Evidence map›Paper›PMID 32764785›Full record

ArticlePloS one2020

Trends and forecasts of leprosy for a hyperendemic city from Brazil's northeast: Evidence from an eleven-year time-series analysis.

Antônio Carlos Vieira Ramos, Dulce Gomes, Marcelino Santos Neto, Thaís Zamboni Berra, Ivaneliza Simionato de Assis, Mellina Yamamura, Juliane de Almeida Crispim, José Francisco Martoreli Júnior, Alexandre Tadashi Inomata Bruce, Felipe Lima Dos Santos and 6 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.3field-weighted citation impact, top 28% of its field
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

4 citing papers in PubMed, 16 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Observational
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

16 authors at 7 institutions in 2 countries.

Antônio Carlos Vieira RamosDepartment of Maternal-Infant Nursing and Public Health, University of São Paulo at Ribeirão Preto College of Nursing, Ribeirão Preto, São Paulo, Brazil.ORCID 0000-0002-7862-1355
Dulce GomesDepartment of Mathematics, University of Évora, Évora, Portugal.
Marcelino Santos NetoCenter for Social Sciences, Health and Technology, Federal University of Maranhão, Imperatriz, Maranhão, Brazil.
Thaís Zamboni BerraDepartment of Maternal-Infant Nursing and Public Health, University of São Paulo at Ribeirão Preto College of Nursing, Ribeirão Preto, São Paulo, Brazil.
Ivaneliza Simionato de AssisUniversity Center Dinâmica of Cataratas, Foz do Iguaçu, Paraná, Brazil.
Mellina YamamuraNursing Department, Federal University of São Carlos, São Carlos, São Paulo, Brazil.
Juliane de Almeida CrispimDepartment of Maternal-Infant Nursing and Public Health, University of São Paulo at Ribeirão Preto College of Nursing, Ribeirão Preto, São Paulo, Brazil.
José Francisco Martoreli JúniorDepartment of Maternal-Infant Nursing and Public Health, University of São Paulo at Ribeirão Preto College of Nursing, Ribeirão Preto, São Paulo, Brazil.
Alexandre Tadashi Inomata BruceDepartment of Maternal-Infant Nursing and Public Health, University of São Paulo at Ribeirão Preto College of Nursing, Ribeirão Preto, São Paulo, Brazil.
Felipe Lima Dos SantosDepartment of Maternal-Infant Nursing and Public Health, University of São Paulo at Ribeirão Preto College of Nursing, Ribeirão Preto, São Paulo, Brazil.ORCID 0000-0001-5606-9478
Ludmilla Leidianne Limirio SouzaDepartment of Maternal-Infant Nursing and Public Health, University of São Paulo at Ribeirão Preto College of Nursing, Ribeirão Preto, São Paulo, Brazil.
Yan Mathias AlvesDepartment of Maternal-Infant Nursing and Public Health, University of São Paulo at Ribeirão Preto College of Nursing, Ribeirão Preto, São Paulo, Brazil.
Hamilton Leandro Pinto de AndradeDepartment of Maternal-Infant Nursing and Public Health, University of São Paulo at Ribeirão Preto College of Nursing, Ribeirão Preto, São Paulo, Brazil.
Marcos Augusto Moraes ArcoverdeCenter for Education, Letters and Health, Western Paraná State University, Campus Foz do Iguaçu, Foz do Iguaçu, Paraná, Brazil.
Flávia Meneguetti PieriDepartment of Nursing, Londrina State University, Londrina, Paraná, Brazil.
Ricardo Alexandre ArcêncioDepartment of Maternal-Infant Nursing and Public Health, University of São Paulo at Ribeirão Preto College of Nursing, Ribeirão Preto, São Paulo, Brazil.
Universidade de Ribeirão Preto · BRUnião Dinâmica de Faculdades Cataratas · BRUniversidade Estadual de Londrina · BRUniversidade Estadual do Oeste do Paraná · BRUniversidade Federal de São Carlos · BRUniversidade Federal do Maranhão · BRUniversity of Évora · PT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study's objective was to estimate the temporal trends of leprosy according to sex and age groups, as well as to estimate and predict the progression of the disease in a hyperendemic city located in the northeast of Brazil. This ecological time-series study was conducted in Imperatriz, Maranhão, Brazil. Leprosy cases diagnosed between 2006 and 2016 were included. Detection rates stratified by sex and age groups were estimated. The study of temporal trends was accomplished using the Seasonal-Trend Decomposition method and temporal modeling of detection rates using linear seasonal autoregressive integrated moving average model according to Box and Jenkins method. Trend forecasts were performed for the 2017-2020 period. A total of 3,212 cases of leprosy were identified, the average incidence among men aged between 30 and 59 years old was 201.55/100,000 inhabitants and among women in the same age group was 135.28/100,000 inhabitants. Detection rates in total and by sex presented a downward trend, though rates stratified according to sex and age presented a growing trend among men aged less than 15 years old and among women aged 60 years old or over. The final models selected in the time-series analysis show the forecasts of total detection rates and rates for men and women presented a downward trend for the 2017-2020 period. Even though the forecasts show a downward trend in Imperatriz, the city is unlikely to meet a significant decrease of the disease burden by 2020.

Indexed as

AdolescentAdultAge FactorsBrazilCitiesEndemic DiseasesFemaleForecastingHumansIncidenceLeprosyLinear ModelsMaleMiddle AgedSex FactorsTime Factors

Identifiers

PMID32764785
PMCPMC7413479
OpenAlexW3047659766

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.