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. 2024 May 9;43(1):58.
doi: 10.1186/s41043-024-00555-x.

Social contacts patterns relevant to the transmission of infectious diseases in Suzhou, China following the COVID-19 epidemic

Mengru Wang #  1 , Congju Wang #  2 , Guoping Gui  2 , Feng Guo  2 , Risheng Zha  2 , Hongpeng Sun  3
Affiliations

Social contacts patterns relevant to the transmission of infectious diseases in Suzhou, China following the COVID-19 epidemic

Mengru Wang et al. J Health Popul Nutr. .

Abstract

Background: The COVID-19 pandemic has profoundly affected human social contact patterns, but there is limited understanding regarding the post-pandemic social contact patterns. Our objective is to quantitatively assess social contact patterns in Suzhou post-COVID-19.

Methods: We employed a diary design and conducted social contact surveys from June to October 2023, utilizing paper questionnaires. A generalized linear model was utilized to analyze the relationship between individual contacts and covariates. We examined the proportions of contact type, location, duration, and frequency. Additionally, age-related mixed matrices were established.

Results: The participants reported an average of 11.51 (SD 5.96) contact numbers and a total of 19.78 (SD 20.94) contact numbers per day, respectively. The number of contacts was significantly associated with age, household size, and the type of week. Compared to the 0-9 age group, those in the 10-19 age group reported a higher number of contacts (IRR = 1.12, CI: 1.01-1.24), while participants aged 20 and older reported fewer (IRR range: 0.54-0.67). Larger households (5 or more) reported more contacts (IRR = 1.09, CI: 1.01-1.18) and fewer contacts were reported on weekends (IRR = 0.95, CI: 0.90-0.99). School had the highest proportion of contact durations exceeding 4 h (49.5%) and daily frequencies (90.4%), followed by home and workplace. The contact patterns exhibited clear age-assortative mixing, with Q indices of 0.27 and 0.28.

Conclusions: We assessed the characteristics of social contact patterns in Suzhou, which are essential for parameterizing models of infectious disease transmission. The high frequency and intensity of contacts among school-aged children should be given special attention, making school intervention policies a crucial component in controlling infectious disease transmission.

Keywords: Age-structured contact matrices; Contact pattern; Post-COVID-19 era.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Distribution of the number of reported contacts and total contacts. (A, B) Correspond to the number of reported contacts; (C, D) Correspond to the total number of reported contacts
Fig. 2
Fig. 2
The relationship between contact type, location, duration and frequency. The proportion of contacts that were physical or non-physical by (A) location, (B) duration and (C) frequency of contacts. The proportion between (D) location and frequency, (E) location and duration, and (F) duration and frequency of contacts
Fig. 3
Fig. 3
Contact matrix of reported contacts consisting of average number of contacts per day per participant. (A) Original contact matrice; (B) Symmetrized contact matrice. The symmetrized contact matrices are calculated using formula image
See this image and copyright information in PMC

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