LymphedemaV1, PubMed, Checkpoint, bibRecord, 000D74

Modelling strategies to break transmission of lymphatic filariasis--aggregation, adherence and vector competence greatly alter elimination.

Identifieur interne : 000D74 ( PubMed/Checkpoint ); précédent : 000D73; suivant : 000D75

Modelling strategies to break transmission of lymphatic filariasis--aggregation, adherence and vector competence greatly alter elimination.

Auteurs : M A Irvine [Royaume-Uni] ; L J Reimer [Royaume-Uni] ; S M Njenga [Kenya] ; S. Gunawardena [Sri Lanka] ; L. Kelly-Hope [Royaume-Uni] ; M. Bockarie [Royaume-Uni] ; T D Hollingsworth [Royaume-Uni]

Source :

Parasites & vectors [ 1756-3305 ] ; 2015.

RBID : pubmed:26489753

Descripteurs français

KwdFr :
- Filaricides (administration et posologie), Filariose lymphatique (traitement médicamenteux), Filariose lymphatique (transmission), Filariose lymphatique (épidémiologie), Kenya (épidémiologie), Lutte contre les insectes (), Modèles théoriques, Prévalence, Sri Lanka (épidémiologie), Transmission de maladie infectieuse ().
MESH :
- administration et posologie : Filaricides.
- traitement médicamenteux : Filariose lymphatique.
- épidémiologie : Filariose lymphatique, Kenya, Sri Lanka.
- Lutte contre les insectes, Modèles théoriques, Prévalence, Transmission de maladie infectieuse.
Wicri :
- geographic : Kenya, Sri Lanka.

English descriptors

KwdEn :
- Disease Transmission, Infectious (prevention & control), Elephantiasis, Filarial (drug therapy), Elephantiasis, Filarial (epidemiology), Elephantiasis, Filarial (transmission), Filaricides (administration & dosage), Insect Control (methods), Kenya (epidemiology), Models, Theoretical, Prevalence, Sri Lanka (epidemiology).
MESH :
- chemical , administration & dosage : Filaricides.
- geographic , epidemiology : Kenya, Sri Lanka.
- drug therapy : Elephantiasis, Filarial.
- epidemiology : Elephantiasis, Filarial.
- methods : Insect Control.
- prevention & control : Disease Transmission, Infectious.
- transmission : Elephantiasis, Filarial.
- Models, Theoretical, Prevalence.

Abstract

With ambitious targets to eliminate lymphatic filariasis over the coming years, there is a need to identify optimal strategies to achieve them in areas with different baseline prevalence and stages of control. Modelling can assist in identifying what data should be collected and what strategies are best for which scenarios.

DOI: 10.1186/s13071-015-1152-3
PubMed: 26489753

Affiliations:

Kenya, Royaume-Uni, Sri Lanka

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

to stream PubMed, to step Corpus: 000B71
to stream PubMed, to step Curation: 000B71

Links to Exploration step

pubmed:26489753

Le document en format XML

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<term>Elephantiasis, Filarial (drug therapy)</term>
<term>Elephantiasis, Filarial (epidemiology)</term>
<term>Elephantiasis, Filarial (transmission)</term>
<term>Filaricides (administration & dosage)</term>
<term>Insect Control (methods)</term>
<term>Kenya (epidemiology)</term>
<term>Models, Theoretical</term>
<term>Prevalence</term>
<term>Sri Lanka (epidemiology)</term>
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<keywords scheme="KwdFr" xml:lang="fr"><term>Filaricides (administration et posologie)</term>
<term>Filariose lymphatique (traitement médicamenteux)</term>
<term>Filariose lymphatique (transmission)</term>
<term>Filariose lymphatique (épidémiologie)</term>
<term>Kenya (épidémiologie)</term>
<term>Lutte contre les insectes ()</term>
<term>Modèles théoriques</term>
<term>Prévalence</term>
<term>Sri Lanka (épidémiologie)</term>
<term>Transmission de maladie infectieuse ()</term>
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</keywords>
<keywords scheme="MESH" type="geographic" qualifier="epidemiology" xml:lang="en"><term>Kenya</term>
<term>Sri Lanka</term>
</keywords>
<keywords scheme="MESH" qualifier="administration et posologie" xml:lang="fr"><term>Filaricides</term>
</keywords>
<keywords scheme="MESH" qualifier="drug therapy" xml:lang="en"><term>Elephantiasis, Filarial</term>
</keywords>
<keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>Elephantiasis, Filarial</term>
</keywords>
<keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Insect Control</term>
</keywords>
<keywords scheme="MESH" qualifier="prevention & control" xml:lang="en"><term>Disease Transmission, Infectious</term>
</keywords>
<keywords scheme="MESH" qualifier="traitement médicamenteux" xml:lang="fr"><term>Filariose lymphatique</term>
</keywords>
<keywords scheme="MESH" qualifier="transmission" xml:lang="en"><term>Elephantiasis, Filarial</term>
</keywords>
<keywords scheme="MESH" qualifier="épidémiologie" xml:lang="fr"><term>Filariose lymphatique</term>
<term>Kenya</term>
<term>Sri Lanka</term>
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<term>Prevalence</term>
</keywords>
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<term>Modèles théoriques</term>
<term>Prévalence</term>
<term>Transmission de maladie infectieuse</term>
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<term>Sri Lanka</term>
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<front><div type="abstract" xml:lang="en">With ambitious targets to eliminate lymphatic filariasis over the coming years, there is a need to identify optimal strategies to achieve them in areas with different baseline prevalence and stages of control. Modelling can assist in identifying what data should be collected and what strategies are best for which scenarios.</div>
</front>
</TEI>
<pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">26489753</PMID>
<DateCreated><Year>2015</Year>
<Month>10</Month>
<Day>22</Day>
</DateCreated>
<DateCompleted><Year>2016</Year>
<Month>07</Month>
<Day>22</Day>
</DateCompleted>
<DateRevised><Year>2017</Year>
<Month>09</Month>
<Day>02</Day>
</DateRevised>
<Article PubModel="Electronic"><Journal><ISSN IssnType="Electronic">1756-3305</ISSN>
<JournalIssue CitedMedium="Internet"><Volume>8</Volume>
<PubDate><Year>2015</Year>
<Month>Oct</Month>
<Day>22</Day>
</PubDate>
</JournalIssue>
<Title>Parasites & vectors</Title>
<ISOAbbreviation>Parasit Vectors</ISOAbbreviation>
</Journal>
<ArticleTitle>Modelling strategies to break transmission of lymphatic filariasis--aggregation, adherence and vector competence greatly alter elimination.</ArticleTitle>
<Pagination><MedlinePgn>547</MedlinePgn>
</Pagination>
<ELocationID EIdType="doi" ValidYN="Y">10.1186/s13071-015-1152-3</ELocationID>
<Abstract><AbstractText Label="BACKGROUND" NlmCategory="BACKGROUND">With ambitious targets to eliminate lymphatic filariasis over the coming years, there is a need to identify optimal strategies to achieve them in areas with different baseline prevalence and stages of control. Modelling can assist in identifying what data should be collected and what strategies are best for which scenarios.</AbstractText>
<AbstractText Label="METHODS" NlmCategory="METHODS">We develop a new individual-based, stochastic mathematical model of the transmission of lymphatic filariasis. We validate the model by fitting to a first time point and predicting future timepoints from surveillance data in Kenya and Sri Lanka, which have different vectors and different stages of the control programme. We then simulate different treatment scenarios in low, medium and high transmission settings, comparing once yearly mass drug administration (MDA) with more frequent MDA and higher coverage. We investigate the potential impact that vector control, systematic non-compliance and different levels of aggregation have on the dynamics of transmission and control.</AbstractText>
<AbstractText Label="RESULTS" NlmCategory="RESULTS">In all settings, increasing coverage from 65 to 80 % has a similar impact on control to treating twice a year at 65 % coverage, for fewer drug treatments being distributed. Vector control has a large impact, even at moderate levels. The extent of aggregation of parasite loads amongst a small portion of the population, which has been estimated to be highly variable in different settings, can undermine the success of a programme, particularly if high risk sub-communities are not accessing interventions.</AbstractText>
<AbstractText Label="CONCLUSION" NlmCategory="CONCLUSIONS">Even moderate levels of vector control have a large impact both on the reduction in prevalence and the maintenance of gains made during MDA, even when parasite loads are highly aggregated, and use of vector control is at moderate levels. For the same prevalence, differences in aggregation and adherence can result in very different dynamics. The novel analysis of a small amount of surveillance data and resulting simulations highlight the need for more individual level data to be analysed to effectively tailor programmes in the drive for elimination.</AbstractText>
</Abstract>
<AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Irvine</LastName>
<ForeName>M A</ForeName>
<Initials>MA</Initials>
<AffiliationInfo><Affiliation>School of Life Sciences, University of Warwick, Gibbet Hill Road, CV4 7AL, Coventry, UK. M.Irvine.1@Warwick.ac.uk.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Reimer</LastName>
<ForeName>L J</ForeName>
<Initials>LJ</Initials>
<AffiliationInfo><Affiliation>Liverpool School of Tropical Medicine, Pembroke Place, Liverpool, L3 5QA, UK.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Njenga</LastName>
<ForeName>S M</ForeName>
<Initials>SM</Initials>
<AffiliationInfo><Affiliation>Kenya Medical Research Institute (KEMRI), P.O. Box 54840, 00200, Nairobi, Kenya.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Gunawardena</LastName>
<ForeName>S</ForeName>
<Initials>S</Initials>
<AffiliationInfo><Affiliation>Faculty of Medicine, University of Colombo, Colombo, Sri Lanka.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Kelly-Hope</LastName>
<ForeName>L</ForeName>
<Initials>L</Initials>
<AffiliationInfo><Affiliation>Liverpool School of Tropical Medicine, Pembroke Place, Liverpool, L3 5QA, UK.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Bockarie</LastName>
<ForeName>M</ForeName>
<Initials>M</Initials>
<AffiliationInfo><Affiliation>Liverpool School of Tropical Medicine, Pembroke Place, Liverpool, L3 5QA, UK.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Hollingsworth</LastName>
<ForeName>T D</ForeName>
<Initials>TD</Initials>
<AffiliationInfo><Affiliation>School of Life Sciences, University of Warwick, Gibbet Hill Road, CV4 7AL, Coventry, UK.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>Mathematics Institute, University of Warwick, Gibbet Hill Road, CV4 7AL, Coventry, UK.</Affiliation>
</AffiliationInfo>
</Author>
</AuthorList>
<Language>eng</Language>
<GrantList CompleteYN="Y"><Grant><GrantID>MRC_G1001337</GrantID>
<Agency>Medical Research Council</Agency>
<Country>United Kingdom</Country>
</Grant>
</GrantList>
<PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType>
<PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType>
</PublicationTypeList>
<ArticleDate DateType="Electronic"><Year>2015</Year>
<Month>10</Month>
<Day>22</Day>
</ArticleDate>
</Article>
<MedlineJournalInfo><Country>England</Country>
<MedlineTA>Parasit Vectors</MedlineTA>
<NlmUniqueID>101462774</NlmUniqueID>
<ISSNLinking>1756-3305</ISSNLinking>
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<NameOfSubstance UI="D005369">Filaricides</NameOfSubstance>
</Chemical>
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Modelling strategies to break transmission of lymphatic filariasis--aggregation, adherence and vector competence greatly alter elimination.

Modelling strategies to break transmission of lymphatic filariasis--aggregation, adherence and vector competence greatly alter elimination.

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