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Clustering of SARS-CoV-2 in Households in New York City: A Building-Level Analysis, March-December 2020.
Gulley, Catherine; Kepler, Kelsey L; Ngai, Stephanie; Waechter, HaeNa; Fitzhenry, Robert; Thompson, Corinne N; Fine, Anne; Reddy, Vasudha.
  • Gulley C; New York City Department of Health and Mental Hygiene, Queens, New York. Ms Gulley is now with JBS International, Rockville, Maryland.
J Public Health Manag Pract ; 29(4): 587-595, 2023.
Article in English | MEDLINE | ID: covidwho-2261524
ABSTRACT

OBJECTIVES:

To identify the proportion of coronavirus disease 2019 (COVID-19) cases that occurred within households or buildings in New York City (NYC) beginning in March 2020 during the first stay-at-home order to determine transmission attributable to these settings and inform targeted prevention strategies.

DESIGN:

The residential addresses of cases were geocoded (converting descriptive addresses to latitude and longitude coordinates) and used to identify clusters of cases residing in unique buildings based on building identification number (BIN), a unique building identifier. Household clusters were defined as 2 or more cases within 2 weeks of onset or diagnosis date in the same BIN with the same unit number, last name, or in a single-family home. Building clusters were defined as 3 or more cases with onset date or diagnosis date within 2 weeks in the same BIN who do not reside in the same household.

SETTING:

NYC from March to December 2020.

PARTICIPANTS:

NYC residents with a positive SARS-CoV-2 nucleic acid amplification or antigen test result with a specimen collected during March 1, 2020, to December 31, 2020. MAIN OUTCOME

MEASURE:

The proportion of NYC COVID-19 cases in a household or building cluster.

RESULTS:

The BIN analysis identified 65 343 building and household clusters 17 139 (26%) building clusters and 48 204 (74%) household clusters. A substantial proportion of NYC COVID-19 cases (43%) were potentially attributable to household transmission in the first 9 months of the pandemic.

CONCLUSIONS:

Geocoded address matching assisted in identifying COVID-19 household clusters. Close contact transmission within a household or building cluster was found in 43% of noncongregate cases with a valid residential NYC address. The BIN analysis should be utilized to identify disease clustering for improved surveillance.
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 Type of study: Observational study / Prognostic study Limits: Humans Country/Region as subject: North America Language: English Journal: J Public Health Manag Pract Journal subject: Public Health / Health Services Year: 2023 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 Type of study: Observational study / Prognostic study Limits: Humans Country/Region as subject: North America Language: English Journal: J Public Health Manag Pract Journal subject: Public Health / Health Services Year: 2023 Document Type: Article