RESUMEN
Theoretical predictions of disease prevalence due to helminth infections based upon a simple probabilistica model which considers the infection prevalence, the mean worm urden and the degree of worm aggregation are presented. A numerical reappraisal of the likely estimates of the degree of aggregation based upon maximun likelihood estimates of the negative binomial distribution is presented. The prevalence of disease shows a positive relationship with the mean worm burden. This association is hyperbolic when helminth parasites are severely aggregated but is s-shaped when helminth parasites tend to be oversidpersed. The prevalence of disease decreases with the degree of worm aggregation whem the values of the mean intensity are low; as the mean intensity increases this association becomes positive. The relationship between prevalence of disease and prevalence of infection is hyperbolic for severe degrees of parasite aggregation and is s-shaped for intermediate degrees of aggregation. However, if the mean intesnsity is low and the degree of aggreation is high there could be a negative raltionship between the prevalence of disease due to helminth parasites is feasible for determined ranges of values of the infection prevalence, mena intensity and the degree of worm clumping