Modelling the effect of bednet coverage on malaria transmission in South Sudan.

 

Show simple item record

dc.contributor.author Mukhtar, Abdulaziz Y A
dc.contributor.author Munyakaz, Justin B
dc.contributor.author Ouifki, Rachid
dc.contributor.author Clark, A E
dc.date.accessioned 2019-04-01T12:01:58Z
dc.date.available 2019-04-01T12:01:58Z
dc.date.issued 2008-06-07
dc.identifier.citation Mukhtar, A., Munyakaz, J., Ouifki, R., Clark, A. 2008-06-07. Modelling the effect of bednet coverage on malaria transmission in South Sudan. Plos One. 13; 6; 1-22. en_ZA
dc.identifier.uri http://hdl.handle.net/11427/29959
dc.description.abstract A campaign for malaria control, using Long Lasting Insecticide Nets (LLINs) was launched in South Sudan in 2009. The success of such a campaign often depends upon adequate available resources and reliable surveillance data which help officials understand existing infections. An optimal allocation of resources for malaria control at a sub-national scale is therefore paramount to the success of efforts to reduce malaria prevalence. In this paper, we extend an existing SIR mathematical model to capture the effect of LLINs on malaria transmission. Available data on malaria is utilized to determine realistic parameter values of this model using a Bayesian approach via Markov Chain Monte Carlo (MCMC) methods. Then, we explore the parasite prevalence on a continued rollout of LLINs in three different settings in order to create a sub-national projection of malaria. Further, we calculate the model’s basic reproductive number and study its sensitivity to LLINs’ coverage and its efficacy. From the numerical simulation results, we notice a basic reproduction number, R0, confirming a substantial increase of incidence cases if no form of intervention takes place in the community. This work indicates that an effective use of LLINs may reduce R0 and hence malaria transmission. We hope that this study will provide a basis for recommending a scaling-up of the entry point of LLINs’ distribution that targets households in areas at risk of malaria. en_US
dc.language.iso en en_US
dc.rights.uri http://creativecommons.org/licenses/by/4.0/ en_US
dc.source Plos One en_US
dc.source.uri https://journals.plos.org/plosone/
dc.title Modelling the effect of bednet coverage on malaria transmission in South Sudan. en_US
dc.type Journal Article en_US
dc.publisher.faculty Faculty of Science en_US
dc.publisher.department Department of Statistical Sciences en_US
dc.source.journalvolume 13 en_US
dc.source.journalissue 6 en_US
dc.source.pagination 1-22 en_US
dc.identifier.apacitation Mukhtar, A. Y. A., Munyakaz, J. B., Ouifki, R., & Clark, A. E. (2008). Modelling the effect of bednet coverage on malaria transmission in South Sudan. <i>Plos One</i>, 13(6), 1-22. http://hdl.handle.net/11427/29959 en_ZA
dc.identifier.chicagocitation Mukhtar, Abdulaziz Y A, Justin B Munyakaz, Rachid Ouifki, and A E Clark "Modelling the effect of bednet coverage on malaria transmission in South Sudan." <i>Plos One</i> 13, 6. (2008): 1-22. http://hdl.handle.net/11427/29959 en_ZA
dc.identifier.vancouvercitation Mukhtar AYA, Munyakaz JB, Ouifki R, Clark AE. Modelling the effect of bednet coverage on malaria transmission in South Sudan. Plos One. 2008;13(6):1-22. http://hdl.handle.net/11427/29959. en_ZA
dc.identifier.ris TY - Journal Article AU - Mukhtar, Abdulaziz Y A AU - Munyakaz, Justin B AU - Ouifki, Rachid AU - Clark, A E AB - A campaign for malaria control, using Long Lasting Insecticide Nets (LLINs) was launched in South Sudan in 2009. The success of such a campaign often depends upon adequate available resources and reliable surveillance data which help officials understand existing infections. An optimal allocation of resources for malaria control at a sub-national scale is therefore paramount to the success of efforts to reduce malaria prevalence. In this paper, we extend an existing SIR mathematical model to capture the effect of LLINs on malaria transmission. Available data on malaria is utilized to determine realistic parameter values of this model using a Bayesian approach via Markov Chain Monte Carlo (MCMC) methods. Then, we explore the parasite prevalence on a continued rollout of LLINs in three different settings in order to create a sub-national projection of malaria. Further, we calculate the model’s basic reproductive number and study its sensitivity to LLINs’ coverage and its efficacy. From the numerical simulation results, we notice a basic reproduction number, R0, confirming a substantial increase of incidence cases if no form of intervention takes place in the community. This work indicates that an effective use of LLINs may reduce R0 and hence malaria transmission. We hope that this study will provide a basis for recommending a scaling-up of the entry point of LLINs’ distribution that targets households in areas at risk of malaria. DA - 2008-06-07 DB - OpenUCT DP - University of Cape Town IS - 6 J1 - Plos One LK - https://open.uct.ac.za PY - 2008 T1 - Modelling the effect of bednet coverage on malaria transmission in South Sudan TI - Modelling the effect of bednet coverage on malaria transmission in South Sudan UR - http://hdl.handle.net/11427/29959 ER - en_ZA


Files in this item

This item appears in the following Collection(s)

Show simple item record

http://creativecommons.org/licenses/by/4.0/ Except where otherwise noted, this item's license is described as http://creativecommons.org/licenses/by/4.0/