Possible changes in the transmissibility of trachoma following MDA and transmission reduction: implications for the GET2020 goals

Abstract

BackgroundThe role of mass drug administration (MDA) and the implementation of transmission reduction measures are essential to successfully control and eliminate a wide range of NTDs, including the ocular disease trachoma. Immunity to trachoma infection acts by reducing the duration of an individual’s infectious period and by reducing their infectivity with each successive infection. MethodsIn this study, we use a model of trachoma infection, which includes population immunity, to explore the impact of treatment and transmission reduction measures on trachoma prevalence. Specifically, we investigate the possibility of increasing transmissibility of trachoma arising as MDA and transmission reduction measures are scaled up in endemic settings.ResultsWe demonstrate this increase in transmissibility by calculating the effective reproduction number during several simulated control programmes and show that it is related to a decrease in the level of immunity in the population.ConclusionsThis effect should be studied in the field by measuring the rate of return of infection and disease in at least two separate age groups. If the decline of population immunity is operating, it should be accounted for when planning for the GET2020 goal of eliminating blinding trachoma by 2020.Electronic supplementary materialThe online version of this article (doi:10.1186/s13071-015-1133-6) contains supplementary material, which is available to authorized users.

Improving our forecasts for trachoma elimination: What else do we need to know?

“…However, in general, this functional form led to an overall better fit to the cross-sectional data ( Table 1 ). This somewhat counterintuitive effect with exponentially declining infectivity (explored in [ 37 ]) results in the reproduction number associated with the full model increasing with each subsequent treatment round of MDA. This is as a result of the concentration of infectivity increasing with multiple rounds of MDA, as a higher number of individuals in the population have experienced fewer infections, resulting in individuals aggregating at higher infectivities as their progress along the ‘ladder of infection’ is slowed or halted due to MDA.…”

Measuring and modelling the effects of systematic non-adherence to mass drug administration

“…The majority of modelling predictions for the outcome of mass drug administration campaigns assume random coverage ( Truscott et al, 2015 , Gambhir and Pinsent, 2015 , Liu et al, 2015 , Blok et al, 2015 , Pandey et al, 2015 , Singh and Michael, 2015 , Gurarie et al, 2015 , Anderson et al, 2015 ). In this scheme, each individual in each round has the same probability, c , of receiving treatment, where c is the coverage achieved by the campaign.…”

“…Mathematical modelling plays an important role in the design of MDA programs—who to treat, when to treat ( Anderson et al, 2012 , Anderson et al, 2015 , Coffeng et al, 2014 , Coffeng et al, 2015 , Gambhir and Pinsent, 2015 , Gurarie et al, 2015 , Irvine et al, 2015 , Jambulingam et al, 2016 , Liu et al, 2015 , Singh and Michael, 2015 , Stolk et al, 2015 , Truscott et al, 2015 , Winnen et al, 2002 )—and in setting the ‘expected’ prevalence after a certain number of rounds, particularly for onchocerciasis ( Tekle et al, 2016 ). Modelling studies have highlighted the importance of coverage (the proportion of the target population who are treated), with high coverage leading to more rapid declines in prevalence and sustained high coverage leading to the possibility of elimination ( Okell et al, 2011 , Slater et al, 2014 ).…”

Quantitative analyses and modelling to support achievement of the 2020 goals for nine neglected tropical diseases

“…Two distinct models were developed to address two key areas in trachoma transmission control and surveillance. The developed model by Gambhir and Pinsent [ 45 ] was a deterministic susceptible, infected, susceptible (SIS) transmission model, which was age-structured and followed individuals from their first infection to their last (a ‘ladder of infection’), and accounted for the development of immunity within the population as the number of infections experienced increased. This model assessed the impact of multiple annual rounds of MDA and the implementation of F and E on the long-term transmission dynamics of infection, within three different transmission settings.…”

“…5 Schematic of trachoma results. The schematic includes results from: a) a transmission model including consideration of immunity by Gambhir et al [ 45 ]; and b) a statistical analysis of the most informative data for forecasting trends in prevalence by Liu et al [ 44 ] …”