Electronic Case Reporting Development, Implementation, and Expansion in the United States.

INTRODUCTION: The COVID-19 pandemic highlighted the need for a nationwide health information technology solution that could improve upon manual case reporting and decrease the clinical and administrative burden on the US health care system. We describe the development, implementation, and nationwide expansion of electronic case reporting (eCR), including its effect on public health surveillance and pandemic readiness. METHODS: Multidisciplinary teams developed and implemented a standards-based, shared, scalable, and interoperable eCR infrastructure during 2014-2020. From January 27, 2020, to January 7, 2023, the team conducted a nationwide scale-up effort and determined the number of eCR-capable electronic health record (EHR) products, the number of reportable conditions available within the infrastructure, and technical connections of health care organizations (HCOs) and jurisdictional public health agencies (PHAs) to the eCR infrastructure. The team also conducted data quality studies to determine whether HCOs were discontinuing manual case reporting and early results of eCR timeliness. RESULTS: During the study period, the number of eCR-capable EHR products developed or in development increased 11-fold (from 3 to 33), the number of reportable conditions available increased 28-fold (from 6 to 173), the number of HCOs connected to the eCR infrastructure increased 143-fold (from 153 to 22 000), and the number of jurisdictional PHAs connected to the eCR infrastructure increased 2.75-fold (from 24 to 66). Data quality reviews with PHAs resulted in select HCOs discontinuing manual case reporting and using eCR-exclusive case reporting in 13 PHA jurisdictions. The timeliness of eCR was <1 minute. PRACTICE IMPLICATIONS: The growth of eCR can revolutionize public health case surveillance by producing data that are more timely and complete than manual case reporting while reducing reporting burden.

Enhancing the Applied Epidemiology Workforce: The Impact of the 2021 Epidemiology Capacity Assessment on CSTE's Workforce Priorities.

The Council of State and Territorial Epidemiologists (CSTE) conducted the seventh Epidemiology Capacity Assessment (ECA) from January to April 2021 in state and territorial health departments. The ECA serves to enumerate the applied epidemiology workforce and evaluate workforce capacity across the nation. The results of the ECA demonstrated a need for additional epidemiologists across jurisdictions and challenges of maintaining a trained workforce and improving public health infrastructure. The results of the ECA serve as the foundation for CSTE's workforce priorities, which focus on transforming applied epidemiology by promoting the field as a career opportunity, recruitment, and retention strategies, upskilling the workforce, and enhancing infrastructure. CSTE has outlined current and future workforce priorities, and these priorities contribute to a larger strategy to transform the field and enhance applied epidemiology capacity nationwide. This report describes the programmatic actions taken by CSTE in response to the results of the 2021 ECA.

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.

Detecting COVID-19 Clusters at High Spatiotemporal Resolution, New York City, New York, USA, June-July 2020.

A surveillance system that uses census tract resolution and the SaTScan prospective space-time scan statistic detected clusters of increasing severe acute respiratory syndrome coronavirus 2 test percent positivity in New York City, NY, USA. Clusters included one in which patients attended the same social gathering and another that led to targeted testing and outreach.

Infectious Disease Hospitalizations, New York City, 2001-2014.

OBJECTIVE: Hospital discharge data are a means of monitoring infectious diseases in a population. We investigated rates of infectious disease hospitalizations in New York City. METHODS: We analyzed data for residents discharged from New York State hospitals with a principal diagnosis of an infectious disease during 2001-2014 by using the Statewide Planning and Research Cooperative System. We calculated annual age-adjusted hospitalization rates and the percentage of hospitalizations in which in-hospital death occurred. We examined diagnoses by site of infection or sepsis and by pathogen type. RESULTS: During 2001-2014, the mean annual age-adjusted rate of infectious disease hospitalizations in New York City was 1661.6 (95% CI, 1659.2-1663.9) per 100 000 population; the mean annual age-adjusted hospitalization rate decreased from 2001-2003 to 2012-2014 (rate ratio = 0.9; 95% CI, 0.9-0.9). The percentage of in-hospital death during 2001-2014 was 5.9%. The diagnoses with the highest mean annual age-adjusted hospitalization rates among all sites of infection and sepsis diagnoses were the lower respiratory tract, followed by sepsis. From 2001-2003 to 2012-2014, the mean annual age-adjusted hospitalization rate per 100 000 population for HIV decreased from 123.1 (95% CI, 121.7-124.5) to 40.0 (95% CI, 39.2-40.7) and for tuberculosis decreased from 10.2 (95% CI, 9.8-10.6) to 4.6 (95% CI, 4.4-4.9). CONCLUSIONS: Although hospital discharge data are subject to limitations, particularly for tracking sepsis, lower respiratory tract infections and sepsis are important causes of infectious disease hospitalizations in New York City. Hospitalizations for HIV infection and tuberculosis appear to be declining.

Brucella Exposure Risk Events in 10 Clinical Laboratories, New York City, USA, 2015 to 2017.

From 2015 to 2017, 11 confirmed brucellosis cases were reported in New York City, leading to 10 Brucella exposure risk events (Brucella events) in 7 clinical laboratories (CLs). Most patients had traveled to countries where brucellosis is endemic and presented with histories and findings consistent with brucellosis. CLs were not notified that specimens might yield a hazardous organism, as the clinicians did not consider brucellosis until they were notified that bacteremia with Brucella was suspected. In 3 Brucella events, the CLs did not suspect that slow-growing, small Gram-negative bacteria might be harmful. Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS), which has a limited capacity to identify biological threat agents (BTAs), was used during 4 Brucella events, which accounted for 84% of exposures. In 3 of these incidents, initial staining of liquid media showed Gram-positive rods or cocci, including some cocci in chains, suggesting streptococci. Over 200 occupational exposures occurred when the unknown isolates were manipulated and/or tested on open benches, including by procedures that could generate infectious aerosols. During 3 Brucella events, the CLs examined and/or manipulated isolates in a biological safety cabinet (BSC); in each CL, the CL had previously isolated Brucella Centers for Disease Control and Prevention recommendations to prevent laboratory-acquired brucellosis (LAB) were followed; no seroconversions or LAB cases occurred. Laboratory assessments were conducted after the Brucella events to identify facility-specific risks and mitigations. With increasing MALDI-TOF MS use, CLs are well-advised to adhere strictly to safe work practices, such as handling and manipulating all slow-growing organisms in BSCs and not using MALDI-TOF MS for identification until BTAs have been ruled out.

Identifying Areas at Greatest Risk for Recent Zika Virus Importation - New York City, 2016.

INTRODUCTION: The New York City Department of Health and Mental Hygiene sought to detect and minimize the risk of local, mosquito-borne Zika virus (ZIKV) transmission. We modeled areas at greatest risk for recent ZIKV importation, in the context of spatially biased ZIKV case ascertainment and no data on the local spatial distribution of persons arriving from ZIKV-affected countries. METHODS: For each of 14 weeks during June-September 2016, we used logistic regression to model the census tract-level presence of any ZIKV cases in the prior month, using eight covariates from static sociodemographic census data and the latest surveillance data, restricting to census tracts with any ZIKV testing in the prior month. To assess whether the model discriminated better than random between census tracts with and without recent cases, we compared the area under the receiver operating characteristic (ROC) curve for each week's fitted model versus an intercept-only model applied to cross-validated data. For weeks where the ROC contrast test was significant at P < 0.05, we output and mapped the model-predicted individual probabilities for all census tracts, including those with no recent testing. RESULTS: The ROC contrast test was significant for 8 of 14 weekly analyses. No covariates were consistently associated with the presence of recent cases. Modeled risk areas fluctuated across these 8 weeks, with Spearman correlation coefficients ranging from 0.30 to 0.93, all P < 0.0001. Areas in the Bronx and upper Manhattan were in the highest risk decile as of late June, while as of late August, the greatest risk shifted to eastern Brooklyn. CONCLUSION: We used observable characteristics of areas with recent, known travel-associated ZIKV cases to identify similar areas with no observed cases that might also be at-risk each week. Findings were used to target public education and Aedes spp. mosquito surveillance and control. These methods are applicable to other conditions for which biased case ascertainment is suspected and knowledge of how cases are geographically distributed is important for targeting public health activities.

Epidemiological Characteristics and Laboratory Findings of Zika Virus Cases in New York City, January 1, 2016-June 30, 2017.

BACKGROUND: An outbreak of Zika virus (ZIKV) began in May 2015 in Brazil and rapidly spread throughout the Americas; New York City (NYC) has a diverse population with ∼1.8 million residents who were born in ZIKV-affected areas. Before July 24, 2017, the Centers for Disease Control and Prevention (CDC) ZIKV testing recommendations included nucleic acid amplification-based tests for serum and urine specimens collected ≤14 days of illness onset or last potential exposure, and ZIKV immunoglobulin M (IgM) assay when ZIKV RNA is not detected or for specimens collected within 2-12 weeks of illness onset or last potential exposure, followed by a plaque reduction neutralization test (PRNT). However, the New York public health laboratories and commercial laboratories tested specimens collected beyond these time frames. METHODS: We analyzed 1080 noncongenital ZIKV cases in NYC residents who met the Council for State and Territorial Epidemiologist's ZIKV case definitions. RESULTS: Among cases, 98% were travel associated, 1% were sexually transmitted, and 1% had unknown exposures; 412 (38%) cases were pregnant women. Of 672 patients with ZIKV RNA detected in serum or urine specimens, 48 (7%) tested positive >14 days after either symptom onset or last potential exposure date (range 15-99 days). Of 390 patients diagnosed based on serology alone (i.e., not tested or not detectable for ZIKV RNA), 60 (15%) had a positive ZIKV IgM and PRNT >12 weeks after symptom onset or last potential exposure date (range 85-273 days). CONCLUSION: Our findings correspond with CDC's updated guidance to test symptomatic pregnant women up to 12 weeks past onset of symptoms. ZIKV IgM antibody testing may also be warranted for pregnant women regardless of symptoms if their exposure occurred during their pregnancy or periconception period. Providers should understand the scope of diagnostic testing and its limitations to appropriately counsel patients, especially pregnant women.

A Large Community Outbreak of Legionnaires' Disease Associated With a Cooling Tower in New York City, 2015.

OBJECTIVES: Infections caused by Legionella are the leading cause of waterborne disease outbreaks in the United States. We investigated a large outbreak of Legionnaires' disease in New York City in summer 2015 to characterize patients, risk factors for mortality, and environmental exposures. METHODS: We defined cases as patients with pneumonia and laboratory evidence of Legionella infection from July 2 through August 3, 2015, and with a history of residing in or visiting 1 of several South Bronx neighborhoods of New York City. We describe the epidemiologic, environmental, and laboratory investigation that identified the source of the outbreak. RESULTS: We identified 138 patients with outbreak-related Legionnaires' disease, 16 of whom died. The median age of patients was 55. A total of 107 patients had a chronic health condition, including 43 with diabetes, 40 with alcoholism, and 24 with HIV infection. We tested 55 cooling towers for Legionella, and 2 had a strain indistinguishable by pulsed-field gel electrophoresis from 26 patient isolates. Whole-genome sequencing and epidemiologic evidence implicated 1 cooling tower as the source of the outbreak. CONCLUSIONS: A large outbreak of Legionnaires' disease caused by a cooling tower occurred in a medically vulnerable community. The outbreak prompted enactment of a new city law on the operation and maintenance of cooling towers. Ongoing surveillance and evaluation of cooling tower process controls will determine if the new law reduces the incidence of Legionnaires' disease in New York City.

Daily Reportable Disease Spatiotemporal Cluster Detection, New York City, New York, USA, 2014-2015.

Each day, the New York City Department of Health and Mental Hygiene uses the free SaTScan software to apply prospective space-time permutation scan statistics to strengthen early outbreak detection for 35 reportable diseases. This method prompted early detection of outbreaks of community-acquired legionellosis and shigellosis.

Disparities in Reportable Communicable Disease Incidence by Census Tract-Level Poverty, New York City, 2006-2013.

OBJECTIVES: We described disparities in selected communicable disease incidence across area-based poverty levels in New York City, an area with more than 8 million residents and pronounced household income inequality. METHODS: We geocoded and categorized cases of 53 communicable diseases diagnosed during 2006 to 2013 by census tract-based poverty level. Age-standardized incidence rate ratios (IRRs) were calculated for areas with 30% or more versus fewer than 10% of residents below the federal poverty threshold. RESULTS: Diseases associated with high poverty included rickettsialpox (IRR = 3.69; 95% confidence interval [CI] = 2.29, 5.95), chronic hepatitis C (IRR for new reports = 3.58; 95% CI = 3.50, 3.66), and malaria (IRR = 3.48; 95% CI = 2.97, 4.08). Diseases associated with low poverty included domestic tick-borne diseases acquired through travel to areas where infected vectors are prevalent, such as human granulocytic anaplasmosis (IRR = 0.08; 95% CI = 0.03, 0.19) and Lyme disease (IRR = 0.34; 95% CI = 0.32, 0.36). CONCLUSIONS: Residents of high poverty areas were disproportionately affected by certain communicable diseases that are amenable to public health interventions. Future work should clarify subgroups at highest risk, identify reasons for the observed associations, and use findings to support programs to minimize disparities.

Building-level analyses to prospectively detect influenza outbreaks in long-term care facilities: New York City, 2013-2014.

BACKGROUND: Timely outbreak detection is necessary to successfully control influenza in long-term care facilities (LTCFs) and other institutions. To supplement nosocomial outbreak reports, calls from infection control staff, and active laboratory surveillance, the New York City (NYC) Department of Health and Mental Hygiene implemented an automated building-level analysis to proactively identify LTCFs with laboratory-confirmed influenza activity. METHODS: Geocoded addresses of LTCFs in NYC were compared with geocoded residential addresses for all case-patients with laboratory-confirmed influenza reported through passive surveillance. An automated daily analysis used the geocoded building identification number, approximate text matching, and key-word searches to identify influenza in residents of LTCFs for review and follow-up by surveillance coordinators. Our aim was to determine whether the building analysis improved prospective outbreak detection during the 2013-2014 influenza season. RESULTS: Of 119 outbreaks identified in LTCFs, 109 (92%) were ever detected by the building analysis, and 55 (46%) were first detected by the building analysis. Of the 5,953 LTCF staff and residents who received antiviral prophylaxis during the 2013-2014 season, 929 (16%) were at LTCFs where outbreaks were initially detected by the building analysis. CONCLUSIONS: A novel building-level analysis improved influenza outbreak identification in LTCFs in NYC, prompting timely infection control measures.

Ebola virus disease in a humanitarian aid worker - New York City, October 2014.

In late October 2014, Ebola virus disease (Ebola) was diagnosed in a humanitarian aid worker who recently returned from West Africa to New York City (NYC). The NYC Department of Health and Mental Hygiene (DOHMH) actively monitored three close contacts of the patient and 114 health care personnel. No secondary cases of Ebola were detected. In collaboration with local and state partners, DOHMH had developed protocols to respond to such an event beginning in July 2014. These protocols included safely transporting a person at the first report of symptoms to a local hospital prepared to treat a patient with Ebola, laboratory testing for Ebola, and monitoring of contacts. In response to this single case of Ebola, initial health care worker active monitoring protocols needed modification to improve clarity about what types of exposure should be monitored. The response costs were high in both human resources and money: DOHMH alone spent $4.3 million. However, preparedness activities that include planning and practice in effectively monitoring the health of workers involved in Ebola patient care can help prevent transmission of Ebola.

Refining historical limits method to improve disease cluster detection, New York City, New York, USA.

Since the early 2000s, the Bureau of Communicable Disease of the New York City Department of Health and Mental Hygiene has analyzed reportable infectious disease data weekly by using the historical limits method to detect unusual clusters that could represent outbreaks. This method typically produced too many signals for each to be investigated with available resources while possibly failing to signal during true disease outbreaks. We made method refinements that improved the consistency of case inclusion criteria and accounted for data lags and trends and aberrations in historical data. During a 12-week period in 2013, we prospectively assessed these refinements using actual surveillance data. The refined method yielded 74 signals, a 45% decrease from what the original method would have produced. Fewer and less biased signals included a true citywide increase in legionellosis and a localized campylobacteriosis cluster subsequently linked to live-poultry markets. Future evaluations using simulated data could complement this descriptive assessment.

Assessment of reportable disease incidence after Hurricane Sandy, New York City, 2012.

OBJECTIVE: Hurricane Sandy's October 29, 2012 arrival in New York City caused flooding, power disruption, and population displacement. Infectious disease risk may have been affected by floodwater exposure, residence in emergency shelters, overcrowding, and lack of refrigeration or heating. For 42 reportable diseases that could have been affected by hurricane-related exposures, we developed methods to assess whether hurricane-affected areas had higher disease incidence than other areas of NYC. METHODS: We identified post-hurricane cases as confirmed, probable, or suspected cases with onset or diagnosis between October 30 and November 26 that were reported via routine passive surveillance. Pre-hurricane cases for the same 4-week period were identified in 5 prior years, 2007-2011. Cases were geocoded to the census tract of residence. Using data compiled by the NYC Office of Emergency Management, we determined (1) the proportion of the population in each census tract living in a flooded block and (2) the subset of flooded tracts severely "impacted", e.g., by prolonged service outages or physical damage. A separate multivariable regression model was constructed for each disease, modeling the outcome of case counts using a negative binomial distribution. Independent variables were: neighborhood poverty; whether cases were pre- or post-hurricane (time); the proportion of the population flooded in impacted and not impacted tracts; and interaction terms between the flood/impact variables and time. Models used repeated measures to adjust for correlated observations from the same tract and an offset term of the log of the population size. Sensitivity analyses assessed the effects of case count fluctuations and accounted for variations in reporting volume by using an offset term of the log of total cases. RESULTS: Only legionellosis was statistically significantly associated with increased occurrence in flooded/impacted areas post-hurricane, adjusting for baseline differences (P = .04). However, there was only 1 legionellosis case post-hurricane in a flooded/impacted area. CONCLUSIONS: Hurricane Sandy did not appear to elevate reportable disease incidence in NYC. Defining and acquiring reliable data and meta-data regarding hurricane-affected areas was a challenge in the weeks post-storm. Relevant metrics could be developed during disaster preparedness planning. These methods to detect excess disease can be adapted for future emergencies.

Fatalities associated with the 2009 H1N1 influenza A virus in New York city.

BACKGROUND. When the 2009 H1N1 influenza A virus emerged in the United States, epidemiologic and clinical information about severe and fatal cases was limited. We report the first 47 fatal cases of 2009 H1N1 influenza in New York City. METHODS. The New York City Department of Health and Mental Hygiene conducted enhanced surveillance for hospitalizations and deaths associated with 2009 H1N1 influenza A virus. We collected basic demographic and clinical information for all patients who died and compared abstracted data from medical records for a sample of hospitalized patients who died and hospitalized patients who survived. RESULTS. From 24 April through 1 July 2009, 47 confirmed fatal cases of 2009 H1N1 influenza were reported to the New York City Department of Health and Mental Hygiene. Most decedents (60%) were ages 18-49 years, and only 4% were aged 65 years. Many (79%) had underlying risk conditions for severe seasonal influenza, and 58% were obese according to their body mass index. Thirteen (28%) had evidence of invasive bacterial coinfection. Approximately 50% of the decedents had developed acute respiratory distress syndrome. Among all hospitalized patients, decedents had presented for hospitalization later (median, 3 vs 2 days after illness onset; P < .05) and received oseltamivir later (median, 6.5 vs 3 days; P < .01) than surviving patients. Hospitalized patients who died were less likely to have received oseltamivir within 2 days of hospitalization than hospitalized patients who survived (61% vs 96%; P < .01). CONCLUSIONS. With community-wide transmission of 2009 H1N1 influenza A virus, timely medical care and antiviral therapy should be considered for patients with severe influenza-like illness or with underlying risk conditions for complications from influenza.

Public health and environmental response to the first case of naturally acquired inhalational anthrax in the United States in 30 years: infection of a new york city resident who worked with dried animal hides.

In Pennsylvania on February 16, 2006, a New York City resident collapsed with rigors and was hospitalized. On February 21, the Centers for Disease Control and Prevention and the New York City Department of Health and Mental Hygiene were notified that Bacillus anthracis had been identified in the patient's blood. Although the patient's history of working with dried animal hides to make African drums indicated the likelihood of a natural exposure to aerosolized anthrax spores, bioterrorism had to be ruled out first. Ultimately, this case proved to be the first case of naturally occurring inhalational anthrax in 30 years. This article describes the epidemiologic and environmental investigation to identify other cases and persons at risk and to determine the source of exposure and scope of contamination. Because stricter regulation of the importation of animal hides from areas where anthrax is enzootic is difficult, public healthcare officials should consider the possibility of future naturally occurring anthrax cases caused by contaminated hides. Federal protocols are needed to assist in the local response, which should be tempered by our growing understanding of the epidemiology of naturally acquired anthrax. These protocols should include recommended methods for reliable and efficient environmental sample collection and laboratory testing, and environmental risk assessments and remediation.

Long-term prognosis for clinical West Nile virus infection.

Relatively little is known about the long-term prognosis for patients with clinical West Nile virus (WNV) infection. We conducted a study to describe the recovery of New York City residents infected during the 1999 WNV encephalitis outbreak. Patients were interviewed by telephone on self-perceived health outcomes 6, 12, and 18 months after WNV illness onset. At 12 months, the prevalence of physical, functional, and cognitive symptoms was significantly higher than that at baseline, including muscle weakness, loss of concentration, confusion, and lightheadedness. Only 37% achieved a full recovery by 1 year. Younger age at infection was the only significant predictor of recovery. Efforts aimed at preventing WNV infection should focus on elderly populations who are at increased risk for neurologic manifestations and more likely to experience long-term sequelae of WNV illness. More studies are needed to document the long-term sequelae of this increasingly common infection.

Use of ambulance dispatch data as an early warning system for communitywide influenzalike illness, New York City.

In 1998, the New York City Department of Health and the Mayor's Office of Emergency Management began monitoring the volume of ambulance dispatch calls as a surveillance tool for biologic terrorism. We adapted statistical techniques designed to measure excess influenza mortality and applied them to outbreak detection using ambulance dispatch data. Since 1999, we have been performing serial daily regressions to determine the alarm threshold for the current day. In this article, we evaluate this approach by simulating a series of 2,200 daily regressions. In the influenza detection implementation of this model, there were 71 (3.2%) alarms at the 99% level. Of these alarms, 64 (90%) occurred shortly before or during a period of peak influenza in each of six influenza seasons. In the bioterrorism detection implementation of this methodology, after accounting for current influenza activity, there were 24 (1.1%) alarms at the 99% level. Two occurred during a large snowstorm, 1 is unexplained, and 21 occurred shortly before or during a period of peak influenza activity in each of six influenza seasons. Our findings suggest that this surveillance system is sensitive to communitywide respiratory outbreaks with relatively few false alarms. More work needs to be done to evaluate the sensitivity of this approach for detecting nonrespiratory illness and more localized outbreaks.