ABSTRACT
OBJECTIVE: To adapt an existing surveillance system to monitor the collateral impacts of the COVID-19 pandemic on health outcomes in New York City across 6 domains: access to care, chronic disease, sexual/reproductive health, food/economic insecurity, mental/behavioral health, and environmental health. DESIGN: Epidemiologic assessment. Public health surveillance system. SETTING: New York City. PARTICIPANTS: New York City residents. MAIN OUTCOME MEASURES: We monitored approximately 30 indicators, compiling data from 2006 to 2022. Sources of data include clinic visits, surveillance surveys, vital statistics, emergency department visits, lead and diabetes registries, Medicaid claims, and public benefit enrollment. RESULTS: We observed disruptions across most indicators including more than 50% decrease in emergency department usage early in the pandemic, which rebounded to prepandemic levels by late 2021, changes in reporting levels of probable anxiety and depression, and worsening birth outcomes for mothers who identified as Asian/Pacific Islander or Black. Data are processed in SAS and analyzed using the R Surveillance package to detect possible inflections. Data are updated monthly to an internal Tableau Dashboard and shared with agency leadership. CONCLUSIONS: As the COVID-19 pandemic continues into its third year, public health priorities are returning to addressing non-COVID-19-related diseases and conditions, their collateral impacts, and postpandemic recovery needs. Substantial work is needed to return even to a suboptimal baseline across multiple health topic areas. Our surveillance framework offers a valuable starting place to effectively allocate resources, develop interventions, and issue public communications.
Subject(s)
COVID-19 , Humans , Asian , COVID-19/epidemiology , Medicaid , New York City/epidemiology , Pandemics , United States , Pacific Island People , Black or African AmericanABSTRACT
From January 21 through February 23, 2020, public health agencies detected 14 U.S. cases of coronavirus disease 2019 (COVID-19), all related to travel from China (1,2). The first nontravel-related U.S. case was confirmed on February 26 in a California resident who had become ill on February 13 (3). Two days later, on February 28, a second nontravel-related case was confirmed in the state of Washington (4,5). Examination of four lines of evidence provides insight into the timing of introduction and early transmission of SARS-CoV-2, the virus that causes COVID-19, into the United States before the detection of these two cases. First, syndromic surveillance based on emergency department records from counties affected early by the pandemic did not show an increase in visits for COVID-19-like illness before February 28. Second, retrospective SARS-CoV-2 testing of approximately 11,000 respiratory specimens from several U.S. locations beginning January 1 identified no positive results before February 20. Third, analysis of viral RNA sequences from early cases suggested that a single lineage of virus imported directly or indirectly from China began circulating in the United States between January 18 and February 9, followed by several SARS-CoV-2 importations from Europe. Finally, the occurrence of three cases, one in a California resident who died on February 6, a second in another resident of the same county who died February 17, and a third in an unidentified passenger or crew member aboard a Pacific cruise ship that left San Francisco on February 11, confirms cryptic circulation of the virus by early February. These data indicate that sustained, community transmission had begun before detection of the first two nontravel-related U.S. cases, likely resulting from the importation of a single lineage of virus from China in late January or early February, followed by several importations from Europe. The widespread emergence of COVID-19 throughout the United States after February highlights the importance of robust public health systems to respond rapidly to emerging infectious threats.
Subject(s)
Coronavirus Infections/epidemiology , Pneumonia, Viral/epidemiology , Sentinel Surveillance , Betacoronavirus/genetics , COVID-19 , Humans , Pandemics , Phylogeny , SARS-CoV-2 , Travel , United States/epidemiologyABSTRACT
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.
Subject(s)
Coronavirus Infections/epidemiology , Disease Outbreaks , Pneumonia, Viral/epidemiology , Adolescent , Adult , Aged , Betacoronavirus/isolation & purification , COVID-19 , COVID-19 Testing , Child , Child, Preschool , Clinical Laboratory Techniques , Coronavirus Infections/diagnosis , Coronavirus Infections/mortality , Coronavirus Infections/therapy , Female , Hospitalization/statistics & numerical data , Humans , Infant , Infant, Newborn , Male , Middle Aged , New York City/epidemiology , Pandemics , Pneumonia, Viral/diagnosis , Pneumonia, Viral/mortality , Pneumonia, Viral/therapy , SARS-CoV-2 , Young AdultABSTRACT
A large number of imported cases of Zika virus infection and the potential for transmission by Aedes albopictus mosquitoes prompted the New York City Department of Health and Mental Hygiene to conduct sentinel, enhanced passive, and syndromic surveillance for locally acquired mosquitoborne Zika virus infections in New York City, NY, USA, during June-October 2016. Suspected case-patients were those >5 years of age without a travel history or sexual exposure who had >3 compatible signs/symptoms (arthralgia, fever, conjunctivitis, or rash). We identified 15 suspected cases and tested urine samples for Zika virus by using real-time reverse transcription PCR; all results were negative. We identified 308 emergency department visits for Zika-like illness, 40,073 visits for fever, and 17 unique spatiotemporal clusters of visits for fever. We identified no evidence of local transmission. Our experience offers possible surveillance tools for jurisdictions concerned about local mosquitoborne Zika virus or other arboviral transmission.
Subject(s)
Culicidae/virology , Sentinel Surveillance , Zika Virus Infection/diagnosis , Zika Virus Infection/epidemiology , Zika Virus/isolation & purification , Adolescent , Adult , Animals , Child , Female , Humans , Male , Middle Aged , New York City/epidemiology , Pregnancy , Young AdultABSTRACT
BACKGROUND: Many types of tree pollen trigger seasonal allergic illness, but their population-level impacts on allergy and asthma morbidity are not well established, likely due to the paucity of long records of daily pollen data that allow analysis of multi-day effects. Our objective in this study was therefore to determine the impacts of individual spring tree pollen types on over-the-counter allergy medication sales and asthma emergency department (ED) visits. METHODS: Nine clinically-relevant spring tree pollen genera (elm, poplar, maple, birch, beech, ash, sycamore/London planetree, oak, and hickory) measured in Armonk, NY, were analyzed for their associations with over-the-counter allergy medication sales and daily asthma syndrome ED visits from patients' chief complaints or diagnosis codes in New York City during March 1st through June 10th, 2002-2012. Multi-day impacts of pollen on the outcomes (0-3 days and 0-7 days for the medication sales and ED visits, respectively) were estimated using a distributed lag Poisson time-series model adjusting for temporal trends, day-of-week, weather, and air pollution. For asthma syndrome ED visits, age groups were also analyzed. Year-to-year variation in the average peak dates and the 10th-to-90th percentile duration between pollen and the outcomes were also examined with Spearman's rank correlation. RESULTS: Mid-spring pollen types (maple, birch, beech, ash, oak, and sycamore/London planetree) showed the strongest significant associations with both outcomes, with cumulative rate ratios up to 2.0 per 0-to-98th percentile pollen increase (e.g., 1.9 [95% CI: 1.7, 2.1] and 1.7 [95% CI: 1.5, 1.9] for the medication sales and ED visits, respectively, for ash). Lagged associations were longer for asthma syndrome ED visits than for the medication sales. Associations were strongest in children (ages 5-17; e.g., a cumulative rate ratio of 2.6 [95% CI: 2.1, 3.1] per 0-to-98th percentile increase in ash). The average peak dates and durations of some of these mid-spring pollen types were also associated with those of the outcomes. CONCLUSIONS: Tree pollen peaking in mid-spring exhibit substantive impacts on allergy, and asthma exacerbations, particularly in children. Given the narrow time window of these pollen peak occurrences, public health and clinical approaches to anticipate and reduce allergy/asthma exacerbation should be developed.
Subject(s)
Allergens/adverse effects , Asthma/epidemiology , Hypersensitivity/epidemiology , Multi-Ingredient Cold, Flu, and Allergy Medications/economics , Pollen/adverse effects , Adolescent , Adult , Aged , Aged, 80 and over , Asthma/etiology , Child , Child, Preschool , Emergency Service, Hospital/statistics & numerical data , Female , Humans , Hypersensitivity/etiology , Infant , Infant, Newborn , Male , Middle Aged , New York City/epidemiology , Nonprescription Drugs/economics , Young AdultABSTRACT
PURPOSE: We examined colon cancer risk in atomic bomb survivors to investigate whether excess body weight after the bombings alters sensitivity to radiation effects. METHODS: Of the 56,064 Japanese atomic bomb survivors with follow-up through 2002 with self-reported anthropometric data obtained from periodic mail surveys, 1,142 were diagnosed with colon cancer. We evaluated the influence of body mass index (BMI) and height on radiation-associated colon cancer risk using Poisson regression. RESULTS: We observed a similar linear dose-response relationship for the 56,064 subjects included in our analysis and the entire cohort of Japanese atomic bomb survivors [excess relative risk (ERR) per Gray (Gy) = 0.53, 95 % confidence interval (CI) 0.25-0.86]. Elevation in earliest reported BMI, BMI reported closest to colon cancer diagnosis, and time-varying BMI were associated with an elevated risk of colon cancer [relative risk (RR) per 5 kg/m(2) increase in BMI = 1.14, 95 % CI 1.03-1.26; RR = 1.16, 95 % CI 1.05-1.27; and RR = 1.15, 95 % CI 1.04-1.27, respectively]. Height was not significantly related to colon cancer risk. Inclusion of anthropometric variables in models had little impact on radiation risk estimates, and there was no evidence that sensitivity to the effect of radiation on colon cancer risk depended on BMI. CONCLUSIONS: Radiation exposure and BMI are both risk factors for colon cancer. BMI at various times after exposure to the atomic bombings does not significantly influence the relationship between radiation dose and colon cancer risk, suggesting that BMI and radiation impact colon cancer risk independently of each other.
Subject(s)
Body Weights and Measures/statistics & numerical data , Carcinoma/epidemiology , Colonic Neoplasms/epidemiology , Environmental Exposure/adverse effects , Neoplasms, Radiation-Induced/epidemiology , Nuclear Weapons , Survivors/statistics & numerical data , Age Distribution , Anthropometry , Carcinoma/etiology , Cohort Studies , Colonic Neoplasms/etiology , Environmental Exposure/statistics & numerical data , Female , Humans , Incidence , Japan/epidemiology , Longevity/physiology , Longevity/radiation effects , Male , Nuclear Weapons/statistics & numerical data , Risk FactorsABSTRACT
BACKGROUND: Comparing disease severity between SARS-CoV-2 variants among populations with varied vaccination and infection histories can help characterize emerging variants and support healthcare system preparedness. METHODS: We compared COVID-19 hospitalization risk among New York City residents with positive laboratory-based SARS-CoV-2 tests when ≥98% of sequencing results were Delta (August-November 2021) or Omicron (BA.1 and sublineages, January 2022). A secondary analysis defined variant exposure using patient-level sequencing results during July 2021-January 2022, comprising 1-18% of weekly confirmed cases. RESULTS: Hospitalization risk was lower among patients testing positive when Omicron (16,025/488,053, 3.3%) than when Delta predominated (8268/158,799, 5.2%). In multivariable analysis adjusting for demographic characteristics and prior diagnosis and vaccination status, patients testing positive when Omicron predominated, compared with Delta, had 0.72 (95% CI: 0.63, 0.82) times the hospitalization risk. In a secondary analysis of patients with sequencing results, hospitalization risk was similar among patients infected with Omicron (2042/29,866, 6.8%), compared with Delta (1780/25,272, 7.0%), and higher among the subset who received two mRNA vaccine doses (adjusted relative risk 1.64; 95% CI: 1.44, 1.87). CONCLUSIONS: Hospitalization risk was lower among patients testing positive when Omicron predominated, compared with Delta. This finding persisted after adjusting for prior diagnosis and vaccination status, suggesting intrinsic virologic properties, not population-based immunity, explained the lower severity. Secondary analyses demonstrated collider bias from the sequencing sampling frame changing over time in ways associated with disease severity. Representative data collection is necessary to avoid bias when comparing disease severity between previously dominant and newly emerging variants.
Subject(s)
COVID-19 , SARS-CoV-2 , Humans , SARS-CoV-2/genetics , COVID-19/diagnosis , COVID-19/epidemiology , New York City/epidemiology , HospitalizationABSTRACT
Existing public health surveillance systems that rely on predefined symptom categories, or syndromes, are effective at monitoring known illnesses, but there is a critical need for innovation in "presyndromic" surveillance that detects biothreats with rare or previously unseen symptomology. We introduce a data-driven, automated machine learning approach for presyndromic surveillance that learns newly emerging syndromes from free-text emergency department chief complaints, identifies localized case clusters among subpopulations, and incorporates practitioner feedback to automatically distinguish between relevant and irrelevant clusters, thus providing personalized, actionable decision support. Blinded evaluations by New York City's Department of Health and Mental Hygiene demonstrate that our approach identifies more events of public health interest and achieves a lower false-positive rate compared to a state-of-the-art baseline.
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.
ABSTRACT
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.
ABSTRACT
Prediction skill is a key test of models for epidemic dynamics. However, future validation of models against out-of-sample data is rare, partly because of a lack of timely surveillance data. We address this gap by analyzing the response of rotavirus dynamics to infant vaccination. Syndromic surveillance of emergency department visits for diarrhea in New York City reveals a marked decline in diarrheal incidence among infants and young children, in line with data on rotavirus-coded hospitalizations and laboratory-confirmed cases, and a shift from annual to biennial epidemics increasingly affecting older children and adults. A published mechanistic model qualitatively predicted these patterns more than 2 years in advance. Future efforts to increase vaccination coverage may disrupt these patterns and lead to further declines in the incidence of rotavirus-attributable gastroenteritis.
Subject(s)
Gastroenteritis/epidemiology , Models, Biological , Rotavirus Infections/epidemiology , Rotavirus , Child, Preschool , Gastroenteritis/prevention & control , Gastroenteritis/virology , Humans , Incidence , Infant , Male , New York City , Rotavirus Infections/prevention & control , Rotavirus Infections/transmissionABSTRACT
Previous studies identified radiation therapy as a key modifier of basal cell carcinoma (BCC) risk in survivors of hematopoietic cell transplantation (HCT). In the present analysis, risk of BCC was analyzed in relation to age at transplant, attained age, race, total-body irradiation (TBI), and radiation fractionation in 6,306 patients who received HCT at ages 0-65 years after conditioning regimens with (n = 3870) or without (n = 2436) TBI, and who were followed from 100 days to 36.2 years after HCT. While age-specific BCC rates in the unirradiated patient population were higher than those reported for two non-patient populations, the general characteristics were similar; rates increased with attained age, were eightfold lower for non-white patients, and were higher in more recent birth cohorts. After adjusting for these effects, risk in unirradiated patients did not vary significantly with age at HCT. The additional BCC risk associated with radiation exposure was largest for the youngest ages at exposure to radiation, with relative risks exceeding 20 for those transplanted at ages less than 10 years, and decreased with increasing age at exposure until age 40 years, above which no excess risk was identified. Relative risk in the irradiated population did not vary significantly with attained age, dose fractionation or race. Risks per unit dose in HCT patients were similar to other populations exposed under clinical settings to similar radiation doses and were more than 10-fold lower than seen in the atomic bomb survivors, 97% of whom were exposed to doses <1 Sv.
Subject(s)
Carcinoma, Basal Cell/etiology , Hematopoietic Stem Cell Transplantation/adverse effects , Neoplasms, Second Primary/etiology , Skin Neoplasms/etiology , Whole-Body Irradiation/adverse effects , Adolescent , Aged , Child , Child, Preschool , Female , Humans , Infant , Infant, Newborn , MaleABSTRACT
BACKGROUND: Histamine(2)-receptor antagonist (H(2) blocker) medications are used to treat heartburn, gastroesophageal reflux disease, and ulcers. Some H(2) blockers, specifically cimetidine and ranitidine, also increase serum prolactin concentrations. Given the positive relationship between prolactin levels and postmenopausal breast cancer risk, use of H(2) blockers is a potential breast cancer risk factor. The few previous studies evaluating this association have been null but have been limited by small sample sizes, and none have evaluated risk by either histologic type or estrogen receptor/progesterone receptor status. METHODS: Combining data from two population-based case-control studies conducted in western Washington, we assessed the relationship between use of H(2) blockers and risk of different types of breast cancer among 1,941 cases and 1,476 controls 55 to 79 years old. Odds ratios and 95% confidence intervals (95% CI) were calculated using polytomous logistic regression. RESULTS: Current use of H(2) blockers overall, cimetidine, and famotidine was not associated with an increased risk of either invasive ductal or invasive lobular breast cancer. Current users of ranitidine had a 2.2-fold (95% CI, 1.1-4.3) increased risk of ductal carcinoma that was confined to a 2.4-fold (95% CI, 1.2-4.9) increased risk of estrogen receptor-positive/progesterone receptor-positive ductal carcinoma. CONCLUSIONS: Use of H(2) blockers in general is not associated with an increased risk of breast cancer, although current use of ranitidine may increase risk of hormone receptor-positive ductal carcinoma. Further studies to confirm this finding are warranted.
Subject(s)
Anti-Ulcer Agents/therapeutic use , Breast Neoplasms/epidemiology , Carcinoma, Ductal, Breast/epidemiology , Carcinoma, Lobular/epidemiology , Histamine H2 Antagonists/therapeutic use , Aged , Case-Control Studies , Cimetidine/therapeutic use , Famotidine/therapeutic use , Female , Humans , Middle Aged , Neoplasm Invasiveness/pathology , Ranitidine/therapeutic use , Risk Factors , Washington/epidemiologyABSTRACT
BACKGROUND: The frequency of migraine headache changes at various times of a woman's reproductive cycle. Menarche, menses, pregnancy, and perimenopause may carry a different migraine risk conceivably because of fluctuating estrogen levels, and in general, migraine frequency is associated with falling estrogen levels. Given the strong relationship between endogenous estrogen levels and breast cancer risk, migraine sufferers may experience a reduced risk of breast cancer. METHODS: We combined data from two population-based case-control studies to examine the relationship between migraine and risk of postmenopausal invasive breast cancer among 1,199 ductal carcinoma cases, 739 lobular carcinoma cases, and 1,474 controls 55 to 79 years of age. Polytomous logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (95% CI). RESULTS: Women who reported a clinical diagnosis of migraine had reduced risks of ductal carcinoma (OR, 0.67; 95% CI, 0.54-0.82) and lobular carcinoma (OR, 0.68; 95% CI, 0.52-0.90). These associations were primarily limited to hormone receptor-positive tumors as migraine was associated with a 0.65-fold (95% CI, 0.51-0.83) reduced risk of estrogen receptor-positive (ER+)/progesterone receptor-positive (PR+) ductal carcinoma. The reductions in risk observed were seen among migraine sufferers who did and did not use prescription medications for their migraines. CONCLUSIONS: These data suggest that a history of migraine is associated with a decreased risk of breast cancer, particularly among ER+/PR+ ductal and lobular carcinomas. Because this is the first study to address an association between migraine history and breast cancer risk, additional studies are needed to confirm this finding.
Subject(s)
Breast Neoplasms/epidemiology , Carcinoma, Ductal, Breast/epidemiology , Carcinoma, Lobular/epidemiology , Migraine Disorders/epidemiology , Postmenopause , Aged , Anti-Inflammatory Agents, Non-Steroidal/therapeutic use , Case-Control Studies , Female , Humans , Logistic Models , Middle Aged , Migraine Disorders/drug therapy , Neoplasm Invasiveness , Risk AssessmentABSTRACT
The impact of heat on mortality is well documented but deaths tend to occur after (or lag) extreme heat events, and mortality data is generally not available for timely surveillance during extreme heat events. Recently, systems for near-real time surveillance of heat illness have been reported but have not been validated as predictors of non-external cause of deaths associated with extreme heat events. We analyzed associations between daily weather conditions, emergency medical system (EMS) calls flagged as heat-related by EMS dispatchers, emergency department (ED) visits classified as heat-related based on chief complaint text, and excess non-external cause mortality in New York City. EMS and ED data were obtained from data reported daily to the city health department for syndromic surveillance. We fit generalized linear models to assess the relationships of daily counts of heat related EMS and ED visits to non-external cause deaths after adjustment for weather conditions during the months of May-September between 1999 and 2013. Controlling for temporal trends, a 7% (95% confidence interval (CI): 2-12) and 6% (95% CI: 3-10) increase in non-external cause mortality was associated with an increase from the 50th percentile to 99th percentile of same-day and one-day lagged heat-related EMS calls and ED visits, respectively. After controlling for both temporal trends and weather, we observed a 7% (95% CI: 3-12) increase in non-external cause mortality associated with one-day lagged heat-related EMS calls and a 5% mortality increase with one-day lagged ED visits (95% CI: 2-8). Heat-related illness can be tracked during extreme heat events using EMS and ED data which are indicators of heat associated excess non-external cause mortality during the warm weather season.
Subject(s)
Emergency Medical Services/statistics & numerical data , Emergency Medicine/statistics & numerical data , Emergency Service, Hospital/statistics & numerical data , Extreme Heat , Heat Stress Disorders/therapy , Algorithms , Emergencies , Humans , Linear Models , Morbidity , New York City , Seasons , Time FactorsABSTRACT
INTRODUCTION: The use of syndromic surveillance has expanded from its initial purpose of bioterrorism detection. We present 6 use cases from New York City that demonstrate the value of syndromic surveillance for public health response and decision making across a broad range of health outcomes: synthetic cannabinoid drug use, heat-related illness, suspected meningococcal disease, medical needs after severe weather, asthma exacerbation after a building collapse, and Ebola-like illness in travelers returning from West Africa. MATERIALS AND METHODS: The New York City syndromic surveillance system receives data on patient visits from all emergency departments (EDs) in the city. The data are used to assign syndrome categories based on the chief complaint and discharge diagnosis, and analytic methods are used to monitor geographic and temporal trends and detect clusters. RESULTS: For all 6 use cases, syndromic surveillance using ED data provided actionable information. Syndromic surveillance helped detect a rise in synthetic cannabinoid-related ED visits, prompting a public health investigation and action. Surveillance of heat-related illness indicated increasing health effects of severe weather and led to more urgent public health messaging. Surveillance of meningitis-related ED visits helped identify unreported cases of culture-negative meningococcal disease. Syndromic surveillance also proved useful for assessing a surge of methadone-related ED visits after Superstorm Sandy, provided reassurance of no localized increases in asthma after a building collapse, and augmented traditional disease reporting during the West African Ebola outbreak. PRACTICE IMPLICATIONS: Sharing syndromic surveillance use cases can foster new ideas and build capacity for public health preparedness and response.
Subject(s)
Disease Outbreaks/prevention & control , Emergency Service, Hospital/statistics & numerical data , Population Surveillance/methods , Public Health Informatics/methods , Asthma/epidemiology , Communicable Diseases, Emerging/epidemiology , Communicable Diseases, Emerging/prevention & control , Emergency Service, Hospital/organization & administration , Heat Stroke/epidemiology , Humans , Marijuana Abuse/epidemiology , New York City/epidemiologyABSTRACT
The New York City Department of Health and Mental Hygiene has operated an emergency department syndromic surveillance system since 2001, using temporal and spatial scan statistics run on a daily basis for cluster detection. Since the system was originally implemented, a number of new methods have been proposed for use in cluster detection. We evaluated six temporal and four spatial/spatio-temporal detection methods using syndromic surveillance data spiked with simulated injections. The algorithms were compared on several metrics, including sensitivity, specificity, positive predictive value, coherence, and timeliness. We also evaluated each method's implementation, programming time, run time, and the ease of use. Among the temporal methods, at a set specificity of 95%, a Holt-Winters exponential smoother performed the best, detecting 19% of the simulated injects across all shapes and sizes, followed by an autoregressive moving average model (16%), a generalized linear model (15%), a modified version of the Early Aberration Reporting System's C2 algorithm (13%), a temporal scan statistic (11%), and a cumulative sum control chart (<2%). Of the spatial/spatio-temporal methods we tested, a spatial scan statistic detected 3% of all injects, a Bayes regression found 2%, and a generalized linear mixed model and a space-time permutation scan statistic detected none at a specificity of 95%. Positive predictive value was low (<7%) for all methods. Overall, the detection methods we tested did not perform well in identifying the temporal and spatial clusters of cases in the inject dataset. The spatial scan statistic, our current method for spatial cluster detection, performed slightly better than the other tested methods across different inject magnitudes and types. Furthermore, we found the scan statistics, as applied in the SaTScan software package, to be the easiest to program and implement for daily data analysis.
Subject(s)
Disease Outbreaks , Population Surveillance/methods , Algorithms , Datasets as Topic , Humans , Models, Statistical , New York City , ROC Curve , Reproducibility of Results , Spatial Analysis , Spatio-Temporal Analysis , SyndromeABSTRACT
Following the Gulf War (GW), large numbers of individuals reported illness that they attributed to exposures encountered during the GW deployment. In response, the Department of Veterans Affairs and the Department of Defense established programs and registries for the evaluation and documentation of GW-related illness. We obtained registrants' medical records, which contained information on outpatient encounters during the 1-year period before their GW deployment, to determine whether registrants with multisymptom illness (cases) have patterns of predeployment health care seeking that are different from those of well registrants (controls). We found that subjects had significantly more predeployment outpatient visits than controls, but this varied by type of visit. Although the number of certain types of predeployment outpatient visits is significantly associated with subsequent multisymptom illness, these associations will have limited predictive value. These findings increase our understanding of multisymptom illness, especially its chronic nature, and justify doing additional studies.
Subject(s)
Gulf War , Military Personnel , Patient Acceptance of Health Care , Adult , California , Female , Humans , Male , Medical Audit , RegistriesABSTRACT
Health status was sought for approximately 1600 Korean War veterans who contracted hemorrhagic fever with renal syndrome (HFRS) during deployment to Korea between 1951 and 1953. To determine whether long-term sequelae were present for these individuals, mortality and morbidity data were collected from the Department of Veterans Affairs, the Centers for Medicare and Medicaid Services, the Social Security Administration, and the National Death Index records. Control subjects were selected from military units in Korea with no reported cases of HFRS. Those with HFRS had a slightly higher mortality rate (33.2%) than did noninfected individuals (32.0%), but this difference was not statistically significant. Non-Caucasian cases had significantly higher morbidity rates than did non-Caucasian controls only for transient ischemic attacks (4.8% versus 0%) and diabetes mellitus (19.3% versus 8.1%). In conclusion, HFRS did not increase mortality rates in this cohort but might have had an impact on selected morbidity outcomes.
Subject(s)
Hantaan virus , Health Status , Hemorrhagic Fever with Renal Syndrome/epidemiology , Korean War , Veterans , Comorbidity , Humans , Proportional Hazards Models , Risk Adjustment , Survival Analysis , United States/epidemiology , Veterans/statistics & numerical data , White People/statistics & numerical dataABSTRACT
In response to two isolated cases of Mycobacterium chelonae infections in tattoo recipients where tap water was used to dilute ink, the New York City (NYC) Department of Health and Mental Hygiene conducted an investigation using Emergency Department (ED) syndromic surveillance to assess whether an outbreak was occuring. ED visits with chief complaints containing the key word "tattoo" from November 1, 2012 to March 18, 2013 were selected for study. NYC laboratories were also contacted and asked to report skin or soft tissue cultures in tattoo recipients that were positive for non-tuberculosis mycobacterial infection (NTM). Thirty-one TREDV were identified and 14 (45%) were interviewed to determine if a NTM was the cause for the visit. One ED visit met the case definition and was referred to a dermatologist. This individual was negative for NTM. No tattoo-associated NTM cases were reported by NYC laboratories. ED syndromic surveillance was utilized to investigate a non-reportable condition for which no other data source existed. The results were reassuring that an outbreak of NTM in tattoo recipients was not occurring. In response to concerns about potential NTM infections, the department sent a letter to all licensed tattoo artists advising them not to dilute tattoo ink with tap water.