Modelling the effect of bednet coverage on malaria transmission in South Sudan.
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...
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| _version_ | 1849766398706843648 |
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| author | Abdulaziz Y A Mukhtar Justin B Munyakazi Rachid Ouifki Allan E Clark |
| author_facet | Abdulaziz Y A Mukhtar Justin B Munyakazi Rachid Ouifki Allan E Clark |
| author_sort | Abdulaziz Y A Mukhtar |
| collection | DOAJ |
| description | 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, [Formula: see text], 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 [Formula: see text] 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. |
| format | Article |
| id | doaj-art-9f290f8d92184724aff7a4d48d632182 |
| institution | DOAJ |
| issn | 1932-6203 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-9f290f8d92184724aff7a4d48d6321822025-08-20T03:04:35ZengPublic Library of Science (PLoS)PLoS ONE1932-62032018-01-01136e019828010.1371/journal.pone.0198280Modelling the effect of bednet coverage on malaria transmission in South Sudan.Abdulaziz Y A MukhtarJustin B MunyakaziRachid OuifkiAllan E ClarkA 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, [Formula: see text], 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 [Formula: see text] 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.https://storage.googleapis.com/plos-corpus-prod/10.1371/journal.pone.0198280/1/pone.0198280.pdf?X-Goog-Algorithm=GOOG4-RSA-SHA256&X-Goog-Credential=wombat-sa%40plos-prod.iam.gserviceaccount.com%2F20210222%2Fauto%2Fstorage%2Fgoog4_request&X-Goog-Date=20210222T125733Z&X-Goog-Expires=3600&X-Goog-SignedHeaders=host&X-Goog-Signature=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 |
| spellingShingle | Abdulaziz Y A Mukhtar Justin B Munyakazi Rachid Ouifki Allan E Clark Modelling the effect of bednet coverage on malaria transmission in South Sudan. PLoS ONE |
| title | Modelling the effect of bednet coverage on malaria transmission in South Sudan. |
| title_full | Modelling the effect of bednet coverage on malaria transmission in South Sudan. |
| title_fullStr | Modelling the effect of bednet coverage on malaria transmission in South Sudan. |
| title_full_unstemmed | Modelling the effect of bednet coverage on malaria transmission in South Sudan. |
| title_short | Modelling the effect of bednet coverage on malaria transmission in South Sudan. |
| title_sort | modelling the effect of bednet coverage on malaria transmission in south sudan |
| url | https://storage.googleapis.com/plos-corpus-prod/10.1371/journal.pone.0198280/1/pone.0198280.pdf?X-Goog-Algorithm=GOOG4-RSA-SHA256&X-Goog-Credential=wombat-sa%40plos-prod.iam.gserviceaccount.com%2F20210222%2Fauto%2Fstorage%2Fgoog4_request&X-Goog-Date=20210222T125733Z&X-Goog-Expires=3600&X-Goog-SignedHeaders=host&X-Goog-Signature=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 |
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