ArticlePLoS neglected tropical diseases2023
Spatial and temporal dynamics of leptospirosis in South Brazil: A forecasting and nonlinear regression analysis.
Article in PLoS neglected tropical diseases, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- Structural barriers in the prevention and control of leptospirosis in a municipality in Southern Brazil: a qualitative study.BMC health services research · 2025Article
- Emergence and spatiotemporal incidence of dengue in Rio Grande do Sul, Brazil.Scientific reports · 2025Article
- Factors associated with the lethality of human leptospirosis in Brazil.Cadernos de saude publica · 2025Article
- Spatio-temporal risk prediction of leptospirosis: A machine-learning-based approach.PLoS neglected tropical diseases · 2025Article
- Spatiotemporal distribution of leptospirosis in the Espirito Santo State, Brazil.Revista do Instituto de Medicina Tropical de Sao Paulo · 2025Article
- Spatiotemporal relationship between agriculture, livestock, deforestation, and visceral leishmaniasis in Brazilian legal Amazon.Scientific reports · 2024Article
- Risk of human leptospirosis in Colombia: spatiotemporal analysis and related hydroclimatic factors.Transactions of the Royal Society of Tropical Medicine and Hygiene · 2024Article
- Prediction of influenza outbreaks in Fuzhou, China: comparative analysis of forecasting models.BMC public health · 2024Article
- Determining the relationship between dengue and vulnerability in a Brazilian city: a spatial modeling analysis.Pathogens and global health · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Although leptospirosis is endemic in most Brazilian regions, South Brazil shows the highest morbidity and mortality rates in the country. The present study aimed to analyze the spatial and temporal dynamics of leptospirosis cases in South Brazil to identify the temporal trends and high-risk areas for transmission and to propose a model to predict the disease incidence. An ecological study of leptospirosis cases in the 497 municipalities of the state of Rio Grande do Sul, Brazil, was conducted from 2007 to 2019. The spatial distribution of disease incidence in southern Rio Grande do Sul municipalities was evaluated, and a high incidence of the disease was identified using the hotspot density technique. The trend of leptospirosis over the study period was evaluated by time series analyses using a generalized additive model and a seasonal autoregressive integrated moving average model to predict its future incidence. The highest incidence was recorded in the Centro Oriental Rio Grandense and metropolitan of Porto Alegre mesoregions, which were also identified as clusters with a high incidence and high risk of contagion. The analysis of the incidence temporal series identified peaks in the years 2011, 2014, and 2019. The SARIMA model predicted a decline in incidence in the first half of 2020, followed by an increase in the second half. Thus, the developed model proved to be adequate for predicting leptospirosis incidence and can be used as a tool for epidemiological analyses and healthcare services.Temporal and spatial clustering of leptospirosis cases highlights the demand for intersectorial surveillance and community control policies, with a focus on reducing the disparity among municipalities in Brazil.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.