Back

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

Dorelien, A. M.; Venkateswaran, N.; Deng, J.; Searle, K.; Enns, E.; Kulasingam, S.

2021-07-15 epidemiology
10.1101/2021.07.12.21260216 medRxiv
Show 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.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

1
Epidemics
104 papers in training set
Top 0.1%
22.5%
2
PLOS ONE
4510 papers in training set
Top 13%
14.4%
3
Scientific Reports
3102 papers in training set
Top 7%
10.1%
4
BMC Public Health
147 papers in training set
Top 0.6%
6.4%
50% of probability mass above
5
American Journal of Epidemiology
57 papers in training set
Top 0.1%
6.3%
6
Clinical Infectious Diseases
231 papers in training set
Top 1%
3.6%
7
Annals of Epidemiology
19 papers in training set
Top 0.1%
2.7%
8
Emerging Infectious Diseases
103 papers in training set
Top 0.8%
2.6%
9
eLife
5422 papers in training set
Top 43%
1.7%
10
International Journal of Environmental Research and Public Health
124 papers in training set
Top 4%
1.7%
11
BMC Infectious Diseases
118 papers in training set
Top 3%
1.5%
12
Science
429 papers in training set
Top 16%
1.3%
13
Frontiers in Public Health
140 papers in training set
Top 6%
1.2%
14
JAIDS Journal of Acquired Immune Deficiency Syndromes
19 papers in training set
Top 0.3%
1.2%
15
PNAS Nexus
147 papers in training set
Top 0.8%
1.1%
16
mSphere
281 papers in training set
Top 5%
0.9%
17
Proceedings of the National Academy of Sciences
2130 papers in training set
Top 41%
0.9%
18
Influenza and Other Respiratory Viruses
44 papers in training set
Top 0.3%
0.9%
19
The Lancet Public Health
20 papers in training set
Top 0.5%
0.9%
20
Science Advances
1098 papers in training set
Top 30%
0.7%
21
JMIR Public Health and Surveillance
45 papers in training set
Top 4%
0.7%
22
Epidemiology
26 papers in training set
Top 0.6%
0.7%
23
Nature Communications
4913 papers in training set
Top 64%
0.7%
24
PLOS Medicine
98 papers in training set
Top 5%
0.7%
25
Epidemiology and Infection
84 papers in training set
Top 4%
0.6%
26
Disaster Medicine and Public Health Preparedness
16 papers in training set
Top 2%
0.6%
27
Eurosurveillance
80 papers in training set
Top 2%
0.6%
28
Journal of The Royal Society Interface
189 papers in training set
Top 5%
0.6%