Application of logistic regression model on the spread of malaria infection in Calabar municipality (A case study of university of Calabar teaching hospital)
Department of Mathematics and Statistics, Faculty of Physical Sciences, University of Calabar, Calabar Nigeria.
Review
Open Access Research Journal of Multidisciplinary Studies, 2024, 07(01), 022–038.
Article DOI: 10.53022/oarjms.2024.7.1.0055
Publication history:
Received on 20 November 2023; revised on 23 January 2024; accepted on 26 January 2024
Abstract:
Background: The malaria disease is the outcome of the interaction among three elements which includes; man, mosquito and the parasite. The intensity of the disease is being regulated by the physical and socio-economic determinant in the area which interact with these elements. The physical conditions of the region determine the growth and proliferation of mosquito and parasite, while the socio-economic conditions of the people determine the distribution of mosquito and parasites. This piece of research work has been devoted to the study of vector species (Plasmodium), spatial-temporal incidence pattern of malaria i.e parasite load, physical and socio-economic determinants responsible for the spread of mosquito and parasites, control measures and risk factor assessment. The favourable explanatory variables considered in the prediction of malaria prevalence such as age group, gender, blood group and genotype presents suitable conditions to determine the validity of malaria prevalence across the metropolis which as well substantially contributed and facilitate the growth and diffusion of malarial incidence in Calabar Municipality. The data obtained was initially entered in Microsoft Excel (2016) and checked for errors after which it was exported to IBM SPSS Statistics 23 software for logistic regression analysis. The metropolis records high incidence of malaria. The predominant parasite plasmodium falciparum is considered vital for causing considerable morbidity and mortality in the area. From our analysis, it is observed that fifty nine of our patients were malaria negative and one hundred and one patients were malaria positive. The model predicted in respect to gender that seventy four percent of female population were malaria positive likewise the male gender predicted at eighty percent to be malaria positive.
Keywords:
Malaria; Calabar Municipality; Plasmodium vivax; Plasmodium falciparum; Remote sensing; Spatial analysis; Epidemiology
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