Evidence map›Paper›PMID 37058534›Full record

ArticlePLoS neglected tropical diseases2023

Spatial and temporal dynamics of leptospirosis in South Brazil: A forecasting and nonlinear regression analysis.

Alessandra Jacomelli Teles, Bianca Conrad Bohm, Suellen Caroline Matos Silva, Nádia Campos Pereira Bruhn, Fábio Raphael Pascoti Bruhn

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Spatiotemporal distribution of leptospirosis in the Espirito Santo State, Brazil.Revista do Instituto de Medicina Tropical de Sao Paulo · 2025
    Article
  6. Article
  7. Risk of human leptospirosis in Colombia: spatiotemporal analysis and related hydroclimatic factors.Transactions of the Royal Society of Tropical Medicine and Hygiene · 2024
    Article
  8. Article
  9. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Alessandra Jacomelli TelesSecretaria Municipal de Saúde de Herval, Herval, Rio Grande do Sul, Brasil.
Bianca Conrad BohmUniversidade Federal de Pelotas, Programa de Pós Graduação em Veterinária, Capão do Leão, Rio Grande do Sul, Brasil.
Suellen Caroline Matos SilvaUniversidade Federal de Pelotas, Programa de Pós Graduação em Veterinária, Capão do Leão, Rio Grande do Sul, Brasil.ORCID 0000-0002-7604-905X
Nádia Campos Pereira BruhnCentro de Integração do Mercosul, Universidade Federal de Pelotas, Pelotas, Rio Grande do Sul, Brasil.
Fábio Raphael Pascoti BruhnDepartamento de Veterinária Preventiva, Universidade Federal de Pelotas, Capão do Leão, Rio Grande do Sul, Brasil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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

LeptospirosisBrazilCitiesHumansIncidenceRegression AnalysisSpatial Analysis

Identifiers

PMID37058534
PMCPMC10132658

What OpenQuestion holds

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Registered trials

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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.