@article{95751,
  keywords = {leprosy, Northeast Brazil, Public health, Spatial Analysis, Time Series},
  author = {Damasceno D and Paz WSD and Souza CDFD and Santos A and Bezerra-Santos M},
  title = {High-risk transmission clusters of leprosy in an endemic area in the Northeastern Brazil: a retrospective spatiotemporal modelling (2001 - 2019).},
  abstract = {<p><b>OBJECTIVES: </b>To analyze and map the leprosy risk areas in the state of Alagoas, an endemic region in the Northeastern Brazil, between 2001 and 2019.</p><p><b>METHODS: </b>Eecological and time series study, using spatial analysis techniques. First, we analyze the epidemiological aspects of leprosy cases, using the data available in the Notifiable Diseases Information System; then we used the segmented log-linear regression model to assess time trends. Spatial distribution was analyzed by the Local Empirical Bayesian Estimator, and by calculating the Global and Local Moran Index. Finally, spatiotemporal clusters were identified through scanning statistics, using the Kulldorf method of retrospective analysis.</p><p><b>RESULTS: </b>We observed that Alagoas showed an average new case detection rate of 14.43/100,000 inhabitants between 2001 and 2019, being classified as highly endemic. The area of highest risk was the 9th health region (state hinterland), with increasing time trend (Annual Percentage Change/APC=7.2; p-value<0.05). Several clusters of high risk of leprosy transmission were verified in Alagoas, including the state capital and hinterland municipalities.</p><p><b>CONCLUSIONS: </b>Our data indicate that active M. leprae transmission persists in Alagoas; that diagnosis is delayed and that there are high-risk areas, especially in inland municipalities.</p>},
  year = {2021},
  journal = {Tropical medicine & international health : TM & IH},
  month = {07/2021},
  issn = {1365-3156},
  doi = {10.1111/tmi.13657},
  language = {eng},
}