@Article{cmc.2020.010893,
AUTHOR = {Muhammad Rafiq, Ali Ahmadian, Ali Raza, Dumitru Baleanu, Muhammad Sarwar Ahsan, Mohammad Hasan Abdul Sathar},
TITLE = {Numerical Control Measures of Stochastic Malaria Epidemic  Model},
JOURNAL = {Computers, Materials \& Continua},
VOLUME = {65},
YEAR = {2020},
NUMBER = {1},
PAGES = {33--51},
URL = {http://www.techscience.com/cmc/v65n1/39552},
ISSN = {1546-2226},
ABSTRACT = {Nonlinear stochastic modeling has significant role in the all discipline of 
sciences. The essential control measuring features of modeling are positivity, 
boundedness and dynamical consistency. Unfortunately, the existing stochastic methods 
in literature do not restore aforesaid control measuring features, particularly for the 
stochastic models. Therefore, these gaps should be occupied up in literature, by 
constructing the control measuring features numerical method. We shall present a 
numerical control measures for stochastic malaria model in this manuscript. The results 
of the stochastic model are discussed in contrast of its equivalent deterministic model. If 
the basic reproduction number is less than one, then the disease will be in control while 
its value greater than one shows the perseverance of disease in the population. The
standard numerical procedures are conditionally convergent. The propose method is 
competitive and preserve all the control measuring features unconditionally. It has also 
been concluded that the prevalence of malaria in the human population may be controlled
by reducing the contact rate between mosquitoes and humans. The awareness programs 
run by world health organization in developing countries may overcome the spread of 
malaria disease.},
DOI = {10.32604/cmc.2020.010893}
}