Evidence map›Paper›PMID 34281057›Full record

ArticleInternational journal of environmental research and public health2021

Spatio-Temporal Analysis of Influenza-Like Illness and Prediction of Incidence in High-Risk Regions in the United States from 2011 to 2020.

Zhijuan Song, Xiaocan Jia, Junzhe Bao, Yongli Yang, Huili Zhu, Xuezhong Shi

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

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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

14 citing papers in PubMed.

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  14. Epidemiological Trends of Malaria in Five Years and under Children of Nsanje District in Malawi, 2015-2019.International journal of environmental research and public health · 2021
    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

6 authors.

Zhijuan SongDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou 450001, China.
Xiaocan JiaDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou 450001, China.
Junzhe BaoDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou 450001, China.
Yongli YangDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou 450001, China.
Huili ZhuDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou 450001, China.
Xuezhong ShiDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou 450001, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

About 8% of the Americans contract influenza during an average season according to the Centers for Disease Control and Prevention in the United States. It is necessary to strengthen the early warning for influenza and the prediction of public health. In this study, Spatial autocorrelation analysis and spatial scanning analysis were used to identify the spatiotemporal patterns of influenza-like illness (ILI) prevalence in the United States, during the 2011-2020 transmission seasons. A seasonal autoregressive integrated moving average (SARIMA) model was constructed to predict the influenza incidence of high-risk states. We found the highest incidence of ILI was mainly concentrated in the states of Louisiana, District of Columbia and Virginia. Mississippi was a high-risk state with a higher influenza incidence, and exhibited a high-high cluster with neighboring states. A SARIMA (1, 0, 0) (1, 1, 0)

Indexed as

Influenza, HumanDistrict of ColumbiaHumansIncidenceLouisianaMississippiSeasonsSpatio-Temporal AnalysisUnited StatesVirginiainfluenza-like illnesspredictionSARIMA modelspatiotemporal analysis

Identifiers

PMID34281057
PMCPMC8297262

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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.