Home > Research > Publications & Outputs > Understanding the spatial distribution of trich...

Links

Text available via DOI:

View graph of relations

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

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Published
  • Rebecca Mann Flueckiger
  • Jorge Cano
  • Mariamo Abdala
  • Olga Nelson Amiel
  • Gilbert Baayenda
  • Ana Bakhtiari
  • Wilfrid Batcho
  • Kamal Hashim Bennawi
  • Michael Dejene
  • Balgesa Elkheir Elshafie
  • Aba Ange Elvis
  • Missamou Francois
  • Andre Goepogui
  • Khumbo Kalua
  • Biruck Kebede
  • Genet Kiflu
  • Michael P. Masika
  • Marilia Massangaie
  • Caleb Mpyet
  • Jean Ndjemba
  • Jeremiah M. Ngondi
  • Nicholas Olobio
  • Patrick Turyaguma
  • Rebecca Willis
  • Souleymane Yeo
  • Anthony W. Solomon
  • Rachel L. Pullan
Close
Article number364
<mark>Journal publication date</mark>30/04/2019
<mark>Journal</mark>BMC Infectious Diseases
Volume19
Number of pages16
Publication StatusPublished
<mark>Original language</mark>English

Abstract

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.