Lúcia Rolim Santana de Freitas, Fernanda Fernandez Nóbrega
{"title":"2012-2022年巴西各州麻风病指标的聚类分析及时间趋势","authors":"Lúcia Rolim Santana de Freitas, Fernanda Fernandez Nóbrega","doi":"10.1590/0074-02760240163","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Leprosy, a neglected tropical disease caused by Mycobacterium leprae, presents significant public health challenges in Brazil due to its slow progression, dermato-neurological manifestations, and potential for disability. Understanding leprosy's spatial distribution and temporal trends is important for effective control and elimination strategies.</p><p><strong>Objectives: </strong>This study aimed to identify clusters of leprosy in Brazilian states using agglomerative hierarchical clustering and to analyse their temporal trends from 2012 to 2022.</p><p><strong>Methods: </strong>An ecological study was conducted using data from the National System of Notifiable Diseases (SINAN). The agglomerative hierarchical clustering method was used to group states using the new case detection rate (NCDR) of leprosy per 100,000 inhabitants, the proportion of new cases of leprosy with grade 2 physical disability at the time of diagnosis (G2R), and the Gini index, a measure of socioeconomic inequality. Temporal trends within the clusters were assessed using Prais-Winsten regression analysis.</p><p><strong>Findings: </strong>In the period 2012-2022, 293,030 new cases of leprosy were reported in Brazil. Five distinct clusters were identified. Cluster 4, comprising Mato Grosso and Tocantins, had the highest NCDR and stable temporal trends (APC: 3.2%, 95% CI: -0.1%, 6.7%). Clusters 1 and 3 had the highest proportions of grade 2 disability, indicating late diagnosis. Clusters 4 and 5 had the lowest percentages of individuals with incomplete/complete higher education (7.6% and 7.4%, respectively). Cluster 4 had the highest percentage of individuals with the Diforma clinical form (69.8%) and with cases classified as multibacillary (84.5%).</p><p><strong>Main conclusions: </strong>The use of agglomerative hierarchical clustering, a novel application of a non-supervised algorithm in this context, highlighting the integration of multiple epidemiological and socioeconomic variables for a better understanding the dynamics of leprosy transmission in Brazil. Significant variations in the spatial distribution and temporal trends of leprosy were observed across Brazilian states. To improve leprosy surveillance and control in Brazil, targeted interventions are needed, particularly in high-endemicity regions with late diagnosis.</p>","PeriodicalId":18469,"journal":{"name":"Memorias do Instituto Oswaldo Cruz","volume":"120 ","pages":"e240163"},"PeriodicalIF":2.5000,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11984828/pdf/","citationCount":"0","resultStr":"{\"title\":\"Agglomerative hierarchical cluster analysis and temporal trend of leprosy indicators in Brazilian states, 2012-2022.\",\"authors\":\"Lúcia Rolim Santana de Freitas, Fernanda Fernandez Nóbrega\",\"doi\":\"10.1590/0074-02760240163\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Leprosy, a neglected tropical disease caused by Mycobacterium leprae, presents significant public health challenges in Brazil due to its slow progression, dermato-neurological manifestations, and potential for disability. Understanding leprosy's spatial distribution and temporal trends is important for effective control and elimination strategies.</p><p><strong>Objectives: </strong>This study aimed to identify clusters of leprosy in Brazilian states using agglomerative hierarchical clustering and to analyse their temporal trends from 2012 to 2022.</p><p><strong>Methods: </strong>An ecological study was conducted using data from the National System of Notifiable Diseases (SINAN). The agglomerative hierarchical clustering method was used to group states using the new case detection rate (NCDR) of leprosy per 100,000 inhabitants, the proportion of new cases of leprosy with grade 2 physical disability at the time of diagnosis (G2R), and the Gini index, a measure of socioeconomic inequality. Temporal trends within the clusters were assessed using Prais-Winsten regression analysis.</p><p><strong>Findings: </strong>In the period 2012-2022, 293,030 new cases of leprosy were reported in Brazil. Five distinct clusters were identified. Cluster 4, comprising Mato Grosso and Tocantins, had the highest NCDR and stable temporal trends (APC: 3.2%, 95% CI: -0.1%, 6.7%). Clusters 1 and 3 had the highest proportions of grade 2 disability, indicating late diagnosis. Clusters 4 and 5 had the lowest percentages of individuals with incomplete/complete higher education (7.6% and 7.4%, respectively). Cluster 4 had the highest percentage of individuals with the Diforma clinical form (69.8%) and with cases classified as multibacillary (84.5%).</p><p><strong>Main conclusions: </strong>The use of agglomerative hierarchical clustering, a novel application of a non-supervised algorithm in this context, highlighting the integration of multiple epidemiological and socioeconomic variables for a better understanding the dynamics of leprosy transmission in Brazil. Significant variations in the spatial distribution and temporal trends of leprosy were observed across Brazilian states. To improve leprosy surveillance and control in Brazil, targeted interventions are needed, particularly in high-endemicity regions with late diagnosis.</p>\",\"PeriodicalId\":18469,\"journal\":{\"name\":\"Memorias do Instituto Oswaldo Cruz\",\"volume\":\"120 \",\"pages\":\"e240163\"},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2025-04-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11984828/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Memorias do Instituto Oswaldo Cruz\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1590/0074-02760240163\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"PARASITOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Memorias do Instituto Oswaldo Cruz","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1590/0074-02760240163","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"PARASITOLOGY","Score":null,"Total":0}
Agglomerative hierarchical cluster analysis and temporal trend of leprosy indicators in Brazilian states, 2012-2022.
Background: Leprosy, a neglected tropical disease caused by Mycobacterium leprae, presents significant public health challenges in Brazil due to its slow progression, dermato-neurological manifestations, and potential for disability. Understanding leprosy's spatial distribution and temporal trends is important for effective control and elimination strategies.
Objectives: This study aimed to identify clusters of leprosy in Brazilian states using agglomerative hierarchical clustering and to analyse their temporal trends from 2012 to 2022.
Methods: An ecological study was conducted using data from the National System of Notifiable Diseases (SINAN). The agglomerative hierarchical clustering method was used to group states using the new case detection rate (NCDR) of leprosy per 100,000 inhabitants, the proportion of new cases of leprosy with grade 2 physical disability at the time of diagnosis (G2R), and the Gini index, a measure of socioeconomic inequality. Temporal trends within the clusters were assessed using Prais-Winsten regression analysis.
Findings: In the period 2012-2022, 293,030 new cases of leprosy were reported in Brazil. Five distinct clusters were identified. Cluster 4, comprising Mato Grosso and Tocantins, had the highest NCDR and stable temporal trends (APC: 3.2%, 95% CI: -0.1%, 6.7%). Clusters 1 and 3 had the highest proportions of grade 2 disability, indicating late diagnosis. Clusters 4 and 5 had the lowest percentages of individuals with incomplete/complete higher education (7.6% and 7.4%, respectively). Cluster 4 had the highest percentage of individuals with the Diforma clinical form (69.8%) and with cases classified as multibacillary (84.5%).
Main conclusions: The use of agglomerative hierarchical clustering, a novel application of a non-supervised algorithm in this context, highlighting the integration of multiple epidemiological and socioeconomic variables for a better understanding the dynamics of leprosy transmission in Brazil. Significant variations in the spatial distribution and temporal trends of leprosy were observed across Brazilian states. To improve leprosy surveillance and control in Brazil, targeted interventions are needed, particularly in high-endemicity regions with late diagnosis.
期刊介绍:
Memórias do Instituto Oswaldo Cruz is a journal specialized in microbes & their vectors causing human infections. This means that we accept manuscripts covering multidisciplinary approaches and findings in the basic aspects of infectious diseases, e.g. basic in research in prokariotes, eukaryotes, and/or virus. Articles must clearly show what is the main question to be answered, the hypothesis raised, and the contribution given by the study.
Priority is given to manuscripts reporting novel mechanisms and general findings concerning the biology of human infectious prokariotes, eukariotes or virus. Papers reporting innovative methods for diagnostics or that advance the basic research with these infectious agents are also welcome.
It is important to mention what we do not publish: veterinary infectious agents research, taxonomic analysis and re-description of species, epidemiological studies or surveys or case reports and data re-analysis. Manuscripts that fall in these cases or that are considered of low priority by the journal editorial board, will be returned to the author(s) for submission to another journal.