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.

A Comparison of Common Health Indicators From Two Surveys of Latinos in the Bronx, New York.

INTRODUCTION: Population health surveys inform and demonstrate the impact of public health policies. However, the performance of such surveys in specific groups of interest (e.g., Hispanics/Latinos in a neighborhood of New York City) is rarely studied. METHOD: We compared measures for obesity, hypertension, diabetes, and current smoking based on the New York City Community Health Survey (CHS, a telephone survey of New York City adults) with the Hispanic Community Health Survey/Study of Latinos (HCHS/SOL), an in-person survey of Hispanic/Latino adults in four communities in the United States (2008-2011), including the Bronx. CHS data were limited to Hispanic/Latinos living in the HCHS/SOL Bronx catchment area. RESULTS: Compared with CHS, HCHS/SOL estimated higher prevalence of obesity (in HCHS/SOL, PHCHS/SOL = 45.0% vs. in CHS, PCHS = 30.6%, p < .01) and current smoking (PHCHS/SOL = 21.2% vs. PCHS = 16.2%, p < .01) but similar for hypertension (PHCHS/SOL = 33.1% vs. PCHS = 33.8%, p > .05) and diabetes (PHCHS/SOL = 15.2% vs. PCHS = 15.7%, p > .05). Stratified estimates (by age, sex, education, and Hispanic/Latino heritage) followed similar trends. CONCLUSION: Our study emphasizes the importance of assessing potential bias in population-based surveys of Hispanics/Latinos and other populations of interest and highlights the complex nature of measuring health outcomes via population-based surveys.

Temporal and Spatial Patterns in Utilization of Mental Health Services During and After Hurricane Sandy: Emergency Department and Inpatient Hospitalizations in New York City.

OBJECTIVE: Hurricane Sandy made landfall on October 29, 2012, causing a coastal storm surge and extensive flooding, which led to the closure of several health care facilities in New York City (NYC) and prolonged interruptions in service delivery. The impact on mental health-related emergency department (ED) and inpatient hospital service utilization was studied. METHODS: Data came from the New York Statewide Planning and Research Cooperative System. We obtained mental health-related data among NYC residents from 2010 to 2013. Patients were grouped into 5 geographic areas, including service areas of closed hospitals, the Hurricane Sandy evaluation zone, and all of NYC. The Farrington method was used to detect increases in ED visits and hospitalizations for the post-Sandy period. RESULTS: Open hospitals experienced a substantial increase in psychiatric ED visits from patients living in the service areas of closed hospitals. This surge in psychiatric ED visits persisted for 4 to 6 months after Hurricane Sandy. However, the increase in psychiatric hospitalizations was observed for 1 to 3 months. CONCLUSIONS: Several NYC hospitals received a substantially larger number of ED patients from service areas of closed hospitals after Hurricane Sandy, unlike other hospitals that experienced a decrease. Because of potential surges in the number of psychiatric ED visits, resource allocation to hospitals should be considered. (Disaster Med Public Health Preparedness. 2016;10:512-517).

Spatial Shift in the Utilization of Mental Health Services After Hurricane Sandy Among New York City Residents Enrolled in Medicaid.

OBJECTIVE: Closure of several New York City (NYC) hospitals after Hurricane Sandy caused an unanticipated, extended surge in patient demand at open hospitals. This study identified hospitals with a significant increase in mental-health-related emergency department, inpatient, and outpatient visits from Medicaid patients displaced by Hurricane Sandy. METHODS: NYC Medicaid patients were classified into non-mutually-exclusive geographic categories corresponding to residence in areas served by Bellevue Hospital Center and Coney Island Hospital, the hurricane impact area, and all of NYC. For each geographic region, we compared the observed to the expected number of service visits in the 6 months after the storm. The expected number of visits was calculated from 2-year trends in mental health claims. RESULTS: Twenty-four facilities in all 5 NYC boroughs experienced patient redistribution from storm-affected areas. Eighteen facilities had a concurrent surge in total Medicaid patients, which suggested that redistribution had a greater impact on resource use at these locations. CONCLUSIONS: The redistribution of Medicaid patients after Hurricane Sandy increased mental health service utilization at facilities not near flooded areas. Our findings can aid in surge capacity planning and thereby improve the continuity of mental health care after a natural disaster. (Disaster Med Public Health Preparedness. 2016;10:420-427).