Evidence map›Paper›PMID 34449729›Full record

ArticleTropical medicine and infectious disease2021

Spatial and Temporal Patterns of Ross River Virus in Queensland, 2001-2020.

Wei Qian, Cameron Hurst, Kathryn Glass, David Harley, Elvina Viennet

Abstract read
In one paragraph

Article in Tropical medicine and infectious disease, 2021. 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. Review
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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.

Wei QianUQ Centre for Clinical Research, The University of Queensland, Herston, QLD 4059, Australia.
Cameron HurstDepartment of Statistics, QIMR Berghofer Medical Research Institute, Brisbane, QLD 4006, Australia.ORCID 0000-0002-4577-8962
Kathryn GlassResearch School of Population Health, Australian National University, Acton, ACT 2601, Australia.
David HarleyUQ Centre for Clinical Research, The University of Queensland, Herston, QLD 4059, Australia.ORCID 0000-0001-6691-5420
Elvina ViennetInstitute for Health and Biomedical Innovation, School of Biomedical Sciences, Queensland University of Technology, Kelvin Grove, QLD 4059, Australia.ORCID 0000-0002-1418-1426

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ross River virus (RRV), the most common human arbovirus infection in Australia, causes significant morbidity and substantial medical costs. About half of Australian cases occur in Queensland. We describe the spatial and temporal patterns of RRV disease in Queensland over the past two decades. RRV notifications, human population data, and weather data from 2001 to 2020 were analysed by the Statistical Area Level 2 (SA2) area. Spatial interpolation or linear extrapolation were used for missing weather values and the estimated population in 2020, respectively. Notifications and incidence rates were analysed through space and time. During the study period, there were 43,699 notifications in Queensland. The highest annual number of notifications was recorded in 2015 (6182), followed by 2020 (3160). The average annual incidence rate was 5 per 10,000 people and the peak period for RRV notifications was March to May. Generally, SA2 areas in northern Queensland had higher numbers of notifications and higher incidence rates than SA2 areas in southern Queensland. The SA2 areas with high incidence rates were in east coastal areas and western Queensland. The timely prediction may aid disease prevention and routine vector control programs, and RRV management plans are important for these areas.

Indexed as

disease burdenepidemiologyRoss River virusspatial patterntemporal pattern

Identifiers

PMID34449729
PMCPMC8396220

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.