RT Journal Article
SR Electronic
T1 P3.012 How Robust Are the Descriptions of Chlamydia Natural History Used in Economic Evaluations of Control Strategies?
JF Sexually Transmitted Infections
JO Sex Transm Infect
FD BMJ Publishing Group Ltd
SP A151
OP A151
DO 10.1136/sextrans-2013-051184.0472
VO 89
IS Suppl 1
A1 Davies, B
A1 Anderson, S
A1 Turner, K M E
A1 Ward, H
YR 2013
UL http://sti.bmj.com/content/89/Suppl_1/A151.2.abstract
AB Background The decision to implement a Chlamydia screening programme is based on a detailed assessment of its projected impact and cost-effectiveness. In the absence of evidence from randomised controlled trials, transmission dynamic models are crucial to this process. However these models are highly sensitive to the representation of the infection. We review the evidence used to inform the model parameters highlighting their strengths and limitations. Methods Published economic analyses of chlamydia screening interventions were identified following a systematic search of the literature. Only transmission dynamic models were included as they represent the gold standard. Parameters describing chlamydia infection were extracted and the variability across the studies assessed. The data used to inform each parameter was sourced and critically evaluated. Results Eleven studies were included in this review, all evaluating chlamydia screening programme designs in developed countries. Many key natural history parameters are based on sparse historical data and there is wide variation in the values used across the models. For example, The per act transmission probability ranging from 3.75% to 15.3%.The modelled duration of asymptomatic infection was between 180–370 days in women and 40–200 days in men.Only one paper includes a period of protective immunity following infection.Only 2 studies consider the role of reinfection in the development of complicationsHowever, there is a general consensus in the proportion of people that are asymptomatic; between 70–75% of women and 25–50% of men. Conclusion We highlight the variability in descriptions of the natural history and emphasise the importance of using contemporary data to inform modelling studies. A clear consensus on the appropriate representation of the natural history is needed, with estimates continuously updated using new evidence.