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Probabilistic forecasts of trachoma transmission at the district level: A statistical model comparison.

ABSTRACT: The World Health Organization and its partners are aiming to eliminate trachoma as a public health problem by 2020. In this study, we compare forecasts of TF prevalence in 2011 for 7 different statistical and mechanistic models across 9 de-identified trachoma endemic districts, representing 4 unique trachoma endemic countries. We forecast TF prevalence between 1-6 years ahead in time and compare the 7 different models to the observed 2011 data using a log-likelihood score. An SIS model, including a district-specific random effect for the district-specific transmission coefficient, had the highest log-likelihood score across all 9 districts and was therefore the best performing model. While overall the deterministic transmission model was the least well performing model, although it did comparably well to the other models for 8 of 9 districts. We perform a statistically rigorous comparison of the forecasting ability of a range of mathematical and statistical models across multiple endemic districts between 1 and 6 years ahead of the last collected TF prevalence data point in 2011, assessing results against surveillance data. This study is a step towards making statements about likelihood and time to elimination with regard to the WHO GET2020 goals.

SUBMITTER: Pinsent A

PROVIDER: S-EPMC5340843 | biostudies-other | 2017 Mar

REPOSITORIES: biostudies-other

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Probabilistic forecasts of trachoma transmission at the district level: A statistical model comparison.

Pinsent Amy A Liu Fengchen F Deiner Michael M Emerson Paul P Bhaktiari Ana A Porco Travis C TC Lietman Thomas T Gambhir Manoj M

Epidemics 20170301

The World Health Organization and its partners are aiming to eliminate trachoma as a public health problem by 2020. In this study, we compare forecasts of TF prevalence in 2011 for 7 different statistical and mechanistic models across 9 de-identified trachoma endemic districts, representing 4 unique trachoma endemic countries. We forecast TF prevalence between 1-6 years ahead in time and compare the 7 different models to the observed 2011 data using a log-likelihood score. An SIS model, includin ...[more]

PMID: 28279456

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Project description:BackgroundTo eliminate blinding trachoma, the World Health Organization emphasizes implementing the SAFE strategy, which includes annual mass drug administration (MDA) with azithromycin to the whole population of endemic districts. Prevalence surveys to assess impact at the district level are recommended after at least 3 years of intervention. The decision to stop MDA is based on a prevalence of trachomatous inflammation follicular (TF) among children aged 1-9 years below 5% at the sub-district level, as determined by an additional round of surveys limited within districts where TF prevalence is below 10%. We conducted impact surveys powered to estimate prevalence simultaneously at the sub-district and district in two zones of Amhara, Ethiopia to determine whether MDA could be stopped.MethodologySeventy-two separate population-based, sub-district surveys were conducted in 25 districts. In each survey all residents from 10 randomly selected clusters were screened for clinical signs of trachoma. Data were weighted according to selection probabilities and adjusted for correlation due to clustering.Principal findingsOverall, 89,735 residents were registered from 21,327 households of whom 72,452 people (80.7%) were examined. The prevalence of TF in children aged 1-9 years was below 5% in six sub-districts and two districts. Sub-district level prevalence of TF in children aged 1-9 years ranged from 0.9-76.9% and district-level from 0.9-67.0%. In only one district was the prevalence of trichiasis below 0.1%.Conclusions/significanceThe experience from these zones in Ethiopia demonstrates that impact assessments designed to give a prevalence estimate of TF at sub-district level are possible, although the scale of the work was challenging. Given the assessed district-level prevalence of TF, sub-district-level surveys would have been warranted in only five districts. Interpretation was not as simple as stopping MDA in sub-districts below 5% given programmatic challenges of exempting sub-districts from a highly regarded program and the proximity of hyper-endemic sub-districts.

Project description:The World Health Organization (WHO) has targeted trachoma for elimination as a public health concern by 2020. Mathematical modelling is used for a range of infectious diseases to assess the impact of different intervention strategies on the prevalence of infection or disease. Here we evaluate the performance of four different mechanistic mathematical models that could all realistically represent trachoma transmission. We fit the four different mechanistic models of trachoma transmission to cross-sectional age-specific Polymerase Chain Reaction (PCR) and Trachomatous inflammation, follicular (TF) prevalence data. We estimate 4 or 3 parameters within each model, including the duration of an individual's infection and disease episode using Markov Chain Monte Carlo. We assess the performance of each models fit to the data by calculating the deviance information criterion. We then model the implementation of different interventions for each model structure to assess the feasibility of elimination of trachoma with different model structures. A model structure which allowed some re-infection in the disease state (Model 2) was statistically the most well performing model. All models struggled to fit to the very high prevalence of active disease in the youngest age group. Our simulations suggested that for Model 3, with annual antibiotic treatment and transmission reduction, the chance of reducing active disease prevalence to < 5% within 5 years was very low, while Model 2 and 4 could ensure that active disease prevalence was reduced within 5 years. Model 2 here fitted to the data best of the models evaluated. The appropriate level of susceptibility to re-infection was, however, challenging to identify given the amount and kind of data available. We demonstrate that the model structure assumed can lead to different end points following the implementation of the same interventions. Our findings are likely to extend beyond trachoma and should be considered when modelling other neglected tropical diseases.

Project description:BackgroundThe WHO seeks to control trachoma as a public health problem in endemic areas. Achham District in western Nepal was found to have TF (trachoma follicular) above 20% in a 2006 government survey, triggering 3 annual mass drug administrations finishing in 2010. Here we assess the level of control that has been achieved using surveillance for clinical disease, ocular chlamydia trachomatis infection, and serology for antibodies against chlamydia trachomatis protein antigens.MethodsWe conducted a cross-sectional survey of children aged 1-9 years in communities in Achham District in early 2014 including clinical examination validated with photographs, conjunctival samples for Chlamydia trachomatis (Amplicor PCR), and serological testing for antibodies against chlamydia trachomatis protein antigens pgp3 and CT694 using the Luminex platform.FindingsIn 24 randomly selected communities, the prevalence of trachoma (TF and/or TI) in 1-9 year olds was 3/1124 (0.3%, 95% CI 0.1 to 0.8%), and the prevalence of ocular chlamydia trachomatis infection was 0/1124 (0%, 95% CI 0 to 0.3%). In 18 communities selected because they had the highest prevalence of trachoma in a previous survey, the prevalence of TF and/or TI was 7/716 (1.0%, 95% CI 0.4 to 2.0%) and the prevalence of ocular chlamydia trachomatis infection was 0/716 (0%, 95% CI 0 to 0.5%). In 3 communities selected for serological testing, the prevalence of trachoma was 0/68 (0%, 95% CI 0 to 5.3%), the prevalence of ocular chlamydia trachomatis infection was 0/68 (0%, 95% CI 0 to 0.5%), the prevalence of antibodies against chlamydia trachomatis protein antigen pgp3 was 1/68 (1.5%, 95% CI 0.04% to 7.9%), and the prevalence of antibodies against chlamydia trachomatis protein antigen CT694 was 0/68 (0%, 95% CI 0 to 5.3%).Conclusion/significanceThis previously highly endemic district in Nepal has little evidence of recent clinical disease, chlamydia trachomatis infection, or serological evidence of trachoma, suggesting that epidemiological control has been achieved.

Project description:BackgroundTrachoma, the worldwide leading infectious cause of blindness, is due to repeated conjunctival infection with Chlamydia trachomatis. The effects of control interventions on population levels of infection and active disease can be promptly measured, but the effects on severe ocular sequelae require long-term monitoring. We present an age-structured mathematical model of trachoma transmission and disease to predict the impact of interventions on the prevalence of blinding trachoma.Methodology/principal findingsThe model is based on the concept of multiple reinfections leading to progressive conjunctival scarring, trichiasis, corneal opacity and blindness. It also includes aspects of trachoma natural history, such as an increasing rate of recovery from infection and a decreasing chlamydial load with subsequent infections that depend upon a (presumed) acquired immunity that clears infection with age more rapidly. Parameters were estimated using maximum likelihood by fitting the model to pre-control infection prevalence data from hypo-, meso- and hyperendemic communities from The Gambia and Tanzania. The model reproduces key features of trachoma epidemiology: 1) the age-profile of infection prevalence, which increases to a peak at very young ages and declines at older ages; 2) a shift in this prevalence peak, toward younger ages in higher force of infection environments; 3) a raised overall profile of infection prevalence with higher force of infection; and 4) a rising profile, with age, of the prevalence of the ensuing severe sequelae (trachomatous scarring, trichiasis), as well as estimates of the number of infections that need to occur before these sequelae appear.Conclusions/significanceWe present a framework that is sufficiently comprehensive to examine the outcomes of the A (antibiotic) component of the SAFE strategy on disease. The suitability of the model for representing population-level patterns of infection and disease sequelae is discussed in view of the individual processes leading to these patterns.

Dataset Information

Probabilistic forecasts of trachoma transmission at the district level: A statistical model comparison.

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Probabilistic forecasts of trachoma transmission at the district level: A statistical model comparison.

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