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      Optimal control analysis of Ebola disease with control strategies of quarantine and vaccination

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          Abstract

          Background

          The 2014 Ebola epidemic is the largest in history, affecting multiple countries in West Africa. Some isolated cases were also observed in other regions of the world.

          Method

          In this paper, we introduce a deterministic SEIR type model with additional hospitalization, quarantine and vaccination components in order to understand the disease dynamics. Optimal control strategies, both in the case of hospitalization (with and without quarantine) and vaccination are used to predict the possible future outcome in terms of resource utilization for disease control and the effectiveness of vaccination on sick populations. Further, with the help of uncertainty and sensitivity analysis we also have identified the most sensitive parameters which effectively contribute to change the disease dynamics. We have performed mathematical analysis with numerical simulations and optimal control strategies on Ebola virus models.

          Results

          We used dynamical system tools with numerical simulations and optimal control strategies on our Ebola virus models. The original model, which allowed transmission of Ebola virus via human contact, was extended to include imperfect vaccination and quarantine. After the qualitative analysis of all three forms of Ebola model, numerical techniques, using MATLAB as a platform, were formulated and analyzed in detail. Our simulation results support the claims made in the qualitative section.

          Conclusion

          Our model incorporates an important component of individuals with high risk level with exposure to disease, such as front line health care workers, family members of EVD patients and Individuals involved in burial of deceased EVD patients, rather than the general population in the affected areas. Our analysis suggests that in order for R 0 (i.e., the basic reproduction number) to be less than one, which is the basic requirement for the disease elimination, the transmission rate of isolated individuals should be less than one-fourth of that for non-isolated ones. Our analysis also predicts, we need high levels of medication and hospitalization at the beginning of an epidemic. Further, optimal control analysis of the model suggests the control strategies that may be adopted by public health authorities in order to reduce the impact of epidemics like Ebola.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s40249-016-0161-6) contains supplementary material, which is available to authorized users.

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          Most cited references11

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          Uncertainty and sensitivity analysis of the basic reproductive rate. Tuberculosis as an example.

          The basic reproductive rate (R0) is a measure of the severity of an epidemic. On the basis of replicated Latin hypercube sampling, the authors performed an uncertainty and sensitivity analysis of the basic reproductive rate of tuberculosis (TB). The uncertainty analysis allowed for the derivation of a frequency distribution for R0 and the assessment of the relative contribution each of the three components of R0 made when TB epidemics first arose centuries ago. (The three components of R0 are associated with fast, slow, and relapse TB.) R0 estimates indicated the existence of fairly severe epidemics when TB epidemics first arose. The R0 for the susceptible persons who developed TB slowly (R0(slow)) contributed the most to the R0 estimates; however, the relative R0(slow) contribution decreased as the severity of TB epidemics increased. The sensitivity of the magnitude of R0 to the uncertainty in estimating values of each of the input parameters was assessed. These results indicated that five of the nine input parameters, because of their estimation uncertainty, were influential in determining the magnitude of R0. This uncertainty and sensitivity methodology provides results that can aid investigators in understanding the historical epidemiology of TB by quantifying the effect of the transmission processes involved. Additionally, this method can be applied to the R0 of any other infectious disease to estimate the probability of an epidemic outbreak.
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            Coinfection with malaria and intestinal parasites, and its association with anaemia in children in Cameroon

            Background The purpose of this study was to determine the prevalence of coinfection with malaria and intestinal parasites, as well as to determine its association with anaemia in children aged 10 years and below in Muyuka, Cameroon. Materials and methods This was a cross-sectional study. Participants were febrile children who were admitted to the Muyuka district hospital between April and October 2012. Blood and stool samples were collected from those participants who gave consent to take part in the study. Haemoglobin concentration (Hb) and complete blood count (CBC) were performed using an automated haematology analyser (Mindray®, BC-2800). Giemsa-stained blood film was examined to detect malaria parasites, while the formol-ether concentration technique was used to detect intestinal parasitic infections (IPIs). The Pearson’s chi-square, Student’s T-test and correlation analysis were all performed as part of the statistical analyses. Results Four hundred and eleven (411) children successfully took part in this study. The prevalence of malaria, IPIs, malaria and IPI coinfection, and anaemia observed were 98.5 %, 11.9 %, 11.9 % and 44.8 %, respectively. Anaemia and IPIs were significantly associated with age; anaemia was more prevalent in children under five years of age (p = 0.000), whereas IPIs were more prevalent in children aged between five and 10 years (p = 0.006). The parasite species isolated included Ascaris lumbricoides (36 [73.5 %]), Entamoeba histolytica/dispar (9 [18.4 %]) and hookworm (4 [8.2 %]). The mean Hb observed was 10.64 g/dl (±1.82). A significant negative correlation was observed between malaria parasite density and Hb. There was no significant difference in the prevalence of anaemia among children infected with malaria, IPIs, or malaria and IPI coinfection, or among non-infected children. Similarly, the mean Hb did not differ among infected and non-infected children. Conclusion This study showed that malaria and IPIs still constitute a major public health problem in the study area despite a lack of any significant association between these infections and anaemia. The findings suggest that there is a need for the implementation of control measures to curb the rate of malaria and IPIs in the study area.
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              Optimal chemoprophylaxis and treatment control strategies of a tuberculosis transmission model

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                Author and article information

                Contributors
                mdureahm@asu.edu
                musman1@udayton.edu
                adnan.khan@lums.edu.pk
                mimran@asu.edu
                Journal
                Infect Dis Poverty
                Infect Dis Poverty
                Infectious Diseases of Poverty
                BioMed Central (London )
                2049-9957
                13 July 2016
                13 July 2016
                2016
                : 5
                : 72
                Affiliations
                [ ]Department of Mathematics, Prince Sultan University, Riyadh, Kingdom of Saudi Arabia
                [ ]Department of Mathematics, University of Dayton, Dayton, OH USA
                [ ]Department of Mathematics, Lahore University of Management Sciences, Lahore, Pakistan
                [ ]Department of Mathematics and Natural Sciences, GULF University for Science and Technology, Mishref, Kuwait
                Article
                161
                10.1186/s40249-016-0161-6
                4942907
                27405359
                617b5140-a13d-46db-adab-c115ceb8359b
                © The Author(s) 2016

                Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 11 August 2015
                : 22 June 2016
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2016

                epidemiology,ebola virus disease,optimal control strategies,disease transmission

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