Gender differences in the surgical management of trachomatous trichiasis: an exploratory analysis of global trachoma survey data, 2015-2019.

BACKGROUND: Trachomatous trichiasis (TT) is a painful, potentially blinding eye condition that can be managed through epilation or surgery. Women are affected by TT approximately twice as often as men and are believed to face gendered barriers to receiving surgical care to prevent vision loss. METHODS: We used data from 817 cross-sectional surveys conducted during 2015-2019 in 20 African countries to estimate the prevalence difference (PD) between female and male eyes for four outcomes potentially indicating gender-related differences in TT management: (1) received surgery and developed postoperative TT (PTT), (2) never offered surgery, (3) offered surgery but declined it, and (4) offered epilation but never offered surgery. RESULTS: The prevalence was modestly elevated among female eyes compared with male eyes for having PTT (PD:1.8 [95% confidence limits (CL): 0.6, 3.0]) and having declined surgery for the eye (PD: 6.2 [95% CL: 1.8, 10.7]). The proportion offered epilation was similar by gender (PD:0.5 [95% CL: -0.4, 1.3]), while never having been offered surgery was somewhat more prevalent among male eyes (PD: -2.1 [95% CL: -3.5, -0.7]). CONCLUSIONS: Our results suggest potential gender differences in TT management. More research is needed to determine the causes and implications of the observed differences.

Using model-based geostatistics for assessing the elimination of trachoma.

BACKGROUND: Trachoma is the commonest infectious cause of blindness worldwide. Efforts are being made to eliminate trachoma as a public health problem globally. However, as prevalence decreases, it becomes more challenging to precisely predict prevalence. We demonstrate how model-based geostatistics (MBG) can be used as a reliable, efficient, and widely applicable tool to assess the elimination status of trachoma. METHODS: We analysed trachoma surveillance data from Brazil, Malawi, and Niger. We developed geostatistical Binomial models to predict trachomatous inflammation-follicular (TF) and trachomatous trichiasis (TT) prevalence. We proposed a general framework to incorporate age and gender in the geostatistical models, whilst accounting for residual spatial and non-spatial variation in prevalence through the use of random effects. We also used predictive probabilities generated by the geostatistical models to quantify the likelihood of having achieved the elimination target in each evaluation unit (EU). RESULTS: TF and TT prevalence varied considerably by country, with Brazil showing the lowest prevalence and Niger the highest. Brazil and Malawi are highly likely to have met the elimination criteria for TF in each EU, but, for some EUs, there was high uncertainty in relation to the elimination of TT according to the model alone. In Niger, the predicted prevalence varied significantly across EUs, with the probability of having achieved the elimination target ranging from values close to 0% to 100%, for both TF and TT. CONCLUSIONS: We demonstrated the wide applicability of MBG for trachoma programmes, using data from different epidemiological settings. Unlike the standard trachoma prevalence survey approach, MBG provides a more statistically rigorous way of quantifying uncertainty around the achievement of elimination prevalence targets, through the use of spatial correlation. In addition to the analysis of existing survey data, MBG also provides an approach to identify areas in which more sampling effort is needed to improve EU classification. We advocate MBG as the new standard method for analysing trachoma survey outputs.

Exploring water, sanitation, and hygiene coverage targets for reaching and sustaining trachoma elimination: G-computation analysis.

BACKGROUND: Trachoma is the leading infectious cause of blindness. To reduce transmission, water, sanitation, and hygiene (WaSH) improvements are promoted through a comprehensive public health strategy. Evidence supporting the role of WaSH in trachoma elimination is mixed and it remains unknown what WaSH coverages are needed to effectively reduce transmission. METHODS/FINDINGS: We used g-computation to estimate the impact on the prevalence of trachomatous inflammation-follicular among children aged 1-9 years (TF1-9) when hypothetical WaSH interventions raised the minimum coverages from 5% to 100% for "nearby" face-washing water (<30 minutes roundtrip collection time) and adult latrine use in an evaluation unit (EU). For each scenario, we estimated the generalized prevalence difference as the TF1-9 prevalence under the intervention scenarios minus the observed prevalence. Data from 574 cross-sectional surveys conducted in 16 African and Eastern Mediterranean countries were included. Surveys were conducted from 2015-2019 with support from the Global Trachoma Mapping Project and Tropical Data. When modeling interventions among EUs that had not yet met the TF1-9 elimination target, increasing nearby face-washing water and latrine use coverages above 30% was generally associated with consistent decreases in TF1-9. For nearby face-washing water, we estimated a ≥25% decrease in TF1-9 at 65% coverage, with a plateau upon reaching 85% coverage. For latrine use, the estimated decrease in TF1-9 accelerated from 80% coverage upward, with a ≥25% decrease in TF1-9 by 85% coverage. Among EUs that had previously met the elimination target, results were inconclusive. CONCLUSIONS: Our results support Sustainable Development Goal 6 and provide insight into potential WaSH-related coverage targets for trachoma elimination. Targets can be tested in future trials to improve evidence-based WaSH guidance for trachoma.

The global burden of trichiasis in 2016.

BACKGROUND: Trichiasis is present when one or more eyelashes touches the eye. Uncorrected, it can cause blindness. Accurate estimates of numbers affected, and their geographical distribution, help guide resource allocation. METHODS: We obtained district-level trichiasis prevalence estimates in adults for 44 endemic and previously-endemic countries. We used (1) the most recent data for a district, if more than one estimate was available; (2) age- and sex-standardized corrections of historic estimates, where raw data were available; (3) historic estimates adjusted using a mean adjustment factor for districts where raw data were unavailable; and (4) expert assessment of available data for districts for which no prevalence estimates were available. FINDINGS: Internally age- and sex-standardized data represented 1,355 districts and contributed 662 thousand cases (95% confidence interval [CI] 324 thousand-1.1 million) to the global total. Age- and sex-standardized district-level prevalence estimates differed from raw estimates by a mean factor of 0.45 (range 0.03-2.28). Previously non- stratified estimates for 398 districts, adjusted by ×0.45, contributed a further 411 thousand cases (95% CI 283-557 thousand). Eight countries retained previous estimates, contributing 848 thousand cases (95% CI 225 thousand-1.7 million). New expert assessments in 14 countries contributed 862 thousand cases (95% CI 228 thousand-1.7 million). The global trichiasis burden in 2016 was 2.8 million cases (95% CI 1.1-5.2 million). INTERPRETATION: The 2016 estimate is lower than previous estimates, probably due to more and better data; scale-up of trichiasis management services; and reductions in incidence due to lower active trachoma prevalence.

Understanding the spatial distribution of trichiasis and its association with trachomatous inflammation-follicular.

BACKGROUND: Whilst previous work has identified clustering of the active trachoma sign "trachomatous inflammation-follicular" (TF), there is limited understanding of the spatial structure of trachomatous trichiasis (TT), the rarer, end-stage, blinding form of disease. Here we use community-level TF prevalence, information on access to water and sanitation, and large-scale environmental and socio-economic indicators to model the spatial variation in community-level TT prevalence in Benin, Cote d'Ivoire, DRC, Guinea, Ethiopia, Malawi, Mozambique, Nigeria, Sudan and Uganda. METHODS: We fit binomial mixed models, with community-level random effects, separately for each country. In countries where spatial correlation was detected through a semi-variogram diagnostic check we then fitted a geostatistical model to the TT prevalence data including TF prevalence as an explanatory variable. RESULTS: The estimated regression relationship between community-level TF and TT was significant in eight countries. We estimate that a 10% increase in community-level TF prevalence leads to an increase in the odds for TT ranging from 20 to 86% when accounting for additional covariates. CONCLUSION: We find evidence of an association between TF and TT in some parts of Africa. However, our results also suggest the presence of additional, country-specific, spatial risk factors which modulate the variation in TT risk.