Predicting future community-level ocular Chlamydia trachomatis infection prevalence using serological, clinical, molecular, and geospatial data

Trachoma is an infectious disease characterized by repeated exposures to Chlamydia trachomatis (Ct) that may ultimately lead to blindness. Efficient identification of communities with high infection burden could help target more intensive control efforts. We hypothesized that IgG seroprevalence in combination with geospatial layers, machine learning, and model-based geostatistics would be able to accurately predict future community-level ocular Ct infections detected by PCR. We used measurements from 40 communities in the hyperendemic Amhara region of Ethiopia to assess this hypothesis. Median Ct infection prevalence among children 0–5 years old increased from 6% at enrollment, in the context of recent mass drug administration (MDA), to 29% by month 36, following three years without MDA. At baseline, correlation between seroprevalence and Ct infection was stronger among children 0–5 years old (ρ = 0.77) than children 6–9 years old (ρ = 0.48), and stronger than the correlation between active trachoma and Ct infection (0-5y ρ = 0.56; 6-9y ρ = 0.40). Seroprevalence was the strongest concurrent predictor of infection prevalence at month 36 among children 0–5 years old (cross-validated R2 = 0.75, 95% CI: 0.58–0.85), though predictive performance declined substantially with increasing temporal lag between predictor and outcome measurements. Geospatial variables, a spatial Gaussian process, and stacked ensemble machine learning did not meaningfully improve predictions. Serological markers among children 0–5 years old may be an objective tool for identifying communities with high levels of ocular Ct infections, but accurate, future prediction in the context of changing transmission remains an open challenge.Author summary: Trachoma, one of the leading infectious causes of blindness globally, is targeted for elimination as a public health problem by 2030. District-level estimates of active trachoma among children 1–9 years old are currently used to guide control programs and assess elimination. However, active trachoma, based on diagnosis of clinical signs, is a subjective indicator. Serological markers present an objective, scalable alternative that could be measured in integrated platforms. In a hyperendemic region, community-level seroprevalence aligned more closely with concurrent infection prevalence than active trachoma. The correlation between seroprevalence and infection prevalence was stronger among 0–5-year-olds compared to 6–9-year-olds and was consistent over a three-year period of increasing transmission. Serosurveillance among children 0–5 years old may be a promising monitoring strategy to identify communities with the highest burdens of ocular chlamydial infection.