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1.
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)
COVID-19 , SARS-CoV-2 , Humans , COVID-19/epidemiology , New York City/epidemiology , Family Characteristics , Cluster Analysis
2.
Sci Adv ; 8(4): eabm0300, 2022 Jan 28.
Article in English | MEDLINE | ID: covidwho-2287593

ABSTRACT

To characterize the epidemiological properties of the B.1.526 SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) variant of interest, here we used nine epidemiological and population datasets and model-inference methods to reconstruct SARS-CoV-2 transmission dynamics in New York City, where B.1.526 emerged. We estimated that B.1.526 had a moderate increase (15 to 25%) in transmissibility, could escape immunity in 0 to 10% of previously infected individuals, and substantially increased the infection fatality risk (IFR) among adults 65 or older by >60% during November 2020 to April 2021, compared to estimates for preexisting variants. Overall, findings suggest that new variants like B.1.526 likely spread in the population weeks before detection and that partial immune escape (e.g., resistance to therapeutic antibodies) could offset prior medical advances and increase IFR. Early preparedness for and close monitoring of SARS-CoV-2 variants, their epidemiological characteristics, and disease severity are thus crucial to COVID-19 (coronavirus disease 2019) response.

3.
Ann Epidemiol ; 63: 46-51, 2021 11.
Article in English | MEDLINE | ID: covidwho-1351545

ABSTRACT

PURPOSE: To examine neighborhood-level disparities in SARS-CoV-2 molecular test percent positivity in New York City (NYC) by demographics and socioeconomic status over time to better understand COVID-19 inequities. METHODS: Across 177 neighborhoods, we calculated the Spearman correlation of neighborhood characteristics with SARS-CoV-2 molecular test percent positivity during March 1-July 25, 2020 by five periods defined by trend in case counts: increasing, declining, and three plateau periods to account for differential testing capacity and reopening status. RESULTS: Percent positivity was positively correlated with neighborhood racial and ethnic characteristics and socioeconomic status, including the proportion of the population who were Latino and Black non-Latino, uninsured, Medicaid enrollees, transportation workers, or had low educational attainment. Correlations were generally consistent over time despite increasing testing rates. Neighborhoods with high proportions of these correlates had median percent positivity values of 62.6%, 28.7%, 6.4%, 2.8%, and 2.2% in the five periods, respectively, compared with 40.6%, 11.7%, 1.7%, 0.9%, and 1.0% in neighborhoods with low proportions of these correlates. CONCLUSIONS: Disparities in SARS-CoV-2 molecular test percent positivity persisted in disadvantaged neighborhoods during multiple phases of the first few months of the COVID-19 epidemic in NYC. Mitigation of the COVID-19 burden is still urgently needed in disproportionately affected communities.


Subject(s)
COVID-19 , SARS-CoV-2 , Hispanic or Latino , Humans , New York City/epidemiology , Residence Characteristics , Socioeconomic Factors
4.
MMWR Morb Mortal Wkly Rep ; 70(19): 712-716, 2021 May 14.
Article in English | MEDLINE | ID: covidwho-1227231

ABSTRACT

Recent studies have documented the emergence and rapid growth of B.1.526, a novel variant of interest (VOI) of SARS-CoV-2, the virus that causes COVID-19, in the New York City (NYC) area after its identification in NYC in November 2020 (1-3). Two predominant subclades within the B.1.526 lineage have been identified, one containing the E484K mutation in the receptor-binding domain (1,2), which attenuates in vitro neutralization by multiple SARS-CoV-2 antibodies and is present in variants of concern (VOCs) first identified in South Africa (B.1.351) (4) and Brazil (P.1).* The NYC Department of Health and Mental Hygiene (DOHMH) analyzed laboratory and epidemiologic data to characterize cases of B.1.526 infection, including illness severity, transmission to close contacts, rates of possible reinfection, and laboratory-diagnosed breakthrough infections among vaccinated persons. Preliminary data suggest that the B.1.526 variant does not lead to more severe disease and is not associated with increased risk for infection after vaccination (breakthrough infection) or reinfection. Because relatively few specimens were sequenced over the study period, the statistical power might have been insufficient to detect modest differences in rates of uncommon outcomes such as breakthrough infection or reinfection. Collection of timely viral genomic data for a larger proportion of citywide cases and rapid integration with population-based surveillance data would enable improved understanding of the impact of emerging SARS-CoV-2 variants and specific mutations to help guide public health intervention efforts.


Subject(s)
COVID-19/epidemiology , COVID-19/virology , SARS-CoV-2/genetics , Adolescent , Adult , Aged , COVID-19 Nucleic Acid Testing , Child , Child, Preschool , Female , Humans , Infant , Infant, Newborn , Male , Middle Aged , New York City/epidemiology , Young Adult
5.
Lancet Infect Dis ; 21(2): 203-212, 2021 02.
Article in English | MEDLINE | ID: covidwho-1137671

ABSTRACT

BACKGROUND: As the COVID-19 pandemic continues to unfold, the infection-fatality risk (ie, risk of death among all infected individuals including those with asymptomatic and mild infections) is crucial for gauging the burden of death due to COVID-19 in the coming months or years. Here, we estimate the infection-fatality risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in New York City, NY, USA, the first epidemic centre in the USA, where the infection-fatality risk remains unclear. METHODS: In this model-based analysis, we developed a meta-population network model-inference system to estimate the underlying SARS-CoV-2 infection rate in New York City during the 2020 spring pandemic wave using available case, mortality, and mobility data. Based on these estimates, we further estimated the infection-fatality risk for all ages overall and for five age groups (<25, 25-44, 45-64, 65-74, and ≥75 years) separately, during the period March 1 to June 6, 2020 (ie, before the city began a phased reopening). FINDINGS: During the period March 1 to June 6, 2020, 205 639 people had a laboratory-confirmed infection with SARS-CoV-2 and 21 447 confirmed and probable COVID-19-related deaths occurred among residents of New York City. We estimated an overall infection-fatality risk of 1·39% (95% credible interval 1·04-1·77) in New York City. Our estimated infection-fatality risk for the two oldest age groups (65-74 and ≥75 years) was much higher than the younger age groups, with a cumulative estimated infection-fatality risk of 0·116% (0·0729-0·148) for those aged 25-44 years and 0·939% (0·729-1·19) for those aged 45-64 years versus 4·87% (3·37-6·89) for those aged 65-74 years and 14·2% (10·2-18·1) for those aged 75 years and older. In particular, weekly infection-fatality risk was estimated to be as high as 6·72% (5·52-8·01) for those aged 65-74 years and 19·1% (14·7-21·9) for those aged 75 years and older. INTERPRETATION: Our results are based on more complete ascertainment of COVID-19-related deaths in New York City than other places and thus probably reflect the true higher burden of death due to COVID-19 than that previously reported elsewhere. Given the high infection-fatality risk of SARS-CoV-2, governments must account for and closely monitor the infection rate and population health outcomes and enact prompt public health responses accordingly as the COVID-19 pandemic unfolds. FUNDING: National Institute of Allergy and Infectious Diseases, National Science Foundation Rapid Response Research Program, and New York City Department of Health and Mental Hygiene.


Subject(s)
COVID-19/mortality , Pandemics , SARS-CoV-2 , Adolescent , Adult , Aged , Algorithms , COVID-19/epidemiology , COVID-19/transmission , COVID-19/virology , Child , Child, Preschool , Humans , Infant , Infant, Newborn , Male , Middle Aged , Models, Theoretical , Mortality , New York City/epidemiology , Public Health Surveillance , Young Adult
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