Schistosoma mansoni egg counts by faecal examination
vary
considerably
and are not very sensitive, so prevalences are
underestimated. The distribution of egg counts can adequately be described
by a
stochastic model which distinguishes
variation in counts between persons and variation in repeated counts within
a
person. Based on this model a pocket chart
has been developed which predicts the proportion of individuals harbouring
at
least 1 S. mansoni worm pair – the ‘true
prevalence’ – from a simple single survey prevalence and geometric
mean egg
count (using common duplicate 25 mg
Kato–Katz smears). The current paper describes the validation of
this chart
by comparing predicted true prevalences with
prevalences observed after 5–7 repeated Kato–Katz faecal examinations
(Burundi), by examination of a large quantity of
stool using the Visser filter (Brazil) or a selective sedimentation–filtration
method (Surinam). Because 5–7 repeated
examinations do not suffice to measure all infections, predictions have
been
made of the cumulative proportion positives
over 5–7 surveys – the ‘approximate true prevalence’
– as well. After dividing
the data into age groups, 12 different subsets
were considered for validation. In all 12 cases, predicted true prevalences
(or
approximate true prevalences for the Burundi
data) agree well with those observed. The overall agreement depends only
slightly
on the assumed relationship between
worm numbers and mean egg counts, with a good fit for a productivity between
0·8
and 4·4 eggs per gramme faeces (EPG)
per worm pair (WP). This interval includes the most plausible value from
the
literature, i.e. 1·0 EPG/WP, which has been
applied in the initial pocket chart. These findings support the validity
of the
chart to predict true prevalences for a wide
range of productivity assumptions, and reinforces the applicability of
its
underlying stochastic model to describe egg count
variation. However, as predictions appear to vary importantly when using
only
part of the data, it is also concluded that
the pocket chart never compensates for limited validity of initial single
survey prevalences and geometric means in consequence of small sample sizes.