Module 6: Syndromic Surveillance

Syndromic Surveillance in the Developed World

The CDC endorses the definition of syndromic surveillance (SS) as a type of health surveillance system that is "used for early detection of outbreaks, to follow the size, spread, and tempo of outbreaks, to monitor disease trends, and to provide reassurance that an outbreak has not occurred. Syndromic surveillance systems seek to use existing health data in real time to provide immediate analysis and feedback to those charged with investigation and follow-up of potential outbreaks."(1) SS can use readily available information such as increased drug purchases or school absences to identify potential disease outbreaks before the victims seek medical attention.(2) Speed of detection is crucial when a timely intervention can improve patient outcomes and decrease the rate of transmission. Out of fear of potential bioterrorism attacks, increased research and investment have been poured into SS in the developed world.

In the United States, the CDC developed the National Syndromic Surveillance Program called BioSense. The program was launched in 2003 in response to the Public Health Security and Bioterrorism Preparedness and Response Act of 2002, and it aims to guard the health of U.S. citizens by improving data collection and analysis to give public health officials a better picture of community health.(3) The BioSense Platform is the revised version of former BioSense software which allows for users to rapidly collect, evaluate, share, and store surveillance data using an integrated electronic health information system.(4) Syndromic surveillance is expected to improve in the U.S. now that the American Reinvestment and Recovery Act (2009) gives clinicians incentives to switch to electronic health records (EHR). EHRs make it easier to send health data (e.g. symptoms) to public health agencies for SS.(5)

SS data can come from clinical sites (such as emergency rooms and urgent care centers) and non-clinical sites (such as EMS, 911 and poison control, and schools).(6) According to the International Society for Disease Surveillance, the following are characteristics of SS that separate it from other types of surveillance:(7)

• Timeliness (almost real-time data collection)

• Pre-diagnostic (does not have to wait for diagnostics to identify a public health problem)

• Population focus (focuses on community, not individual health)

• De-identified data (no names or personal information attached to health information)

• Unfiltered records (all patients recorded, not just those that meet specific requirements; this helps with case detection when the disease might not be well known or identified at first by clinicians)

Application of Syndromic Surveillance in Developing Countries

Many experts in the field of syndromic surveillance believe that there is great potential for surveillance in developing countries. SS costs less than other forms of surveillance, can help with the detection of outbreaks where there are shortages of doctors, and can be undertaken with relatively minimal technology.(8) SS may be a realistic alternative option where lab diagnosis is not readily available or cost effective.(9) Some countries are using health indicators like changes in weather patterns to predict disease epidemics.(10) Syndromic surveillance could also be useful in cases of novel and emerging infections where the technology or expertise is not available to identify new pathogens.(11) In the developing world, there has been a substantial increase in access to the internet and to mobile phones, facilitating the feasibility of syndromic surveillance in low-income countries.(12) In countries challenged by inadequate infrastructure, syndromic surveillance may be used to enhance existing surveillance and outbreak detection infrastructure, rather than as a replacement.(13)

Case Study: Early Warning Outbreak Recognition System in Jakarta

The Early Warning Outbreak Recognition System (EWORS), developed by the Indonesian Ministry of Health and the U.S. Naval Medical Research Unit, became the official national health surveillance system of Indonesia in 2007.(14) EWORS is a computer software-based syndromic surveillance system. Participating health care providers fill out a standard questionnaire about each of their patients that includes the patient’s clinical and demographic information. This information is emailed to the Ministry of Health, where the data across many geographic areas is collected and analyzed in the hopes of quickly identifying potential outbreaks. While there have been some challenges to the system, (including issues with standardization across the platform and mobilizing appropriate agencies to act upon data when necessary,) the program has been successful, and has expanded to include other Southeast Asian countries. In the case of Jakarta, Syndromic surveillance systems have proven to be functional and effective in controlling disease outbreaks in a developing region. More studies ought to be done to confirm that SS is helpful and cost effective in developing countries.

Information in the above case study was adapted from the following article:(15)

http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.0050072

Footnotes

(1) Henning, K. J. (2004). What is syndromic surveillance. Morbidity and mortality weekly report, 53(Supplement), 7-11.

(2) Mack, A., Choffnes, E. R., Sparling, P. F., Hamburg, M. A., & Lemon, S. M. (Eds.). (2007). Global Infectious Disease Surveillance and Detection: Assessing the Challenges" Finding Solutions: Workshop Summary. National Academies Press.

(3) Centers for Disease Control and Prevention. (2019) National Syndromic Surveillance Program (NSSP).  https://www.cdc.gov/nssp/index.html.

(4) Ibid.

(5) International Society for Disease Surveillance. (2011) Final Recommendation: Core Processes and EHR Requirements for Public Health Syndromic Surveillance.

(6) Ibid.

(7) Ibid.

(8) Chretien, J. P., Burkom, H. S., Sedyaningsih, E. R., Larasati, R. P., Lescano, A. G., Mundaca, C. C., ... & Lewis, S. H. (2008). Syndromic surveillance: adapting innovations to developing settings. PLoS medicine, 5(3), e72.

(9) Mack, A., Choffnes, E. R., Sparling, P. F., Hamburg, M. A., & Lemon, S. M. (Eds.). (2007). Global Infectious Disease Surveillance and Detection: Assessing the Challenges" Finding Solutions: Workshop Summary. National Academies Press.

(10) Chretien J-P, Burkom HS, Sedyaningsih ER, Larasati RP, Lescano AG, et al. (2008) Syndromic Surveillance: Adapting Innovations to Developing Settings. PLoS Med 5(3): e72.

(11) Ibid.

(12) Ibid.

(13) Zatorski, C., & May, L. (2013). Emerging Infectious Diseases and the Role of Syndromic Surveillance in the Developing World. Journal of Medical Bacteriology, 2(1-2), 60-64.

(14) May, L., Chretien, J., & Pavlin, J. (2009). Beyond traditional surveillance: applying syndromic surveillance to developing settings – opportunities and challenges. BMC Public Health 9(1), 242. Zatorski, C., & May, L. (2013). Emerging Infectious Diseases and the Role of Syndromic Surveillance in the Developing World. Journal of Medical Bacteriology, 2(1-2), 60-64.

(15) Ibid.