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About

This dashboard shows results from Wave 1 of the Berkeley Interpersonal Contact Study (BICS) in Spring 2020.

Caveats / underway:

  • the estimates have been weighted to improve sample representativeness. Weights are based on age, sex, race/ethnicity, household size, and urbanicity

  • see the ‘Contact definition’ tab for some important notes on how we define contacts

  • these results are from Wave 1; the dashboard previously showed results from the pilot Wave 0 (the previous dashboard is here

  • a comparison to Wave 0 results is coming soon; the instrument changed in some ways, and so a careful comparison will take some time

If you have questions or are interested in funding this study, please contact us at .

This project has been approved by the UC Berkeley IRB (Protocols 2020-03-13128 and 2020-04-13215). Initial support provided by a Berkeley Population Center pilot grant (NICHD P2CHD073964).

Updates

Wave 1 results updated 2020-05-20

2020-05-20:

  • Updated mixing matrix to add symmetrization

2020-05-07:

  • Updated dashboard to show most recent results from Wave 1. The first set of results, Wave 0, can be found in the previous dashboard

2020-04-20:

  • Most plots are now weighted to improve sample representativeness using raking. (These weights have made little difference to the previous estimates)

2020-04-17:

Column

Number of conversational contacts

Number of conversational contacts

Number of conversational contacts outside the household

Conversational contacts by age

Conversational contacts outside household by age

Mixing

NB: please see the ‘data’ tab if you want the numbers behind these mixing estimates

By age/sex - non hh contacts

The matrix calculated below uses the symmetrization formula found in the vignette for the socialmixr package.
(We calculate it by hand, since the package was not designed for data collected using our instrument.) We used the 2018 American Community Survey to obtain the national age-distribution.

Relationships - non-hh contacts

Locations - non-hh contacts

Contact durations - by relationship, non-hh contacts

Contact durations - by respondent age, non-hh contacts

COVID-19

Awareness

Concern

Behavior change

Respondent characteristics

Weights

The pooled estimates have been weighted using raking to improve sample representativeness. Weights are based on

  • Age
  • Sex
  • Age/sex interaction
  • Race (Black, White, Other)
  • Hispanic status
  • Household size (1/2/3/4/5+)
  • Urbanicity

Population values are taken from the 2018 ACS, estimated from an IPUMS USA extract. We used the R packages ipumsr, leafpeepr and autumn to help perform the raking.

Number of interviews by date

Age/sex

Race/ethnicity

Household size

Contact definition

We analyze two types of contacts: total contacts and non-household contacts.

We ask respondents to provide the age and gender of everyone in her household. We assume that a respondent had contact with everyone in her household; thus, total contacts is the sum of non-household contacts and household members.

For non-household contacts, respondents to the survey were told to consider someone a contact using this text:

We would like to ask you some questions about people you had in-person conversational contact with yesterday.

By in-person conversational contact, we mean a two-way conversation with three or more words in the physical presence of another person.

You might have conversational contact with family members, friends, co-workers, store clerks, bus drivers, and so forth.

(Please do not count people you contacted exclusively by telephone, text, or online. Only consider people you interacted with face-to-face.)

Using this definition, respondents were asked how many people who do not live in their households they had contact with on the day before the survey.

 

Data

Microdata

We plan to make a version of the data with no identifying information publicly available as soon as we can. If you are a disease modeler who urgently needs to see the microdata, please reach out to us by email.

The estimated mixing matrices are reproduced as tables below. Note that these are the crude estimates, and have not had a symmetry constraint enforced.

Non-hh contact mixing estimates

ego_age alter_age weighted_n raw_n num_interviews weighted_num_interviews ego_acs_N alter_acs_N unadj_avg_per_ego
[18,25) [0,18) 103.495964 59 346 338.9917 30.64812 NA 0.3053053
[18,25) [18,25) 504.163825 115 346 338.9917 30.64812 30.64812 1.4872452
[18,25) [25,35) 199.184302 56 346 338.9917 30.64812 45.27702 0.5875787
[18,25) [35,45) 128.714485 24 346 338.9917 30.64812 41.68729 0.3796980
[18,25) [45,55) 67.630782 27 346 338.9917 30.64812 41.59234 0.1995057
[18,25) [55,65) 5.811184 14 346 338.9917 30.64812 42.28218 0.0171426
[18,25) [65,100] 138.593498 12 346 338.9917 30.64812 52.40755 0.4088404
[25,35) [0,18) 108.686890 74 471 446.9116 45.27702 NA 0.2431955
[25,35) [18,25) 76.862824 69 471 446.9116 45.27702 30.64812 0.1719866
[25,35) [25,35) 459.441062 207 471 446.9116 45.27702 45.27702 1.0280356
[25,35) [35,45) 122.354911 80 471 446.9116 45.27702 41.68729 0.2737788
[25,35) [45,55) 71.957376 55 471 446.9116 45.27702 41.59234 0.1610103
[25,35) [55,65) 55.147666 37 471 446.9116 45.27702 42.28218 0.1233973
[25,35) [65,100] 26.977919 28 471 446.9116 45.27702 52.40755 0.0603652
[35,45) [0,18) 160.757386 116 557 439.7286 41.68729 NA 0.3655832
[35,45) [18,25) 110.860701 47 557 439.7286 41.68729 30.64812 0.2521116
[35,45) [25,35) 264.457715 173 557 439.7286 41.68729 45.27702 0.6014112
[35,45) [35,45) 578.402703 262 557 439.7286 41.68729 41.68729 1.3153629
[35,45) [45,55) 59.527055 53 557 439.7286 41.68729 41.59234 0.1353723
[35,45) [55,65) 78.751121 39 557 439.7286 41.68729 42.28218 0.1790903
[35,45) [65,100] 24.931269 28 557 439.7286 41.68729 52.40755 0.0566969
[45,55) [0,18) 119.733935 54 442 410.7716 41.59234 NA 0.2914854
[45,55) [18,25) 28.478275 23 442 410.7716 41.59234 30.64812 0.0693287
[45,55) [25,35) 112.330049 83 442 410.7716 41.59234 45.27702 0.2734611
[45,55) [35,45) 173.477957 98 442 410.7716 41.59234 41.68729 0.4223222
[45,55) [45,55) 233.006605 122 442 410.7716 41.59234 41.59234 0.5672412
[45,55) [55,65) 69.539094 49 442 410.7716 41.59234 42.28218 0.1692889
[45,55) [65,100] 62.286875 46 442 410.7716 41.59234 52.40755 0.1516338
[55,65) [0,18) 60.399464 30 421 463.4103 42.28218 NA 0.1303369
[55,65) [18,25) 37.201584 31 421 463.4103 42.28218 30.64812 0.0802779
[55,65) [25,35) 204.945243 96 421 463.4103 42.28218 45.27702 0.4422544
[55,65) [35,45) 212.242349 77 421 463.4103 42.28218 41.68729 0.4580009
[55,65) [45,55) 250.749405 77 421 463.4103 42.28218 41.59234 0.5410959
[55,65) [55,65) 100.761223 76 421 463.4103 42.28218 42.28218 0.2174342
[55,65) [65,100] 101.909932 60 421 463.4103 42.28218 52.40755 0.2199130
[65,100] [0,18) 26.165494 20 394 531.1861 52.40755 NA 0.0492586
[65,100] [18,25) 23.641320 25 394 531.1861 52.40755 30.64812 0.0445067
[65,100] [25,35) 96.356465 62 394 531.1861 52.40755 45.27702 0.1813987
[65,100] [35,45) 147.293389 71 394 531.1861 52.40755 41.68729 0.2772915
[65,100] [45,55) 180.725264 60 394 531.1861 52.40755 41.59234 0.3402296
[65,100] [55,65) 71.803476 34 394 531.1861 52.40755 42.28218 0.1351757
[65,100] [65,100] 240.920099 79 394 531.1861 52.40755 52.40755 0.4535512