The median (IQR) prevalence of follicular trachoma, using the WHO criteria of TF, was 9.4% (6.6%, 15.0%) (
Fig. 1). Only one community had no trachoma signs, and 12 communities (16%) had a prevalence below 5%. The maximum trachoma prevalence was 38%. The median prevalence of infection in the 71 communities was 3.8% (IQR: 1.8%, 7.5%) (
Fig. 1). Nine communities (13%) had no infection, and seven communities (10%) had minimal infection below 1%. However, 69% of the communities still had a prevalence of infection ≥2%, and 44% had a prevalence of infection ≥5%. A scatterplot shows the relationship between the prevalence of follicular trachoma, using the WHO criteria of TF, and infection (
Fig. 2). Of interest, none of the villages with no infection had TF rates >10%, although many of the villages with infection also had TF rates <10%. The children were categorized according to the combination of clinical signs of trachoma as described in
Table 1. Within each category, the percentage of infected children varied from 2% to 64% (
Table 2). The severity of TF and TI increased from none (absence of the minimum follicular or inflammatory signs) to severe (a grade more severe than the minimum WHO criteria). As expected, the infection rate increased as the severity of the clinical signs increased, with the infection rates above 36% in children with severe TI regardless of the presence of TF. The groups at highest risk for infection were those with any severe TI (grade 3), both TF and TI at grade 2, and severe TF (grade 3) with any sign of inflammation (TI grades 1–3). From here on, these clinical signs are referred to as HRS. Of note, though children without signs of trachoma had a prevalence of infection of only 2%, they represented 72% of all children in the study.
The sensitivity and specificity of using HRS to identify a child with infection is shown in
Table 3. Although the sensitivity is not high (28%), the specificity of the absence of HRS to indicate the absence of infection is good (97%). However, we wish to use these signs at a community level to indicate infection; to the extent that these HRS cluster in a community, they may or may not be useful to assess the overall community level of infection. Only 10 communities had no HRS. One of the 10 also had no infection, and 3 of 10 had infection <1%; three communities had infection rates between 1% and 5%, and three had infection rates >5%. These data suggest that a different approach from the strict absence of HRS as a marker may be more useful.
Thus, we further evaluated the sensitivity and specificity of a community prevalence of HRS of 5% to gauge whether the prevalence of infection was below 2% (
Table 4); the specificity was 96%, and the sensitivity was 35%. Despite high specificity, in communities with a prevalence of HRS <5%, most still had a prevalence of infection >2% (32 of 53 communities). Thus, though the positive predictive value of HRS was strong enough (94%) to identify those communities that still needed treatment, the negative predictive value was poor (40%), and the absence of signs did not mean those villages should have stopped treatment. Adjusting the cutoff prevalence of HRS lower, from 5% to 3%, improved sensitivity but, again, at the expense of specificity (
Table 5). Consequently, no combination of HRS and low level of infection suggested a useful approach with programmatic utility.