Estimating underreporting of leprosy in Brazil using a Bayesian approach

Area of Science:

• Epidemiology
• Public Health
• Infectious Disease Control

Background:

• Leprosy disproportionately affects impoverished populations in low- and middle-income nations, serving as a major cause of infectious disability.
• Despite advancements in leprosy surveillance, underreporting remains a persistent issue, potentially compromising resource allocation and intervention efficacy.
• Accurate case detection is crucial for effective leprosy control and management.

Purpose of the Study:

• To estimate the proportion of unreported leprosy cases within Brazilian microregions between 2007 and 2015.
• To identify socioeconomic factors influencing spatial variations in leprosy incidence and underreporting.
• To provide data for improving leprosy surveillance and resource allocation in Brazil.

Main Methods:

• A Bayesian hierarchical model was employed using data from 557 Brazilian microregions (2007-2015).
• Grade 2 leprosy-related physical disabilities were utilized as a direct indicator of delayed diagnosis and a proxy for surveillance effectiveness.
• Spatial variability in incidence rates and the influence of socioeconomic factors were analyzed.

Main Results:

• An estimated average of 33,252 (9.6%) new leprosy cases were unreported nationwide during the study period.
• The proportion of underreported cases varied from 8.4% to 14.1% across Brazilian states.
• Grade 2 disability effectively indicated the system's capacity to detect missed leprosy cases.

Conclusions:

• Significant underreporting of leprosy cases was identified in Brazil, necessitating improved case detection strategies.
• The findings underscore the importance of addressing socioeconomic determinants in leprosy control.
• Microregion-specific estimates can inform targeted interventions, optimize resource distribution, and reduce disease transmission.