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

• Published in: BMC infectious diseases Vol. 19; no. 1; p. 364
• Main Authors: Flueckiger, Rebecca Mann, Giorgi, Emanuele, Cano, Jorge, Abdala, Mariamo, Amiel, Olga Nelson, Baayenda, Gilbert, Bakhtiari, Ana, Batcho, Wilfrid, Bennawi, Kamal Hashim, Dejene, Michael, Elshafie, Balgesa Elkheir, Elvis, Aba Ange, François, Missamou, Goepogui, André, Kalua, Khumbo, Kebede, Biruck, Kiflu, Genet, Masika, Michael P, Massangaie, Marilia, Mpyet, Caleb, Ndjemba, Jean, Ngondi, Jeremiah M, Olobio, Nicholas, Turyaguma, Patrick, Willis, Rebecca, Yeo, Souleymane, Solomon, Anthony W, Pullan, Rachel L
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 30.04.2019; BioMed Central; BMC
• Subjects: Antibiotics; Blindness; Chlamydia infections; Clustering; Complications and side effects; Diagnostic systems; Disease; Economic indicators; Economic models; Epidemiology; Geostatistics; Infectious diseases; Inflammation; Neglected tropical disease; Pathogenesis; Public health; Risk analysis; Risk factors; Sanitation; Spatial distribution; Trachoma; Trichiasis; Tumor necrosis factor-TNF; Visual impairment; Water resource management; Benin; Mozambique; Malawi; Sudan; Tanzania; Uganda; Nigeria; Ethiopia; Global trachoma mapping project; Trichiasis; Neglected tropical disease; Visual impairment; Blindness; Trachoma; Epidemiology
• DOI: 10.1186/s12879-019-3935-1
• ISSN: 1471-2334

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. 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. 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. 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.