Background: Serological data are increasingly being used to monitor malaria transmission intensity and have
been demonstrated to be particularly useful in areas of low transmission where traditional measures such as EIR and
parasite prevalence are limited. The seroconversion rate (SCR) is usually estimated using catalytic models in which
the measured antibody levels are used to categorize individuals as seropositive or seronegative. One limitation
of this approach is the requirement to impose a fixed cut-off to distinguish seropositive and negative individuals.
Furthermore, the continuous variation in antibody levels is ignored thereby potentially reducing the precision of the
estimate.
Methods: An age-specific density model which mimics antibody acquisition and loss was developed to make full
use of the information provided by serological measures of antibody levels. This was fitted to blood-stage antibody
density data from 12 villages at varying transmission intensity in Northern Tanzania to estimate the exposure rate as
an alternative measure of transmission intensity.
Results: The results show a high correlation between the exposure rate estimates obtained and the estimated SCR
obtained from a catalytic model (r = 0.95) and with two derived measures of EIR (r = 0.74 and r = 0.81). Estimates of
exposure rate obtained with the density model were also more precise than those derived from catalytic models.
Conclusion: This approach, if validated across different epidemiological settings, could be a useful alternative framework
for quantifying transmission intensity, which makes more complete use of serological data.