Authors : Callistus Ireneous Nakpih; Bernice Olivia Ama Baako

Volume/Issue : Volume 7 - 2022, Issue 12 - December

Google Scholar : https://bit.ly/3IIfn9N

Scribd : https://bit.ly/3IMBwYg

DOI : https://doi.org/10.5281/zenodo.7532912

Abstract : One of the means for predicting Dengue Fever transmission usually includes, conducting a surveillance of the causal vector in a demarcated area, noting the level of infestation of the vector in the area and computing the House Index (HI), Container Index (CI) and Breteau Index (BI), which are interpreted for possible transmission of the dengue or otherwise. We therefore theorise this physical process and phenomena with a mathematical model in this paper, for predicting the occurrence of dengue fever without going to the field. The main objective of the model is to be able to estimate the time period by which the population of the vector will grow and travel/cover a given area, infest a number of houses and hence translate into a possible transmission of dengue, using the HI specifically. The model we provided is a composite of four key submodels. The first part of the model represents the phenomenon of the population dynamics of the Aedes mosquito which is the vector for dengue transmission; the second part provides the mechanism for predicting the area the mosquitoes will infest over time; the third part estimates the number of houses that may be infested in the area, and the last part computes the HI. In essence, if we introduce one infected female Aedes mosquito into a community (a given area) as our initial population, we should be able to estimate by which time the computed HI will translate into the transmission of dengue fever in that community, holding several mathematical assumptions true for our model.

Keywords : Mathematical Models; Dengue Fever Transmission; Prediction Models; Epidemiological Models for Dengue Transmission; Process Automation;