Evidence map›Paper›PMID 39304902›Full record

ArticleVirology journal2024

Respiratory pathogen dynamics in community fever cases: Jiangsu Province, China (2023-2024).

Fei Deng, Zhuhan Dong, Tian Qiu, Ke Xu, Qigang Dai, Huiyan Yu, Huan Fan, Haifeng Qian, Changjun Bao, Wei Gao and 1 more

Abstract read
In one paragraph

Article in Virology journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
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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

11 authors.

Fei Deng *Department of Acute Infectious Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China.
Zhuhan Dong *Nanjing Medical University, Nanjing, China.
Tian QiuXuanwu District Center for Disease Control and Prevention, Nanjing, China.
Ke XuDepartment of Acute Infectious Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China.
Qigang DaiDepartment of Acute Infectious Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China.
Huiyan YuDepartment of Acute Infectious Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China.
Huan FanDepartment of Acute Infectious Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China.
Haifeng QianXuanwu District Center for Disease Control and Prevention, Nanjing, China.
Changjun BaoDepartment of Acute Infectious Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China.
Wei GaoXuanwu District Center for Disease Control and Prevention, Nanjing, China.
Liguo ZhuNanjing Medical University, Nanjing, China. zhuliguo2002@163.com.

Funding

National Key Research and Development Program of China 2023YFC2605100, 2023YFC2605102
6 · The paper itself

Abstract

backgroundRespiratory infectious diseases have the highest incidence among infectious diseases worldwide. Currently, global monitoring of respiratory pathogens primarily focuses on influenza and coronaviruses. This study included influenza and other common respiratory pathogens to establish a local respiratory pathogen spectrum. We investigated and analyzed the co-infection patterns of these pathogens and explored the impact of lifting non-pharmaceutical interventions (NPIs) on the transmission of influenza and other respiratory pathogens. Additionally, we used a predictive model for infectious diseases, utilizing the commonly used An autoregressive comprehensive moving average model (ARIMA), which can effectively forecast disease incidence.

methodsFrom June 2023 to February 2024, we collected influenza-like illness (ILI) cases weekly from the community in Xuanwu District, Nanjing, and obtained 2046 samples. We established a spectrum of respiratory pathogens in Nanjing and analysed the age distribution and clinical symptom distribution of various pathogens. We compared age, gender, symptom counts, and viral loads between individuals with co-infections and those with single infections. An autoregressive comprehensive moving average model (ARIMA) was constructed to predict the incidence of respiratory infectious diseases.

resultsAmong 2046 samples, the total detection rate of respiratory pathogen nucleic acids was 53.37% (1092/2046), with influenza A virus 479 cases (23.41%), influenza B virus 224 cases (10.95%), and HCoV 95 cases (4.64%) being predominant. Some pathogens were statistically significant in age and number of symptoms. The positive rate of mixed infections was 6.11% (125/2046). There was no significant difference in age or number of symptoms between co-infection and simple infection. After multiple iterative analyses, an ARIMA model (0,1,4), (0,0,0) was established as the optimal model, with an R

conclusionsThe spectrum of respiratory pathogens in Nanjing, Jiangsu Province, was complex in the past. The primary age groups of different viruses were different, causing various symptoms, and the co-infection of viruses did not correlate with the age and gender of patients. The ARIMA model estimated future incidence, which plateaued in subsequent months.

Indexed as

CoinfectionRespiratory Tract InfectionsAdolescentAdultAgedAged, 80 and overChildChild, PreschoolChinaFemaleFeverHumansIncidenceInfantInfant, NewbornInfluenza, HumanAcute respiratory tract infectionARIMA modelBacteriaPathogen spectrumVirus

Identifiers

PMID39304902
PMCPMC11414227

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.