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

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.

Prevalence and Determinants of Trachomatous Trichiasis towards Elimination of Trachoma in Ethiopia: A Systematic Review and Meta- Analysis

“…There have been no additional articles excluded after full-text assessment for reasons as mentioned within the owchart (Figure 1). During the process of removal and exclusion, the main reasons were found to be the focus of the study [29][30][31][32][33][34][35][36], the site of the study [32,[37][38][39][40], and the target study population [31,[33][34][35][36][37][38][39][40]. To this end, our full data evaluation accommodated 13 articles, whereof three articles were excluded for target population and irrelevancy of the content [42,46,47].…”

Insights from mathematical modelling and quantitative analysis on the proposed 2030 goals for trachoma

“…Thus the observed prevalent number of TT cases is partly determined by the speed and efficiency of active case finding and surgical service delivery, which are inherently more challenging and uncertain to model. Mathematical modelling and current surveillance data suggests that EPHP is feasible, and indeed has already been achieved by a number of endemic countries 3 . However, in health districts with long-term persistence, such as a few high prevalence districts in Ethiopia (>40% baseline prevalence), annual MDA alone is not sufficient to achieve EPHP and must be supplemented with additional tools to reduce transmission 6,8-10 .…”

“…Following completion of the prescribed MDA, a follow-up survey is conducted to assess whether further rounds of MDA are required. To date, ten countries have been validated by WHO as having achieved EPHP 3 .…”

Spatial scales in human movement between reservoirs of infection

“…Defining the spatial scales over which transmission should be considered is a relatively recent research area in the context of neglected tropical diseases (NTDs), where much of the effort has been focused on the development of geostatistical methods for each disease in turn ( Pullan et al, 2011 , Schur et al, 2013 , Pullan et al, 2014 , Moyes et al, 2014 , Karagiannis-Voules et al, 2015 , Moraga et al, 2015 , Hamm et al, 2015 , OHanlon et al, 2016 , Ciddio et al, 2017 , Mari et al, 2017 , Flueckiger et al, 2019 ). In particular, mathematical models of helminth transmission have only recently begun to incorporate the dynamical effects of human movement between reservoirs of infection ( Ciddio et al, 2017 , Vegvari et al, 2019 , Hardwick et al, 2019 , Hardwick et al, 2021 ).…”