Abstract:
Leprosy is a chronic disease caused by Mycobacterium leprae.This disease can result physical
disabilities and deformities that develop during the clinical outcome of the disease and also
creates a negative image leading to discrimination and social stigma against the affected individuals
and their families.It causes affected people to loss their social dignity, absence of social confidence
and self-disregard.In Ethiopian among the communicable diseases, leprosy is the leading cause
of prolonged physical disability and causes serious social stigma.The aim of this study was to
identify the determinants of disability among leprosy patients in ALERT center.The data for
this study was collected from the medical chart of leprosy patients at ALERT Center, Addis
Ababa, Ethiopia.Survival analysis techniques and parametric shared frailty model were used in
this study to examine determinants of disability among leprosy patient’s by using R-version
3.6.3 and SAS 9.4 software’s.The study consists of 205 leprosy patients having all required
information who were taking treatment at ALERT Addis Ababa Ethiopia from January,2015 up
to December, 2019.Among those included in the study, 69(33.7%) were experienced the event
or disabled during treatment.Regions were used as clusters which was taken care of the frailty
term at regional level and shared frailty models were explored.Using different baseline distribution
parametric models were employed to have an appropriate model for the determinant of disability
due to leprosy based on Akaike information criteria (AIC) of the model.Heterogeneity or unobserved
covariates were found to be significant at cluster level.Log logistic gamma shared frailty model
is found to be the best model for disability due to leprosy, the result showed that Age, Treatment
Category, Symptom Duration and Sensory Loss are associated with disability.The HR of age
of patients with leprosy was about 1.033 implies that for a unit increased in age, the hazard of
disability of patients was significantly increased by 3.3% keeping all variables constant.The model
also reflected there is evidence of heterogeneity at cluster level therefore, special attention should
be given to these significant predictors, which ultimately reduce the occurrence of disability.To
reduce the patient-related delay (long duration), the program should lay greater emphasis on
raising awareness of the community focusing on key messages like symptoms, the disability
consequence of late detection, availability of free treatment, availability of leprosy care in public
health facility. Additionally, program should put more emphasis on early case detection campaigns
like active survey.
