Optimising sampling regimes and data collection to inform surveillance for trachoma control

Area of Science:

• Ophthalmology
• Infectious Disease Epidemiology
• Mathematical Modeling

Background:

• Trachoma affects 190 million people, with control programs using mass drug administration (MDA).
• Monitoring relies on follicular trachoma (TF) prevalence in children, which becomes challenging at low disease levels.
• Polymerase chain reaction (PCR) and sero-surveillance are explored as complementary tools for monitoring low-level transmission.

Purpose of the Study:

• To explore the dynamic relationship between TF and PCR during trachoma control programs using mathematical modeling.
• To evaluate the utility of two cross-sectional sero-surveys for estimating sero-conversion rates.
• To inform the design of monitoring and evaluation strategies for trachoma elimination.

Main Methods:

• Utilized a previously published mathematical model to simulate the relationship between TF and PCR prevalence during MDA.
• Employed a sero-catalytic model to assess the effectiveness of two cross-sectional sero-surveys for parameter estimation.
• Simulated scenarios to analyze detection probabilities and prevalence correlations under different program stages.

Main Results:

• PCR is more sensitive than TF for detecting infection, but its detection probability decreases faster than TF during MDA.
• A moderate chance exists for low PCR and higher TF prevalence in late-stage programs, potentially explaining observed correlations.
• Two sero-surveys spaced 10 years apart provide more precise epidemiological parameter estimates than a single survey.

Conclusions:

• Quantitative modeling of infection and disease dynamics is crucial for designing effective trachoma monitoring strategies.
• While PCR and serology show promise, their optimal use requires careful consideration of program stage and sampling.
• Longitudinal, individual-level data may be necessary to accurately monitor progress towards trachoma elimination.