Monitoring and understanding household clustering of SARS-CoV-2 cases using surveillance data in Fulton County, Georgia

  1. Carol Y. Liu
  2. Sasha Smith
  3. Allison T. Chamberlain
  4. Neel R. Gandhi
  5. Fazle Khan
  6. Steve Williams
  7. Sarita Shah

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

Background

Households are important for SARS-CoV-2 transmission due to high intensity exposure in enclosed living spaces over prolonged durations. Using contact tracing, the secondary attack rate in households is estimated at 18-20%, yet no studies have examined COVID-19 clustering within households to inform testing and prevention strategies. We sought to quantify and characterize household clustering of COVID-19 cases in Fulton County, Georgia and further explore age-specific patterns in household clusters.

Methods

We used state surveillance data to identify all PCR- or antigen-confirmed cases of COVID-19 in Fulton County, Georgia. Household clustered cases were defined as cases with matching residential address with positive sample collection dates within 28 days of one another. We described proportion of COVID-19 cases that were clustered, stratified by age and over time and explored trends in age of first diagnosed case within clusters and age patterns between first diagnosed case and subsequent household cases.

Results

Between 6/1/20–10/31/21, there were 106,233 COVID-19 cases with available address reported in Fulton County. Of these, 31,449 (37%) were from 12,955 household clusters. Children were more likely to be in household clusters than any other age group and children increasingly accounted for the first diagnosed household case, rising from 11% in February 2021 to a high of 31% in August 2021. Bubble plot density of age of first diagnosed case and subsequent household cases mirror age-specific patterns in household social mixing.

Discussion

One-third of COVID-19 cases in Fulton County were part of a household cluster. High proportion of children in household clusters reflects higher probability of living in larger homes with caregivers or other children. Increasing probability of children as the first diagnosed case coincide with temporal trends in vaccine roll-out among the elderly in March 2021 and the return to in-person schooling for the Fall 2021 semester. While vaccination remains the most effective intervention at reducing household clustering, other household-level interventions should also be emphasized such as timely testing for household members to prevent ongoing transmission.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2022.03.02.22271814: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    EthicsIRB: The Emory University institutional review board approved this activity with a waiver of informed consent.
    Consent: The Emory University institutional review board approved this activity with a waiver of informed consent.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    We report several limitations. Our analysis used surveillance data which is known to under-ascertain COVID-19 cases, especially during the early days of the pandemic46. Individuals with known household exposure may be more likely to present for testing if health conscious or less likely to present if they believe knowing their infection status will have little impact on treatment course and outcome. Changing testing and screening strategies may also affect age-related clustering trends. Moreover, Children 0-18 years were slightly more likely to be included compared to young adults aged 19-29 year and the elderly aged 70 years and above. Furthermore, we do not know if members within household clusters infected each other or whether some subsequent cases were infected from the community. The distribution of infections caused by household exposure versus community exposure has implications for disease control strategies. Finally, the first diagnosed case may not represent the source of infection for the household. The unique advantage of our study is that we use rigorous methods to identify cases from surveillance data residing at the same residential address, producing the first estimates of the extent of household clustering over time in a large, diverse metropolitan area. No other study has used public health surveillance data to systematically track temporal and demographic trends of household clusters of COVID-19 in the US. The use of routinely collected surveillance data p...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2022.03.02.22271814v1 on medRxiv