Page 265 - DCAP601_SIMULATION_AND_MODELING

Unit 13: Simulation Languages (I)

incorporate individual histories or make broad assumptions about their distribution. Therefore, Notes
if individuals in a population differ with respect to some character, and the behavior of the
population critically depends upon these differences, models such as those developed here may
provide a better approach. Discrete-event simulation models are thus worthy partners of
differential-equation models of malaria epidemiology in the many situations in which their
representations can more closely approximate the underlying biological processes and
mechanisms.
Discrete-event models are often criticized because they provide no closed-form analytic solutions.
Obviously we believe that in the appropriate context some advantages of discrete-event models
are compensatory. One such advantage is the intrinsic occurrence of heterogeneous mixing:
interactions may occur between rare variants rather than only between aggregates or averages
within a given distribution. Recent mathematical and empirical studies that examine variously-
defined subdivisions of parasite, host and vector populations suggest that the diversity and
abundance of phenotypes and genotypes involved in malaria may have profound implications
for vaccine, drug and other intervention strategies.
The models presented here have many other shortcomings. We consistently treat human
populations as static, and we largely ignore mosquito population dynamics. There is not a
certainty but some probability that a mosquito biting an infectious human becomes infected,
and this probability should be represented by something other than an ad hoc tuning parameter.
Our operational view of immunity incorporates the existence of partial immunities to reinfection,
but it fails to encompass the possibility that immune responses may act to limit parasite densities
upon reinfection. So little is known about human malaria immunology that the shortest immune
half-life we consider may be too long, or the longest too short. We have not yet examined the
many possibilities of immunologic ally cross-reactive or potentially recombinant strains of
parasite.
Nonetheless, our results are strikingly congruent with those of the differential-equation models
developed and tested during the past century, and the few seemingly anomalous results at this
level of analysis concern factors our predecessors were unable to address in similar terms.
Certainly the unsuspected importance of the duration of host infectivity merits some attention
with respect to planned vaccine-based interventions, at least in regions with intense perennial
transmission. Our preliminary results with a seasonal-transmission extension of the model
suggest that vector mortality is in fact the dominant influence on prevalence in humans in short
seasons, but that the influence of host window grows to near-parity with longer, ultimately
perennial transmission seasons.

Notes The influence of host immunity appears to rise more rapidly with season length
than that of either vector mortality or host window, but still falls short of parity in the
perennial-transmission case.

13.2 Continuous Simulation Languages

Continuous Simulation refers to a computer model of a physical system that incessantly tracks
system response over time according to a set of equations typically involving differential
equations.
Continuous system simulation languages are very high level programming languages which
assist modelling and simulation of systems characterized by ordinary and partial differential
equations. Design principles and implementation techniques for continuous system simulation

LOVELY PROFESSIONAL UNIVERSITY 259