Abstract
BackgroundLeptospirosis is considered a neglected zoonosis associated with infrastructure problems and low socioeconomic status, particularly slums. Since the disease is mainly transmitted in urban settings by rat urine, this risk factor may be important predictor tool for prompt control and effective prevention at the local level in urban endemic areas. Accordingly, the present study aimed to propose an early spatial predictor tool for human leptospirosis in urban settings, to test the methodology of molecular methods for assessing Leptospira spp. in trapped rats, and report associated environmental data.Methodology/Principal findingsOfficial city records and previous study were used to select risk factors for human leptospirosis in an endemic neighborhood of Curitiba, Brazil. Neighborhood census sectors were divided in high- and low-risk areas using 12 selected factors: flood area, water supply, water course, green coverage, afforestation, sewage network, open sewage, open garbage, garbage collection, dumpster, pavement, and rodent complaints. In addition, rats were captured in pre-determined sites from January through March 2017, euthanized, and individual kidneys samples sent for molecular diagnosis. Human cases were obtained from official city records. In total, 95/112 (84.8%) census sectors were classified as low-risk to human leptospirosis. No significant statistical differences were found in human case frequencies between high and low-risk areas. Kidney samples from 17/25 (68.0%) trapped rats were positive for Leptospira spp. The main risk factors associated with rodent presence included inadequate water supply (p = 0.04), sanitary sewage (p = 0.04), unpaved streets (p = 0.04), and complaint of rodents (p = 0.04).Conclusions/SignificanceThis study offers a new approach to score leptospirosis transmission risk, and to compare small areas and their heterogeneity in the same census sector of endemic areas. Environmental risk factors for Leptospira spp. transmission within the neighborhood were mainly due to differences in infrastructure and basic services. To the author’s knowledge, this is the first study using Leptospira spp. in rats as predictor for human disease in an urban setting of a major city. Although the number of rats trapped was low, this methodology may be used as basis for early and effective interventions, focused on high risk areas for leptospirosis prior to human cases, and potentially reducing morbidity and mortality in low-income areas of urban settings.
Highlights
Leptospirosis is a reemerging zoonotic disease with approximately 350,000–500,000 severe human cases reported annually worldwide, a figure which may be underestimated due to inaccurate diagnosis and notification [1,2]
This study offers a new approach to score leptospirosis transmission risk, and to compare small areas and their heterogeneity in the same census sector of endemic areas
17/112 (15.2%) of CS were classified as high risk, and 95/112 (84.8%) of CS were classified as low risk of disease transmission, with a maximum of 7/12 (58.3%) risk factors simultaneously found in the same census sector
Summary
Leptospirosis is a reemerging zoonotic disease with approximately 350,000–500,000 severe human cases reported annually worldwide, a figure which may be underestimated due to inaccurate diagnosis and notification [1,2]. As rats may be infected but not seroconverted at the onset of disease, molecular methods such as PCR have been used for more accurate diagnosis of Leptospira spp. infections in rats, by testing urine and/or kidney tissue [9,14]. This method of disease detection could be used as an early predictor for human exposure and disease, in low-income urban areas. The present study aimed to propose an early spatial predictor tool for human leptospirosis in urban settings, to test the methodology of molecular methods for assessing Leptospira spp. in trapped rats, and report associated environmental data
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.