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Exploring predictive frameworks for malaria in Burundi

Infectious Disease Modelling 2022年第2期7卷 33-44页

作者： Lionel Divin Mfisimana Emile Nibayisabe kingsley badu David Niyukuri Faculte des Sciences Fondamentales Institut Superieur des Cadres MilitairesBurundi Department of Theoretical and Applied Biology Kwame Nkrumah University of Science and TechnologyGhana Division of Epidemiology&Biostatistics Faculty of Medicine and Health SciencesStellenbosch UniversityCape TownSouth Africa The South African Department of Science and TechnologyeNational Research Foundation(DST-NRF)Centre of Excellence in Epidemiological Modelling and Analysis(SACEMA) Stellenbosch UniversityCape TownSouth Africa

In Burundi,malaria infection has been increasing in the last decade despite efforts to increase access to health services,and several intervention *** use of heterogeneous data can help to build predictive models of malaria *** built predictive frameworks:the generalized linear model(GLM),and artificial neural network(ANN),to predict malaria cases in four sub-groups and the overall general *** results showed that more than half of malaria infections are observed in pregnant women and children under 5 years,with high burden to children between 12 and 59 *** results showed that,ANN model performed better in predicting total cases compared to *** model frameworks showed that education rates and Insecticide Treated Bed Nets(ITNs)had decreasing effects on malaria cases,some other variables had an increasing ***,malaria control and prevention interventions program are encouraged to understand those variables,and take appropriate measures such as providing ITNs,sensitization in schools and the communities,starting within high dense communities,among *** prediction of cases can provide timely information needed to be proactive for intervention strategies,and it can help to mitigate the epidemics and reduce its impact on populations and the economy.

关键词： Burundi Malaria Modelling Generalized linear model Neural network

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Optimal control application to an Ebola model

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Asian Pacific Journal of Tropical Biomedicine 2016年第4期6卷 283-289页

作者： Ebenezer Bonyah kingsley badu Samuel Kwesi Asiedu-Addo Department of Mathematics and Statistics Kumasi Polytechnic Noguchi Memorial Institute for Medical Research College of Health ScienceUniversity of Ghana Faculty of Health Sciences Garden City University College Department of Mathematics Education University of Education

Ebola virus is a severe,frequently fatal illness,with a case fatality rate up to 90%.The outbreak of the disease has been acknowledged by World Health Organization as Public Health Emergency of International *** threat of Ebola in West Africa is still a major setback to the socioeconomic *** control theory is applied to a system of ordinary differential equations which is modeling Ebola infection through three different routes including contact between humans and a dead *** an attempt to reduce infection in susceptible population,a preventive control is put in the form of education and campaign and two treatment controls are applied to infected and late-stage infected(super) human *** Pontryagins maximum principle is employed to characterize optimality control,which is then solved *** is observed that time optimal control is existed in the *** activation of each control showed a positive reduction of *** overall effect of activation of all the controls simultaneously reduced the effort required for the reduction of the infection *** obtained results present a good framework for planning and designing cost-effective strategies for good interventions in dealing with Ebola *** is established that in order to reduce Ebola threat all the three controls must be taken into consideration concurrently.

关键词： Ebola Optimal control Pontryagins maximum principle Case finding Case holding

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Entomological Survey of Malaria Vectors within the Kumasi Metropolitan AreamA Study of Three Communities： Emena, Atonsu and Akropong

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Journal of Environmental Science and Engineering(B) 2012年第2期1卷 144-154页

作者： Samuel C.K. Tay Sylvester K. Danuor Andy Morse Caminade Caminade kingsley badu Harry Hoffman Abruquah School of Medical Sciences Kwame Nkrumah University of Science and Technology Kumasi 40100 Ghana Meteorology and Climate Science Unit Department of Physics Kumasi 40100 Ghana School of Environmental Sciences University of Liverpool Liverpool L69 7ZT UK Climate and Human Research Unit Centre for Global Health Kenya Medical Research Institute Kisumu 40100 Kenya Department of Pure and Applied Biology Kwame Nkrumah University of Science and Technology Kumasi 40100 Ghana University Hospital Kwame Nkrumah University of Science and Technology Kumasi 40100 Ghana

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