摘要
Background:As leprosy elimination becomes an increasingly realistic goal,it is essential to determine the factors that contribute to its persistence.We evaluate social and economic factors as predictors of leprosy annual new case detection rates within India,where the majority of leprosy cases occur.Methods:We used correlation and linear mixed effect regressions to assess whether poverty,illiteracy,nighttime satellite radiance(an index of development),and other covariates can explain district-wise annual new case detection rate and Grade 2 disability diagnoses.Results:We find only weak evidence of an association between poverty and annual new case detection rates at the district level,though illiteracy and satellite radiance are statistically significant predictors of leprosy at the district level.We find no evidence of rapid decline over the period 2008-2015 in either new case detection or new Grade 2 disability.Conclusions:Our findings suggest a somewhat higher rate of leprosy detection,on average,in poorer districts;the overall effect is weak.The divide between leprosy case detection and true incidence of clinical leprosy complicates these results,particularly given that the detection rate is likely disproportionately lower in impoverished settings.Additional information is needed to distinguish the determinants of leprosy case detection and transmission during the elimination epoch.
基金
KHG,WC,RKS,BG,and TCP acknowledge support from the Meaningful Modeling of Epidemiological Data(MMED)program,a NIH-funded joint initiative under the University of Florida,the South African Centre for Epidemiological Modelling and Analysis(SACEMA)
the African Institute for Mathematical Sciences(AIMS)(NIH NIGMS R25GM102149 to J.R.C.Pulliam and A.Welte.).LW,TML,AG,and TCP acknowledge funding of the NTD Modelling Consortium by Novartis Foundation.The views,opinions,assumptions and conclusions or any other information set out in this article are solely those of the authors and not of Novartis Foundation.Novartis Foundation was not involved in the establishment of this article and this article should not be attributed to Novartis Foundation or any person connected with Novartis Foundation
TCP acknowledges support from the US NIH NIGMS MIDAS program,U01-GM087728
AG acknowledges support from US NIH NIGMS MIDAS award U01-GM087719.
