Quantifying social contact patterns in Minnesota during Stay-at-Home social distancing order

Abstract

SARS-CoV-2 is primarily transmitted through person-to-person contacts. It is important to collect information on age-specific contact patterns because SARS-CoV-2 susceptibility, transmission, and morbidity vary by age. To reduce risk of infection, social distancing measures have been implemented. Social contact data, which identify who has contact with whom especially by age and place are needed to identify high-risk groups and serve to inform the design of non-pharmaceutical interventions. We estimated and used negative binomial regression to compare the number of daily contacts during the first wave (April-May 2020) of the Minnesota Social Contact Study, based on respondents age, gender, race/ethnicity, region, and other demographic characteristics. We used information on age and location of contacts to generate age-structured contact matrices. Finally, we compared the age-structured contact matrices during the stay-at-home order to pre-pandemic matrices. During the state-wide stay-home order, the mean daily number of contacts was 5.6. We found significant variation in contacts by age, gender, race, and region. Adults between 40 and 50 years had the highest number of contacts. Respondents in Black households had 2.1 more contacts than respondent in White households, while respondents in Asian or Pacific Islander households had approximately the same number of contacts as respondent in White households. Respondents in Hispanic households had approximately two fewer contacts compared to White households. Most contacts were with other individuals in the same age group. Compared to the pre-pandemic period, the biggest declines occurred in contacts between children, and contacts between those over 60 with those below 60.

Characterizing US contact patterns relevant to respiratory transmission from a pandemic to baseline: Analysis of a large cross-sectional survey

“…This result also highlights the importance of high-resolution spatial data: there is high variability in contact within states that would be obscured if data are aggregated to the state level. We find that urban counties had fewer contacts on average during the pandemic; this is unsurprising given evidence that urban counties were more responsive to pandemic restrictions [25, 28, 30]. Under baseline conditions, however, we find that urban areas have more contacts on average than suburban or rural areas, which is consistent with behavioral heuristics based on population density.…”

“…Dorelien and colleagues’ [25] measured contact patterns in 2,083 children and adults in Minnesota, USA in April and May 2020. Contacts were defined as two-way conversations with 3+ words in the physical presence of another person or physical skin-to-skin contact.…”

“…On temporal variation in contact, one pre-pandemic study found no variation in adult contacts over time [24], while another observed changes from September to May [19]. Many studies find that contact is higher in younger adults, men, and non-white populations, although which race/ethnicity group has the highest contact depends on the study [19, 25–27]. Because these past studies are limited in sample size or resolution, they are constrained in their ability to comprehensively characterize heterogeneities in contact patterns across space, time, and social groups.…”

Dependence analysis of social contact behaviors under the impacts of COVID-19 based on a copula approach

“…However, following the definition for previous respiratory diseases ( Mossong et al, 2008 ; Hoang et al, 2019 ; Leung et al, 2017 ), many studies only focused on skin-to-skin touching and face-to-face conversation ( Fadilah and Arsinta, 2020 ; Latsuzbaia et al, 2020 ; Zhang et al, 2020a ; Trentini et al, 2022 ; Zhang et al, 2021b ). Other studies ( Brooks-Pollock et al, 2020 ; Dorélien et al, 2021 ; Wong et al, 2022 ; Tomori et al, 2021 ; McCarthy et al, 2020 ; Tizzani et al, 2022 ; Jarvis et al, 2020 ) mainly cite the definition given by the POLYMOD (Improving Public Health Policy in Europe through Modeling and Economic Evaluation of Interventions for the Control of Infectious Diseases) ( Akakzia et al, 2007 ; Mossong et al, 2008 ), which uses the mean number of contacted persons. However, the SARS-CoV-2 virus can travel more than six feet in aerosol form ( Ge et al, 2020 ), and infect people through their indirect contact with virus-infected surfaces ( Daraei et al, 2020 ; Cai et al, 2020 ; Zhang et al, 2020b ).…”

“…Age, education, ethnicity, household size, residential location, and gender were incorporated in the analysis. Dorélien et al (2021) used a negative binomial regression model to evaluate the number of social contacts from April to May 2020 in Minnesota, U.S.A., and included age, gender, race/ethnicity, region, and other demographic characteristics as explanatory variables. Using data collected in Milan, Italy between July 2020 and March 2021, Trentini et al (2022) also estimated a negative binomial regression model with the number of daily contacts, but under different levels of restrictions.…”