Evidence map›Paper›PMID 42523775›Full record

ArticleFrontiers in public health2026

Social contact patterns and associated factors survey of Shangrao City.

Juan Liu, Wenli Li, Hongfeng Zhao, Yufang Zhao, Xiaomin Zhan, Yanhua Su, Yao Liu, Peng Xu

Abstract read
In one paragraph

Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Juan Liu *Department of Infectious Disease Control, Shangrao Center for Disease Control and Prevention, Shangrao, Jiangxi, China.
Wenli Li *School of Public Health, Xiamen University, Xiamen, Fujian, China.
Hongfeng ZhaoSchool of Public Health, Xiamen University, Xiamen, Fujian, China.
Yufang ZhaoJiangxi Medical College, Shangrao, Jiangxi, China.
Xiaomin ZhanDepartment of Infectious Disease Control, Wuyuan County Center for Disease Control and Prevention, Shangrao, Jiangxi, China.
Yanhua SuSchool of Public Health, Xiamen University, Xiamen, Fujian, China.
Yao LiuDepartment of Infectious Disease Control, Shangrao Center for Disease Control and Prevention, Shangrao, Jiangxi, China.
Peng XuDepartment of Infectious Disease Control, Shangrao Center for Disease Control and Prevention, Shangrao, Jiangxi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aimed to quantitatively analyze social contact patterns among residents of Shangrao City, Jiangxi Province, and to examine their variations across different demographic groups. The findings are intended to provide empirical data for developing localized transmission dynamic models of respiratory infectious diseases and for formulating targeted prevention and control strategies. Methods: A cross-sectional online survey was conducted among Shangrao residents from April to September 2025, and 2,101 valid questionnaires were analyzed. Daily total, household, and non-household contacts were described by demographic groups. Factors associated with daily total contacts were examined using negative binomial regression, with results reported as incidence rate ratios (IRRs) and 95% confidence intervals. Post-stratification weighting based on the 2020 Seventh National Population Census of Shangrao was performed as a sensitivity analysis. Results: The mean daily number of contacts was 7.91, including 2.73 household and 5.19 non-household contacts. Adolescents aged 5-19 years had the highest mean daily total contacts (9.99). In the negative binomial regression, the 5-19 years group had more contacts than the 20-29 years reference group (IRR 1.74, Conclusion: Social contact patterns in Shangrao City are dominated by age, with adolescents (5-19 years) and highly mobile populations exhibiting the highest contact frequencies. These conclusions were robust to post-stratification weighting against the 2020 Seventh National Population Census of Shangrao. The study addresses the absence of empirical social contact data in a Chinese prefecture-level city and provides directly applicable evidence for localized epidemic risk assessment and early-warning modelling of respiratory infectious diseases.

Indexed as

Social NetworkingAdolescentAdultChildChild, PreschoolChinaCross-Sectional StudiesFemaleHumansMaleMiddle AgedSocial GroupSurveys and QuestionnairesYoung Adultage heterogeneitycross-sectional surveyinfectious disease transmissionrespiratory infectious diseasessocial contact patterns

Identifiers

PMID42523775
PMCPMC13407773

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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.