ISSN 15471063(print)
ISSN 15510018(online) 
Current volume

Journal archive


MBE is bimonthly, focusing on new developments in the fastgrowing fields of mathematical biosciences and bioengineering. MBE is now online only.
Authors will be granted full access to all MBE publications for one year.
Areas covered include general mathematical methods and their applications in biology, medical sciences and bioengineering with an emphasis on work related to mathematical modeling, nonlinear and stochastic dynamics.
The editorial board of MBE is strongly committed to promoting cuttingedge integrative and interdisciplinary research bridging mathematics, life sciences and engineering. 
TOP 10 Most Read Articles in MBE, September 2014
1 
Dynamical Models of Tuberculosis and Their Applications
Volume 1, Number 2, Pages: 361  404, 2004
Carlos CastilloChavez
and Baojun Song
Abstract
Full Text
Related Articles
The reemergence of tuberculosis (TB) from the 1980s to the early
1990s instigated extensive researches on the mechanisms behind the
transmission dynamics of TB epidemics. This article provides a
detailed review of the work on the dynamics and control of TB. The
earliest mathematical models describing the TB dynamics appeared in
the 1960s and focused on the prediction and control strategies using
simulation approaches. Most recently developed models not only pay
attention to simulations but also take care of dynamical analysis
using modern knowledge of dynamical systems. Questions addressed by
these models mainly concentrate on TB control strategies, optimal
vaccination policies, approaches toward the elimination of TB in the
U.S.A., TB coinfection with HIV/AIDS, drugresistant TB, responses
of the immune system, impacts of demography, the role of public
transportation systems, and the impact of contact patterns. Model
formulations involve a variety of mathematical areas, such as ODEs
(Ordinary Differential Equations) (both autonomous and
nonautonomous systems), PDEs (Partial Differential Equations),
system of difference equations, system of integrodifferential
equations, Markov chain model, and simulation models.

2 
Shearthinning effects of hemodynamics in patientspecific cerebral aneurysms
Volume 10, Number 3, Pages: 649  665, 2013
Alberto Gambaruto,
João Janela,
Alexandra Moura
and Adélia Sequeira
Abstract
References
Full Text
Related Articles
Two different generalized Newtonian mathematical models for blood flow, derived for the same experimental data, are compared, together with the Newtonian model, in three different anatomically realistic geometries of saccular cerebral aneurysms obtained from rotational CTA. The geometries differ in size of the aneurysm and the existence or not of side branches within the aneurysm.
Results show that the differences between the two generalized Newtonian mathematical models are smaller than the differences between these and the Newtonian solution, in both steady and unsteady simulations.

3 
A partial differential equation model of metastasized prostatic cancer
Volume 10, Number 3, Pages: 591  608, 2013
Avner Friedman
and Harsh Vardhan Jain
Abstract
References
Full Text
Related Articles
Biochemically failing metastatic prostate cancer is typically treated with androgen ablation. However, due to the emergence of castrationresistant cells that can survive in low androgen concentrations, such therapy eventually fails. Here, we develop a partial differential equation model of the growth and response to treatment of prostate cancer that has metastasized to the bone. Existence and uniqueness results are derived for the resulting free boundary problem. In particular, existence and uniqueness of solutions for all time are proven for the radially symmetric case. Finally, numerical simulations of a tumor growing in 2dimensions with radial symmetry are carried in order to evaluate the therapeutic potential of different treatment strategies. These simulations are able to reproduce a variety of clinically observed responses to treatment, and suggest treatment strategies that may result in tumor remission, underscoring our model's potential to make a significant contribution in the field of prostate cancer therapeutics.

4 
The estimation of the effective reproductive number from disease outbreak data
Volume 6, Number 2, Pages: 261  282, 2009
Ariel CintrónArias,
Carlos CastilloChávez,
Luís M. A. Bettencourt,
Alun L. Lloyd
and H.T. Banks
Abstract
Full Text
Related Articles
We consider a single outbreak susceptibleinfectedrecovered (SIR)
model and corresponding estimation procedures for the
effective reproductive number $\mathcal{R}(t)$. We discuss the
estimation of the underlying SIR parameters with a
generalized least squares (GLS) estimation
technique. We do this in the context of appropriate statistical
models for the measurement process. We use asymptotic statistical
theories to derive the mean and variance of the limiting
(Gaussian) sampling distribution and to perform post statistical
analysis of the inverse problems. We illustrate the ideas and
pitfalls (e.g., large condition numbers on the corresponding
Fisher information matrix) with both synthetic and influenza
incidence data sets.

5 
Mathematical modelling of tuberculosis epidemics
Volume 6, Number 2, Pages: 209  237, 2009
Juan Pablo Aparicio
and Carlos CastilloChávez
Abstract
Full Text
Related Articles
The strengths and limitations of using homogeneous mixing and
heterogeneous mixing epidemic models are explored in the context
of the transmission dynamics of tuberculosis. The focus is on
three types of models: a standard incidence homogeneous mixing
model, a nonhomogeneous mixing model that incorporates
'household' contacts, and an agestructured model. The models are
parameterized using demographic and epidemiological data and the
patterns generated from these models are compared. Furthermore,
the effects of population growth, stochasticity, clustering of
contacts, and age structure on disease dynamics are explored. This
framework is used to asses the possible causes for the observed
historical decline of tuberculosis notifications.

6 
Effect of branchings on blood flow in the system of human coronary arteries
Volume 9, Number 1, Pages: 199  214, 2011
Benchawan Wiwatanapataphee,
Yong Hong Wu,
Thanongchai Siriapisith
and Buraskorn Nuntadilok
Abstract
References
Full Text
Related Articles
In this work, we investigate the behavior of the pulsatile blood
flow in the system of human coronary arteries. Blood is modeled as
an incompressible nonNewtonian fluid. The transient phenomena of
blood flow through the coronary system are simulated by solving the
three dimensional unsteady state NavierStokes equations and
continuity equation. Distributions of velocity, pressure and wall
shear stresses are determined in the system under pulsatile
conditions on the boundaries. Effect of branching vessel on the flow
problem is investigated. The numerical results show that blood
pressure in the system with branching vessels of coronary arteries
is lower than the one in the system with no branch. The magnitude of
wall shear stresses rises at the bifurcation.

7 
Regulation of Th1/Th2 cells in asthma development: A mathematical model
Volume 10, Number 4, Pages: 1095  1133, 2013
Yangjin Kim,
Seongwon Lee,
YouSun Kim,
Sean Lawler,
Yong Song Gho,
YoonKeun Kim
and Hyung Ju Hwang
Abstract
References
Full Text
Related Articles
Airway exposure levels of lipopolysaccharide (LPS) determine type I versus type II
helper T cell induced experimental asthma. While high LPS levels induce Th1dominant
responses, low LPS levels derive Th2 cell induced
asthma. The present paper develops a mathematical model of asthma development which
focuses on the relative balance of Th1 and Th2 cell induced asthma. In the present work
we represent
the complex network of interactions between cells and molecules by a mathematical model.
The model describes the behaviors of cells (Th0, Th1, Th2 and macrophages)
and regulatory molecules (IFN$\gamma$, IL4, IL12, TNFα) in response to
high, intermediate, and low levels of LPS.
The simulations show how
variations in the levels of injected LPS
affect the development of
Th1 or Th2 cell responses through differential cytokine induction.
The model also predicts the coexistence of
these two types of response
under certain biochemical and biomechanical conditions in the microenvironment.

8 
Time variations in the generation time of an infectious disease:
Implications for sampling to appropriately quantify transmission
potential
Volume 7, Number 4, Pages: 851  869, 2010
Hiroshi Nishiura
Abstract
References
Full Text
Related Articles
Although the generation time of an infectious disease plays a key role in estimating its transmission potential, the impact of the sampling time of generation times on the estimation procedure has yet to be clarified. The present study defines the period and cohort generation times, both of which are timeinhomogeneous, as a function of the infection time of secondary and primary cases, respectively. By means of analytical and numerical approaches, it is shown that the period generation time increases with calendar time, whereas the cohort generation time decreases as the incidence increases. The initial growth phase of an epidemic of Asian influenza A (H2N2) in the Netherlands in 1957 was reanalyzed, and estimates of the basic reproduction number, $R_0$, from the LotkaEuler equation were examined. It was found that the sampling time of generation time during the course of the epidemic introduced a timeeffect to the estimate of $R_0$. Other historical data of a primary pneumonic plague in Manchuria in 1911 were also examined to help illustrate the empirical evidence of the period generation time. If the serial intervals, which eventually determine the generation times, are sampled during the course of an epidemic, direct application of the sampled generationtime distribution to the LotkaEuler equation leads to a biased estimate of $R_0$. An appropriate quantification of the transmission potential requires the estimation of the cohort generation time during the initial growth phase of an epidemic or adjustment of the timeeffect (e.g., adjustment of the growth rate of the epidemic during the sampling time) on the period generation time. A similar issue also applies to the estimation of the effective reproduction number as a function of calendar time. Mathematical properties of the generation time distribution in a heterogeneously mixing population need to be clarified further.

9 
An application of queuing theory to SIS and SEIS epidemic models
Volume 7, Number 4, Pages: 809  823, 2010
Carlos M. HernándezSuárez,
Carlos CastilloChavez,
Osval Montesinos López
and Karla HernándezCuevas
Abstract
References
Full Text
Related Articles
In this work we consider every individual of a population to be a server whose state can be either busy (infected) or idle (susceptible). This server approach allows to consider a general distribution for the duration of the infectious state, instead of being restricted to exponential distributions. In order to achieve this we first derive new approximations to quasistationary distribution (QSD) of SIS (Susceptible Infected Susceptible) and SEIS (Susceptible Latent Infected Susceptible) stochastic epidemic models. We give an expression that relates the basic reproductive number, $R_0$ and the server utilization, $\rho$.

10 
Influence of environmental factors on college alcohol drinking patterns
Volume 10, Number 5/6, Pages: 1281  1300, 2013
Ridouan Bani,
Rasheed Hameed,
Steve Szymanowski,
Priscilla Greenwood,
Christopher M. KribsZaleta
and Anuj Mubayi
Abstract
References
Full Text
Related Articles
Alcohol abuse is a major problem, especially among students on and around college campuses. We use the mathematical framework of [16] and study the role of environmental factors on the long term dynamics of an alcohol drinking population. Sensitivity and uncertainty analyses are carried out on the relevant functions (for example, on the drinking reproduction number and the extinction time of moderate and heavy drinking because of interventions) to understand the impact of environmental interventions on the distributions of drinkers.
The reproduction number helps determine whether or not the highrisk alcohol drinking behavior will spread and become persistent in the population, whereas extinction time of highrisk drinking measures the effectiveness of control programs.
We found that the reproduction number is most sensitive to social interactions, while the time to extinction of highrisk drinkers is significantly sensitive to the intervention programs that reduce initiation, and the college dropout rate. The results also suggest that in a population, higher rates of intervention programs in lowrisk environments (more than intervention rates in highrisk environments) are needed to reduce heavy drinking in the population.

Go to top

