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. 2019 Apr 30;19(1):364.
doi: 10.1186/s12879-019-3935-1.

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

Rebecca Mann Flueckiger  1 , Emanuele Giorgi  2 , Jorge Cano  3 , Mariamo Abdala  4 , Olga Nelson Amiel  4 , Gilbert Baayenda  5 , Ana Bakhtiari  6 , Wilfrid Batcho  7 , Kamal Hashim Bennawi  8 , Michael Dejene  9 , Balgesa Elkheir Elshafie  10 , Aba Ange Elvis  11 , Missamou François  12 , André Goepogui  13 , Khumbo Kalua  14 , Biruck Kebede  15 , Genet Kiflu  15 , Michael P Masika  16 , Marilia Massangaie  4 , Caleb Mpyet  17   18 , Jean Ndjemba  12 , Jeremiah M Ngondi  19 , Nicholas Olobio  20 , Patrick Turyaguma  5 , Rebecca Willis  6 , Souleymane Yeo  11 , Anthony W Solomon  3 , Rachel L Pullan  3
Affiliations

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

Rebecca Mann Flueckiger et al. BMC Infect Dis. .

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.

Keywords: Blindness; Epidemiology; Global trachoma mapping project; Neglected tropical disease; Trachoma; Trichiasis; Visual impairment.

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Conflict of interest statement

Ethics approval and consent to participate

Informed verbal consent was obtained from all participants. The fundamental purpose of the data collection was to guide the implementation of trachoma elimination programmes. Consent to participate allowed survey teams to examine both eyes of the consenting individual on one occasion only. For this reason, and because local partners with whom the fieldwork protocol was discussed believe that verbal consent is more acceptable than written consent in the largely illiterate rural populations amongst whom the surveys was conducted, we obtained informed verbal consent. All data collection was electronic, using an ODQ-based Android phone application. Consent (or its refusal) was formally noted by a trained, registered data recorder, who has a unique identification number and a signature kept on file. At the conclusion of data collection for each evaluation unit, the recorder signed a statement affirming that informed verbal consent was appropriately obtained from each individual examined in the survey. The study and the verbal consent procedure was approved by the Research Ethics Committee of the London School of Hygiene & Tropical Medicine (11909).

Consent for publication

Not applicable.

Competing interests

The authors have no proprietary or commercial interest in any materials discussed in this article. The authors alone are responsible for the views expressed in this article and they do not necessarily represent the views, decisions or policies of the institutions with which they are affiliated.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1
Fig. 1
Conceptual framework of environmental risk factors influencing progression to TT
Fig. 2
Fig. 2
Semi-variograms were generated with Pearson’s residuals derived from the best fitting non-spatial mixed methods model. The 95% confidence intervals (red dashed lines) and semi-variogram (black dashed line) created through generating 1000 simulations are displayed here. All distances are in kilometres
Fig. 3
Fig. 3
5 km gridded climate raster maps. Data depicted in this map were obtained from the Consortium for Spatial Information (CGIAR-CSI) [41]. The georeferenced raster files were converted to a 5 km × 5 km resolution and visualized by the manuscript authors using ArcGIS 10.1 (ESRI, Redlands, CA, USA)
Fig. 4
Fig. 4
5 km gridded Euclidian distance to water raster map. The manuscript authors produced a continuous surface of distances in km to the nearest water body and permanent rivers based on data obtained from the Global Database of Lakes, Reservoirs and Wetlands [72]
Fig. 5
Fig. 5
5 km gridded soil composition sand fraction raster map. Data depicted in this map were obtained from the ISRIC-World Soil Information project included in the Harmonized Soil Map of the World [43]. The georeferenced raster files were converted to a 5 km × 5 km resolution and visualized by the manuscript authors using ArcGIS 10.1 (ESRI, Redlands, CA, USA)
Fig. 6
Fig. 6
5 km gridded remoteness raster maps. Data depicted in this map were obtained from the Operational Linescan System instrument on board a satellite of the Defence Meteorological Satellite Program [46, 47]. The georeferenced raster files were converted to a 5 km × 5 km resolution and visualized by the manuscript authors using ArcGIS 10.1 (ESRI, Redlands, CA, USA)
See this image and copyright information in PMC

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