Evidence map›Paper›PMID 30180215›Full record

ArticlePloS one2018

Spatiotemporal diffusion of influenza A (H1N1): Starting point and risk factors.

Ana Carolina Carioca da Costa, Cláudia Torres Codeço, Elias Teixeira Krainski, Marcelo Ferreira da Costa Gomes, Aline Araújo Nobre

Abstract read
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Geographic components of SARS-CoV-2 expansion: a hypothesis.Journal of applied physiology (Bethesda, Md. : 1985) · 2020
    Review
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.

Ana Carolina Carioca da CostaNational Institute of Women, Children and Adolescents Health Fernandes Figueira, Department of Clinical Research, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil.ORCID 0000-0002-9456-3319
Cláudia Torres CodeçoScientific Computing Program, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil.
Elias Teixeira KrainskiFederal University of Paraná, Paraná, Brazil.
Marcelo Ferreira da Costa GomesScientific Computing Program, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil.
Aline Araújo NobreScientific Computing Program, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Influenza constitutes a major challenge to world health authorities due to high transmissibility and the capacity to generate large epidemics. This study aimed to characterize the diffusion process of influenza A (H1N1) by identifying the starting point of the epidemic as well as climatic and sociodemographic factors associated with the occurrence and intensity of transmission of the disease. The study was carried out in the Brazilian state of Paraná, where H1N1 caused the largest impact. The units of spatial and temporal analysis were the municipality of residence of the cases and the epidemiological weeks of the year 2009, respectively. Under the Bayesian paradigm, parametric inference was performed through a two-part spatiotemporal model and the integrated nested Laplace approximation (INLA) algorithm. We identified the most likely starting points through the effective distance measure based on mobility networks. The proposed estimation methodology allowed for rapid and efficient implementation of the spatiotemporal model, and provided evidence of different patterns for chance of occurrence and risk of influenza throughout the epidemiological weeks. The results indicate the capital city of Curitiba as the probable starting point, and showed that the interventions that focus on municipalities with greater migration and density of people, especially those with higher Human Development Indexes (HDIs) and the presence of municipal air and road transport, could play an important role in mitigation of effects of future influenza pandemics on public health. These results provide important information on the process of introduction and spread of influenza, and could contribute to the identification of priority areas for surveillance as well as establishment of strategic measures for disease prevention and control. The proposed model also allows identification of epidemiological weeks with high chance of influenza occurrence, which can be used as a reference criterion for creating an immunization campaign schedule.

Indexed as

EpidemicsEpidemiological MonitoringInfluenza A Virus, H1N1 SubtypeSpatio-Temporal AnalysisBrazilHumansIncidenceInfluenza, HumanPublic HealthRisk FactorsSeasonsSocioeconomic Factors

Identifiers

PMID30180215
PMCPMC6122785

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.