Table 1.
Estimates for the negative binomial parasite aggregation parameter, .
Figure 1.
The relationship between mean intensity and prevalence.
A The relationship between the mean intensity of infection, , the prevalence of infection,
, and the negative binomial aggregation parameter,
as described by the relationship in equation 1. B Relationship between the prevalence and intensity of infection as observed in a study of A. lumbricoides [28]. The solid line is the predicted relationship between mean prevalence of infection and worm burden described in equation 1 and plotted in A fitted to estimate the aggregation parameter,
= 0.194.
Table 2.
Percentage of population aged 5 to 14 years in 2011 [40].
Figure 2.
School attendance for a selection of countries.
This figure was generated by data published by UNICEF for 2005–2010 [41].. For each country there is net attendance rate at primary, in urban (open circles) and rural areas (closed circles) and a net attendance rate for secondary schools (filled squares).
Table 6.
Percentage of female children who are enrolled in school [45].
Table 3.
Published estimates of the basic reproductive number for various helminths.
Table 4.
Published estimates of parasite life expectancy, , in the human host [18], [27].
Figure 3.
The proportion of A. lumbricoides worms in children aged 5–14, calculated from equation 3.
The demography of the population, A, results in a proportion of 18.4% of the population aged 5–14 years old [45]. Combining this distribution with B the distribution of worms per person by age [57] gives 49.5% of worms in the school-aged group.
Figure 4.
The proportion of hookworm eggs deposited by children aged 5–14, calculated from equation 5.
The demography of the population, A, gives a proportion of 31.2% of the population aged 5–14 years old [45]. Combining this distribution with B the distribution of egg output by age [36] gives 15.7% of worms in the school-aged group.
Table 5.
Fraction of worm population or egg output in 5–14 year olds (equations 3 and 5).
Figure 5.
Critical fraction of the population to be treated.
The predicted relationship between the critical fraction of the human population to be treated, , per annum with efficacy,
, 0.9, and the basic reproductive number,
, and parasite life expectancy,
in years (from equation 11 in the main text).
Figure 6.
Impact of fraction treated on worm burden, prevalence and effective reproduction number.
The impact of the fraction of the population treated, , on A the mean worm burden
, B the prevalence of infection,
and C the effective reproductive number
, as described in equation 10. Parameter values are set for A. lumbricoides as follows:
= 0.81,
= 3,
= 1 yr,
= 0.967 and
= 0.95.
Figure 7.
Effect of regular treatment on mean A. lumbricoides worm burden for different models.
A homogeneous population (left column), B heterogeneous population with uniform transmission dynamics (central column) and C heterogeneous population with greater contribution from children (right column) as in the text. The two rows represent annual and half-yearly treatment respectively. For all runs, basic reproduction number is 3 and worm lifespan is 1 year. Other parameters (as defined for equations 6 and 7): μ2 = 5/yr, k = 0.7, z = 0.93.
Figure 8.
Effect of regular treatment on mean worm burden of hookworm for different models.
As in Figure 7, the columns are A homogeneous model, B heterogeneous population with uniform transmission dynamics and C heterogeneous population with greater contribution from children, as in the text and different treatment intervals (rows). Simulations for basic reproduction number, = 3, and worm lifespan is 2.5 years. Other parameters as in Figure 7. The two rows represent two-yearly and yearly treatment respectively.
Figure 9.
Schematic illustration of the impact of school-based deworming on the transmission of parasites.
The number of parasites affected by a school-based deworming programme is never 100%, it is reduced by the efficacy of the drug, the proportion of the population of school age and their intensity of infection, as well as school enrolment and attendance on a deworming day. The impact of such a treatment programme on transmission is less easily quantified and depends on the details of transmission between different age-groups in the population. For further details, see main text.