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Modelling the distribution and transmission intensity of lymphatic filariasis in sub-Saharan Africa prior to scaling up interventions: integrated use of geostatistical and mathematical modelling

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Modelling the distribution and transmission intensity of lymphatic filariasis in sub-Saharan Africa prior to scaling up interventions: integrated use of geostatistical and mathematical modelling. / Moraga, Paula; Cano, Jorge; Baggaley, Rebecca F et al.
In: Parasites and Vectors, Vol. 8, 560, 24.10.2015.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Moraga, P, Cano, J, Baggaley, RF, Gyapong, JO, Njenga, SM, Nikolay, B, Davies, E, Rebollo, MP, Pullan, RL, Bockarie, MJ, Hollingsworth, TD, Gambhir, M & Brooker, SJ 2015, 'Modelling the distribution and transmission intensity of lymphatic filariasis in sub-Saharan Africa prior to scaling up interventions: integrated use of geostatistical and mathematical modelling', Parasites and Vectors, vol. 8, 560. https://doi.org/10.1186/s13071-015-1166-x

APA

Moraga, P., Cano, J., Baggaley, R. F., Gyapong, J. O., Njenga, S. M., Nikolay, B., Davies, E., Rebollo, M. P., Pullan, R. L., Bockarie, M. J., Hollingsworth, T. D., Gambhir, M., & Brooker, S. J. (2015). Modelling the distribution and transmission intensity of lymphatic filariasis in sub-Saharan Africa prior to scaling up interventions: integrated use of geostatistical and mathematical modelling. Parasites and Vectors, 8, Article 560. https://doi.org/10.1186/s13071-015-1166-x

Vancouver

Moraga P, Cano J, Baggaley RF, Gyapong JO, Njenga SM, Nikolay B et al. Modelling the distribution and transmission intensity of lymphatic filariasis in sub-Saharan Africa prior to scaling up interventions: integrated use of geostatistical and mathematical modelling. Parasites and Vectors. 2015 Oct 24;8:560. doi: 10.1186/s13071-015-1166-x

Author

Bibtex

@article{8b1c7309616b47d7b0f065f43a64fd04,
title = "Modelling the distribution and transmission intensity of lymphatic filariasis in sub-Saharan Africa prior to scaling up interventions: integrated use of geostatistical and mathematical modelling",
abstract = "BACKGROUND: Lymphatic filariasis (LF) is one of the neglected tropical diseases targeted for global elimination. The ability to interrupt transmission is, partly, influenced by the underlying intensity of transmission and its geographical variation. This information can also help guide the design of targeted surveillance activities. The present study uses a combination of geostatistical and mathematical modelling to predict the prevalence and transmission intensity of LF prior to the implementation of large-scale control in sub-Saharan Africa.METHODS: A systematic search of the literature was undertaken to identify surveys on the prevalence of Wuchereria bancrofti microfilaraemia (mf), based on blood smears, and on the prevalence of antigenaemia, based on the use of an immuno-chromatographic card test (ICT). Using a suite of environmental and demographic data, spatiotemporal multivariate models were fitted separately for mf prevalence and ICT-based prevalence within a Bayesian framework and used to make predictions for non-sampled areas. Maps of the dominant vector species of LF were also developed. The maps of predicted prevalence and vector distribution were linked to mathematical models of the transmission dynamics of LF to infer the intensity of transmission, quantified by the basic reproductive number (R0).RESULTS: The literature search identified 1267 surveys that provide suitable data on the prevalence of mf and 2817 surveys that report the prevalence of antigenaemia. Distinct spatial predictions arose from the models for mf prevalence and ICT-based prevalence, with a wider geographical distribution when using ICT-based data. The vector distribution maps demonstrated the spatial variation of LF vector species. Mathematical modelling showed that the reproduction number (R0) estimates vary from 2.7 to 30, with large variations between and within regions.CONCLUSIONS: LF transmission is highly heterogeneous, and the developed maps can help guide intervention, monitoring and surveillance strategies as countries progress towards LF elimination.",
keywords = "Africa South of the Sahara, Animals, Communicable Disease Control, Elephantiasis, Filarial, Epidemiological Monitoring, Models, Theoretical, Prevalence, Spatio-Temporal Analysis, Topography, Medical, Wuchereria bancrofti, Journal Article, Meta-Analysis, Research Support, Non-U.S. Gov't",
author = "Paula Moraga and Jorge Cano and Baggaley, {Rebecca F} and Gyapong, {John O} and Njenga, {Sammy M} and Birgit Nikolay and Emmanuel Davies and Rebollo, {Maria P} and Pullan, {Rachel L} and Bockarie, {Moses J} and Hollingsworth, {T D{\'e}irdre} and Manoj Gambhir and Brooker, {Simon J}",
year = "2015",
month = oct,
day = "24",
doi = "10.1186/s13071-015-1166-x",
language = "English",
volume = "8",
journal = "Parasites and Vectors",
issn = "1756-3305",
publisher = "BioMed Central",

}

RIS

TY - JOUR

T1 - Modelling the distribution and transmission intensity of lymphatic filariasis in sub-Saharan Africa prior to scaling up interventions

T2 - integrated use of geostatistical and mathematical modelling

AU - Moraga, Paula

AU - Cano, Jorge

AU - Baggaley, Rebecca F

AU - Gyapong, John O

AU - Njenga, Sammy M

AU - Nikolay, Birgit

AU - Davies, Emmanuel

AU - Rebollo, Maria P

AU - Pullan, Rachel L

AU - Bockarie, Moses J

AU - Hollingsworth, T Déirdre

AU - Gambhir, Manoj

AU - Brooker, Simon J

PY - 2015/10/24

Y1 - 2015/10/24

N2 - BACKGROUND: Lymphatic filariasis (LF) is one of the neglected tropical diseases targeted for global elimination. The ability to interrupt transmission is, partly, influenced by the underlying intensity of transmission and its geographical variation. This information can also help guide the design of targeted surveillance activities. The present study uses a combination of geostatistical and mathematical modelling to predict the prevalence and transmission intensity of LF prior to the implementation of large-scale control in sub-Saharan Africa.METHODS: A systematic search of the literature was undertaken to identify surveys on the prevalence of Wuchereria bancrofti microfilaraemia (mf), based on blood smears, and on the prevalence of antigenaemia, based on the use of an immuno-chromatographic card test (ICT). Using a suite of environmental and demographic data, spatiotemporal multivariate models were fitted separately for mf prevalence and ICT-based prevalence within a Bayesian framework and used to make predictions for non-sampled areas. Maps of the dominant vector species of LF were also developed. The maps of predicted prevalence and vector distribution were linked to mathematical models of the transmission dynamics of LF to infer the intensity of transmission, quantified by the basic reproductive number (R0).RESULTS: The literature search identified 1267 surveys that provide suitable data on the prevalence of mf and 2817 surveys that report the prevalence of antigenaemia. Distinct spatial predictions arose from the models for mf prevalence and ICT-based prevalence, with a wider geographical distribution when using ICT-based data. The vector distribution maps demonstrated the spatial variation of LF vector species. Mathematical modelling showed that the reproduction number (R0) estimates vary from 2.7 to 30, with large variations between and within regions.CONCLUSIONS: LF transmission is highly heterogeneous, and the developed maps can help guide intervention, monitoring and surveillance strategies as countries progress towards LF elimination.

AB - BACKGROUND: Lymphatic filariasis (LF) is one of the neglected tropical diseases targeted for global elimination. The ability to interrupt transmission is, partly, influenced by the underlying intensity of transmission and its geographical variation. This information can also help guide the design of targeted surveillance activities. The present study uses a combination of geostatistical and mathematical modelling to predict the prevalence and transmission intensity of LF prior to the implementation of large-scale control in sub-Saharan Africa.METHODS: A systematic search of the literature was undertaken to identify surveys on the prevalence of Wuchereria bancrofti microfilaraemia (mf), based on blood smears, and on the prevalence of antigenaemia, based on the use of an immuno-chromatographic card test (ICT). Using a suite of environmental and demographic data, spatiotemporal multivariate models were fitted separately for mf prevalence and ICT-based prevalence within a Bayesian framework and used to make predictions for non-sampled areas. Maps of the dominant vector species of LF were also developed. The maps of predicted prevalence and vector distribution were linked to mathematical models of the transmission dynamics of LF to infer the intensity of transmission, quantified by the basic reproductive number (R0).RESULTS: The literature search identified 1267 surveys that provide suitable data on the prevalence of mf and 2817 surveys that report the prevalence of antigenaemia. Distinct spatial predictions arose from the models for mf prevalence and ICT-based prevalence, with a wider geographical distribution when using ICT-based data. The vector distribution maps demonstrated the spatial variation of LF vector species. Mathematical modelling showed that the reproduction number (R0) estimates vary from 2.7 to 30, with large variations between and within regions.CONCLUSIONS: LF transmission is highly heterogeneous, and the developed maps can help guide intervention, monitoring and surveillance strategies as countries progress towards LF elimination.

KW - Africa South of the Sahara

KW - Animals

KW - Communicable Disease Control

KW - Elephantiasis, Filarial

KW - Epidemiological Monitoring

KW - Models, Theoretical

KW - Prevalence

KW - Spatio-Temporal Analysis

KW - Topography, Medical

KW - Wuchereria bancrofti

KW - Journal Article

KW - Meta-Analysis

KW - Research Support, Non-U.S. Gov't

U2 - 10.1186/s13071-015-1166-x

DO - 10.1186/s13071-015-1166-x

M3 - Journal article

C2 - 26496983

VL - 8

JO - Parasites and Vectors

JF - Parasites and Vectors

SN - 1756-3305

M1 - 560

ER -