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we have described above. This allows more explicit description of indi-
vidual variability, but can be more challenging to analyze. One particular
aspect of the epidemiology of helminths is the propensity for predispo-
sition to heavy or light infection in the human host. 14,35 e 38 The reason for
this is some poorly understood combination of genetic, social, and
behavioral factors, with perhaps behavioral and social factors playing
a greater role in many settings. The location of a home in a village, the
social standing and degree of poverty of its family occupiers, the pre-
vailing sanitation conditions plus the numbers of young children in the
family could all play a role in exposure to infective stages. Predisposition
is one factor contributing to the aggregated distributions of worm
numbers per host and it often persists over many rounds of treatment
where intensity measures enable the heavy and lightly infected individ-
uals to be examined before and after each round of chemotherapy.
The description of predisposition ideally requires and individual-
based model as first used by Anderson and Medley 39 to explore various
aspects of community-based treatment and how predisposition influ-
enced the choice of treatment program. The model used was age and
gender stratified, with a gamma distribution for the mean exposure rate of
individual hosts. Density dependence in fecundity, age dependence in
exposure (the mean of the gamma distribution varied with age to give
convex curves of intensity by age) and full human demography were also
incorporated. This study examined two different assumptions concerning
the generative mechanisms for worm aggregation
predisposition due to
host genetics and environmental factors. One conclusion from this study
was that worm aggregation was only significantly reduced from its
baseline level (prior to the implementation of mass chemotherapy), if the
causative factor of worm aggregation was predisposition not environ-
mental factors.
It is somewhat surprising that individual-based stochastic models have
not been used more widely to examine epidemiology, control-related
questions, and policy issues since the early studies in 1985. This is espe-
cially the case for parameter estimation from data on intensity of infection
stratified by age and gender, pre- and post-treatment, using Markov chain
Monte Carlo (MCMC) methods. More is said about this later.
e
CO MMUNITY-BASED CHEMOTHERA PY
With greatly increased focus on how best to control soil-transmitted
helminths (STH) in poor regions of the world in recent years, 40 e 42
a great deal of attention is now focused on how models can best help
public health workers to devise optimal and cost-effective control inter-
ventions. The ground work for current activity was laid in models
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