Evidence map›Paper›PMID 28011977›Full record

ArticleScientific reports2016

Multivariate time series analysis on the dynamic relationship between Class B notifiable diseases and gross domestic product (GDP) in China.

Tao Zhang, Fei Yin, Ting Zhou, Xing-Yu Zhang, Xiao-Song Li

Abstract read
In one paragraph

Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

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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.

Tao ZhangWest China School of Public Health, Sichuan University, Chengdu, China.
Fei YinWest China School of Public Health, Sichuan University, Chengdu, China.
Ting ZhouWest China School of Public Health, Sichuan University, Chengdu, China.
Xing-Yu ZhangWest China School of Public Health, Sichuan University, Chengdu, China. xingyu.zhang@emory.edu.
Xiao-Song LiWest China School of Public Health, Sichuan University, Chengdu, China. lixiaosong1101@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The surveillance of infectious diseases is of great importance for disease control and prevention, and more attention should be paid to the Class B notifiable diseases in China. Meanwhile, according to the International Monetary Fund (IMF), the annual growth of Chinese gross domestic product (GDP) would decelerate below 7% after many years of soaring. Under such circumstances, this study aimed to answer what will happen to the incidence rates of infectious diseases in China if Chinese GDP growth remained below 7% in the next five years. Firstly, time plots and cross-correlation matrices were presented to illustrate the characteristics of data. Then, the multivariate time series (MTS) models were proposed to explore the dynamic relationship between incidence rates and GDP. Three kinds of MTS models, i.e., vector auto-regressive (VAR) model for original series, VAR model for differenced series and error-correction model (ECM), were considered in this study. The rank of error-correction term was taken as an indicator for model selection. Finally, our results suggested that four kinds of infectious diseases (epidemic hemorrhagic fever, pertussis, scarlet fever and syphilis) might need attention in China because their incidence rates have increased since the year 2010.

Indexed as

ChinaCommunicable DiseasesGross Domestic ProductHumansIncidenceModels, TheoreticalMultivariate Analysis

Identifiers

PMID28011977
PMCPMC5515987

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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.