Biology Reference
In-Depth Information
The cost of repeated parasitological surveys means that selective
treatment strategies are unlikely to be deployed on a large scale. Rather,
mathematical models of school-age targeted treatments are in broad
consensus with the view that this strategy is a cost-effective means of
controlling morbidity. 206,212 This is in accordance with empirical evidence
demonstrating that de-worming children produces improvements in
growth, educational attainment 214 e 216 and school participation 217
(although it is noteworthy that quantifying the benefit of de-worming is
notoriously difficult and is the subject of some recent controversy). 218
Moreover, the schools' infrastructure offers a convenient conduit to ach-
ieve high coverage of the most heavily infected individuals.
Model Validation
Validation of model predictions against parasitological (or other) data
is imperative, particularly if output is going to be trusted and used by
intervention planners and control strategists. Validation can be under-
taken in a number of ways: a qualitative appraisal of model output
against observed data; 206,210 the calculation of generic statistical measures
of fit, such as the coefficient of determination (R 2 ); 219 or the calculation of
(log-) likelihoods, whereby the higher the likelihood, the better the fit. 208
Ideally, all model parameters should be estimated prior to validation
using independent data. In practice, this is frequently not achieved since
data used for parameter estimation are often validated against post-
intervention data collected from the same individuals or population.
For example, EpiWorm has been fully parameterized for A. lumbricoides
using baseline worm burden data from Burma (Myanmar) and qualita-
tively validated against mean worm burdens collected over a 2-year
period of 3-monthly treatments in the same community. 206,220
For validation data to be fully independent of parameterization data is,
in essence, making the somewhat optimistic assumption that the model in
question is completely generalizable across heterogeneous host
parasite
populations. For example, the fecundity of female A. lumbricoides is highly
variable among geographical locations, yet the underlying processes
causing this are unknown, 46 and consequently reparameterization and
revalidation are necessary on a community basis. More generally, best
practice should involve continual reappraisal of model output especially
in the contemporary context of parasite populations being exposed
to repeated and regular doses of anthelmintics. 113
e
Anthelmintic Resistance
Given the continuing increase in MDA of anthelmintics, 33 population
dynamics models adapted to capture the effects of evolving anthelmintic
drug resistance 221 may become invaluable tools for decision support in
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