Surveillance Alerts Research Articles

1372. Unprecedented West Nile Virus Outbreak — Maricopa County, Arizona, 2021

Abstract Background West Nile virus (WNV) causes a mosquito-borne disease that can lead to permanent paralysis or death. WNV became endemic in Maricopa County in 2003. The Maricopa County Department of Public Health (MCDPH) and Environmental Services Department Vector Control (MCESD VC) and Arizona Department of Health Services (ADHS) collaborated to monitor and respond to mosquito surveillance and human WNV cases. We describe an unprecedented WNV outbreak in 2021. Methods MCESD VC monitored vector complaints, mosquito vector positive traps, and vector index (VI) data. Reported human cases (using the CSTE/CDC case definition) were interviewed by MCDPH. MCDPH and ADHS sent surveillance alerts to healthcare providers regarding WNV symptomology and clinical testing guidance. MCDPH consulted with providers and/or Infection Preventionists during case investigations. Results The first WNV-positive mosquito trap occurred the week of May 1 (VI=0.235); VI peaked the week of September 11 at 53.608; the last positive trap was the week of November 20. MCESD VC fogged >400,000 acres (∼2x the 10-year average) with adulticide, applied larvicide to ∼25,000 sites, and received ∼9,500 mosquito complaints (40% more than prior season). During the 2021 WNV season, 1,487 cases were reported, of which 960 (64.6%) had neuroinvasive illnesses (WNND) and 101 (6.8%) died (all were WNND cases). Median case age was 66 (IQR=53–75) years; for deaths, it was 79 (IQR=71-83) years. In total, 1,017 (68.4%) cases were hospitalized with a median length of stay (LOS) of 7 (IQR=4–10) days. WNND cases accounted for 91.2% of hospitalizations. Median LOS for hospitalized WNND cases was 7 (IQR=4-11) days, compared to 4 (IQR=2-6) days for non-neuroinvasive cases. Despite 3 surveillance alerts sent to providers and media coverage, providers were not consistently aware of the WNV outbreak or that serum can be tested for WNV. Conclusion This was the largest WNV outbreak in Maricopa County. It taxed an already stressed healthcare system during the COVID-19 pandemic with over 1,000 hospitalized cases, including nearly 100 in people without WNND. During WNV season, clinicians should consider WNV testing of both serum and CSF in severely ill patients with and without evidence of neuroinvasive disease. Disclosures Ariella P. Dale, PhD, MPH, Infectious Disease Society of America - Arizona Chapter: Honoraria Karen Zabel, MSN RN, Express Scripts: Immediate family member employment.

A Visual Aquaculture System Using a Cloud-Based Autonomous Drones

This paper presents a low-cost and cloud-based autonomous drone system to survey and monitor aquaculture sites. We incorporated artificial intelligence (AI) services using computer vision and combined various deep learning recognition models to achieve scalability and added functionality, in order to perform aquaculture surveillance tasks. The recognition model is embedded in the aquaculture cloud, to analyze images and videos captured by the autonomous drone. The recognition models detect people, cages, and ship vessels at the aquaculture site. The inclusion of AI functions for face recognition, fish counting, fish length estimation and fish feeding intensity provides intelligent decision making. For the fish feeding intensity assessment, the large amount of data in the aquaculture cloud can be an input for analysis using the AI feeding system to optimize farmer production and income. The autonomous drone and aquaculture cloud services are cost-effective and an alternative to expensive surveillance systems and multiple fixed-camera installations. The aquaculture cloud enables the drone to execute its surveillance task more efficiently with an increased navigation time. The mobile drone navigation app is capable of sending surveillance alerts and reports to users. Our multifeatured surveillance system, with the integration of deep-learning models, yielded high-accuracy results.

Implementation of an Air Quality Forecasting Operating System for Health Surveillance and Sustainability in the Salvador Metropolitan Region, Brazil

Air pollution is a threat to public health in the 21st century. In Latin America, more than 100 million people are exposed to air pollution. There is a gap in air quality monitoring in cities around the world. Environmental risk factor monitoring and forecasting systems are strategic for the adoption of preventive measures and health surveillance alerts. The engagement of stakeholders is crucial to develop strategies to control air pollution. Objective: To define air quality and health risk indicators relevant to health surveillance and civil defense, allowing the mapping of areas of higher risk and vulnerability for the population. Methodology: The SOPRAR project was built through an articulated intersectoral mobilization, scientific institutions, private and public sector. The project includes the configuration of emission, chemical, and transportation models to represent the local conditions. The system operates based on CHIMERE model runs (48h forecast) forced by weather forecast simulations (WRF) performed by the local civil defense, integrating a updated emissions inventory. Model results, pollutants concentration maps and air quality index, will be available by WEB service. A tailored health risk indicator will be developed to make the SOPRAR system. The project is committed with the technology and know-how transfer to local actors. Results: The emission inventory was updated based on available local data regarding traffic, road network, industries processes and land use. Total emissions in the Salvador Metropolitan Region corresponds to 3327.03 tons/year of Particulate Matter, 14964.32 tons/year of Sulfur Dioxide, 75572.28 tons/year of Carbon Monoxide, 24756.30 tons/year of Nitrogen Oxides and 21756.64 tons/year of Volatile Organic. Considerations: The system is as an innovative management tool based on urban environment air quality modeling and will provide support for the activation of air quality protection and communication service protocols for use in research, public policies for primary care and health surveillance.

The effect of medication related clinical decision support at the time of physician order entry

Background In advanced clinical decision support systems, patient characteristics and laboratory values are included in the algorithms that generate alerts. These alerts have a higher specificity than basic medication surveillance alerts. The alerts of advanced clinical decision support systems can be shown directly to the prescriber during order entry, without the risk of generating an overload of irrelevant alerts. We implemented five advanced algorithms that are shown directly to the prescriber. These algorithms are for gastrointestinal prophylaxis, folic or folinic acid prescribed with orally or subcutaneously administered methotrexate, vitamin D prescribed with bisphosphonates, hyponatremia and measuring plasma levels for vancomycin and gentamicin. Objective We evaluated the effect of the implementation of the algorithms. Setting We performed prospective intervention studies with a historical group for comparison in both inpatients and outpatients at a teaching hospital in the Netherlands. Methods We compared the time period after implementation of the algorithm with the time period before implementation, using data from the hospital information system Epic. Difference in guideline adherence were analyzed using Chi square tests. Main outcome measure The outcome measures were the number of alerts, the acceptance rate of the advice in the alert, and for the algorithm measuring plasma levels for vancomycin and gentamicin the time to the correct dose. Results For all algorithms, the implementation resulted in a significant increase in guideline adherence, varying from 11 to 36%. The acceptance rate varied from 14% for hyponatremia to 90% for methotrexate. For gastrointestinal prophylaxis the acceptance rate was 4.4% for basic drug-drug interaction alerts when no gastrointestinal prophylaxis was prescribed and increased to 44.7% after implementation of the advanced algorithm. This algorithm substantially decreased the number of alerts from 812 before implementation to 217 after implementation. After implementation of the algorithm for measuring plasma levels for vancomycin and gentamicin, the proportion of patients receiving the correct dose after 48h increased from 73 to 84% (p = 0.03). Conclusion Implementation of advanced algorithms that take patient characteristics into account and are shown directly to the physician during order entry, result in an increased guideline adherence.

1025. Inappropriate Aztreonam Usage – Antimicrobial Stewardship Strikes Back

BackgroundSeveral studies have demonstrated that patients with reportedly β-lactam allergies (BLA) receive less efficacious and more toxic alternative antibiotics. A previous study at our institution utilizing aztreonam as a surrogate marker for BLA demonstrated nearly 50% of patients receiving aztreonam had previously tolerated an alternative β-lactam (BL). In response to those results, our Antimicrobial Stewardship Program (ASP) provided dedicated hospitalist, medical resident and pharmacist education on appropriate utilization of aztreonam and BLA. Additionally, members of the ASP team began receiving real-time clinical surveillance alerts for all aztreonam orders.MethodsA retrospective chart review of inpatients >18 years old who received at least one dose of aztreonam between July 1, 2018 – December 31, 2018. Patients were excluded if they did not have a documented BLA or if they received aztreonam as de-escalation therapy. Cost of aztreonam therapy was compared with the cost of alternative BL agents based on prior and subsequently tolerated classes of BLs. Comparator agents included: piperacillin/tazobactam (penicillin), cefepime (cephalosporin) and meropenem (carbapenem). Comparisons of total number of aztreonam patients and doses, cost of aztreonam, and cost of alternative therapy were compared with the index population from 2017ResultsSimilar to our prior study, 43.7% (48.5% in 2017) had prior BL tolerance with an additional 31.3% (19.4% in 2017) demonstrated subsequent BL tolerance following aztreonam administration. Following the ASP interventions, orders, doses and cost of aztreonam was reduced. Forty-eight patients during the 6-month period received aztreonam, a 26.7% reduction. There was a 38.5% reduction in the number of aztreonam doses (P = 0.001), which yielded a cost savings of $14,067.67 (extrapolated to 1 year). Median aztreonam cost in 2017 $382.40 vs. $191.20 in 2018 (P = 0.004). In 2018, 41.7% of patient’s allergy profiles were appropriately updated compared with 3.3% in 2017.ConclusionOur study demonstrates that ASP interventions including increased education, allergy documentation and clinical surveillance alerts targeted at reducing aztreonam utilization can reduce pharmaceutical expenditures. Disclosures All authors: No reported disclosures.

National Surveillance for Health-Related Workplace Absenteeism, United States 2017-18

National Surveillance for Health-Related Workplace Absenteeism, United States 2017-18

Characterizing the Effects of Extreme Cold Using Real-time Syndromic Surveillance, Ontario, Canada, 2010-2016.

Morbidity and mortality from exposure to extreme cold highlight the need for meaningful temperature thresholds to activate public health alerts. We analyzed emergency department (ED) records for cold temperature-related visits collected by the Acute Care Enhanced Surveillance system-a syndromic surveillance system that captures data on ED visits from hospitals in Ontario-for geographic trends related to ambient winter temperature. We used 3 Early Aberration Reporting System algorithms of increasing sensitivity-C1, C2, and C3-to determine the temperature at which anomalous counts of cold temperature-related ED visits occurred in northern and southern Ontario from 2010 to 2016. The C2 algorithm was the most sensitive detection method. Results showed lower threshold temperatures for Acute Care Enhanced Surveillance alerts in northern Ontario than in southern Ontario. Public health alerts for cold temperature warnings that are based on cold temperature-related ED visit counts and ambient temperature may improve the accuracy of public warnings about cold temperature risks.

Evaluation of the ability of standardized supports to improve public health response to syndromic surveillance for respiratory diseases in Canada

BackgroundDespite widespread implementation of syndromic surveillance systems within public health agencies, previous studies of the implementation and use of these systems have indicated that the functions and responses taken in response to syndromic surveillance data vary widely according to local context and preferences. The objective of the Syndromic Surveillance Evaluation Study was to develop and implement standardized supports in local public health agencies in Ontario, Canada, and evaluate the ability of these supports to affect actions taken as part of public health communicable disease control programs.MethodsLocal public health agencies (LPHA) in Ontario, which used syndromic surveillance based on emergency department visits for respiratory disease, were recruited and randomly allocated to the study intervention or control group. The intervention group health agencies received standardized supports in terms of a standardized aberrant event detection algorithm and a response protocol dictating steps to investigate and assess the public health significance of syndromic surveillance alerts. The control group continued with their pre-existing syndromic surveillance infrastructure and processes. Outcomes were assessed using logbooks, which collected quantitative and qualitative information about alerts received, investigation steps taken, and public health responses. The study was conducted prospectively for 15 months (October 2013 to February 2015).ResultsFifteen LPHAs participated in the study (n = 9 intervention group, n = 6 control group). A total of 1,969 syndromic surveillance alerts were received by all LPHAs. Variations in the types and amount of responses varied by LPHA, in particularly differences were noted by the size of the health unit. Smaller health units had more challenges to both detect and mount a response to any alerts. LPHAs in the control group were more likely to declare alerts to have public health significance and to initiate any action. Regression models using repeated measures showed an interaction between the year (Year 1 versus Year 2) and the intervention as well as an interaction between year and sustained nature of the alert. Both of these were linked to the control health units reporting more “watchful waiting”.ConclusionsThis study raises questions about the effectiveness of using standardized protocols to improve the performance of syndromic surveillance in a decentralized public health system. Despite efforts to create standardized protocols and engage public health agencies in the process, no significant differences in the effective use of syndromic alerts were observed beyond year 1. It also raises questions about the minimum capacity of the agency and minimum population size that are required for an effective response.

Secondary Analysis of an Electronic Surveillance System Combined with Multi-focal Interventions for Early Detection of Sepsis.

Propensity score matching was used to select subsets of the cohorts with balanced covariates. Bootstrapping was performed to build distributions of the measured difference in rates/means. The effect of the sepsis intervention was evaluated for all patients, and High and Low Risk subgroups for illness severity. A separate analysis was performed patients on the intervention and non-intervention units (without the electronic surveillance). Sensitivity, specificity, and the positive predictive values were calculated to evaluate the accuracy of the alerting system for detecting sepsis or severe sepsis/ septic shock. There was positive effect on the intervention units with sepsis electronic surveillance with an adjusted mortality rate of -6.6%. Mortality rates for non-intervention units also improved, but at a lower rate of -2.9%. Additional outcomes improved for patients on both intervention and non-intervention units for home discharge (7.5% vs 1.1%), total length of hospital stay (-0.9% vs -0.3%), and 30 day readmissions (-6.6% vs -1.6%). Patients on the intervention units showed better outcomes compared with non-intervention unit patients, and even more so for High Risk patients. The sensitivity was 95.2%, specificity of 82.0% and PPV of 50.6% for the electronic surveillance alerts. There was improvement over time across the hospital for patients on the intervention and non-intervention units with more improvement for sicker patients. Patients on intervention units with electronic surveillance have better outcomes; however, due to differences in exclusion criteria and types of units, further study is needed to draw a direct relationship between the electronic surveillance system and outcomes.

Public Health Surveillance Strategies for Mass Gatherings: Super Bowl XLIX and Related Events, Maricopa County, Arizona, 2015.

Super Bowl XLIX took place on February 1, 2015, in Glendale, Arizona. In preparation for this event and associated activities, the Maricopa County Department of Public Health (MCDPH) developed methods for enhanced surveillance, situational awareness, and early detection of public health emergencies. Surveillance strategies implemented from January 22 to February 6, 2015, included enhanced surveillance alerts; animal disease surveillance; review of NFL clinic visits; syndromic surveillance for emergency room visits, urgent care facilities, and hotels; real-time onsite syndromic surveillance; all-hazards mortality surveillance; emergency medical services surveillance, review of poison control center reports; media surveillance; and aberration detection algorithms for notifiable diseases. Surveillance results included increased influenzalike illness activity reported from urgent care centers and a few influenza cases reported in the NFL clinic. A cyanide single event exposure was investigated and determined not to be a public health threat. Real-time field syndromic surveillance documented minor injuries at all events and sporadic cases of gastrointestinal and neurological (mostly headaches) disease. Animal surveillance reports included a cat suspected of carrying plague and tularemia and an investigation of highly pathogenic avian influenza in a backyard chicken flock. Laboratory results in both instances were negative. Aberration detection and syndromic surveillance detected an increase in measles reports associated with a Disneyland exposure, and syndromic surveillance was used successfully during this investigation. Coordinated enhanced epidemiologic surveillance during Super Bowl XLIX increased the response capacity and preparedness of MCDPH to make informed decisions and take public health actions in a timely manner during these mass gathering events.

Characterizing Public Health Actions in Response to Syndromic Surveillance Alerts

Fifteen public health units (PHUs) in Ontario, Canada were randomized to the intervention (9) or control (6) arm of a study on their responses to alerts for respiratory syndromes from emergency department data. The intervention PHUs implemented a standard protocol while the control PHUs continued with usual practices. Intervention PHUs were 3 times more likely to check for alternate explanations. Control health units decided that more alerts warranted a response (53%) but most of these were "watchful waiting". For intervention PHUs, the proportion requiring action was lower (18%). Less than 10% of the alerts led to action.

Public health surveillance response following the southern Alberta floods, 2013.

In June of 2013, southern Alberta underwent flooding that affected approximately 100,000 people. We describe the process put in place for public health surveillance and assessment of the impacts on health. Public health surveillance was implemented for the six-week period after the flood to detect anticipated health events, including injuries, mental health problems and infectious diseases. Data sources were emergency departments (EDs) for presenting complaints, public health data on the post-exposure administration of tetanus vaccine/immunoglobulin, administrative data on prescription drugs, and reportable diseases. An increase in injuries was detected through ED visits among Calgary residents (rate ratio [RR] 1.28, 95% confidence interval [CI]: 1.14-1.43) and was supported by a 75% increase in the average weekly administration of post-exposure prophylaxis against tetanus. Mental health impacts in High River residents were observed among females through a 1.64-fold (95% CI: 1.11-2.43) and 2.32-fold (95% CI: 1.45-3.70) increase in new prescriptions for anti-anxiety medication and sleep aids respectively. An increase in sexual assaults presenting to EDs (RR 3.18, 95% CI: 1.29-7.84) was observed among Calgary residents. No increases in infectious gastrointestinal disease or respiratory illness were identified. Timely identification and communication of surveillance alerts allowed for messaging around the use of personal protective equipment and precautions for personal safety. Existing data sources were used for surveillance following an emergency situation. The information produced, though limited, was sufficiently timely to inform public health decision-making.

Adecuación de ranelato de estroncio tras alertas de farmacovigilancia en un área de gestión sanitaria

ObjectiveTo analyse the impact of a strategy on the suitability of strontium ranelate, and its level of acceptance, after issuing recommendations based on drug surveillance alerts issued by the Spanish Medicines and Medical Devices Agency. DesignA prospective interventional study conducted from April 2012 to November 2014. SettingSouth Seville Health Management Area. ParticipantsPatients currently prescribed with strontium ranelate. InterventionsThe study consisted of four phases linked to the issue of drug surveillance alerts on strontium ranelate by the Spanish Medicines and Medical Devices Agency, listed by patients and suitability recommendations. Main measurementsSuitability of strontium ranelate treatment and the level of acceptance by physicians. ResultsThere was a reduction of 87.9% in prescriptions from the beginning of the study, with 182 patients included, until the review of the suitability of the drug began. The prescribing of strontium ranelate was unsuitable in 16 out of the 22 patients remaining; 11 of which were due not meeting the treatment criteria, 3 for not having had previous treatments with other drugs for the prevention of fractures, and 2 due to contraindications. The level of acceptance of the recommendations was 87.5%, leading to the stopping of strontium ranelate in 10 patients, and the changing to alendronate or alendronate/cholecalciferol in another four patients. ConclusionsThe number of patients prescribed strontium ranelate has decreased considerably. The interventions directed at reviewing the suitability of this treatment, based on the drug surveillance alerts, have been effective.

Electronic Epidemiologic Biosurveillance in the Cameroon Military

Electronic epi-biosurveillance presents an opportunity to provide real-time disease surveillance alerts from remote areas to central disease management units, to rapidly decrease reporting times for reportable diseases, and to enable appropriate response scenarios to be put in place in a timely manner. Piloting the SAGES system in Cameroon, a resource-limited country in central Africa, has benefits and challenges in developing systems of public health engagement.

Utility of System Generated Syndromic Surveillance Alerts to Detect Reportable Disease Outbreaks

In light of recent outbreaks of pertussis, the ability of Florida Department of Health's (FDOH) Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE-FL) to detect emergent disease outbreaks was examined. Florida's syndromic surveillance system, ESSENCE-FL, has the capacity to monitor reportable disease case data from Merlin, the Bureau of Epidemiology's secure web-based reporting and epidemiologic analysis system. In this study we determine the utility of ESSENCE-FL system generated disease alerts originally designed for use with emergency department chief complaint data to reportable disease data to assist in timely detection of outbreaks to promote appropriate response measures.

Use of Workplace Absenteeism Surveillance Data for Outbreak Detection

To the Editor: We applaud Mann et al. on their use of a school-based absenteeism surveillance system to compare daily all-causes absenteeism data against a historic baseline to detect outbreaks of influenza-like illness (ILI) as an adjunct to traditional disease reporting (1). The growing availability of electronic human resources systems has increased the potential to harness near real-time workplace absenteeism data to complement school absenteeism surveillance and other sources of traditional outbreak surveillance. In London, United Kingdom, during the first wave of pandemic influenza A (H1N1) 2009, workplace absenteeism data from the Transport for London attendance/absence reporting system were compared with the historical baseline 3-year mean for comparative weeks of the year. The proportion of Transport for London employees absent because of self-reported or medically certified ILI, during June 28–October 17, 2010, generated surveillance alerts when compared with historical baseline data above the 95th and 99th percentile thresholds (SDs 1.96 and 2.58). For the same period, cause-specific workplace influenza absenteeism data were highly correlated with routinely published ILI surveillance, including the National Pandemic Flu Surveillance and sentinel General Practitioner systems (Figure) (2). Figure Comparison of transport for London absenteeism rates from influenza data to syndromic surveillance indicators of influenza-like illness rates, London, United Kingdom, 2009. A) National Pandemic Flu Service (NPFS); B) Royal College of General Practitioners ... In Australia, workplace all-causes absenteeism for a major Australia-wide employer has been included as a nonspecific indicator of influenza surveillance by the Australian government for >15 years. A recent study during a severe influenza season in Australia confirmed that employee absenteeism was highly correlated with laboratory-confirmed influenza, and such information could be used to provide surveillance alerts up to 2 weeks before other traditional influenza surveillance data sources (3). The use of workplace absenteeism data, particularly from large employers, has the potential for overcoming the major limitation of school-based absenteeism data in detecting outbreaks of ILI: the effects of school holidays and local planned school closures. Near real-time workplace absenteeism is an effective surveillance tool and should be more widely incorporated in influenza surveillance systems.

Optimizing the response to surveillance alerts in automated surveillance systems

Although much research effort has been directed toward refining algorithms for disease outbreak alerting, considerably less attention has been given to the response to alerts generated from statistical detection algorithms. Given the inherent inaccuracy in alerting, it is imperative to develop methods that help public health personnel identify optimal policies in response to alerts. This study evaluates the application of dynamic decision making models to the problem of responding to outbreak detection methods, using anthrax surveillance as an example. Adaptive optimization through approximate dynamic programming is used to generate a policy for decision making following outbreak detection. We investigate the degree to which the model can tolerate noise theoretically, in order to keep near optimal behavior. We also evaluate the policy from our model empirically and compare it with current approaches in routine public health practice for investigating alerts. Timeliness of outbreak confirmation and total costs associated with the decisions made are used as performance measures. Using our approach, on average, 80 per cent of outbreaks were confirmed prior to the fifth day of post-attack with considerably less cost compared to response strategies currently in use. Experimental results are also provided to illustrate the robustness of the adaptive optimization approach and to show the realization of the derived error bounds in practice.

Tailoring adverse drug event surveillance to the paediatric inpatient

IntroductionAlthough paediatric patients have an increased risk for adverse drug events, few detection methodologies target this population. To utilise computerised adverse event surveillance, specialised trigger rules are required to accommodate the unique needs of children. The aim was to develop new, tailored rules sustainable for review and robust enough to support aggregate event rate monitoring.MethodsThe authors utilised a voluntary staff incident-reporting system, lab values and physician insight to design trigger rules. During Phase 1, problem areas were identified by reviewing 5 years of paediatric voluntary incident reports. Based on these findings, historical lab electrolyte values were analysed to devise critical value thresholds. This evidence informed Phase 2 rule development. For 3 months, surveillance alerts were evaluated for occurrence of adverse drug events.ResultsIn Phase 1, replacement preparations and total parenteral nutrition comprised the majority (36.6%) of adverse drug events in 353 paediatric patients. During Phase 2, nine new trigger rules produced 225 alerts in 103 paediatric inpatients. Of these, 14 adverse drug events were found by the paediatric hypoglycaemia rule, but all other electrolyte trigger rules were ineffective. Compared with the adult-focused hypoglycaemia rule, the new, tailored version increased the paediatric event detection rate from 0.43 to 1.51 events per 1000 patient days.ConclusionsRelying solely on absolute lab values to detect electrolyte-related adverse drug events did not meet our goals. Use of compound rule logic improved detection of hypoglycaemia. More success may be found in designing real-time rules that leverage lab trends and additional clinical information.

Framework for the Development of Response Protocols for Public Health Syndromic Surveillance Systems: Case Studies of 8 US States

To describe current syndromic surveillance system response protocols in health departments from 8 diverse states in the United States and to develop a framework for health departments to use as a guide in initial design and/or enhancement of response protocols. Case study design that incorporated in-depth interviews with health department staff, textual analysis of response plans, and a Delphi survey of syndromic surveillance response experts. All 8 states and 30 of the 33 eligible health departments agreed to participate (91% response rate). Fewer than half (48%) of surveyed health departments had a written response protocol, and health departments reported conducting in-depth investigations on fewer than 15% of syndromic surveillance alerts. A convened panel of experts identified 32 essential elements for inclusion in public health protocols for response to syndromic surveillance system alerts. Because of the lack of guidance, limited resources for development of response protocols, and few examples of syndromic surveillance detecting previously unknown events of public health significance, health departments have not prioritized the development and refinement of response protocols. Systems alone, however, are not effective without an organized public health response. The framework proposed here can guide health departments in creating protocols that will be standardized, tested, and relevant given their goals with such systems.

Congenital anomaly surveillance in England and Wales

The National Congenital Anomaly System (NCAS) was set up in 1964, following the thalidomide epidemic, as a monitoring system designed to detect changes in the frequency of reporting of malformations. Its original aim was to detect anomalies reported within 7 days of birth. The NCAS is voluntary at all stages and covers all live- and stillbirths. It has two tiers; a 'passive system' receiving congenital anomaly notifications through a standard paper notification form, known as the SD56, and the congenital anomaly registers that send notifications electronically. Congenital anomalies are classified using the International Classification of Diseases codes and 10 monitoring groups. The Office for National Statistics performs a statistical analysis on a monthly, quarterly and annual basis, using the cumulative sum technique, which is the basis upon which surveillance alerts are raised within the system. The NCAS is now an open database where congenital anomalies can be notified whenever they are detected. The aim of this paper is to describe the current operation and uses of the NCAS based on guidelines for the evaluation of public health surveillance systems published by the Centers for Disease Control and Prevention.