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dc.contributor.author
Cohen, Joel E
dc.contributor.author
zu Dohna, Heinrich
dc.contributor.author
Gurtler, Ricardo Esteban
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dc.date.available
2022-06-25T02:58:46Z
dc.date.issued
2019-12
dc.identifier.citation
Cohen, Joel E; zu Dohna, Heinrich; Gurtler, Ricardo Esteban; Insights from quantitative and mathematical modelling on the proposed WHO 2030 goals for Chagas disease; Bill and Melinda Gates Foundation; Gates Open Research; 3; 12-2019; 1539-1539
dc.identifier.issn
2572-4754
dc.identifier.uri
http://hdl.handle.net/11336/160563
dc.description.abstract
Chagas disease (CD) persists as one of the neglected tropical diseases (NTDs) with a particularly large impact in the Americas. The World Health Organization (WHO) recently proposed goals for CD elimination as a public health problem to be reached by 2030 by means of achieving intradomiciliary transmission interruption (IDTI), blood transfusion and transplant transmission interruption, diagnostic and treatment scaling-up and prevention and control of congenital transmission. The NTD Modelling Consortium has developed mathematical models to study Trypanosoma cruzi transmission dynamics and the potential impact of control measures. Modelling insights have shown that IDTI is feasible in areas with sustained vector control programmes and no presence of native triatomine vector populations. However, IDTI in areas with native vectors it is not feasible in a sustainable manner. Combining vector control with trypanocidal treatment can reduce the timeframes necessary to reach operational thresholds for IDTI (<2% seroprevalence in children aged <5 years), but the most informative age groups for serological monitoring are yet to be identified. Measuring progress towards the 2030 goals will require availability of vector surveillance and seroprevalence data at a fine scale, and a more active surveillance system, as well as a better understanding of the risks of vector re-colonization and disease resurgence after vector control cessation. Also, achieving scaling-up in terms of access to treatment to the expected levels (75%) will require a substantial increase in screening asymptomatic populations, which is anticipated to become very costly as CD prevalence decreases. Further modelling work includes refining and extending mathematical models (including transmission dynamics and statistical frameworks) to predict transmission at a sub-national scale, and developing quantitative tools to inform IDTI certification, post-certification and re-certification protocols. Potential perverse incentives associated with operational thresholds are discussed. These modelling insights aim to inform discussions on the goals and treatment guidelines for CD.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Bill and Melinda Gates Foundation
dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by/2.5/ar/
dc.subject
Chagas disease
dc.subject
mathematical model
dc.subject
disease control
dc.subject
vector control
dc.subject.classification
Ecología
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dc.subject.classification
Ciencias Biológicas
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dc.subject.classification
CIENCIAS NATURALES Y EXACTAS
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dc.title
Insights from quantitative and mathematical modelling on the proposed WHO 2030 goals for Chagas disease
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2020-11-20T14:43:40Z
dc.journal.volume
3
dc.journal.pagination
1539-1539
dc.journal.pais
Estados Unidos
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dc.journal.ciudad
Seattle
dc.description.fil
Fil: Cohen, Joel E. The Rockefeller University; Estados Unidos
dc.description.fil
Fil: zu Dohna, Heinrich. The Rockefeller University; Estados Unidos
dc.description.fil
Fil: Gurtler, Ricardo Esteban. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ecología, Genética y Evolución; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Ecología, Genética y Evolución de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Ecología, Genética y Evolución de Buenos Aires; Argentina
dc.journal.title
Gates Open Research
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.21956/gatesopenres.14202.r27887
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://gatesopenresearch.org/articles/3-1539/v1#referee-response-27887
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