Spatio-temporal six-year retrospective study on dermatophytosis in Rio de Janeiro, Southeast Brazil: A tropical tourist locality tale

Simone Cristina Pereira Brito,Marcia Ribeiro Pinto,Lucas Martins Alcantara,Nathalia Faria Reis, Thiago Lacerda Duraes, Christina Teresa Machado Bittar, Jeferson Carvalhaes de Oliveira,Elisabeth Martins da Silva da Rocha,Ricardo Luiz Dantas Machado, Ricardo Jose de Paula Souza e Guimaraes,Andrea Regina de Souza Baptista

PLOS NEGLECTED TROPICAL DISEASES(2023)

引用 0|浏览7
暂无评分
摘要
Trichophyton, Microsporum, Nannizzia and Epidermophyton genera cause dermatophytosis, the most common and highly contagious infectious skin disease. Rio de Janeiro is one of the most visited cities in the Southern Hemisphere, located in the most visited state of Brazil. This retrospective study investigated epidemiological and laboratorial aspects of dermatophytosis in Rio de Janeiro state, Brazil, by using spatiotemporal analysis. More than half of all individuals were infected by one or more dermatophytes. A variation between 18 and 106 years-old of the studied population was verified, and women more frequently affected. Patients were more frequently infected by Trichophyton spp., most of them T. rubrum, followed by T. mentagrophytes. M. canis and N. gypsea were more frequently isolated in the age group between 40 and 60 years old, while T. rubrum predominates among younger patients. All species presented homogeneous distribution while T. tonsurans appears to be restricted to the Rio de Janeiro capital while E. floccosum to the municipality of Macae (190 Km apart from RJ). Rio de Janeiro state presented spatial clusters of dermatophytosis with high density in Guanabara Bay (E. floccosum, M. canis, N. gypsea, T. tonsurans) and Niteroi (T. rubrum, T. mentagrophytes) but low density in Macae (E. floccosum). Significant spatiotemporal clusters on dermatophytosis cases were detected in distinct municipalities (p-value <= 0.05). The Vulnerability Index (r = 0.293) and Demographic Density (r = 0.652) distributed according to neighborhoods in Niteroi were direct related with dermatophytosis cases whereas Income (r = -0.306) was inversely correlated (p-value <= 0.05). The dermatophytosis spatiotemporal distinct distribution after two major international events in Rio de Janeiro, Brazil, highlight the pressing need for specific measures of its prevention and controlling. This is particularly relevant in touristic tropical localities which must consider both socio-economical and traveler's medicine variables. Author summaryFour genera of fungi cause dermatophytosis, the most common and highly contagious infectious skin disease. Distinguishing dermatophyte species is crucial since ecological origin (geophilic, zoophilic or anthropophilic) provides clues about the source of infection, contributing to avoid reinfection and to the establishment of prevention measures. Rio de Janeiro is one of the most visited cities in the Southern Hemisphere, located in the most visited state of Brazil. This retrospective study investigated epidemiological and laboratorial aspects of dermatophytosis in Rio de Janeiro state, Brazil, by using spatiotemporal analysis. More than half of all individuals were infected by one or more dermatophytes. Microsporum canis and Nannizzia gypsea were more frequently isolated in the age group between 40 and 60 years old while T. rubrum predominates among younger patients. All species presented homogeneous distribution while T. tonsurans appears to be restricted to Rio de Janeiro capital and Epydermophyton floccosum to the municipality of Macae. Significant spatiotemporal clusters on dermatophytosis cases were detected in distinct municipalities (p-value <= 0.05). Dermatophytosis spatiotemporal distinct distribution after two major international events in Rio de Janeiro, Brazil (2014 Football World Cup and the 2016 Olympic Games), highlight the pressing need for specific measures of prevention and controlling.
更多
查看译文
关键词
rio dermatophytosis janeiro,southeast brazil,tropical tourist locality tale,spatio-temporal,six-year
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要