In this section
@article{Pothin:2016:10.1186/s12936-016-1121-0,
author = {Pothin, E and Ferguson, NM and Drakeley, CJ and Ghani, AC},
doi = {10.1186/s12936-016-1121-0},
journal = {Malaria Journal},
title = {Estimating malaria transmission intensity from Plasmodium falciparum serological data using antibody density models},
url = {http://dx.doi.org/10.1186/s12936-016-1121-0},
volume = {15},
year = {2016}
}
TY - JOUR
AB - Background: Serological data are increasingly being used to monitor malaria transmission intensity and havebeen demonstrated to be particularly useful in areas of low transmission where traditional measures such as EIR andparasite prevalence are limited. The seroconversion rate (SCR) is usually estimated using catalytic models in whichthe measured antibody levels are used to categorize individuals as seropositive or seronegative. One limitationof 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 theestimate.Methods: An age-specific density model which mimics antibody acquisition and loss was developed to make fulluse of the information provided by serological measures of antibody levels. This was fitted to blood-stage antibodydensity data from 12 villages at varying transmission intensity in Northern Tanzania to estimate the exposure rate asan alternative measure of transmission intensity.Results: The results show a high correlation between the exposure rate estimates obtained and the estimated SCRobtained from a catalytic model (r = 0.95) and with two derived measures of EIR (r = 0.74 and r = 0.81). Estimates ofexposure 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 frameworkfor quantifying transmission intensity, which makes more complete use of serological data.
AU - Pothin,E
AU - Ferguson,NM
AU - Drakeley,CJ
AU - Ghani,AC
DO - 10.1186/s12936-016-1121-0
PY - 2016///
SN - 1475-2875
TI - Estimating malaria transmission intensity from Plasmodium falciparum serological data using antibody density models
T2 - Malaria Journal
UR - http://dx.doi.org/10.1186/s12936-016-1121-0
UR - http://hdl.handle.net/10044/1/30713
VL - 15
ER -