Cost-effectiveness of adding measurement of Chlamydia trachomatis infection and serology to trachoma prevalence surveys in Tanzania and Mozambique

Abstract

Background: Accurate methods to measure trachoma prevalence are critical to monitor progress and guide mass drug administration as countries near elimination. Currently, countries conduct trachoma prevalence surveys via clinical examination using the simplified trachoma grading system. Grading can have reduced accuracy in low prevalence settings, potentially resulting in errors. Adding ocular swabbing and Chlamydia trachomatis (Ct) infection testing and dried blood spot (DBS) collection and testing can be more sensitive and specific methods for trachoma identification, with potential cost-saving and information benefits. While previous studies have examined the costs of trachoma prevalence surveys, we present the first costing and cost-effectiveness analysis of enhanced trachoma prevalence surveys with ocular swabs and DBS in addition to grading.

Methodology/principal findings: We calculated the incremental financial cost of enhanced trachoma prevalence surveys with swabs, DBS, and grading using expenditure records from four districts in Tanzania and four districts in Mozambique in 2022. In Tanzania, the cost per cluster of an enhanced survey was $2,337.39 compared to $459.75 for a standard survey. In Mozambique, the cost per cluster of an enhanced survey was $2,147.12, compared to $1,381.46 for a standard survey. We calculated the incremental cost-effectiveness ratio for each method, defined as the ratio of incremental cost to additional instances of trachoma indicators identified, and explored variation in cost-effectiveness via sensitivity analyses. Adding swabs, DBS, or both was cost-increasing and more effective at identification of trachoma indicators than grading alone. In Tanzania, swabs were the most cost-effective method, while DBS was more cost-effective in Mozambique. Swabs and DBS were less cost-effective when combined than individually. The main factor determining cost-effectiveness was sensitivity.

Conclusions/significance: Adding swabs or DBS to trachoma prevalence surveys can be viable, cost-effective methods for identifying trachoma indicators. The additional costs are commensurate with additional information that would support elimination efforts.

Fig 1. Map of survey region.

This map shows the districts included in the surveys mentioned in this study. Colors correspond to region. Shapefiles accessed from https://data.humdata.org/dataset/cod-ab-tza (Tanzania) and https://data.humdata.org/dataset/cod-ab-moz (Mozambique). Contains information from OpenStreetMap and OpenStreetMap Foundation, which is made available under the Open Database License.

Fig 2. Tanzania deterministic sensitivity analysis results plotted on cost-effectiveness planes, showing the change in incremental cost and incremental effect corresponding to a change in the value of a given parameter, holding all other parameters constant.

This figure shows the results from the deterministic sensitivity analysis for Tanzania plotted on individual cost-effectiveness planes for each parameter value. Each plot corresponds to the parameter that was varied according to its maximum and minimum values, holding all other parameters constant. Each point on the plot represents an ICER value, where color corresponds to the evaluation method and shape corresponds to the value used in the ICER calculation.

Fig 3. Mozambique deterministic sensitivity analysis results plotted on cost-effectiveness planes, showing the change in incremental cost and incremental effect corresponding to a change in the value of a given parameter, holding all other parameters constant.

This figure shows the results from the deterministic sensitivity analysis for Mozambique plotted on individual cost-effectiveness planes for each parameter value. Each plot corresponds to the parameter that was varied according to its maximum and minimum values, holding all other parameters constant. Each point on the plot represents an ICER value, where color corresponds to the evaluation method and shape corresponds to the value used in the ICER calculation.

Fig 4. Tanzania probabilistic sensitivity analysis results showing incremental cost per person surveyed and additional instances of trachoma indicators identified for each of the three enhanced evaluation methods plotted on a cost-effectiveness plane.

This figure shows all 10,000 runs of the probabilistic sensitivity analysis for Tanzania. Each point represents a single ICER value, with color corresponding to evaluation method. The ellipse encompasses the 95% confidence interval.

Fig 5. Mozambique probabilistic sensitivity analysis results showing incremental cost per person surveyed and additional instances of trachoma indicators identified for each of the three enhanced evaluation methods plotted on a cost-effectiveness plane.

This figure shows all 10,000 runs of the probabilistic sensitivity analysis for Mozambique. Each point represents a single ICER value, with color corresponding to evaluation method. The ellipse encompasses the 95% confidence interval.