DOI: 10.5061/dryad.pg4f4qs14
title: Factors associated with new leprosy diagnosis in Kwale County, Kenya

description: Leprosy, a chronic bacterial disease caused by Mycobacterium leprae, is
 curable yet neglected. Approximately 200,000 new cases are reported
 globally each year, with India contributing 60%. In 2020, the African WHO
 regions had a leprosy burden of 14.9 per 1,000,000 population. Despite
 maintaining the global elimination target of &lt;1/10000 population,
 Kenya reported a six-fold increase in cases(63-163) from 2011 to 2021,
 with Kwale County contributing 24.3%. This study aimed to determine the
 factors associated with new leprosy diagnoses. We conducted a 1:3
 case-control study in the Kwale from June to September 2023. Cases
 included people who were treated for leprosy based on clinical/laboratory
 and epidemiological criteria between January 2022 and May 2023. Controls
 were persons with no signs or symptoms and were a neighboring household to
 a case in another or nearby plot, matched by sex, age group of ±10 years,
 and village. Questionnaires were administered to both groups. Factors
 associated with Leprosy were evaluated using multivariable logistic
 regression. Stepwise backward elimination was used to build a final model;
 p-values of ≤0.05 were considered significant. A total of 65 cases and 195
 controls were enrolled. The mean age was 55 years (SD±16) for the cases
 and 54 years (SD±15) for the controls. Among cases,56.6% (n=37) were
 married, compared to 71.1% (n=139) of controls. 55% (n=36) of the cases
 and 41% (n=81) of the controls were illiterate. The odds of being
 diagnosed with leprosy were seven times higher among patients with a
 family size ≥5 members (aOR=6.99, 95% CI: 2.71–18.06) and four times
 higher among those with a family contact (aOR=4.33, 95% CI: 2.18–8.58).
 Social contact (aOR=2.24,95% CI: 1.16–4.32) and non-vaccination with BCG
 (aOR=2.24,95% CI: 1.11–4.53) are associated with double odds of new
 leprosy diagnosis. Leprosy prevention efforts in high-burden counties
 should prioritize early detection, prompt treatment of cases, enhanced
 community-based surveillance, and household contact tracing to reduce
 transmission. In addition, the Ministry of Health should sustain and
 expand the BCG vaccination coverage among all eligible persons.
description: Data were analyzed using MS Excel and STATA version 16.1.
 Descriptive analysis summarized continuous variables as means and standard
 deviations. Categorical variables as proportions. Bivariate logistic
 regression assessed the associations between independent variables and the
 leprosy disease. Variables with p-values ≤0.2 were included in the
 multivariable analysis. Stepwise backward elimination was applied to build
 the best-fitting model, given the multiple variables under consideration
 and the nature of the study design, where the outcome is already known.
 This technique allowed the efficient selection of the statistically
 significant risk factors while controlling for potential confounders.
 Factors with p-values ≤0.05 were retained in the final model. Adjusted
 odds ratios with 95% confidence intervals were reported to determine the
 significance of associations.
description: # Factors associated with new leprosy diagnosis in Kwale County, Kenya
 [https://doi.org/10.5061/dryad.pg4f4qs14](https://doi.org/10.5061/dryad.pg4f4qs14) ## Description of the data and file structure File: Factors_Associated_with_New_Leprosy_Diagnosis_in__Kwale_CountyVersion_III.xlsx The repository contains data and supporting files for the manuscript titled: “Factors Associated with New Leprosy Diagnosis in Kwale County, Kenya.” **Data Structure:** The dataset consists of de-identified data collected from participants in Kwale County, Kenya, focusing on Factors Associated with New Leprosy Diagnosis **Dataset:** * data_leprosy_kwale_Kenya. Xlsx-Contains anonymized individual-level data with demographic, clinical, behavioural, and environmental risk factors. * Metadata text -Explains the data collection methods, inclusion/exclusion criteria, and ethical considerations. **File Structure:** * Main datasets, variable descriptions, data collection details, descriptive analysis results, manuscript for submission **Description of key variables:** * Demographic factors: Age, gender, occupation, residence * Clinical factors: Contact history, BCG vaccination * Behavioural Factors: Frequency of changing line * Environmental factors: Family size, overcrowding **Data access & ethical considerations** * The data is de-identified to protect participant privacy. * Ethical approval was obtained from Moi University Institutional Review and Ethics Committee (Reference number: IREC/405/2023)