A New Influenza-Tracking Smartphone App (Flu-Report) Based on a Self-Administered Questionnaire: Cross-Sectional Study (Preprint)

BACKGROUND Influenza infections can spread rapidly, and influenza outbreaks are a major public health concern worldwide. Early detection of signs of an influenza pandemic is important to prevent global outbreaks. Development of information and communications technologies for influenza surveillance, including participatory surveillance systems involving lay users, has recently increased. Many of these systems can estimate influenza activity faster than the conventional influenza surveillance systems. Unfortunately, few of these influenza-tracking systems are available in Japan. OBJECTIVE This study aimed to evaluate the flu-tracking ability of Flu-Report, a new influenza-tracking mobile phone app that uses a self-administered questionnaire for the early detection of influenza activity. METHODS Flu-Report was used to collect influenza-related information (ie, dates on which influenza infections were diagnosed) from November 2016 to March 2017. Participants were adult volunteers from throughout Japan, who also provided information about their cohabiting family members. The utility of Flu-Report was evaluated by comparison with the conventional influenza surveillance information and basic information from an existing large-scale influenza-tracking system (an automatic surveillance system based on electronic records of prescription drug purchases). RESULTS Information was obtained through Flu-Report for approximately 10,094 volunteers. In total, 2134 participants were aged <20 years, 6958 were aged 20-59 years, and 1002 were aged ≥60 years. Between November 2016 and March 2017, 347 participants reported they had influenza or an influenza-like illness in the 2016 season. Flu-Report-derived influenza infection time series data displayed a good correlation with basic information obtained from the existing influenza surveillance system (rho, ρ=.65, P=.001). However, the influenza morbidity ratio for our participants was approximately 25% of the mean influenza morbidity ratio for the Japanese population. The Flu-Report influenza morbidity ratio was 5.06% (108/2134) among those aged <20 years, 3.16% (220/6958) among those aged 20-59 years, and 0.59% (6/1002) among those aged ≥60 years. In contrast, influenza morbidity ratios for Japanese individuals aged <20 years, 20-59 years, and ≥60 years were recently estimated at 31.97% to 37.90%, 8.16% to 9.07%, and 2.71% to 4.39%, respectively. CONCLUSIONS Flu-Report supports easy access to near real-time information about influenza activity via the accumulation of self-administered questionnaires. However, Flu-Report users may be influenced by selection bias, which is a common issue associated with surveillance using information and communications technologies. Despite this, Flu-Report has the potential to provide basic data that could help detect influenza outbreaks.

Download Full-text

Evaluation of Point of Need Diagnostic Tests for Use in California Influenza Outbreaks

Online Journal of Public Health Informatics ◽

10.5210/ojphi.v8i1.6518 ◽

2016 ◽

Vol 8 (1) ◽

Author(s):

Ashlynn Daughton ◽

Alina Deshpande

Keyword(s):

Data Streams ◽

Surveillance System ◽

Laboratory Data ◽

Developed Countries ◽

The United States ◽

Diagnostic Tools ◽

Influenza Surveillance ◽

Mortality Data ◽

Surveillance Systems ◽

Influenza Outbreaks

Because of the potential threats flu viruses pose, the United States, like many developed countries, has a very well established flu surveillance system consisting of 10 components collecting laboratory data, mortality data, hospitalization data and sentinel outpatient care data. Currently, this surveillance system is estimated to lag behind the actual seasonal outbreak by one to two weeks. As new data streams come online, it is important to understand what added benefit they bring to the flu surveillance system complex. For data streams to be effective, they should provide data in a more timely fashion or provide additional data that current surveillance systems cannot provide. Two multiplexed diagnostic tools designed to test syndromically relevant pathogens and wirelessly upload data for rapid integration and interpretation were evaluated to see how they fit into the influenza surveillance scheme in California.

Download Full-text

The use of near patient tests in influenza surveillance: Swiss experience and EISS recommendations

Eurosurveillance ◽

10.2807/esm.08.12.00438-en ◽

2003 ◽

Vol 8 (12) ◽

pp. 240-246 ◽

Cited By ~ 9

Author(s):

Y Thomas ◽

L Kaiser ◽

W Wunderli ◽

Keyword(s):

Surveillance System ◽

High Specificity ◽

Influenza Surveillance ◽

Surveillance Systems ◽

Community Practice ◽

Additional Information ◽

System A ◽

Influenza Activity ◽

Different Seasons

Surveillance requires time for analysis and for the communication to physicians. In order to reduce this delay, a new surveillance system based on the use of a near patient test (NPT) has been evaluated. The high specificity of NPT together with the rapidity in obtaining the results, make these tests attractive for surveillance of influenza epidemic in community practice. Such surveillance has been used in several countries including Switzerland. Four different seasons - between 1999 and 2003 - of this type of surveillance experienced in Switzerland have been analysed. The heterogeneity in terms of intensity and type of strains detected during these four epidemics seasons allowed an efficient evaluation. The average gain of time with NPT compared to cell culture was nine days. Furthermore, training of participants appeared to be essential to assure the quality of the surveillance system. A statement on the use of NPTs for influenza surveillance has finally been endorsed by EISS members. Included are recommendations that the network should use the NPTs data, which provides additional information to the classical surveillance systems, as an "early warning" system of a change in influenza activity.

Download Full-text

Derivation of New Surveillance System for Influenza-like Illness Using Claims Data 2014-2018 in Korea (Preprint)

10.2196/preprints.25155 ◽

2020 ◽

Author(s):

HeeKyung Choi ◽

Won Suk Choi ◽

Euna Han

Keyword(s):

Surveillance System ◽

Claims Data ◽

Health Concern ◽

Influenza Surveillance ◽

Utilization Review ◽

Surveillance Systems ◽

Influenza Like Illness ◽

System P ◽

National Patient ◽

Antitussive Agents

BACKGROUND Influenza is an important public health concern. A national surveillance system that easily and rapidly detects influenza epidemics is lacking. OBJECTIVE We assumed that the rate of influenza-like illness (ILI) related-claims is similar to the current ILI surveillance system. METHODS We used the Health Insurance Review and Assessment Service-National Patient Samples (HIRA-NPS), 2014-2018. We defined ILI-related claims as outpatient claims that contain both antipyretic and antitussive agents and calculated the weekly rate of ILI-related claims. We compared ILI-related claims and weekly ILI rates from clinical sentinel surveillance data. RESULTS We observed a strong correlation between the two surveillance systems each season. The absolute thresholds for the four-years were 84.64 and 86.19 cases claims per 1,000 claims for claims data and 12.27 and 16.82 per 1,000 patients for sentinel data (Figure 5). Both the claims and sentinel data surpassed the epidemic thresholds each season. The peak epidemic in the claims data was reached one to two weeks later than in the sentinel data. The epidemic patterns were more similar in the 2016-2017 and 2017-2018 seasons than the 2014-2015 and 2015-2016 seasons. CONCLUSIONS Based on hospital reports, ILI-related claims rates were similar to the ILI surveillance system. ILI claims data can be loaded to a drug utilization review system in Korea to make an influenza surveillance system.

Download Full-text

Development and Evaluation of a Fully Automated Surveillance System for Influenza-Associated Hospitalization at a Multihospital Health System in Northeast Ohio

Applied Clinical Informatics ◽

10.1055/s-0040-1715651 ◽

2020 ◽

Vol 11 (04) ◽

pp. 564-569

Author(s):

Patrick C. Burke ◽

Rachel Benish Shirley ◽

Jacob Raciniewski ◽

James F. Simon ◽

Robert Wyllie ◽

...

Keyword(s):

Health System ◽

Surveillance System ◽

Cost Savings ◽

Automated System ◽

Surveillance Systems ◽

Predictive Values ◽

Visualization Software ◽

Independent Information ◽

Influenza Activity ◽

Automated Surveillance

Abstract Background Performing high-quality surveillance for influenza-associated hospitalization (IAH) is challenging, time-consuming, and essential. Objectives Our objectives were to develop a fully automated surveillance system for laboratory-confirmed IAH at our multihospital health system, to evaluate the performance of the automated system during the 2018 to 2019 influenza season at eight hospitals by comparing its sensitivity and positive predictive value to that of manual surveillance, and to estimate the time and cost savings associated with reliance on the automated surveillance system. Methods Infection preventionists (IPs) perform manual surveillance for IAH by reviewing laboratory records and making a determination about each result. For automated surveillance, we programmed a query against our Enterprise Data Vault (EDV) for cases of IAH. The EDV query was established as a dynamic data source to feed our data visualization software, automatically updating every 24 hours.To establish a gold standard of cases of IAH against which to evaluate the performance of manual and automated surveillance systems, we generated a master list of possible IAH by querying four independent information systems. We reviewed medical records and adjudicated whether each possible case represented a true case of IAH. Results We found 844 true cases of IAH, 577 (68.4%) of which were detected by the manual system and 774 (91.7%) of which were detected by the automated system. The positive predictive values of the manual and automated systems were 89.3 and 88.3%, respectively.Relying on the automated surveillance system for IAH resulted in an average recoup of 82 minutes per day for each IP and an estimated system-wide payroll redirection of $32,880 over the four heaviest weeks of influenza activity. Conclusion Surveillance for IAH can be entirely automated at multihospital health systems, saving time, and money while improving case detection.

Download Full-text

Performance of Avian Influenza Surveillance System, Ogun State Nigeria, 2015-2019

Global Journal of Medical Research ◽

10.34257/gjmrgvol20is1pg25 ◽

2020 ◽

pp. 25-35

Author(s):

Folajimi. O. Shorunke ◽

Aisha Usman ◽

Tade Adeniyi Olanrewaju ◽

Ndadilnasiya Endie Waziri ◽

S. N. Grace

Keyword(s):

Avian Influenza ◽

Surveillance System ◽

Highly Pathogenic Avian Influenza ◽

Health Workers ◽

Action Plan ◽

Influenza Surveillance ◽

Surveillance Systems ◽

Highly Pathogenic ◽

Pathogenic Avian Influenza ◽

Ogun State

Background: In 2019, two Highly pathogenic avian influenza (HPAI) A(H5N8) outbreaks in poultry establishments in Bulgaria, two of wild birds in Denmark and one low pathogenic avian influenza (LPAI) A(H5N3) in captive birds in the Netherlands were reported. Nigeria recorded the first outbreak of Highly Pathogenic Avian Influenza (HPAI) in February 2006 in a commercial poultry farm. Nigerian Pandemic Preparedness and Action Plan for Avian Influenza were then used to respond. Although influenza sentinel surveillance has been established in several African countries including Nigeria, data about the performance of established surveillance systems are limited on the continent. We described the avian influenza (AI) surveillance system in Ogun State, accessed veterinary health workers and farmers knowledge, evaluated all its attributes and made recommendations to improve the AI surveillance system. Methods: We adopted 2001 CDC Updated Guidelines for Evaluating Public Health Surveillance Systems. We reviewed and analyzed passive surveillance data from Ogun State Ministry of Agric, key informant interviews were conducted for relevant stakeholders at the state level and Local Government divisional veterinary clinics and farms to obtain additional information on the operations of the system.

Download Full-text

Implementation of Real-Time Laboratory-Based Influenza Surveillance System, Thailand

Online Journal of Public Health Informatics ◽

10.5210/ojphi.v10i1.8921 ◽

2018 ◽

Vol 10 (1) ◽

Author(s):

Phunlerd Piyaraj ◽

Nira Pet-hoi ◽

Chaiyos Kunanusont ◽

Supanee Sangiamsak ◽

Somsak Wankijcharoen ◽

...

Keyword(s):

Infectious Disease ◽

Influenza Virus ◽

Real Time ◽

Surveillance System ◽

Influenza A ◽

Medical Services ◽

Influenza Surveillance ◽

Surveillance Systems ◽

Private Hospitals ◽

Influenza A H1n1

Objective: We describe the Bangkok Dusit Medical Services Surveillance System (BDMS-SS) and use of surveillance efforts for influenza as an example of surveillance capability in near real-time among a network of 20 hospitals in the Bangkok Dusit Medical Services group (BDMS).Introduction: Influenza is one of the significant causes of morbidity and mortality globally. Previous studies have demonstrated the benefit of laboratory surveillance and its capability to accurately detect influenza outbreaks earlier than syndromic surveillance.1-3 Current laboratory surveillance has an approximately 4-week lag due to laboratory test turn-around time, data collection and data analysis. As part of strengthening influenza virus surveillance in response to the 2009 influenza A (H1N1) pandemic, the real-time laboratory-based influenza surveillance system, the Bangkok Dusit Medical Services Surveillance System (BDMS-SS), was developed in 2010 by the Bangkok Health Research Center (BHRC). The primary objective of the BDMS-SS is to alert relevant stakeholders on the incidence trends of the influenza virus. Type-specific results along with patient demographic and geographic information were available to physicians and uploaded for public health awareness within 24 hours after patient nasopharyngeal swab was collected. This system advances early warning and supports better decision making during infectious disease events.2 The BDMS-SS operates all year round collecting results of all routinely tested respiratory clinical samples from participating hospitals from the largest group of private hospitals in Thailand.Methods: The BDMS has a comprehensive network of laboratory, epidemiologic, and early warning surveillance systems which represents the largest body of information from private hospitals across Thailand. Hospitals and clinical laboratories have deployed automatic reporting mechanisms since 2010 and have effectively improved timeliness of laboratory data reporting. In April 2017, the capacity of near real-time influenza surveillance in BDMS was found to have a demonstrated and sustainable capability.Results: From October 2010 to April 2017, a total of 482,789 subjects were tested and 86,110 (17.8%) cases of influenza were identified. Of those who tested positive for influenza they were aged <2 years old (4.6%), 2-4 year old (10.9%), 5-14 years old (29.8%), 15-49 years old (41.9%), 50-64 years old (8.3%) and >65 years old (3.7%). Approximately 50% of subjects were male and female. Of these, 40,552 (47.0%) were influenza type B, 31,412 (36.4%) were influenza A unspecified subtype, 6,181 (7.2%) were influenza A H1N1, 4,001 (4.6%) were influenza A H3N2, 3,835 (4.4%) were influenza A seasonal and 196 (0.4%) were respiratory syncytial virus (RSV).The number of influenza-positive specimens reported by the real-time influenza surveillance system were from week 40, 2015 to week 39, 2016. A total of 117,867 subjects were tested and 17,572 (14.91%) cases tested positive for the influenza virus (Figure 1). Based on the long-term monitoring of collected information, this system can delineate the epidemiologic pattern of circulating viruses in near real-time manner, which clearly shows annual peaks in winter dominated by influenza subtype B in 2015-1016 season. This surveillance system helps to provide near real-time reporting, enabling rapid implementation of control measures for influenza outbreaks.Conclusions: This surveillance system was the first real-time, daily reporting surveillance system to report on the largest data base of private hospitals in Thailand and provides timely reports and feedback to all stakeholders. It provides an important supplement to the routine influenza surveillance system in Thailand. This illustrates a high level of awareness and willingness among the BDMS hospital network to report emerging infectious diseases, and highlights the robust and sensitive nature of BDMS’s surveillance system. This system demonstrates the flexibility of the surveillance systems in BDMS to evaluate to emerging infectious disease and major communicable diseases. Through participation in the Thailand influenza surveillance network, BDMS can more actively collaborate with national counterparts and use its expertise to strengthen global and regional surveillance capacity in Southeast Asia, in order to secure advances for a world safe and secure from infectious disease. Furthermore, this system can be quickly adapted and used to monitor future influenzas pandemics and other major outbreaks of respiratory infectious disease, including novel pathogens.

Download Full-text

Utility of Nontraditional Data Sources for Early Detection of Influenza

Online Journal of Public Health Informatics ◽

10.5210/ojphi.v9i1.7636 ◽

2017 ◽

Vol 9 (1) ◽

Author(s):

Shari Barlow ◽

Jonathan Temte ◽

Yenlik Zheteyeva ◽

Ashley Fowlkes ◽

Carrie Reed ◽

...

Keyword(s):

Age Groups ◽

School Closure ◽

Influenza Viruses ◽

Influenza Surveillance ◽

Surveillance Systems ◽

School Absenteeism ◽

School Closures ◽

School Based ◽

Influenza Transmission ◽

Influenza Outbreaks

ObjectiveThis session will provide an overview of the current systemsfor influenza surveillance; review the role of schools in influenzatransmission; discuss relationships between school closures, schoolabsenteeism, and influenza transmission; and explore the usefulnessof school absenteeism and unplanned school closure monitoring forearly detection of influenza in schools and broader communities.IntroductionInfluenza surveillance is conducted through a complex networkof laboratory and epidemiologic systems essential for estimatingpopulation burden of disease, selecting influenza vaccine viruses,and detecting novel influenza viruses with pandemic potential (1).Influenza surveillance faces numerous challenges, such as constantlychanging influenza viruses, substantial variability in the number ofaffected people and the severity of disease, nonspecific symptoms,and need for laboratory testing to confirm diagnosis. Exploringadditional components that provide morbidity information mayenhance current influenza surveillance.School-aged children have the highest influenza incidence ratesamong all age groups. Due to the close interaction of children inschools and subsequent introduction of influenza into households,it is recognized that schools can serve as amplification points ofinfluenza transmission in communities. For this reason, pandemicpreparedness recommendations include possible pre-emptive schoolclosures, before transmission is widespread within a school system orbroader community, to slow influenza transmission until appropriatevaccines become available. During seasonal influenza epidemics,school closures are usually reactive, implemented in response tohigh absenteeism of students and staff after the disease is alreadywidespread in the community. Reactive closures are often too late toreduce influenza transmission and are ineffective.To enhance timely influenza detection, a variety of nontraditionaldata sources have been explored. School absenteeism was suggestedby several research groups to improve school-based influenzasurveillance. A study conducted in Japan demonstrated that influenza-associated absenteeism can predict influenza outbreaks with highsensitivity and specificity (2). Another study found the use of all-causes absenteeism to be too nonspecific for utility in influenzasurveillance (3). Creation of school-based early warning systemsfor pandemic influenza remains an interest, and further studies areneeded. The panel will discuss how school-based surveillance cancomplement existing influenza surveillance systems.

Download Full-text

The Fever Coach Mobile App for Participatory Influenza Surveillance in Children: Usability Study

JMIR mhealth and uhealth ◽

10.2196/14276 ◽

2019 ◽

Vol 7 (10) ◽

pp. e14276 ◽

Cited By ~ 8

Author(s):

Myeongchan Kim ◽

Sehyo Yune ◽

Seyun Chang ◽

Yuseob Jung ◽

Soon Ok Sa ◽

...

Keyword(s):

Health Care Providers ◽

Surveillance System ◽

Central Government ◽

Time Lag ◽

Target Population ◽

Mobile App ◽

Influenza Surveillance ◽

Care Providers ◽

Surveillance Network ◽

Influenza Activity

Background Effective surveillance of influenza requires a broad network of health care providers actively reporting cases of influenza-like illnesses and positive laboratory results. Not only is this traditional surveillance system costly to establish and maintain but there is also a time lag between a change in influenza activity and its detection. A new surveillance system that is both reliable and timely will help public health officials to effectively control an epidemic and mitigate the burden of the disease. Objective This study aimed to evaluate the use of parent-reported data of febrile illnesses in children submitted through the Fever Coach app in real-time surveillance of influenza activities. Methods Fever Coach is a mobile app designed to help parents and caregivers manage fever in young children, currently mainly serviced in South Korea. The app analyzes data entered by a caregiver and provides tailored information for care of the child based on the child’s age, sex, body weight, body temperature, and accompanying symptoms. Using the data submitted to the app during the 2016-2017 influenza season, we built a regression model that monitors influenza incidence for the 2017-2018 season and validated the model by comparing the predictions with the public influenza surveillance data from the Korea Centers for Disease Control and Prevention (KCDC). Results During the 2-year study period, 70,203 diagnosis data, including 7702 influenza reports, were submitted. There was a significant correlation between the influenza activity predicted by Fever Coach and that reported by KCDC (Spearman ρ=0.878; P<.001). Using this model, the influenza epidemic in the 2017-2018 season was detected 10 days before the epidemic alert announced by KCDC. Conclusions The Fever Coach app successfully collected data from 7.73% (207,699/2,686,580) of the target population by providing care instruction for febrile children. These data were used to develop a model that accurately estimated influenza activity measured by the central government agency using reports from sentinel facilities in the national surveillance network.

Download Full-text

Evaluation of the Influenza Sentinel Surveillance System in the Democratic Republic of Congo, 2012-2015

10.21203/rs.2.10330/v1 ◽

2019 ◽

Author(s):

Pélagie Diambalula Babakazo ◽

Joelle Kabamba-Tshilobo ◽

Emile Okitolonda Wemakoy ◽

Léopold Lubula ◽

Léonie Kitoko Manya ◽

...

Keyword(s):

Data Quality ◽

Surveillance System ◽

Democratic Republic ◽

Democratic Republic Of Congo ◽

Sentinel Surveillance ◽

World Health ◽

Influenza Surveillance ◽

Surveillance Systems ◽

Republic Of Congo ◽

Sentinel Surveillance System

Abstract Background The World Health Organization recommends periodic evaluations of influenza surveillance systems to identify areas for improvement and provide evidence of data reliability for policymaking. However, data about the performance of established influenza surveillance systems are limited in Africa, including in the Democratic Republic of Congo (DRC). Methods We used the Centers for Disease Control and Prevention guidelines to evaluate the performance of the influenza sentinel surveillance system (ISSS) in DRC during 2012-2015. The performance of the system was evaluated using eight surveillance attributes: (i) data quality and completeness for key variables, (ii) timeliness, (iii) representativeness, (iv) flexibility, (v) simplicity, (vi) acceptability, (vii) stability and (viii) utility. For each attribute, specific indicators were developed and described using quantitative and qualitative methods. Scores for each indicator were as follows: <60% weak performance; 60-79% moderate performance; ≥80% good performance. Results During 2012-2015, we enrolled and tested 4,339 patients with influenza-like illness (ILI) and 2,869 patients with severe acute respiratory illness (SARI) from 11 sentinel sites situated in 5 of 11 provinces. Influenza viruses were detected in 446 (10.3%) samples from patients with ILI and in 151 (5.5%) samples from patients with SARI with higher detection during December-May. Data quality and completeness was >90% for all evaluated indicators. Other strengths of the system were timeliness, representativeness, simplicity, stability and utility that scored >70% each. Flexibility and acceptability had moderate to week performance. It was reported that the ISSS contributed to: (i) a better understanding of the epidemiology, circulating patterns and proportional contribution of influenza virus among patients with ILI or SARI; (ii) acquisition of new key competences related to influenza surveillance and diagnosis; and (iii) continuous education of surveillance staff and clinicians at sentinel sites about influenza. However, due to limited resources no actions were undertaken to mitigate the impact of seasonal influenza epidemics. Conclusions The system performed overall satisfactorily and provided reliable and timely data about influenza circulation in DRC. The simplicity of the system contributed to its stability. A better use of the available data could be made to inform and promote prevention interventions especially among the most vulnerable groups.

Download Full-text

Detecting influenza and emerging avian influenza virus by influenza and pneumonia surveillance systems in a large city in China, 2005 to 2016

BMC Infectious Diseases ◽

10.1186/s12879-019-4405-5 ◽

2019 ◽

Vol 19 (1) ◽

Author(s):

Xiaorong Guo ◽

Dong Yang ◽

Ruchun Liu ◽

Yaman Li ◽

Qingqing Hu ◽

...

Keyword(s):

Influenza Virus ◽

Avian Influenza ◽

Avian Influenza Virus ◽

Surveillance System ◽

Large City ◽

Influenza Viruses ◽

Influenza Surveillance ◽

Surveillance Systems ◽

Incident Cases ◽

Death Cases

Abstract Background Detecting avian influenza virus has become an important public health strategy for controlling the emerging infectious disease. Methods The HIS (hospital information system) modified influenza surveillance system (ISS) and a newly built pneumonia surveillance system (PSS) were used to monitor the influenza viruses in Changsha City, China. The ISS was used to monitor outpatients in two sentinel hospitals and to detect mild influenza and avian influenza cases, and PSS was used to monitor inpatients in 49 hospitals and to detect severe and death influenza cases. Results From 2005 to 2016, there were 3,551,917 outpatients monitored by the ISS system, among whom 126,076 were influenza-like illness (ILI) cases, with the ILI proportion (ILI%) of 3.55%. After the HIS was used, the reported incident cases of ILI and ILI% were increased significantly. From March, 2009 to September, 2016, there were 5,491,560 inpatient cases monitored by the PSS system, among which 362,743 were pneumonia cases, with a proportion of 6.61%. Among pneumonia cases, about 10.55% (38,260/362,743) of cases were severe or death cases. The pneumonia incidence increased each year in the city. Among 15 avian influenza cases reported from January, 2005 to September, 2016, there were 26.7% (4/15) mild cases detected by the HIS-modified ISS system, while 60.0% (9/15) were severe or death cases detected by the PSS system. Two H5N1 severe cases were missed by the ISS system in January, 2009 when the PSS system was not available. Conclusions The HIS was able to improve the efficiency of the ISS for monitoring ILI and emerging avian influenza virus. However, the efficiency of the system needs to be verified in a wider area for a longer time span in China.

Download Full-text