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Volume 32, Number 11—November 2026

Dispatch

Serologic Assessment of Public Health Action Needed for Trachoma, Coastal Ecuador, 2021–2024

Everlyn Kamau, Lesly Simbaña, Stuart Torres, Nikolina Walas, Gretchen Cooley, Chabier Coleman, E. Brook Goodhew, Diana L. Martin, Hadley Burroughs, Manuel Calvopiña, William Cevallos, Sandra Vivero, Victoria Nipaz, Josefina Coloma, Gwenyth O. Lee, Gabriel Trueba, Joseph N.S. Eisenberg, Karen Levy, and Benjamin F. ArnoldComments to Author 
Author affiliation: University of California, San Francisco, California, USA (E. Kamau, N. Walas, H. Burroughs, B.F. Arnold); Universidad de San Francisco de Quito, Quito, Ecuador (L. Simbaña, S. Torres, V. Nipaz, G. Trueba); Centers for Disease Control and Prevention, Atlanta, Georgia, USA (G. Cooley, C. Coleman, E.B. Goodhew, D.L. Martin); Universidad de las Americas, Quito (M. Calvopiña); Universidad Central del Ecuador, Quito (W. Cevallos, S. Vivero); University of California, Berkeley, California, USA (J. Coloma); Rutgers University, New Brunswick, New Jersey, USA (G.O. Lee); University of Michigan, Ann Arbor, Michigan, USA (J.N.S. Eisenberg); University of Washington, Seattle, Washington, USA (K. Levy)

Main Article

Figure 2

Model-based probability estimates of SCRs for IgGs against Chlamydia trachomatis plasma gene protein 3 in study of serologic assessment of public health action needed for trachoma, coastal Ecuador, 2021–2024. Estimates compared data from Esmeraldas Province in Ecuador and global trachoma serology distributions (5). A) Probability density of SCRs for Borbón (commercial center) and 9 rural villages estimated for children who were 1–5 years of age. We superimposed those data with pooled SCR distributions from populations classified as public health action not needed (dashed line) and public health action needed (solid line), according to public health responses for trachoma control in a global analysis across a range of disease endemicity (5). B) Ridgeline plot of SCR probability densities for Borbón and rural villages from panel A compared with illustrative thresholds of 2 and 4/100 person-years (vertical dashed lines). We identified SCR <2 as a region of >90% probability that public health action is not needed, whereas SCR >4 is a region of >90% probability that public health action is needed. Intermediate ranges of SCR that are >2 and <4 per 100 person-years could motivate additional testing (e.g., PCR testing for infection or consideration for further monitoring depending on programmatic context [5]). SCR, seroconversion rate.

Figure 2. Model-based probability estimates of SCRs for IgGs against Chlamydia trachomatis plasma gene protein 3 in study of serologic assessment of public health action needed for trachoma, coastal Ecuador, 2021–2024. Estimates compared data from Esmeraldas Province in Ecuador and global trachoma serology distributions (5). A) Probability density of SCRs for Borbón (commercial center) and 9 rural villages estimated for children who were 1–5 years of age. We superimposed those data with pooled SCR distributions from populations classified as public health action not needed (dashed line) and public health action needed (solid line), according to public health responses for trachoma control in a global analysis across a range of disease endemicity (5). B) Ridgeline plot of SCR probability densities for Borbón and rural villages from panel A compared with illustrative thresholds of 2 and 4/100 person-years (vertical dashed lines). We identified SCR <2 as a region of >90% probability that public health action is not needed, whereas SCR >4 is a region of >90% probability that public health action is needed. Intermediate ranges of SCR that are >2 and <4 per 100 person-years could motivate additional testing (e.g., PCR testing for infection or consideration for further monitoring depending on programmatic context [5]). SCR, seroconversion rate.

Main Article

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