Dataset Information

Mukhta2018-the effect of bednet coverage on malaria transmission in South Sudan

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, [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. Model is encoded by Ruby and submitted to BioModels by Ahmad Zyoud

SUBMITTER: Ahmad Zyoud

PROVIDER: MODEL2003160003 | BioModels | 2020-03-20

REPOSITORIES: BioModels

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

Mukhtar Abdulaziz Y A AYA Munyakazi Justin B JB Ouifki Rachid R Clark Allan E AE

PloS one 20180607 6

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 cap ...[more]

PMID: 29879166

Publication: 1/2

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Project description:Malaria represents a major public health problem in Africa [1]. In the East African highlands, even in high-altitude areas previously considered too cold to support vector population and parasite transmission [2], frequent malaria epidemics have been reported since the 1980M-bM-^@M-^Ys [3]. Plasmodium falciparum infections have been detected in areas as high as 1,600-2,400m above sea level in Africa [4], albeit there is a marked gradient of parasite prevalence along the altitude transect [5-7]. Both the historical absence of malaria in the African highlands and now the intensive malaria control efforts put in place after the recent outbreaks have reduced malaria prevalence and incidence [8], rendering the East African highlands particularly prone to epidemic malaria due to the lack of the protective immunity, and causing significant human mortality amongst all age groups [9]. Therefore, malaria transmission monitoring in the East African highlands becomes a particularly important public health issue.Despite the overall lower immunity of the population in these historically malaria-free areas, the many successive outbreaks since the 1980M-bM-^@M-^Ys may have generated some level of immunity against P. falciparum amongst highland residents. The antibody response to Plasmodium is cumulative and long lasting, developing after repeated exposures to the parasite and persisting for months or years after infection was resolved. The antibody response to Plasmodium varies amongst individuals of different age groups (i.e. toddlers, children and adults) as well as amongst individuals of same age groups from areas of different parasite prevalence [10]. The repertoire of targets of the antibody response also expands after multiple infections, with the number of recognized antigens being correlated to parasite prevalence, age and immunity to clinical malaria [11,12]. Serological studies bring forth indirect evidence of human exposure to the parasite, and can reliably assess its prevalence and transmission intensity in an endemic area [13-15]. However, the vast majority of serological studies of malaria have been, hereto, limited to a small number of the parasiteM-bM-^@M-^Ys antigens. The work we present here is an expansion of the study published by Badu et al. [16], in which the antibody response to the 19kDa fragment of merozoite surface protein 1 (MSP-119) was examined in populations from two endemic areas in the western Kenyan highlands. There, the tremendous variations of malaria transmission intensity in a small spatial scale are caused by substantial differences in altitude, topography and other environmental conditions [6,7,17,18]. We now expand our antibody profiling survey to include 854 P. falciparum proteins by using high-throughput proteomic microarray technology. Protein microarrays have been used to explore the humoral response to P. falciparum in other African settings [19-24], but this is the broadest characterization of the antibody responses of the population of western Kenyan highlands to date. In the present study we: i) determined the serological reactivity against P. falciparum (Pf) in subjects residing in a low transmission area, and detected hotspots of transmission; ii) examined the dynamics of antibody response to hundreds of Pf proteins generated by sera from toddlers, older children and adults residing in two endemic areas differing in transmission intensities, during two distinct malaria seasons, and compared the intensity, breadth and antigenic targets of these responses; and iii) identified candidate Pf antigenic markers that could provide more sensitive serological surveillance to detect micro-geographic variations in malaria transmission levels and differentiate hotspots of infection in low endemic areas. (references provided in the 'readme.txt') Antibody profiling was performed on sera from residents of western Kenyan highlands against Plasmodium falciparum. One-hundred and ten age-stratified serum samples collected during the dry and the wet seasons, from residents of two locations with differing parasite transmission levels (uphill and valley bottom), and 10 unexposed USA controls were probed on a protein microarray displaying 854 unique proteins of P. falciparum.

Project description:Malaria represents a major public health problem in Africa [1]. In the East African highlands, even in high-altitude areas previously considered too cold to support vector population and parasite transmission [2], frequent malaria epidemics have been reported since the 1980’s [3]. Plasmodium falciparum infections have been detected in areas as high as 1,600-2,400m above sea level in Africa [4], albeit there is a marked gradient of parasite prevalence along the altitude transect [5-7]. Both the historical absence of malaria in the African highlands and now the intensive malaria control efforts put in place after the recent outbreaks have reduced malaria prevalence and incidence [8], rendering the East African highlands particularly prone to epidemic malaria due to the lack of the protective immunity, and causing significant human mortality amongst all age groups [9]. Therefore, malaria transmission monitoring in the East African highlands becomes a particularly important public health issue.Despite the overall lower immunity of the population in these historically malaria-free areas, the many successive outbreaks since the 1980’s may have generated some level of immunity against P. falciparum amongst highland residents. The antibody response to Plasmodium is cumulative and long lasting, developing after repeated exposures to the parasite and persisting for months or years after infection was resolved. The antibody response to Plasmodium varies amongst individuals of different age groups (i.e. toddlers, children and adults) as well as amongst individuals of same age groups from areas of different parasite prevalence [10]. The repertoire of targets of the antibody response also expands after multiple infections, with the number of recognized antigens being correlated to parasite prevalence, age and immunity to clinical malaria [11,12]. Serological studies bring forth indirect evidence of human exposure to the parasite, and can reliably assess its prevalence and transmission intensity in an endemic area [13-15]. However, the vast majority of serological studies of malaria have been, hereto, limited to a small number of the parasite’s antigens. The work we present here is an expansion of the study published by Badu et al. [16], in which the antibody response to the 19kDa fragment of merozoite surface protein 1 (MSP-119) was examined in populations from two endemic areas in the western Kenyan highlands. There, the tremendous variations of malaria transmission intensity in a small spatial scale are caused by substantial differences in altitude, topography and other environmental conditions [6,7,17,18]. We now expand our antibody profiling survey to include 854 P. falciparum proteins by using high-throughput proteomic microarray technology. Protein microarrays have been used to explore the humoral response to P. falciparum in other African settings [19-24], but this is the broadest characterization of the antibody responses of the population of western Kenyan highlands to date. In the present study we: i) determined the serological reactivity against P. falciparum (Pf) in subjects residing in a low transmission area, and detected hotspots of transmission; ii) examined the dynamics of antibody response to hundreds of Pf proteins generated by sera from toddlers, older children and adults residing in two endemic areas differing in transmission intensities, during two distinct malaria seasons, and compared the intensity, breadth and antigenic targets of these responses; and iii) identified candidate Pf antigenic markers that could provide more sensitive serological surveillance to detect micro-geographic variations in malaria transmission levels and differentiate hotspots of infection in low endemic areas. (references provided in the 'readme.txt')

Dataset Information

Mukhta2018-the effect of bednet coverage on malaria transmission in South Sudan

Publications

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

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