Kazeem Okosun

Dr. Kazeem Okosun

orcid

Research Focus & Metrics

Academic Career Length

17Years (2010-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 February 2013 in BioSystems
Verified
Journal Article
Closed access
KOKazeem Okosun
Kazeem Okosun
OROuifki Rachid
Ouifki Rachid
NMNizar Marcus
Nizar Marcus

15 July 2016 in Malaria Journal
Verified
Journal Article
Open access
PDF file
GAGbenga J. Abiodun
Gbenga J. Abiodun
RMRajendra Maharaj
Rajendra Maharaj
PWPeter Witbooi
Peter Witbooi
KOKazeem Okosun
Kazeem Okosun
Malaria continues to be one of the most devastating diseases in the world, killing more humans than any other infectious disease. Malaria parasites are entirely dependent on Anopheles mosquitoes for transmission. For this reason, vector population dynamics is a crucial determinant of malaria risk. Consequently, it is important to understand the biology of malaria vector mosquitoes in the study of malaria transmission. Temperature and precipitation also play a significant role in both aquatic and adult stages of the Anopheles. In this study, a climate-based, ordinary-differential-equation model is developed to analyse how temperature and the availability of water affect mosquito population size. In the model, the influence of ambient temperature on the development and the mortality rate of Anopheles arabiensis is considered over a region in KwaZulu-Natal Province, South Africa. In particular, the model is used to examine the impact of climatic factors on the gonotrophic cycle and the dynamics of mosquito population over the study region. The results fairly accurately quantify the seasonality of the population of An. arabiensis over the region and also demonstrate the influence of climatic factors on the vector population dynamics. The model simulates the population dynamics of both immature and adult An. arabiensis. The simulated larval density produces a curve which is similar to observed data obtained from another study. The model is efficiently developed to predict An. arabiensis population dynamics, and to assess the efficiency of various control strategies. In addition, the model framework is built to accommodate human population dynamics with the ability to predict malaria incidence in future.

1 November 2011 in BioSystems
Verified
Journal Article
Closed access
KOKazeem Okosun
Kazeem Okosun
RORachid Ouifki
Rachid Ouifki
NMNizar Marcus
Nizar Marcus

1 December 2014 in Mathematical Biosciences
Verified
Journal Article
Closed access
KOKazeem Okosun
Kazeem Okosun
OMOluwole Daniel Makinde
Oluwole Daniel Makinde

1 March 2013 in Applied Mathematical Modelling
Verified
Journal Article
Closed access
KOKazeem Okosun
Kazeem Okosun
OMOluwole Daniel Makinde
Oluwole Daniel Makinde
ITI. Takaidza
I. Takaidza

1 April 2011 in BioSystems
Verified
Journal Article
Closed access
OMOluwole Daniel Makinde
Oluwole Daniel Makinde
KOKazeem Okosun
Kazeem Okosun