Epidemiological and spatio-temporal characteristics of new leprosy cases in municipalities in the state of Alagoas, Brazil

Introduction: The difficulties in coping with leprosy reaffirm the importance of epidemiological studies in different locations to better assess the magnitude of its endemicity. Objective: to analyze the distribution of new cases and leprosy detection coefficients in the state of Alagoas. Method: Th...

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Bibliographic Details
Authors: Alves, Gracinda Maria Gomes, Melo, Géssyca Cavalcante de, Teixeira, Camila Silveira Silva, Carvalho, Lucyo Wagner Torres de, Tavares, Clodis Maria, Araújo, Karina Conceição Gomes Machado de
Format: article
Status:Published version
Publication Date:2021
Country:Brasil
Institution:Universidade Federal de Itajubá (UNIFEI)
Repository:Research, Society and Development
Language:Portuguese
OAI Identifier:oai:ojs.pkp.sfu.ca:article/14962
Online Access:https://rsdjournal.org/index.php/rsd/article/view/14962
Access Level:Open access
Keyword:Lepra
Epidemiología
Análisis espacio-temporal.
Leprosy
Epidemiology
Spatio-temporal analysis.
Hanseníase
Epidemiologia
Análise espaço-temporal.
Description
Summary:Introduction: The difficulties in coping with leprosy reaffirm the importance of epidemiological studies in different locations to better assess the magnitude of its endemicity. Objective: to analyze the distribution of new cases and leprosy detection coefficients in the state of Alagoas. Method: This is an ecological study. Leprosy cases reported in the municipalities of Alagoas were included. The study was based on records obtained in the National Notification System, from State Department of Health (2010-2019) and demographic data from the population census (2010). Association, spatial and trend temporal analysis were used. Results: 4,343 cases of leprosy were reported in the municipalities. The average rate of detection of new cases for the total population was estimated at 10.85, ranging from 12.57 (2010) to 11.63 (2019). The highest rate was estimated for the municipality of Santana do Ipanema (58.2), considered to be hyper-endemic. Rates with very high endemic values were observed in 13 municipalities. There was a downward trend in the mean number of cases in 2010-2014 (APC = -4.34, CI95%: -10.5-2.3) and an increase in 2015-2019 (APC = 3.04, CI95%: -15.1-25). The gross and Bayesian rates showed many municipalities with a high endemic characteristic, in the west, northwest, northeast and south regions. Conclusion: This study showed clusters in areas of greater socioeconomic vulnerability. It is recommended to plan preventive actions, to actively search for cases and to evaluate contacts in the identified areas.