Evidence map›Paper›PMID 37316780›Full record

ArticleBMC infectious diseases2023

Interrupted time series analysis using the ARIMA model of the impact of COVID-19 on the incidence rate of notifiable communicable diseases in China.

Qin Zhou, Junxian Hu, Wensui Hu, Hailin Li, Guo-Zhen Lin

Open access · goldAbstract read
In one paragraph

Article in BMC infectious diseases, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
6.6field-weighted citation impact, top 2% 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

15 citing papers in PubMed, 30 citations in OpenAlex.

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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 at 1 institution in 1 country.

Qin ZhouDepartment of disease control and prevention, Guangzhou Center for Disease Control and Prevention, No. 1 Qide Road, Baiyun district, 510440, 510440, Guangzhou, Guangzhou, Guangdong, China. 273142563@qq.com.
Junxian HuDepartment of disease control and prevention, Guangzhou Center for Disease Control and Prevention, No. 1 Qide Road, Baiyun district, 510440, 510440, Guangzhou, Guangzhou, Guangdong, China.
Wensui HuDepartment of disease control and prevention, Guangzhou Center for Disease Control and Prevention, No. 1 Qide Road, Baiyun district, 510440, 510440, Guangzhou, Guangzhou, Guangdong, China.
Hailin LiDepartment of disease control and prevention, Guangzhou Center for Disease Control and Prevention, No. 1 Qide Road, Baiyun district, 510440, 510440, Guangzhou, Guangzhou, Guangdong, China.
Guo-Zhen LinDepartment of disease control and prevention, Guangzhou Center for Disease Control and Prevention, No. 1 Qide Road, Baiyun district, 510440, 510440, Guangzhou, Guangzhou, Guangdong, China.
Guangzhou Center for Disease Control and Prevention · CN

Funding

the Guangzhou Health Science and technology project 20211A010054
6 · The paper itself

Abstract

backgroundThe coronavirus disease 2019 (COVID-19) pandemic in China is ongoing. Some studies have shown that the incidence of respiratory and intestinal infectious diseases in 2020 decreased significantly compared with previous years. Interrupted time series (ITS) is a time series analysis method that evaluates the impact of intervention measures on outcomes and can control the original regression trend of outcomes before and after the intervention. This study aimed to analyse the impact of COVID-19 on the incidence rate of notifiable communicable diseases using ITS in China.

methodsNational data on the incidence rate of communicable diseases in 2009-2021 were obtained from the National Health Commission website. Interrupted time series analysis using autoregressive integrated moving average (ARIMA) models was used to analyse the changes in the incidence rate of infectious diseases before and after the COVID-19 epidemic.

resultsThere was a significant short-term decline in the incidence rates of respiratory infectious diseases and enteric infectious diseases (step values of -29.828 and - 8.237, respectively), which remained at a low level for a long time after the decline. There was a short-term decline in the incidence rates of blood-borne and sexually transmitted infectious diseases (step = -3.638), which tended to recover to previous levels in the long term (ramp = 0.172). There was no significant change in the incidence rate of natural focus diseases or arboviral diseases before and after the epidemic.

conclusionThe COVID-19 epidemic had strong short-term and long-term effects on respiratory and intestinal infectious diseases and short-term control effects on blood-borne and sexually transmitted infectious diseases. Our methods for the prevention and control of COVID-19 can be used for the prevention and control of other notifiable communicable diseases, especially respiratory and intestinal infectious diseases.

Indexed as

Communicable DiseasesCOVID-19Intraabdominal InfectionsChinaHumansIncidenceInterrupted Time Series AnalysisModels, StatisticalPandemicsAutoregressive integrated moving average modelsCommunicable diseasesCOVID-19Incidence rateInterrupted time series analysis

Identifiers

PMID37316780
PMCPMC10266306
OpenAlexW4380685942

What OpenQuestion holds

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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.