Mathematical modeling is the manner of the use of a variety of mathematical shapes, it’s involves the use of mathematical tools and concepts to relate and solve real life problems. The factors affecting or accelerating the occurrence of such problems can be associated with parameters from the field of mathematics to the tools and procedures of solving such problems in mathematics. A malaria Journal stated that ” mathematical models have been used to provide an explicit framework for understanding diseases transmission dynamics in human population for over 100 years”( Mandal, 2011).
One of these transmitted diseases is malaria. Our world Data mentioned that “malaria is a disease that is transmitted from person to person by infected mosquitoes. Malaria can be fatal. The World Health Organization (WHO) estimates that 438,000 people died because of malaria in 2015; the Institute of Health Metrics and Evaluation (IHME), Global Burden of Disease (GBD) puts this estimate at 720,000” ( Roser an Ritchie 2018). Mathematical modelling can role an important function in quantifying
the consequences of malaria control strategies and finding out which strategies are effective in exclusive transmission settings.
In order to understand the spread of this disease the article said, “The first aim of this article is to develop, starting from the basic models, a hierarchical structure of a range of deterministic models of different levels of complexity. The second objective is to elaborate, using some of the representative mathematical models, the evolution of modelling strategies to describe malaria incidence by including the critical features of host-vector-parasite interactions. Emphasis is more on the evolution of the deterministic differential equation based epidemiological compartment models with a brief discussion on data based statistical models”( Mandal 2011).
Therefore, mathematical modeling has a variety of areas of application and can be viewed as one of the core multi-discipline course cutting across major specializations of disciplines. I narrow down these applications of mathematical modeling and focus on its application in medicine and in particular leveraging climate variables and the distribution of different species in modeling malaria prevalence using differential equations and logistic regression as an example.
In this case, those climatic factors such as temperature, rainfall and the distribution of different species such as forest cover do vary from time to time or from one area to another and hence are called variables or covariates. We also refer them as, independent variables. Conversely, the transmission of malaria and the rate of breeding of mosquito larva will also be varying but in this case it depends on both the climatic factors and the distribution of different species in the area of study, thus they are called dependent variables their outcome in based on independent variables. This concept is important when generating and developing the differential equations as one of the tools extracted from mathematics in modeling.
Logistic regression can be applied, according to the medcalc.org, “logistic regression is a statistical method for analyzing a dataset in which there are one or more independent variables that determine an outcome. The outcome is measured with a dichotomous variable”(Schoonjans 2018). Differential Equations and Logistic regression strategy would be used to discover the impact of topography and the climatic conditions on the malaria incidence in the learn about area. This kind of study will be seeking to do Mathematical Modeling and Statistical Modeling using Differential Equations and Logistic Regression of malaria prevalence. The general objective of this study is to establish and formulate ordinary and partial differential equations model to the prevalence of malaria. Narrowing down to specific objectives then we shall have;
?To establish the effects variation in climatic condition including temperature, amount of rainfall on the prevalence of malaria.
?To explore the effect of topography, land use and forest cover on the prevalence of malaria.
?To formulate and relate mathematical models of differential equations and logistic regression with malaria prevalence.
?To generate remedial mathematical dynamical systems to malaria prevalence with an aid of technology.
Mathematical modeling has its’ own significance in the field of medicine, for instance;
i)Health workers will be able to identify high risk in the areas they work so that they can do the right interventions and do effective health monitoring.
ii)The result of the research will instill concern to medics and climatologists for the variation of the climate conditions that accompany the transmission of such diseases hence basis for locating appropriate interventions for its control and a means to monitor their productiveness.
iii)Proper interventions for the disease’s prevalence control and its power will highly contribute to economic development.
In conclusion, mathematical modeling gives a predictive result which is reliable when it comes to decision making.