COVID-19 Case Investigation and Contact Tracing in New York City, June 1, 2020, to October 31, 2021.

Importance: Contact tracing is a core strategy for preventing the spread of many infectious diseases of public health concern. Better understanding of the outcomes of contact tracing for COVID-19 as well as the operational opportunities and challenges in establishing a program for a jurisdiction as large as New York City (NYC) is important for the evaluation of this strategy. Objective: To describe the establishment, scaling, and maintenance of Trace, NYC's contact tracing program, and share data on outcomes during its first 17 months. Design, Setting, and Participants: This cross-sectional study included people with laboratory test-confirmed and probable COVID-19 and their contacts in NYC between June 1, 2020, and October 31, 2021. Trace launched on June 1, 2020, and had a workforce of 4147 contact tracers, with the majority of the workforce performing their jobs completely remotely. Data were analyzed in March 2022. Main Outcomes and Measures: Number and proportion of persons with COVID-19 and contacts on whom investigations were attempted and completed; timeliness of interviews relative to symptom onset or exposure for symptomatic cases and contacts, respectively. Results: Case investigations were attempted for 941 035 persons. Of those, 840 922 (89.4%) were reached and 711 353 (75.6%) completed an intake interview (women and girls, 358 775 [50.4%]; 60 178 [8.5%] Asian, 110 636 [15.6%] Black, 210 489 [28.3%] Hispanic or Latino, 157 349 [22.1%] White). Interviews were attempted for 1 218 650 contacts. Of those, 904 927 (74.3%) were reached, and 590 333 (48.4%) completed intake (women and girls, 219 261 [37.2%]; 47 403 [8.0%] Asian, 98 916 [16.8%] Black, 177 600 [30.1%] Hispanic or Latino, 116 559 [19.7%] White). Completion rates were consistent over time and resistant to changes related to vaccination as well as isolation and quarantine guidance. Among symptomatic cases, median time from symptom onset to intake completion was 4.7 days; a median 1.4 contacts were identified per case. Median time from contacts' last date of exposure to intake completion was 2.3 days. Among contacts, 30.1% were tested within 14 days of notification. Among cases, 27.8% were known to Trace as contacts. The overall expense for Trace from May 6, 2020, through October 31, 2021, was approximately $600 million. Conclusions and Relevance: Despite the complexity of developing a contact tracing program in a diverse city with a population of over 8 million people, in this case study we were able to identify 1.4 contacts per case and offer resources to safely isolate and quarantine to over 1 million cases and contacts in this study period.

Built by epidemiologists for epidemiologists: an internal COVID-19 dashboard for real-time situational awareness in New York City.

Objective: New York City (NYC) experienced a large first wave of coronavirus disease 2019 (COVID-19) in the spring of 2020, but the Health Department lacked tools to easily visualize and analyze incoming surveillance data to inform response activities. To streamline ongoing surveillance, a group of infectious disease epidemiologists built an interactive dashboard using open-source software to monitor demographic, spatial, and temporal trends in COVID-19 epidemiology in NYC in near real-time for internal use by other surveillance and epidemiology experts. Materials and methods: Existing surveillance databases and systems were leveraged to create daily analytic datasets of COVID-19 case and testing information, aggregated by week and key demographics. The dashboard was developed iteratively using R, and includes interactive graphs, tables, and maps summarizing recent COVID-19 epidemiologic trends. Additional data and interactive features were incorporated to provide further information on the spread of COVID-19 in NYC. Results: The dashboard allows key staff to quickly review situational data, identify concerning trends, and easily maintain granular situational awareness of COVID-19 epidemiology in NYC. Discussion: The dashboard is used to inform weekly surveillance summaries and alleviated the burden of manual report production on infectious disease epidemiologists. The system was built by and for epidemiologists, which is critical to its utility and functionality. Interactivity allows users to understand broad and granular data, and flexibility in dashboard development means new metrics and visualizations can be developed as needed. Conclusions: Additional investment and development of public health informatics tools, along with standardized frameworks for local health jurisdictions to analyze and visualize data in emergencies, are warranted.

Shigellosis Cases With Bacterial Sexually Transmitted Infections: Population-Based Data From 6 US Jurisdictions, 2007 to 2016.

BACKGROUND: Shigella species, which cause acute diarrheal disease, are transmitted via fecal-oral and sexual contact. To better understand the overlapping populations affected by Shigella infections and sexually transmitted infections (STIs) in the United States, we examined the occurrence of reported STIs within 24 months among shigellosis case-patients. METHODS: Culture-confirmed Shigella cases diagnosed from 2007 to 2016 among residents of 6 US jurisdictions were matched to reports of STIs (chlamydia, gonorrhea, and all stages of syphilis) diagnosed 12 months before or after the shigellosis case. We examined epidemiologic characteristics and reported temporal trends of Shigella cases by sex and species. RESULTS: From 2007 to 2016, 10,430 shigellosis cases were reported. The annual number of reported shigellosis cases across jurisdictions increased 70%, from 821 cases in 2007 to 1398 cases in 2016; males saw a larger increase compared with females. Twenty percent of male shigellosis case-patients had an STI reported in the reference period versus 4% of female case-patients. The percentage of male shigellosis case-patients with an STI increased from 11% (2007) to 28% (2016); the overall percentage among females remained low. CONCLUSIONS: We highlight the substantial proportion of males with shigellosis who were diagnosed with STIs within 24 months and the benefit of matching data across programs. Sexually transmitted infection screening may be warranted for male shigellosis case-patients.

Reduced COVID-19 hospitalizations among New York City residents following age-based SARS-CoV-2 vaccine eligibility: Evidence from a regression discontinuity design.

BACKGROUND: In clinical trials, several SARS-CoV-2 vaccines were shown to reduce risk of severe COVID-19 illness. Local, population-level, real-world evidence of vaccine effectiveness is accumulating. We assessed vaccine effectiveness for community-dwelling New York City (NYC) residents using a quasi-experimental, regression discontinuity design, leveraging a period (January 12-March 9, 2021) when ≥ 65-year-olds were vaccine-eligible but younger persons, excluding essential workers, were not. METHODS: We constructed segmented, negative binomial regression models of age-specific COVID-19 hospitalization rates among 45-84-year-old NYC residents during a post-vaccination program implementation period (February 21-April 17, 2021), with a discontinuity at age 65 years. The relationship between age and hospitalization rates in an unvaccinated population was incorporated using a pre-implementation period (December 20, 2020-February 13, 2021). We calculated the rate ratio (RR) and 95% confidence interval (CI) for the interaction between implementation period (pre or post) and age-based eligibility (45-64 or 65-84 years). Analyses were stratified by race/ethnicity and borough of residence. Similar analyses were conducted for COVID-19 deaths. RESULTS: Hospitalization rates among 65-84-year-olds decreased from pre- to post-implementation periods (RR 0.85, 95% CI: 0.74-0.97), controlling for trends among 45-64-year-olds. Accordingly, an estimated 721 (95% CI: 126-1,241) hospitalizations were averted. Residents just above the eligibility threshold (65-66-year-olds) had lower hospitalization rates than those below (63-64-year-olds). Racial/ethnic groups and boroughs with higher vaccine coverage generally experienced greater reductions in RR point estimates. Uncertainty was greater for the decrease in COVID-19 death rates (RR 0.85, 95% CI: 0.66-1.10). CONCLUSION: The vaccination program in NYC reduced COVID-19 hospitalizations among the initially age-eligible ≥ 65-year-old population by approximately 15% in the first eight weeks. The real-world evidence of vaccine effectiveness makes it more imperative to improve vaccine access and uptake to reduce inequities in COVID-19 outcomes.

Monitoring Incidence of COVID-19 Cases, Hospitalizations, and Deaths, by Vaccination Status - 13 U.S. Jurisdictions, April 4-July 17, 2021.

COVID-19 vaccine breakthrough infection surveillance helps monitor trends in disease incidence and severe outcomes in fully vaccinated persons, including the impact of the highly transmissible B.1.617.2 (Delta) variant of SARS-CoV-2, the virus that causes COVID-19. Reported COVID-19 cases, hospitalizations, and deaths occurring among persons aged ≥18 years during April 4-July 17, 2021, were analyzed by vaccination status across 13 U.S. jurisdictions that routinely linked case surveillance and immunization registry data. Averaged weekly, age-standardized incidence rate ratios (IRRs) for cases among persons who were not fully vaccinated compared with those among fully vaccinated persons decreased from 11.1 (95% confidence interval [CI] = 7.8-15.8) to 4.6 (95% CI = 2.5-8.5) between two periods when prevalence of the Delta variant was lower (<50% of sequenced isolates; April 4-June 19) and higher (≥50%; June 20-July 17), and IRRs for hospitalizations and deaths decreased between the same two periods, from 13.3 (95% CI = 11.3-15.6) to 10.4 (95% CI = 8.1-13.3) and from 16.6 (95% CI = 13.5-20.4) to 11.3 (95% CI = 9.1-13.9). Findings were consistent with a potential decline in vaccine protection against confirmed SARS-CoV-2 infection and continued strong protection against COVID-19-associated hospitalization and death. Getting vaccinated protects against severe illness from COVID-19, including the Delta variant, and monitoring COVID-19 incidence by vaccination status might provide early signals of changes in vaccine-related protection that can be confirmed through well-controlled vaccine effectiveness (VE) studies.

Rapid Emergence and Epidemiologic Characteristics of the SARS-CoV-2 B.1.526 Variant - New York City, New York, January 1-April 5, 2021.

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.

COVID-19 Outbreak - New York City, February 29-June 1, 2020.

New York City (NYC) was an epicenter of the coronavirus disease 2019 (COVID-19) outbreak in the United States during spring 2020 (1). During March-May 2020, approximately 203,000 laboratory-confirmed COVID-19 cases were reported to the NYC Department of Health and Mental Hygiene (DOHMH). To obtain more complete data, DOHMH used supplementary information sources and relied on direct data importation and matching of patient identifiers for data on hospitalization status, the occurrence of death, race/ethnicity, and presence of underlying medical conditions. The highest rates of cases, hospitalizations, and deaths were concentrated in communities of color, high-poverty areas, and among persons aged ≥75 years or with underlying conditions. The crude fatality rate was 9.2% overall and 32.1% among hospitalized patients. Using these data to prevent additional infections among NYC residents during subsequent waves of the pandemic, particularly among those at highest risk for hospitalization and death, is critical. Mitigating COVID-19 transmission among vulnerable groups at high risk for hospitalization and death is an urgent priority. Similar to NYC, other jurisdictions might find the use of supplementary information sources valuable in their efforts to prevent COVID-19 infections.

Use of Capture-Recapture Analysis to Assess Reporting Completeness of Births to Hepatitis B-Positive Women in New York City, 2013-2014.

OBJECTIVES: The New York City (NYC) Department of Health and Mental Hygiene (DOHMH) depends on reporting by health care facilities and laboratories for disease surveillance. Our objective was to evaluate the completeness of DOHMH surveillance to identify births to hepatitis B virus (HBV)-positive women to prevent perinatal transmission. METHODS: We identified infants born to HBV-positive women by matching mothers of all infants born in NYC during May 1, 2013-May 1, 2014, identified from the Citywide Immunization Registry (CIR) to persons with HBV-positive laboratory reports in the Electronic Laboratory Reporting (ELR) system. We then matched infants born to mothers identified in the CIR/ELR match to infants born to HBV-positive women from the DOHMH perinatal HBV surveillance database. We performed capture-recapture analysis to evaluate completeness of DOHMH case identification. We compared the proportion of infants born to HBV-positive mothers reported to DOHMH with the proportion of infants identified only through the CIR/ELR match for receipt of postexposure prophylaxis (PEP) and completion of the HBV vaccination series and post-vaccination serology testing. RESULTS: Of 1662 infants identified from the CIR/ELR match and 1554 infants in the DOHMH database, 1493 infants matched. Of 169 infants only in the CIR/ELR data set, 55 were born to HBV-positive women residing in NYC. Sixty-one infants were only in the DOHMH database. An estimated 2 infants were not identified by either method. The CIR/ELR match increased infant identification by 3.5%, from 1554 to 1609 infants. The proportion of infants who received PEP was significantly higher among infants whose mothers were reported to DOHMH (vs not reported to DOHMH). PRACTICAL IMPLICATIONS: Use of the CIR/ELR match may further improve DOHMH identification of infants born to HBV-positive women and receipt of infant PEP.

Discovering foodborne illness in online restaurant reviews.

Objective: We developed a system for the discovery of foodborne illness mentioned in online Yelp restaurant reviews using text classification. The system is used by the New York City Department of Health and Mental Hygiene (DOHMH) to monitor Yelp for foodborne illness complaints. Materials and Methods: We built classifiers for 2 tasks: (1) determining if a review indicated a person experiencing foodborne illness and (2) determining if a review indicated multiple people experiencing foodborne illness. We first developed a prototype classifier in 2012 for both tasks using a small labeled dataset. Over years of system deployment, DOHMH epidemiologists labeled 13 526 reviews selected by this classifier. We used these biased data and a sample of complementary reviews in a principled bias-adjusted training scheme to develop significantly improved classifiers. Finally, we performed an error analysis of the best resulting classifiers. Results: We found that logistic regression trained with bias-adjusted augmented data performed best for both classification tasks, with F1-scores of 87% and 66% for tasks 1 and 2, respectively. Discussion: Our error analysis revealed that the inability of our models to account for long phrases caused the most errors. Our bias-adjusted training scheme illustrates how to improve a classification system iteratively by exploiting available biased labeled data. Conclusions: Our system has been instrumental in the identification of 10 outbreaks and 8523 complaints of foodborne illness associated with New York City restaurants since July 2012. Our evaluation has identified strong classifiers for both tasks, whose deployment will allow DOHMH epidemiologists to more effectively monitor Yelp for foodborne illness investigations.