilitates the estimation of the proportion of individuals highly infected with Loa loa using only estimated community level prevalence. It can be used to assess the risk of rolling out MDA in a specific community, or to guide policy decisions.
DOI: 10.1371/journal.pntd.0005157
PubMed: 27906982
Affiliations:
Links toward previous steps (curation, corpus...)
- to stream PubMed, to step Corpus: 000493
- to stream PubMed, to step Curation: 000493
- to stream PubMed, to step Checkpoint: 000493
- to stream Ncbi, to step Merge: 008A64
- to stream Ncbi, to step Curation: 008A64
- to stream Ncbi, to step Checkpoint: 008A64
- to stream Main, to step Merge: 000946
- to stream Main, to step Curation: 000945
Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Using Community-Level Prevalence of Loa loa Infection to Predict the Proportion of Highly-Infected Individuals: Statistical Modelling to Support Lymphatic Filariasis and Onchocerciasis Elimination Programs.</title><author><name sortKey="Schluter, Daniela K" sort="Schluter, Daniela K" uniqKey="Schluter D" first="Daniela K" last="Schlüter">Daniela K. Schlüter</name><affiliation wicri:level="1"><nlm:affiliation>CHICAS, Lancaster Medical School, Lancaster University, Lancaster, United Kingdom.</nlm:affiliation><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>CHICAS, Lancaster Medical School, Lancaster University, Lancaster</wicri:regionArea><wicri:noRegion>Lancaster</wicri:noRegion></affiliation></author><author><name sortKey="Ndeffo Mbah, Martial L" sort="Ndeffo Mbah, Martial L" uniqKey="Ndeffo Mbah M" first="Martial L" last="Ndeffo-Mbah">Martial L. Ndeffo-Mbah</name><affiliation wicri:level="2"><nlm:affiliation>Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut</wicri:regionArea><placeName><region type="state">Connecticut</region></placeName></affiliation></author><author><name sortKey="Takougang, Innocent" sort="Takougang, Innocent" uniqKey="Takougang I" first="Innocent" last="Takougang">Innocent Takougang</name><affiliation wicri:level="1"><nlm:affiliation>Foundation for Health Research & Development, Department of Public Health, University of Yaoundé 1, Yaoundé, Cameroon.</nlm:affiliation><country xml:lang="fr">Cameroun</country><wicri:regionArea>Foundation for Health Research & Development, Department of Public Health, University of Yaoundé 1, Yaoundé</wicri:regionArea><wicri:noRegion>Yaoundé</wicri:noRegion></affiliation></author><author><name sortKey="Ukety, Tony" sort="Ukety, Tony" uniqKey="Ukety T" first="Tony" last="Ukety">Tony Ukety</name><affiliation wicri:level="1"><nlm:affiliation>World Health Organisation, Geneva, Switzerland.</nlm:affiliation><country xml:lang="fr">Suisse</country><wicri:regionArea>World Health Organisation, Geneva</wicri:regionArea><wicri:noRegion>Geneva</wicri:noRegion></affiliation></author><author><name sortKey="Wanji, Samuel" sort="Wanji, Samuel" uniqKey="Wanji S" first="Samuel" last="Wanji">Samuel Wanji</name><affiliation wicri:level="1"><nlm:affiliation>Parasites and Vectors Research Unit, Department of Microbiology and Parasitology, University of Buea, Cameroon.</nlm:affiliation><country xml:lang="fr">Cameroun</country><wicri:regionArea>Parasites and Vectors Research Unit, Department of Microbiology and Parasitology, University of Buea</wicri:regionArea><wicri:noRegion>University of Buea</wicri:noRegion></affiliation></author><author><name sortKey="Galvani, Alison P" sort="Galvani, Alison P" uniqKey="Galvani A" first="Alison P" last="Galvani">Alison P. Galvani</name><affiliation wicri:level="2"><nlm:affiliation>Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut</wicri:regionArea><placeName><region type="state">Connecticut</region></placeName></affiliation></author><author><name sortKey="Diggle, Peter J" sort="Diggle, Peter J" uniqKey="Diggle P" first="Peter J" last="Diggle">Peter J. Diggle</name><affiliation wicri:level="1"><nlm:affiliation>CHICAS, Lancaster Medical School, Lancaster University, Lancaster, United Kingdom.</nlm:affiliation><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>CHICAS, Lancaster Medical School, Lancaster University, Lancaster</wicri:regionArea><wicri:noRegion>Lancaster</wicri:noRegion></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2016">2016</date><idno type="RBID">pubmed:27906982</idno><idno type="pmid">27906982</idno><idno type="doi">10.1371/journal.pntd.0005157</idno><idno type="wicri:Area/PubMed/Corpus">000493</idno><idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Corpus" wicri:corpus="PubMed">000493</idno><idno type="wicri:Area/PubMed/Curation">000493</idno><idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Curation">000493</idno><idno type="wicri:Area/PubMed/Checkpoint">000493</idno><idno type="wicri:explorRef" wicri:stream="Checkpoint" wicri:step="PubMed">000493</idno><idno type="wicri:Area/Ncbi/Merge">008A64</idno><idno type="wicri:Area/Ncbi/Curation">008A64</idno><idno type="wicri:Area/Ncbi/Checkpoint">008A64</idno><idno type="wicri:Area/Main/Merge">000946</idno><idno type="wicri:Area/Main/Curation">000945</idno><idno type="wicri:Area/Main/Exploration">000945</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Using Community-Level Prevalence of Loa loa Infection to Predict the Proportion of Highly-Infected Individuals: Statistical Modelling to Support Lymphatic Filariasis and Onchocerciasis Elimination Programs.</title><author><name sortKey="Schluter, Daniela K" sort="Schluter, Daniela K" uniqKey="Schluter D" first="Daniela K" last="Schlüter">Daniela K. Schlüter</name><affiliation wicri:level="1"><nlm:affiliation>CHICAS, Lancaster Medical School, Lancaster University, Lancaster, United Kingdom.</nlm:affiliation><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>CHICAS, Lancaster Medical School, Lancaster University, Lancaster</wicri:regionArea><wicri:noRegion>Lancaster</wicri:noRegion></affiliation></author><author><name sortKey="Ndeffo Mbah, Martial L" sort="Ndeffo Mbah, Martial L" uniqKey="Ndeffo Mbah M" first="Martial L" last="Ndeffo-Mbah">Martial L. Ndeffo-Mbah</name><affiliation wicri:level="2"><nlm:affiliation>Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut</wicri:regionArea><placeName><region type="state">Connecticut</region></placeName></affiliation></author><author><name sortKey="Takougang, Innocent" sort="Takougang, Innocent" uniqKey="Takougang I" first="Innocent" last="Takougang">Innocent Takougang</name><affiliation wicri:level="1"><nlm:affiliation>Foundation for Health Research & Development, Department of Public Health, University of Yaoundé 1, Yaoundé, Cameroon.</nlm:affiliation><country xml:lang="fr">Cameroun</country><wicri:regionArea>Foundation for Health Research & Development, Department of Public Health, University of Yaoundé 1, Yaoundé</wicri:regionArea><wicri:noRegion>Yaoundé</wicri:noRegion></affiliation></author><author><name sortKey="Ukety, Tony" sort="Ukety, Tony" uniqKey="Ukety T" first="Tony" last="Ukety">Tony Ukety</name><affiliation wicri:level="1"><nlm:affiliation>World Health Organisation, Geneva, Switzerland.</nlm:affiliation><country xml:lang="fr">Suisse</country><wicri:regionArea>World Health Organisation, Geneva</wicri:regionArea><wicri:noRegion>Geneva</wicri:noRegion></affiliation></author><author><name sortKey="Wanji, Samuel" sort="Wanji, Samuel" uniqKey="Wanji S" first="Samuel" last="Wanji">Samuel Wanji</name><affiliation wicri:level="1"><nlm:affiliation>Parasites and Vectors Research Unit, Department of Microbiology and Parasitology, University of Buea, Cameroon.</nlm:affiliation><country xml:lang="fr">Cameroun</country><wicri:regionArea>Parasites and Vectors Research Unit, Department of Microbiology and Parasitology, University of Buea</wicri:regionArea><wicri:noRegion>University of Buea</wicri:noRegion></affiliation></author><author><name sortKey="Galvani, Alison P" sort="Galvani, Alison P" uniqKey="Galvani A" first="Alison P" last="Galvani">Alison P. Galvani</name><affiliation wicri:level="2"><nlm:affiliation>Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut</wicri:regionArea><placeName><region type="state">Connecticut</region></placeName></affiliation></author><author><name sortKey="Diggle, Peter J" sort="Diggle, Peter J" uniqKey="Diggle P" first="Peter J" last="Diggle">Peter J. Diggle</name><affiliation wicri:level="1"><nlm:affiliation>CHICAS, Lancaster Medical School, Lancaster University, Lancaster, United Kingdom.</nlm:affiliation><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>CHICAS, Lancaster Medical School, Lancaster University, Lancaster</wicri:regionArea><wicri:noRegion>Lancaster</wicri:noRegion></affiliation></author></analytic><series><title level="j">PLoS neglected tropical diseases</title><idno type="eISSN">1935-2735</idno><imprint><date when="2016" type="published">2016</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Animals</term><term>Cameroon (epidemiology)</term><term>Congo (epidemiology)</term><term>Democratic Republic of the Congo (epidemiology)</term><term>Elephantiasis, Filarial (epidemiology)</term><term>Elephantiasis, Filarial (prevention & control)</term><term>Humans</term><term>Loa (physiology)</term><term>Loiasis (epidemiology)</term><term>Models, Statistical</term><term>Onchocerciasis (epidemiology)</term><term>Onchocerciasis (prevention & control)</term><term>Residence Characteristics</term><term>Rural Population</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Animaux</term><term>Cameroun (épidémiologie)</term><term>Caractéristiques de l'habitat</term><term>Congo (épidémiologie)</term><term>Filariose lymphatique ()</term><term>Filariose lymphatique (épidémiologie)</term><term>Humains</term><term>Loa (physiologie)</term><term>Loase (épidémiologie)</term><term>Modèles statistiques</term><term>Onchocercose ()</term><term>Onchocercose (épidémiologie)</term><term>Population rurale</term><term>République démocratique du Congo (épidémiologie)</term></keywords><keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>Cameroon</term><term>Congo</term><term>Democratic Republic of the Congo</term><term>Elephantiasis, Filarial</term><term>Loiasis</term><term>Onchocerciasis</term></keywords><keywords scheme="MESH" qualifier="physiologie" xml:lang="fr"><term>Loa</term></keywords><keywords scheme="MESH" qualifier="physiology" xml:lang="en"><term>Loa</term></keywords><keywords scheme="MESH" qualifier="prevention & control" xml:lang="en"><term>Elephantiasis, Filarial</term><term>Onchocerciasis</term></keywords><keywords scheme="MESH" qualifier="épidémiologie" xml:lang="fr"><term>Cameroun</term><term>Congo</term><term>Filariose lymphatique</term><term>Loase</term><term>Onchocercose</term><term>République démocratique du Congo</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Animals</term><term>Humans</term><term>Models, Statistical</term><term>Residence Characteristics</term><term>Rural Population</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Animaux</term><term>Caractéristiques de l'habitat</term><term>Filariose lymphatique</term><term>Humains</term><term>Modèles statistiques</term><term>Onchocercose</term><term>Population rurale</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Lymphatic Filariasis and Onchocerciasis (river blindness) constitute pressing public health issues in tropical regions. Global elimination programs, involving mass drug administration (MDA), have been launched by the World Health Organisation. Although the drugs used are generally well tolerated, individuals who are highly co-infected with Loa loa are at risk of experiencing serious adverse events. Highly infected individuals are more likely to be found in communities with high prevalence. An understanding of the relationship between individual infection and population-level prevalence can therefore inform decisions on whether MDA can be safely administered in an endemic community. Based on Loa loa infection intensity data from individuals in Cameroon, the Republic of the Congo and the Democratic Republic of the Congo we develop a statistical model for the distribution of infection levels in communities. We then use this model to make predictive inferences regarding the proportion of individuals whose parasite count exceeds policy-relevant levels. In particular we show how to exploit the positive correlation between community-level prevalence and intensity of infection in order to predict the proportion of highly infected individuals in a community given only prevalence data from the community in question. The resulting prediction intervals are not substantially wider, and in some cases narrower, than the corresponding binomial confidence intervals obtained from data that include measurements of individual infection levels. Therefore the model developed here facilitates the estimation of the proportion of individuals highly infected with Loa loa using only estimated community level prevalence. It can be used to assess the risk of rolling out MDA in a specific community, or to guide policy decisions.</div></front></TEI><affiliations><list><country><li>Cameroun</li><li>Royaume-Uni</li><li>Suisse</li><li>États-Unis</li></country><region><li>Connecticut</li></region></list><tree><country name="Royaume-Uni"><noRegion><name sortKey="Schluter, Daniela K" sort="Schluter, Daniela K" uniqKey="Schluter D" first="Daniela K" last="Schlüter">Daniela K. Schlüter</name></noRegion><name sortKey="Diggle, Peter J" sort="Diggle, Peter J" uniqKey="Diggle P" first="Peter J" last="Diggle">Peter J. Diggle</name></country><country name="États-Unis"><region name="Connecticut"><name sortKey="Ndeffo Mbah, Martial L" sort="Ndeffo Mbah, Martial L" uniqKey="Ndeffo Mbah M" first="Martial L" last="Ndeffo-Mbah">Martial L. Ndeffo-Mbah</name></region><name sortKey="Galvani, Alison P" sort="Galvani, Alison P" uniqKey="Galvani A" first="Alison P" last="Galvani">Alison P. Galvani</name></country><country name="Cameroun"><noRegion><name sortKey="Takougang, Innocent" sort="Takougang, Innocent" uniqKey="Takougang I" first="Innocent" last="Takougang">Innocent Takougang</name></noRegion><name sortKey="Wanji, Samuel" sort="Wanji, Samuel" uniqKey="Wanji S" first="Samuel" last="Wanji">Samuel Wanji</name></country><country name="Suisse"><noRegion><name sortKey="Ukety, Tony" sort="Ukety, Tony" uniqKey="Ukety T" first="Tony" last="Ukety">Tony Ukety</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Wicri/Sante/explor/LymphedemaV1/Data/Main/Exploration
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 000945 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Main/Exploration/biblio.hfd -nk 000945 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien
|wiki= Wicri/Sante
|area= LymphedemaV1
|flux= Main
|étape= Exploration
|type= RBID
|clé= pubmed:27906982
|texte= Using Community-Level Prevalence of Loa loa Infection to Predict the Proportion of Highly-Infected Individuals: Statistical Modelling to Support Lymphatic Filariasis and Onchocerciasis Elimination Programs.
}}
Pour générer des pages wiki
HfdIndexSelect -h $EXPLOR_AREA/Data/Main/Exploration/RBID.i -Sk "pubmed:27906982" \
| HfdSelect -Kh $EXPLOR_AREA/Data/Main/Exploration/biblio.hfd \
| NlmPubMed2Wicri -a LymphedemaV1
| This area was generated with Dilib version V0.6.31. |  |