Introduction: leprosy is an infectious, dermatoneurological disease characterized by
slow and progressive evolution, caused by Mycobacterium Leprae, transmitted through
the respiratory route, and has disabling potential. With the possibility of clinical epidemiological diagnosis, its treatment is offered free of charge through the Brazilian
Unified Health System, and new cases of the disease must be mandatory registered
through SINAN. Manifesting with heterogeneous characteristics in both population and
space, this ailment exhibits widespread global dissemination, predominantly affecting
underdeveloped countries like Brazil. At the subnational level, it is more consolidated,
a situation observed in the state of Pará, which has shown high disease rates in recent
decades. In this context, based on indicators of public health interest, the use of spatial
mapping techniques aims to enhance the understanding of the epidemic and express
characteristics of the disease's dynamics in the spatiotemporal context at the state
level. Objectives: to demonstrate the territorial distribution of leprosy detection rates
and their temporal evolution, as well as to identify and analyze regions of spatial
autocorrelation of the disease in the state of Pará. Methods: this is an observational,
ecological-analytical study that utilized secondary data from notifications of leprosy
cases to SINAN, assessing 27.541 new cases of leprosy reported among the 144
municipalities and 6 mesoregions of Pará from 2012 to 2021. Average detection rates
were calculated and analyzed by period. Additionally, mapped distribution, Moran's
spatial autocorrelation test, and Local Indicators of Spatial Association (LISA) were
performed to identify clusters with increased risk. Results: in the Pará scenario, the
disease showed a percentage reduction in the cumulative average detection rate of
54.37% at the end of the series, and there was a change in the average classification
from hyperendemicity to high endemicity. In spatial distribution, the disease presented
itself heterogeneously in the state, with the majority of the territory experiencing high,
very high, or hyperendemicity. The mesoregions of Southeast and Southwest Pará
expressed a higher number of municipalities in hyperendemicity. In the spatial
autocorrelation of the Local Moran's Index (li), zones of significance were identified
with few variations over time. On average, 35.69% of the municipalities exhibited
autocorrelation. Among these, clusters of High-High type were observed, indicating
high circulation of M. Leprae in the south-central part of the state, while Baixo
Amazonas exhibited Low-Low clusters, as did the northern coastal portion of the state.
Comparatively, there was a contraction of High-High municipalities from the beginning
of the period, but there was no expansion of Low-Low clusters. Conclusion: leprosy
remains a health problem in the Pará scenario, with the average detection rate being
high in most municipalities, especially in the Southeast and Southwest mesoregions of
Pará. The spatial analysis elucidated the spatial dynamics of the disease over the
years, as well as demonstrated the heterogeneity of its distribution and identified zones
of persistence for M. Leprae circulation. This provides practical and scientific support
for health interventions aimed at mitigating the advancement of the disease in Pará.
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