Syndromic surveillance and bioterrorism-related epidemics

Clinical manifestations of Rift Valley fever in humans: Systematic review and meta-analysis

BACKGROUND

Rift Valley fever (RVF) is an emerging, neglected, mosquito-borne viral zoonosis associated with significant morbidity, mortality and expanding geographical scope. The clinical signs and symptoms in humans are non-specific and case definitions vary. We reviewed and analysed the clinical manifestations of RVF in humans.

METHODS

In this systematic review and meta-analysis we searched on different dates, the Embase (from 1947 to 13th October 2019), Medline (1946 to 14th October 2019), Global Health (1910 to 15th October 2019), and Web of Science (1970 to 15th October 2019) databases. Studies published in English, reporting frequency of symptoms in humans, and laboratory confirmed RVF were included. Animal studies, studies among asymptomatic volunteers, and single case reports for which a proportion could not be estimated, were excluded. Quality assessment was done using a modified Hoy and Brooks et al tool, data was extracted, and pooled frequency estimates calculated using random effects meta-analysis.

RESULTS

Of the 3765 articles retrieved, less than 1% (32 articles) were included in the systematic review and meta-analysis. Nine RVF clinical syndromes were reported including the general febrile, renal, gastrointestinal, hepatic, haemorrhagic, visual, neurological, cardio-pulmonary, and obstetric syndromes. The most common clinical manifestations included fever (81%; 95% Confidence Interval (CI) 69-91; [26 studies, 1286 patients]), renal failure (41%; 23-59; [4, 327]), nausea (38%; 12-67; [6, 325]), jaundice (26%; 16-36; [15, 393]), haemorrhagic disease (26%; 17-36; [16, 277]), partial blindness (24%; 7-45; [11, 225]), encephalitis (21%; 11-33; [4, 327]), cough (4%; 0-17; [4, 11]), and miscarriage (54%) respectively. Death occurred in 21% (95% CI 14-29; [16 studies, 328 patients]) of cases, most of whom were hospitalised.

DISCUSSION

This study delineates the complex symptomatology of human RVF disease into syndromes. This approach is likely to improve case definitions and detection rates, impact outbreak control, increase public awareness about RVF, and subsequently inform 'one-health' policies. This study provides a pooled estimate of the proportion of RVF clinical manifestations alongside a narrative description of clinical syndromes. However, most studies reviewed were case series with small sample sizes and enrolled mostly in-patients and out-patients, and captured symptoms either sparsely or using broad category terms.

Emergency department syndromic surveillance systems: a systematic review

BACKGROUND

Syndromic surveillance provides public health intelligence to aid in early warning and monitoring of public health impacts (e.g. seasonal influenza), or reassurance when an impact has not occurred. Using information collected during routine patient care, syndromic surveillance can be based on signs/symptoms/preliminary diagnoses. This approach makes syndromic surveillance much timelier than surveillance requiring laboratory confirmed diagnoses. The provision of healthcare services and patient access to them varies globally. However, emergency departments (EDs) exist worldwide, providing unscheduled urgent care to people in acute need. This provision of care makes ED syndromic surveillance (EDSyS) a potentially valuable tool for public health surveillance internationally. The objective of this study was to identify and describe the key characteristics of EDSyS systems that have been established and used globally.

METHODS

We systematically reviewed studies published in peer review journals and presented at International Society of Infectious Disease Surveillance conferences (up to and including 2017) to identify EDSyS systems which have been created and used for public health purposes. Search criteria developed to identify "emergency department" and "syndromic surveillance" were applied to NICE healthcare, Global Health and Scopus databases.

RESULTS

In total, 559 studies were identified as eligible for inclusion in the review, comprising 136 journal articles and 423 conference abstracts/papers. From these studies we identified 115 EDSyS systems in 15 different countries/territories across North America, Europe, Asia and Australasia. Systems ranged from local surveillance based on a single ED, to comprehensive national systems. National EDSyS systems were identified in 8 countries/territories: 2 reported inclusion of ≥85% of ED visits nationally (France and Taiwan).

CONCLUSIONS

EDSyS provides a valuable tool for the identification and monitoring of trends in severe illness. Technological advances, particularly in the emergency care patient record, have enabled the evolution of EDSyS over time. EDSyS reporting has become closer to 'real-time', with automated, secure electronic extraction and analysis possible on a daily, or more frequent basis. The dissemination of methods employed and evidence of successful application to public health practice should be encouraged to support learning from best practice, enabling future improvement, harmonisation and collaboration between systems in future.

PROSPERO NUMBER

CRD42017069150 .

Hospital Preparedness Measures for Biological Hazards: A Systematic Review and Meta-Synthesis

BACKGROUND

Biological hazards are one of the most important and common types of hazards in emergencies and disasters. Hospital preparedness measures for biological hazards are essential for a proper response and mitigation of its effects. The aim of this systematic review is to investigate hospital preparedness measures for biological hazards.

METHODS

For this research, electronic databases including Web of Science, PubMed, ScienceDirect, Scopus, ProQuest, Google Scholar, and Cochrane Library from March 1950 to June 2019 were searched. Key words such as hospital, emergency department, preparedness, plan, management, and biological hazards were used in combination with the Boolean operators OR and AND. A thematic synthesis approach through the use of MAXQDA software was applied to analyze the data.

RESULTS

In total, 5257 articles were identified, in which 23 articles meet the inclusion criteria for entering the process of final analysis. The findings showed three main administrative, specialized, and logistical issues regarding preparedness measures for biological hazards in hospitals.

CONCLUSION

Hospital preparedness for biological hazards is one of the most important hospital disaster plans. Results of this systematic review present valuable advice for policy-makers and hospital managers to prepare and enhance hospital performance against biological hazards.

Opportunities and Challenges for Developing Syndromic Surveillance Systems for the Detection of Social Epidemics

This commentary explores the potential and challenges of developing syndromic surveillance systems with the ability to more rapidly detect epidemics of addiction, poverty, housing instability, food insecurity, social isolation and other social determinants of health (SDoH). Epidemiologists tracking SDoH heavily rely on expensive government surveys released annually, delaying for months if not years the timely detection of social epidemics, defined as sudden, rapid or unexpected changes in social determinants of population health. Conversely, infectious disease syndromic surveillance is an effective early warning tool for epidemic diseases using various types of non-traditional epidemiological data from emergency room chief complaints to search query data. Based on such experience, novel social syndromic surveillance systems for early detection of social epidemics with health implications are not only possible but necessary. Challenges to their widespread implementation include incorporating disparate proprietary data sources and database integration. Significantly more resources are critically needed to address these barriers to allow for accessing, integrating and rapidly analyzing appropriate data streams to make syndromic surveillance for social determinants of health widely available to public health professionals.

A re-organizing biosurveillance framework based on fog and mobile edge computing

Biological threats are becoming a serious security issue for many countries across the world. Effective biosurveillance systems can primarily support appropriate responses to biological threats and consequently save human lives. Nevertheless, biosurveillance systems are costly to implement and hard to operate. Furthermore, they rely on static infrastructures that might not cope with the evolving dynamics of the monitored environment. In this paper, we present a reorganizing biosurveillance framework for the detection and localization of biological threats with fog and mobile edge computing support. In the proposed framework, a hierarchy of fog nodes are responsible for aggregating monitoring data within their regions and detecting potential threats. Although fog nodes are deployed on a fixed base station infrastructure, the framework provides an innovative technique for reorganizing the monitored environment structure to adapt to the evolving environmental conditions and to overcome the limitations of the static base station infrastructure. Evaluation results illustrate the ability of the framework to localize biological threats and detect infected areas. Moreover, the results show the effectiveness of the reorganization mechanisms in adjusting the environment structure to cope with the highly dynamic environment.

Syndromic surveillance using ambulance transfer data in Tokyo, Japan

Bioterrorism attacks become more probable when important high-profile international or political events are held, such as G7 summit meetings or mass gathering events including Olympic and Paralympic games and FIFA World Cup tournaments. Outbreaks of infectious disease and widespread incidents of food poisoning are also public health concerns at such times. In Japan, the Tokyo Metropolitan Government operates Ambulance Transfer Syndromic Surveillance (ATSS), which can help monitor such incidents. The present study presents and assesses the ATSS framework. During the study period of October 2017 through November 2018, we monitored 33 areas for symptoms of 9 categories: vomiting/nausea, dizziness, palpitation, unconsciousness, breathing disorder, fever, spasm/paralysis, collapse/weakness, and bloody emesis/nasal hemorrhage. Among all symptoms, we found 9929 low-level aberrations, 2537 medium-level aberrations, and 577 high-level aberrations, with respective frequencies of 9.2%, 2.3%, and 0.5%. Of those, Tokyo Metropolitan Institute of Public Health reported the information to Tokyo Metropolitan Government 28 times during the period. Of the 28 identified clusters, Tokyo Metropolitan Government judged the necessity for investigating 7. All of those were investigated at hospitals by the jurisdictional public health center. Because ATSS covers almost the entire Tokyo metropolitan area, with about 13.8 million residents, it is definitely the largest syndromic surveillance in the world.

Public health delivery in the information age: the role of informatics and technology

AIM

Public health systems have embraced health informatics and information technology as a potential transformational tool to improve real-time surveillance systems, communication, and sharing of information among various agencies. Global pandemic outbreaks like Zika and Ebola were quickly controlled due to electronic surveillance systems enabling efficient information access and exchange. However, there is the need for a more robust technology to enhance adequate epidemic forecasting, data sharing, and effective communication. The purpose of this review was to examine the use of informatics and information technology tools and its impact on public health delivery.

METHOD

Investigators searched six electronic databases. These were MEDLINE, Cumulative Index to Nursing and Allied Health Literature (CINAHL) Complete, Cochrane Database of Systematic Reviews, COMPENDEX, Scopus, and Academic Search Premier from January 2000 to 31 March 2016.

RESULTS

A total of 60 articles met the eligibility criteria for inclusion. These studies were organized into three areas as (1) definition of the term public health informatics; (2) type of public health surveillance systems and implications for public health; and (3) electronic surveillance systems functionality, capability, training, and challenges. Our analysis revealed that due to the growing expectations to provide real-time response and population-centered evidence-based public health in this information-driven age there has been a surge in informatics and information technology adoption. Education and training programs are now available to equip public health students and professionals with skills in public health informatics. However, obstacles including interoperability, data standardization, privacy, and technology transfer persist.

CONCLUSION

Re-engineering the delivery of public health is necessary to meet the demands of the 21st century and beyond. To meet this expectation, public health must invest in workforce development and capacity through education and training in informatics.

Descriptive Study of Foodborne Disease Using Case Monitoring Data in Shandong Province, China, 2016-2017

BACKGROUND

In order to generate data on the burden of foodborne diseases in Shandong Province, we aimed to use the case monitoring data of foodborne diseases from 2016 to 2017 to estimate.

METHODS

Data were obtained from the foodborne disease surveillance reporting system with dates of onset from Jan 1, 2016, to Dec 31, 2017, in Shandong, China.

RESULTS

The places of food exposure were categorized by settings as follows: private home, catering facility, collective canteens, retail markets, rural banquets and other. Exposed food is divided into 23 categories. Overall incidence rate and proportions by exposure categories, age, and sex-specific incidence rates were calculated and sex proportions compared. Approximately 75.00% of cases who had at least one exposure settings were in private homes. The most frequently reported exposed food was a variety of food (meaning more than two kinds of food). The two-year average incidence rate was 75.78/100,000, sex-specific incidence rate was much higher for females compared to males (78.23 vs. 74.69 cases per 100,000 population). An age-specific trend was observed in the cases reported (Chi-Square for linear trend, χ²=4.39, P=0.036<0.05).

CONCLUSION

A preliminary estimate of 14 million cases of foodborne diseases in Shandong province each year. Future studies should focus on cross-sectional and cohort studies to facilitate the assessment of the distribution and burden of foodborne disease of the population in Shandong. Considering strengthening the burden of foodborne diseases in foodborne disease surveillance is also a feasible way.

Global Research on Syndromic Surveillance from 1993 to 2017: Bibliometric Analysis and Visualization

Syndromic Surveillance aims at analyzing medical data to detect clusters of illness or forecast disease outbreaks. Although the research in this field is flourishing in terms of publications, an insight of the global research output has been overlooked. This paper aims at analyzing the global scientific output of the research from 1993 to 2017. To this end, the paper uses bibliometric analysis and visualization to achieve its goal. Particularly, a data processing framework was proposed based on citation datasets collected from Scopus and Clarivate Analytics’ Web of Science Core Collection (WoSCC). The bibliometric method and Citespace were used to analyze the institutions, countries, and research areas as well as the current hotspots and trends. The preprocessed dataset includes 14,680 citation records. The analysis uncovered USA, England, Canada, France and Australia as the top five most productive countries publishing about Syndromic Surveillance. On the other hand, at the Pinnacle of academic institutions are the US Centers for Disease Control and Prevention (CDC). The reference co-citation analysis uncovered the common research venues and further analysis of the keyword cooccurrence revealed the most trending topics. The findings of this research will help in enriching the field with a comprehensive view of the status and future trends of the research on Syndromic Surveillance.

The Impact of Law on Syndromic Disease Surveillance Implementation

CONTEXT

Legal environments influence how health information technologies are implemented in public health practice settings. Syndromic disease surveillance (SyS) is a relatively new approach to surveillance that depends heavily on health information technologies to achieve rapid awareness of disease trends. Evidence suggests that legal concerns have impeded the optimization of SyS.

OBJECTIVES

To (1) understand the legal environments in which SyS is implemented, (2) determine the perceived legal basis for SyS, and (3) identify perceived legal barriers and facilitators to SyS implementation.

DESIGN

Multisite case study in which 35 key informant interviews and 5 focus groups were conducted with 75 SyS stakeholders. Interviews and focus groups were audio recorded, transcribed, and analyzed by 3 coders using thematic content analysis. Legal documents were reviewed.

SETTING

Seven jurisdictions (5 states, 1 county, and 1 city) that were purposively selected on the basis of SyS capacity and legal environment.

PARTICIPANTS

Health department directors, SyS system administrators, legal counsel, and hospital personnel.

RESULTS

Federal (eg, HIPAA) and state (eg, notifiable disease reporting) laws that authorize traditional public health surveillance were perceived as providing a legal basis for SyS. Financial incentives for hospitals to satisfy Meaningful Use regulations have eased concerns about the legality of SyS and increased the number of hospitals reporting SyS data. Legal issues were perceived as barriers to BioSense 2.0 (the federal SyS program) participation but were surmountable.

CONCLUSION

Major legal reforms are not needed to promote more widespread use of SyS. The current legal environment is perceived by health department and hospital officials as providing a firm basis for SyS practice. This is a shift from how law was perceived when SyS adoption began and has policy implications because it indicates that major legal reforms are not needed to promote more widespread use of the technology. Beyond SyS, our study suggests that federal monetary incentives can ameliorate legal concerns regarding novel health information technologies.

Spatial Bayesian surveillance for small area case event data

There has been little development of surveillance procedures for epidemiological data with fine spatial resolution such as case events at residential address locations. This is often due to difficulties of access when confidentiality of medical records is an issue. However, when such data are available, it is important to be able to affect an appropriate analysis strategy. We propose a model for point events in the context of prospective surveillance based on conditional logistic modeling. A weighted conditional autoregressive model is developed for irregular lattices to account for distance effects, and a Dirichlet tessellation is adopted to define the neighborhood structure. Localized clustering diagnostics are compared including the proposed local Kullback-Leibler information criterion. A simulation study is conducted to examine the surveillance and detection methods, and a data example is provided of non-Hodgkin's lymphoma data in South Carolina.

Big Data Analytics, Infectious Diseases and Associated Ethical Impacts

The exponential accumulation, processing and accrual of big data in healthcare are only possible through an equally rapidly evolving field of big data analytics. The latter offers the capacity to rationalize, understand and use big data to serve many different purposes, from improved services modelling to prediction of treatment outcomes, to greater patient and disease stratification. In the area of infectious diseases, the application of big data analytics has introduced a number of changes in the information accumulation models. These are discussed by comparing the traditional and new models of data accumulation. Big data analytics is fast becoming a crucial component for the modelling of transmission-aiding infection control measures and policies-emergency response analyses required during local or international outbreaks. However, the application of big data analytics in infectious diseases is coupled with a number of ethical impacts. Four key areas are discussed in this paper: (i) automation and algorithmic reliance impacting freedom of choice, (ii) big data analytics complexity impacting informed consent, (iii) reliance on profiling impacting individual and group identities and justice/fair access and (iv) increased surveillance and population intervention capabilities impacting behavioural norms and practices. Furthermore, the extension of big data analytics to include information derived from personal devices, such as mobile phones and wearables as part of infectious disease frameworks in the near future and their potential ethical impacts are discussed. Considered together, the need for a constructive and transparent inclusion of ethical questioning in this rapidly evolving field becomes an increasing necessity in order to provide a moral foundation for the societal acceptance and responsible development of the technological advancement.

Advancing the Use of Emergency Department Syndromic Surveillance Data, New York City, 2012-2016

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.

The ethics of withdrawal: the case of follow-up from first-in-human clinical trials

This paper aims to analyze whether patients should be allowed to veto research-related use of medical data collected during routine follow-ups after their withdrawal from first-in-human clinical trials. Forms of withdrawal are identified and it is argued that the right to withdraw might be limited to some of these. The paper concludes that if veto right is denied, then: the research participant should be informed about the potential use of his/her follow-up data in case of his/her withdrawal and consent to it; follow-up should not be initiated for research purposes; compulsory use of follow-up data should imply the use of data anyway collected, requiring no additional effort from the patient; and before deciding about the veto right, investigation of concerned patients' value preferences is needed.

Development of a Core Clinical Dataset to Characterize Serious Illness, Injuries, and Resource Requirements for Acute Medical Responses to Public Health Emergencies

OBJECTIVES

In developed countries, public health systems have become adept at rapidly identifying the etiology and impact of public health emergencies. However, within the time course of clinical responses, shortfalls in readily analyzable patient-level data limit capabilities to understand clinical course, predict outcomes, ensure resource availability, and evaluate the effectiveness of diagnostic and therapeutic strategies for seriously ill and injured patients. To be useful in the timeline of a public health emergency, multi-institutional clinical investigation systems must be in place to rapidly collect, analyze, and disseminate detailed clinical information regarding patients across prehospital, emergency department, and acute care hospital settings, including ICUs. As an initial step to near real-time clinical learning during public health emergencies, we sought to develop an "all-hazards" core dataset to characterize serious illness and injuries and the resource requirements for acute medical response across the care continuum.

SUBJECTS

A multidisciplinary panel of clinicians, public health professionals, and researchers with expertise in public health emergencies.

DESIGN

Group consensus process.

INTERVENTIONS

The consensus process included regularly scheduled conference calls, electronic communications, and an in-person meeting to generate candidate variables. Candidate variables were then reviewed by the group to meet the competing criteria of utility and feasibility resulting in the core dataset.

MEASUREMENTS AND MAIN RESULTS

The 40-member panel generated 215 candidate variables for potential dataset inclusion. The final dataset includes 140 patient-level variables in the domains of demographics and anthropometrics (7), prehospital (11), emergency department (13), diagnosis (8), severity of illness (54), medications and interventions (38), and outcomes (9).

CONCLUSIONS

The resulting all-hazard core dataset for seriously ill and injured persons provides a foundation to facilitate rapid collection, analyses, and dissemination of information necessary for clinicians, public health officials, and policymakers to optimize public health emergency response. Further work is needed to validate the effectiveness of the dataset in a variety of emergency settings.

Historical evolution of human anthrax from occupational disease to potentially global threat as bioweapon

PURPOSE

Anthrax is caused by Bacillus anthracis, which can naturally infect livestock, wildlife and occupationally exposed humans. However, for its resistance due to spore formation, ease of dissemination, persistence in the environment and high virulence, B. anthracis has been considered the most serious bioterrorism agent for a long time. During the last century anthrax evolved from limited natural disease to potentially global threat if used as bioweapon. Several factors may mitigate the consequences of an anthrax attack, including 1. the capability to promptly recognize and manage the illness and its public health consequences; 2. the limitation of secondary contamination risk through an appropriate decontamination; and 3. the evolution of genotyping methods (for microbes characterization at high resolution level) that can influence the course and/or focus of investigations, impacting the response of the government to an attack.

METHODS

A PubMed search has been done using the key words “bioterrorism anthrax”.

RESULTS

Over one thousand papers have been screened and the most significant examined to present a comprehensive literature review in order to discuss the current knowledge and strategies in preparedness for a possible deliberate release of B. anthracis spores and to indicate the most current and complete documents in which to deepen.

CONCLUSIONS

The comprehensive analysis of the two most relevant unnatural anthrax release events, Sverdlovsk in the former Soviet Union (1979) and the contaminated letters in the USA (2001), shows that inhalational anthrax may easily and cheaply be spread resulting in serious consequences. The damage caused by an anthrax attack can be limited if public health organization, first responders, researchers and investigators will be able to promptly manage anthrax cases and use new technologies for decontamination methods and in forensic microbiology.

Seasonal and Pandemic Influenza Surveillance and Disease Severity

Continuous investments in influenza research, surveillance, and prevention efforts are critical to mitigate the consequences of annual influenza epidemics and pandemics. New influenza viruses emerge due to antigenic drift and antigenic shift evading human immune system and causing annual epidemics and pandemics. Three pandemics with varying disease severity occurred in the last 100 years. The disease burden and determinants of influenza severity depend on circulating viral strains and individual demographic and clinical factors. Surveillance is the most effective strategy for appropriate public health response. Active and passive surveillance methods are utilized to monitor influenza epidemics and emergence of novel viruses. Meaningful use of electronic health records could be a cost-effective approach to improved influenza surveillance

Early-warning health and process indicators for sentinel surveillance in Madagascar 2007-2011

BACKGROUND

Epidemics pose major threats in resource-poor countries, and surveillance tools for their early detection and response are often inadequate. In 2007, a sentinel surveillance system was established in Madagascar, with the aim of rapidly identifying potential epidemics of febrile or diarrhoeal syndromes and issuing alerts. We present the health and process indicators for the five years during which this system was constructed, showing the spatiotemporal trends, early-warning sign detection capability and process evaluation through timely analyses of high-quality data.

METHODS

The Malagasy sentinel surveillance network is currently based on data for fever and diarrhoeal syndromes collected from 34 primary health centres and reported daily via the transmission of short messages from mobile telephones. Data are analysed daily at the Institut Pasteur de Madagascar to make it possible to issue alerts more rapidly, and integrated process indicators (timeliness, data quality) are used to monitor the system.

RESULTS

From 2007 to 2011, 917,798 visits were reported. Febrile syndromes accounted for about 11% of visits annually, but the trends observed differed between years and sentinel sites. From 2007 to 2011, 21 epidemic alerts were confirmed. However, delays in data transmission were observed (88% transmitted within 24 hours in 2008; 67% in 2011) and the percentage of forms transmitted each week for validity control decreased from 99.9% in 2007 to 63.5% in 2011.

CONCLUSION

A sentinel surveillance scheme should take into account both epidemiological and process indicators. It must also be governed by the main purpose of the surveillance and by local factors, such as the motivation of healthcare workers and telecommunication infrastructure. Permanent evaluation indicators are required for regular improvement of the system.

A practical approach to designing syndromic surveillance systems for livestock and poultry

The field of animal syndromic surveillance (SyS) is growing, with many systems being developed worldwide. Now is an appropriate time to share ideas and lessons learned from early SyS design and implementation. Based on our practical experience in animal health SyS, with additions from the public health and animal health SyS literature, we put forward for discussion a 6-step approach to designing SyS systems for livestock and poultry. The first step is to formalise policy and surveillance goals which are considerate of stakeholder expectations and reflect priority issues (1). Next, it is important to find consensus on national priority diseases and identify current surveillance gaps. The geographic, demographic, and temporal coverage of the system must be carefully assessed (2). A minimum dataset for SyS that includes the essential data to achieve all surveillance objectives while minimizing the amount of data collected should be defined. One can then compile an inventory of the data sources available and evaluate each using the criteria developed (3). A list of syndromes should then be produced for all data sources. Cases can be classified into syndrome classes and the data can be converted into time series (4). Based on the characteristics of the syndrome-time series, the length of historic data available and the type of outbreaks the system must detect, different aberration detection algorithms can be tested (5). Finally, it is essential to develop a minimally acceptable response protocol for each statistical signal produced (6). Important outcomes of this pre-operational phase should be building of a national network of experts and collective action and evaluation plans. While some of the more applied steps (4 and 5) are currently receiving consideration, more emphasis should be put on earlier conceptual steps by decision makers and surveillance developers (1-3).

Using Bayes' rule to define the value of evidence from syndromic surveillance

In this work we propose the adoption of a statistical framework used in the evaluation of forensic evidence as a tool for evaluating and presenting circumstantial “evidence” of a disease outbreak from syndromic surveillance. The basic idea is to exploit the predicted distributions of reported cases to calculate the ratio of the likelihood of observing n cases given an ongoing outbreak over the likelihood of observing n cases given no outbreak. The likelihood ratio defines the Value of Evidence (V). Using Bayes' rule, the prior odds for an ongoing outbreak are multiplied by V to obtain the posterior odds. This approach was applied to time series on the number of horses showing clinical respiratory symptoms or neurological symptoms. The separation between prior beliefs about the probability of an outbreak and the strength of evidence from syndromic surveillance offers a transparent reasoning process suitable for supporting decision makers. The value of evidence can be translated into a verbal statement, as often done in forensics or used for the production of risk maps. Furthermore, a Bayesian approach offers seamless integration of data from syndromic surveillance with results from predictive modeling and with information from other sources such as disease introduction risk assessments.

Acquired immunity and asymptomatic reservoir impact on frontline and airport ebola outbreak syndromic surveillance and response

The number of surveillance networks for infectious disease diagnosis and response has been growing. In 2000, the World Health Organization (WHO) established the Global Outbreak Alert and Response Network, which has been endorsed by each of the 46 WHO African members since then. Yet, taming the dynamics and plague of the vicious Ebola virus disease (EVD) in African countries has been patchy and erratic due to inadequate surveillance and contact tracing, community defiance and resistance, a lack of detection and response systems, meager/weak knowledge and information on the disease, inadequacies in protective materials protocols, contact tracing nightmare and differing priorities at various levels of the public health system. Despite the widespread acceptance of syndromic surveillance (SS) systems, their ability to provide early warning alerts and notifications of outbreaks is still unverified. Information is often too limited for any outbreak, or emerging or otherwise unexpected disease, to be recognized at either the community or the national level. Indeed, little is known about the role and the interactions between the Ebola infection and exposure to other syndemics and the development of acquired immunity, asymptomatic reservoir, and Ebola seroconversion. Can lessons be learnt from smallpox, polio, and influenza immunity, and can immunization against these serve as a guide? In most endemic countries, community health centers and disease control and prevention at airports solely relies on passive routine immunization control and reactive syndromic response. The frontline and airport Ebola SS systems in West Africa have shown deficiencies in terms of responding with an alarming number of case fatalities, and suggest that more detailed insights into Ebola, and proactive actions, are needed. The quest for effective early indicators (EEE) in shifting the public and global health paradigm requires the development and implementation of a comprehensive and effective community or regional integrated pandemic preparedness and surveillance response systems tailored to local contexts. These systems must have mechanisms for early identification, rapid contact tracing and tracking, confirmation, and communication with the local population and the global community, and must endeavor to respond in a timely manner.

Natural foci diseases as a stable biological threat

The key aspects of the natural foci of especially dangerous diseases as a type of biological threats are presented. Approaches to epidemiological surveillance and control to the spread of the agents of especially dangerous diseases on endemic areas are described for zoonosis that has a medical value. The knowledge of specific design of tools for the implementation of epidemiological surveillance, monitoring and evaluation of natural foci diseases in developing countries is low; accordingly, little is known on the ecology and transmission dynamics for the agents of especially dangerous diseases. Important is to know the effectiveness of serological monitoring of the indigenous population to determine the activity of natural foci of hemorrhagic fever with renal syndrome, tick-borne encephalitis, tularemia, Q-fever, Lyme disease and West Nile disease. The main species of reservoirs and vectors for these agents have been determined in different regions of Ukraine. New tick-borne agents that were unknown for certain regions have been detected. These data indicate the spreading of different pathogens in combination with natural foci.

Clinical microbiology informatics

The clinical microbiology laboratory has responsibilities ranging from characterizing the causative agent in a patient's infection to helping detect global disease outbreaks. All of these processes are increasingly becoming partnered more intimately with informatics. Effective application of informatics tools can increase the accuracy, timeliness, and completeness of microbiology testing while decreasing the laboratory workload, which can lead to optimized laboratory workflow and decreased costs. Informatics is poised to be increasingly relevant in clinical microbiology, with the advent of total laboratory automation, complex instrument interfaces, electronic health records, clinical decision support tools, and the clinical implementation of microbial genome sequencing. This review discusses the diverse informatics aspects that are relevant to the clinical microbiology laboratory, including the following: the microbiology laboratory information system, decision support tools, expert systems, instrument interfaces, total laboratory automation, telemicrobiology, automated image analysis, nucleic acid sequence databases, electronic reporting of infectious agents to public health agencies, and disease outbreak surveillance. The breadth and utility of informatics tools used in clinical microbiology have made them indispensable to contemporary clinical and laboratory practice. Continued advances in technology and development of these informatics tools will further improve patient and public health care in the future.

Advancing a framework to enable characterization and evaluation of data streams useful for biosurveillance

In recent years, biosurveillance has become the buzzword under which a diverse set of ideas and activities regarding detecting and mitigating biological threats are incorporated depending on context and perspective. Increasingly, biosurveillance practice has become global and interdisciplinary, requiring information and resources across public health, One Health, and biothreat domains. Even within the scope of infectious disease surveillance, multiple systems, data sources, and tools are used with varying and often unknown effectiveness. Evaluating the impact and utility of state-of-the-art biosurveillance is, in part, confounded by the complexity of the systems and the information derived from them. We present a novel approach conceptualizing biosurveillance from the perspective of the fundamental data streams that have been or could be used for biosurveillance and to systematically structure a framework that can be universally applicable for use in evaluating and understanding a wide range of biosurveillance activities. Moreover, the Biosurveillance Data Stream Framework and associated definitions are proposed as a starting point to facilitate the development of a standardized lexicon for biosurveillance and characterization of currently used and newly emerging data streams. Criteria for building the data stream framework were developed from an examination of the literature, analysis of information on operational infectious disease biosurveillance systems, and consultation with experts in the area of biosurveillance. To demonstrate utility, the framework and definitions were used as the basis for a schema of a relational database for biosurveillance resources and in the development and use of a decision support tool for data stream evaluation.

The value and validation of broad spectrum biosensors for diagnosis and biodefense

Broad spectrum biosensors capable of identifying diverse organisms are transitioning from the realm of research into the clinic. These technologies simultaneously capture signals from a wide variety of biological entities using universal processes. Specific organisms are then identified through bioinformatic signature-matching processes. This is in contrast to currently accepted molecular diagnostic technologies, which utilize unique reagents and processes to detect each organism of interest. This paradigm shift greatly increases the breadth of molecular diagnostic tools with little increase in biochemical complexity, enabling simultaneous diagnostic, epidemiologic, and biothreat surveillance capabilities at the point of care. This, in turn, offers the promise of increased biosecurity and better antimicrobial stewardship. Efficient realization of these potential gains will require novel regulatory paradigms reflective of the generalized, information-based nature of these assays, allowing extension of empirical data obtained from readily available organisms to support broader reporting of rare, difficult to culture, or extremely hazardous organisms.

Evaluation of a continuous indicator for syndromic surveillance through simulation. application to vector borne disease emergence detection in cattle using milk yield

Two vector borne diseases, caused by the Bluetongue and Schmallenberg viruses respectively, have emerged in the European ruminant populations since 2006. Several diseases are transmitted by the same vectors and could emerge in the future. Syndromic surveillance, which consists in the routine monitoring of indicators for the detection of adverse health events, may allow an early detection. Milk yield is routinely measured in a large proportion of dairy herds and could be incorporated as an indicator in a surveillance system. However, few studies have evaluated continuous indicators for syndromic surveillance. The aim of this study was to develop a framework for the quantification of both disease characteristics and model predictive abilities that are important for a continuous indicator to be sensitive, timely and specific for the detection of a vector-borne disease emergence. Emergences with a range of spread characteristics and effects on milk production were simulated. Milk yields collected monthly in 48 713 French dairy herds were used to simulate 576 disease emergence scenarios. First, the effect of disease characteristics on the sensitivity and timeliness of detection were assessed: Spatio-temporal clusters of low milk production were detected with a scan statistic using the difference between observed and simulated milk yields as input. In a second step, the system specificity was evaluated by running the scan statistic on the difference between observed and predicted milk yields, in the absence of simulated emergence. The timeliness of detection depended mostly on how easily the disease spread between and within herds. The time and location of the emergence or adding random noise to the simulated effects had a limited impact on the timeliness of detection. The main limitation of the system was the low specificity i.e. the high number of clusters detected from the difference between observed and predicted productions, in the absence of disease.

ISS--an electronic syndromic surveillance system for infectious disease in rural China

Background

syndromic surveillance system has great advantages in promoting the early detection of epidemics and reducing the necessities of disease confirmation, and it is especially effective for surveillance in resource poor settings. However, most current syndromic surveillance systems are established in developed countries, and there are very few reports on the development of an electronic syndromic surveillance system in resource-constrained settings.

Objective

this study describes the design and pilot implementation of an electronic surveillance system (ISS) for the early detection of infectious disease epidemics in rural China, complementing the conventional case report surveillance system.

Methods

ISS was developed based on an existing platform ‘Crisis Information Sharing Platform’ (CRISP), combining with modern communication and GIS technology. ISS has four interconnected functions: 1) work group and communication group; 2) data source and collection; 3) data visualization; and 4) outbreak detection and alerting.

Results

As of Jan. 31^st 2012, ISS has been installed and pilot tested for six months in four counties in rural China. 95 health facilities, 14 pharmacies and 24 primary schools participated in the pilot study, entering respectively 74256, 79701, and 2330 daily records into the central database. More than 90% of surveillance units at the study sites are able to send daily information into the system. In the paper, we also presented the pilot data from health facilities in the two counties, which showed the ISS system had the potential to identify the change of disease patterns at the community level.

Conclusions

The ISS platform may facilitate the early detection of infectious disease epidemic as it provides near real-time syndromic data collection, interactive visualization, and automated aberration detection. However, several constraints and challenges were encountered during the pilot implementation of ISS in rural China.

Estimation of Influenza Incidence by Age in the 2011/12 Seasons in Japan using SASSy

Objective

Introduction

Methods

Results

Conclusions

[Syndromic surveillance: review and prospect of a promising concept]

Syndromic surveillance appeared in the field of public health surveillance in the late 90's. Initially proposed for public health identification of bioterrorism events, the method failed to provide convincing evidence of its usefulness and potential benefits. The definition which is proposed today by the Centers for Disease Control and Prevention (CDC) of Atlanta is the most commonly accepted. It defines syndromic surveillance as an automatic process that goes from registration to transfer of data recorded within the framework of a professional rather than public health goal. Systems operating today have integrated a public health approach through routine surveillance procedures with a broader focus than bioterrorism, implying active participation of the official public health surveillance structures. Syndromic surveillance offers several advantages including quick access to a large volume of data in real time, no extra-work for data registration and construction of a historical dataset useful as an historical baseline. Nevertheless, the limitations of this type of surveillance should not be forgotten (sometimes limited sensitivity, specificity, important technical burden…). Today, recorded experience shows that there is no opposition between syndromic surveillance and classical surveillance. On the contrary, they should be presented as complementary procedures. Syndromic surveillance should be analyzed from a temporal perspective, examining its short-term use as an alert mechanism, mid-term use for constitution of historical time series, and long-term use for a description of human health in the 21st century.

The remarkable adaptability of syndromic surveillance to meet public health needs

The goal of syndromic surveillance is the earlier detection of epidemics, allowing a timelier public health response than is possible using traditional surveillance methods. Syndromic surveillance application for public health purposes has changed over time and reflects a dynamic evolution from the collection, interpretation of data with dissemination of data to those who need to act, to a more holistic approach that incorporates response as a core component of the surveillance system. Recent infectious disease threats, such as severe acute respiratory syndrome (SARS), avian influenza (H5N1) and pandemic influenza (H1N1), have all highlighted the need for countries to be rapidly aware of the spread of infectious diseases within a region and across the globe. The International Health Regulations (IHR) obligation to report public health emergencies of international concern has raised the importance of early outbreak detection and response. The emphasis in syndromic surveillance is changing from automated, early alert and detection, to situational awareness and response. Published literature on syndromic surveillance reflects the changing nature of public health threats and responses. Syndromic surveillance has demonstrated a remarkable ability to adapt to rapidly shifting public health needs. This adaptability makes it a highly relevant public health tool.

Prescription surveillance and polymerase chain reaction testing to identify pathogens during outbreaks of infection

Syndromic surveillance, including prescription surveillance, offers a rapid method for the early detection of agents of bioterrorism and emerging infectious diseases. However, it has the disadvantage of not considering definitive diagnoses. Here, we attempted to definitively diagnose pathogens using polymerase chain reaction (PCR) immediately after the prescription surveillance system detected an outbreak. Specimens were collected from 50 patients with respiratory infections. PCR was used to identify the pathogens, which included 14 types of common respiratory viruses and Mycoplasma pneumoniae. Infectious agents including M. pneumoniae, respiratory syncytial virus (RSV), rhinovirus, enterovirus, and parainfluenza virus were detected in 54% of patients. For the rapid RSV diagnosis kit, sensitivity was 80% and specificity was 85%. For the rapid adenovirus diagnosis kit, no positive results were obtained; therefore, sensitivity could not be calculated and specificity was 100%. Many patients were found to be treated for upper respiratory tract infections without the diagnosis of a specific pathogen. In Japan, an outbreak of M. pneumoniae infection began in 2011, and our results suggested that this outbreak may have included false-positive cases. By combining syndromic surveillance and PCR, we were able to rapidly and accurately identify causative pathogens during a recent respiratory infection outbreak.

Nationwide surveillance of influenza during the pandemic (2009-10) and post-pandemic (2010-11) periods in Taiwan

Introduction

Although WHO declared the world moving into the post-pandemic period on August 10, 2010, influenza A(H1N1) 2009 virus continued to circulate globally. Its impact was expected to continue during the 2010–11 influenza season. This study describes the nationwide surveillance findings of the pandemic and post-pandemic influenza periods in Taiwan and assesses the impact of influenza A(H1N1) 2009 during the post-pandemic period.

Methods

The Influenza Laboratory Surveillance Network consisted of 12 contract laboratories for collecting and testing samples with acute respiratory tract infections. Surveillance of emergency room visits and outpatient department visits for influenza-like illness (ILI) were conducted using the Real-Time Outbreak and Disease Surveillance system and the National Health Insurance program data, respectively. Hospitalized cases with severe complications and deaths were reported to the National Notifiable Disease Surveillance System.

Results

During the 2009–10 influenza season, pandemic A(H1N1) 2009 was the predominant circulating strain and caused 44 deaths. However, the 2010–11 influenza season began with A(H3N2) being the predominant circulating strain, changing to A(H1N1) 2009 in December 2010. Emergency room and outpatient department ILI surveillance displayed similar trends. By March 31, 2011, there were 1,751 cases of influenza with severe complications; 50.1% reported underlying diseases. Of the reported cases, 128 deaths were associated with influenza. Among these, 93 (72.6%) were influenza A(H1N1) 2009 and 30 (23.4%) A(H3N2). Compared to the pandemic period, during the immediate post-pandemic period, increased number of hospitalizations and deaths were observed, and the patients were consistently older.

Conclusions

Reemergence of influenza A(H1N1) 2009 during the 2010–11 influenza season had an intense activity with age distribution shift. To further mitigate the impact of future influenza epidemics, Taiwan must continue its multifaceted influenza surveillance systems, remain flexible with antiviral use policies, and revise the vaccine policies to include the population most at risk.

Recombinase polymerase amplification assay for rapid detection of Francisella tularensis

Several real-time PCR approaches to develop field detection for Francisella tularensis, the infectious agent causing tularemia, have been explored. We report the development of a novel qualitative real-time isothermal recombinase polymerase amplification (RPA) assay for use on a small ESEQuant Tube Scanner device. The analytical sensitivity and specificity were tested using a plasmid standard and DNA extracts from infected rabbit tissues. The assay showed a performance comparable to real-time PCR but reduced the assay time to 10 min. The rapid RPA method has great application potential for field use or point-of-care diagnostics.

Assessing the continuum of event-based biosurveillance through an operational lens

This research follows the Updated Guidelines for Evaluating Public Health Surveillance Systems, Recommendations from the Guidelines Working Group, published by the Centers for Disease Control and Prevention nearly a decade ago. Since then, models have been developed and complex systems have evolved with a breadth of disparate data to detect or forecast chemical, biological, and radiological events that have a significant impact on the One Health landscape. How the attributes identified in 2001 relate to the new range of event-based biosurveillance technologies is unclear. This article frames the continuum of event-based biosurveillance systems (that fuse media reports from the internet), models (ie, computational that forecast disease occurrence), and constructs (ie, descriptive analytical reports) through an operational lens (ie, aspects and attributes associated with operational considerations in the development, testing, and validation of the event-based biosurveillance methods and models and their use in an operational environment). A workshop was held in 2010 to scientifically identify, develop, and vet a set of attributes for event-based biosurveillance. Subject matter experts were invited from 7 federal government agencies and 6 different academic institutions pursuing research in biosurveillance event detection. We describe 8 attribute families for the characterization of event-based biosurveillance: event, readiness, operational aspects, geographic coverage, population coverage, input data, output, and cost. Ultimately, the analyses provide a framework from which the broad scope, complexity, and relevant issues germane to event-based biosurveillance useful in an operational environment can be characterized.

Establishing a web-based integrated surveillance system for early detection of infectious disease epidemic in rural China: a field experimental study

BACKGROUND

A crucial goal of infectious disease surveillance is the early detection of epidemics, which is essential for disease control. In China, the current surveillance system is based on confirmed case reports. In rural China, it is not practical for health units to perform laboratory tests to confirm disease and people are more likely to get 'old' and emerging infectious diseases due to poor living conditions and closer contacts with wild animals and poultry. Syndromic surveillance, which collects non-specific syndromes before diagnosis, has great advantages in promoting the early detection of epidemics and reducing the necessities of disease confirmation. It will be especially effective for surveillance in resource poor settings.

METHODS/DESIGN

This is a field experimental study. The experimental tool is an innovative electronic surveillance system, combining syndromic surveillance with the existing case report surveillance in four selected counties in China. In the added syndromic surveillance, three types of data are collected including patients' major symptoms from health clinics, pharmaceutical sales from pharmacies and absenteeism information from primary school. In order to evaluate the early warning capability of the new added syndromic surveillance, the timelines and validity of the alert signals will be analyzed in comparison with the traditional case reporting system. The acceptability, feasibility and economic evaluation of the whole integrated surveillance system will be conducted in a before and after study design.

DISCUSSIONS

Although syndromic surveillance system has mostly been established in developed areas, there are opportunities and advantages of developing it in rural China. The project will contribute to knowledge, experience and evidence on the establishment of an integrated surveillance system, which aims to provide early warning of disease epidemics in developing countries.

Real-time prescription surveillance and its application to monitoring seasonal influenza activity in Japan

Background

Real-time surveillance is fundamental for effective control of disease outbreaks, but the official sentinel surveillance in Japan collects information related to disease activity only weekly and updates it with a 1-week time lag.

Objective

To report on a prescription surveillance system using electronic records related to prescription drugs that was started in 2008 in Japan, and to evaluate the surveillance system for monitoring influenza activity during the 2009–2010 and 2010–2011 influenza seasons.

Methods

We developed an automatic surveillance system using electronic records of prescription drug purchases collected from 5275 pharmacies through the application service provider’s medical claims service. We then applied the system to monitoring influenza activity during the 2009–2010 and 2010–2011 influenza seasons. The surveillance system collected information related to drugs and patients directly and automatically from the electronic prescription record system, and estimated the number of influenza cases based on the number of prescriptions of anti-influenza virus medication. Then it shared the information related to influenza activity through the Internet with the public on a daily basis.

Results

During the 2009–2010 influenza season, the number of influenza patients estimated by the prescription surveillance system between the 28th week of 2009 and the 12th week of 2010 was 9,234,289. In the 2010–2011 influenza season, the number of influenza patients between the 36th week of 2010 and the 12th week of 2011 was 7,153,437. The estimated number of influenza cases was highly correlated with that predicted by the official sentinel surveillance (r = .992, P < .001 for 2009–2010; r = .972, P < .001 for 2010–2011), indicating that the prescription surveillance system produced a good approximation of activity patterns.

Conclusions

Our prescription surveillance system presents great potential for monitoring influenza activity and for providing early detection of infectious disease outbreaks.

Non-communicable health risks during mass gatherings

Mass gatherings (MGs) have been associated with high rates of morbidity and mortality from non-communicable diseases, accidents, and terrorist attacks, thus posing complex public health challenges. We assessed the health risks and public health responses to MGs to identify an evidence-based framework for public health interventions. Human stampedes and heat-related illnesses are the leading causes of mortality. Minor traumatic injuries and medical complaints are the main contributors to morbidity and, particularly, the need for on-site medical care. Infrastructure, crowd density and mood, weather, age, and sex determine the risks to health. Many predictive models for deployment of medical resources are proposed, but none have been validated. We identified the risks for mortality and morbidity during MGs, most efficient public health interventions, and need for robust research into health risks for non-communicable diseases during MGs.

The potential capability of social media as a component of food safety and food terrorism surveillance systems

Social media (i.e., internet applications and platforms that allow users to create and share content) are a potentially rich data source for foodborne disease surveillance. This commentary qualitatively evaluates social media as a foodborne disease surveillance system component and discusses novel ways that social media may facilitate the detection of intentional and unintentional food contamination.

Biosurveillance: a review and update

Since the terrorist attacks and anthrax release in 2001, almost $32 billion has been allocated to biodefense and biosurveillance in the USA alone. Surveillance in health care refers to the continual systematic collection, analysis, interpretation, and dissemination of data. When attempting to detect agents of bioterrorism, surveillance can occur in several ways. Syndromic surveillance occurs by monitoring clinical manifestations of certain illnesses. Laboratory surveillance occurs by looking for certain markers or laboratory data, and environmental surveillance is the process by which the ambient air or environment is continually sampled for the presence of biological agents. This paper focuses on the ways by which we detect bioterrorism agents and the effectiveness of these systems.

Redefining syndromic surveillance

With growing concerns about international spread of disease and expanding use of early disease detection surveillance methods, the field of syndromic surveillance has received increased attention over the last decade. The purpose of this article is to clarify the various meanings that have been assigned to the term syndromic surveillance and to propose a refined categorization of the characteristics of these systems. Existing literature and conference proceedings were examined on syndromic surveillance from 1998 to 2010, focusing on low- and middle-income settings. Based on the 36 unique definitions of syndromic surveillance found in the literature, five commonly accepted principles of syndromic surveillance systems were identified, as well as two fundamental categories: specific and non-specific disease detection. Ultimately, the proposed categorization of syndromic surveillance distinguishes between systems that focus on detecting defined syndromes or outcomes of interest and those that aim to uncover non-specific trends that suggest an outbreak may be occurring. By providing an accurate and comprehensive picture of this field's capabilities, and differentiating among system types, a unified understanding of the syndromic surveillance field can be developed, encouraging the adoption, investment in, and implementation of these systems in settings that need bolstered surveillance capacity, particularly low- and middle-income countries.

[The real-time pharmacy surveillance and its estimation of patients in 2009 influenza A (H1N1)]

OBJECT

Detecting of disease spread is an important task of public health and medical staff, especially in pandemics such as A/H1N1 flu (2009). This requires daily observation and estimation of the infected population. The fully automated real-time pharmacy survey we developed collects information electronically at pharmaceutical prescription. We used the data to analyze the pandemic A/H1N1 flu spread (2009) and to determine the system's and capability in estimating the infected population.

METHOD

Automatic collection of prescription information on antiinfluenza virus drugs from 3959 pharmacies provided the basis for calculating the number of influenza sufferers and determining shape of the epidemic curve compared to that of official influenza sentinel surveys and mandatory reports of A/H1N1 (2009) patients. We also compared infection estimates from the pharmacy survey to those of official sentinel survey and a one-week survey of all hospitals and clinics in Gifu prefecture not reported in sentinel,

RESULTS

Fully automated real-time pharmacy surveillance began on April 20, 2009, and provided feedback at 07:00 daily. It estimated the infected population at 22,708 when official sentinel surveillance recorded an average of 0.99 influenza visits per week in epidemic week 32 when publicly announced that the pandemic had began in Japan. By the end of March, epidemic week 12 in 2010, infected-population estimates totaled 9,234,289, and peaked on November 24 at 234,519 in one day. All A/H1N1 (2009) sufferers reported mandatorily until mid-July numbered 25,526. The pharmacy survey indicated that there were influenza nationalwide by the time the very first outbreak emerged in the Kansai (western Japan) area. The correlation coefficient for the pharmacy and official sentinel survey was 0.992 nationwide, exceeding 0.95 in which only 33 of Japan's 47 prefectures were counted. The estimated infected population in the pharmacy survey was half of that of the official sentinel survey. The pharmacy survey yielded almost the same number as the complete survey in Gifu prefecture, however.

DISCUSSION

Fully automated real-time pharmacy surveys are useful in long-term observation e.g. detection of rapid emergence, identifying the peak, and careful monitoring of reemergence. It was demonstrated as the leading indicator for the official sentinel surveillance because of high correlation among them. Information collected daily is very useful in early detection and estimating the affected population. The survey consistently uses the same estimation criterion and operates automatically and routinely, facilitating the comparison of the latest and past results. The pharmacy survey indicated that official sentinel survey estimates overestimate actual cases and thus require modification to ensure accuracy. The pharmacy survey thus appears to be very valuable as a tool in measuring for the second wave of A/H1N1 (2009) or whatever the next pandemic may be. It can, of course, be applied to diseases other than influenza, e.g., varicella, by following antivaricellazostervirus prescriptions and antibiotic drugs.

Levofloxacin cures experimental pneumonic plague in African green monkeys

BACKGROUND

Yersinia pestis, the agent of plague, is considered a potential bioweapon due to rapid lethality when delivered as an aerosol. Levofloxacin was tested for primary pneumonic plague treatment in a nonhuman primate model mimicking human disease.

METHODS AND RESULTS

Twenty-four African Green monkeys (AGMs, Chlorocebus aethiops) were challenged via head-only aerosol inhalation with 3-145 (mean = 65) 50% lethal (LD(50)) doses of Y. pestis strain CO92. Telemetered body temperature >39 °C initiated intravenous infusions to seven 5% dextrose controls or 17 levofloxacin treated animals. Levofloxacin was administered as a "humanized" dose regimen of alternating 8 mg/kg and 2 mg/kg 30-min infusions every 24-h, continuing until animal death or 20 total infusions, followed by 14 days of observation. Fever appeared at 53-165 h and radiographs found multilobar pneumonia in all exposed animals. All control animals died of severe pneumonic plague within five days of aerosol exposure. All 16 animals infused with levofloxacin for 10 days survived. Levofloxacin treatment abolished bacteremia within 24 h in animals with confirmed pre-infusion bacteremia, and reduced tachypnea and leukocytosis but not fever during the first 2 days of infusions.

CONCLUSION

Levofloxacin cures established pneumonic plague when treatment is initiated after the onset of fever in the lethal aerosol-challenged AGM nonhuman primate model, and can be considered for treatment of other forms of plague. Levofloxacin may also be considered for primary presumptive-use, multi-agent antibiotic in bioterrorism events prior to identification of the pathogen.