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Surveillance Systems

The Karachi Health and Demographic Surveillance System was set up in year 2003 by the Department of Pediatrics and Child Health of the Aga Khan University, Karachi, Pakistan, in four peri-urban low socioeconomic communities of Karachi and covers an area of 17.6 square kilometers.(Figure 1).

Objective:

The mandate of establishing this DSS is to provide a research platform for both observational and interventional studies, with focus on maternal and child health, which could influence decision-making and planning for health strategies at local, national and international levels.

Submitted by elamb on

The Georgia DPH has used its State Electronic Notifiable Disease Surveillance System (SendSS) Syndromic Surveillance (SS) module to collect, analyze and display analyses of ED patient visits, including DDx data from hospitals throughout Georgia for early detection and investigation of cases of reportable diseases before laboratory test results are available. Evidence on the value of syndromic surveillance approaches for outbreak or event detection is limited. Use of the DDx field within datasets, specifically as it might be used for investigation of outbreaks, clusters, and / or individual cases of reportable diseases, has not been widely discussed.

Objective:

To describe how the Georgia Department of Public Health (DPH) uses ICD-9 and ICD-10-based discharge diagnoses (DDx) codes assigned to Emergency Department (ED) patients to support the early detection and investigation of outbreaks, clusters, and individual cases of reportable diseases.

Submitted by elamb on

Definitions of “re-emerging infectious diseases” typically encompass any disease occurrence that was a historic public health threat, declined dramatically, and has since presented itself again as a significant health problem. Examples include antimicrobial resistance leading to resurgence of tuberculosis, or measles re-appearing in previously protected communities. While the language of this verbal definition of “re-emergence” is sensitive enough to capture most epidemiologically relevant resurgences, its qualitative nature obfuscates the ability to quantitatively classify disease re-emergence events as such.

Objective:

Although relying on verbal definitions of "re-emergence", descriptions that classify a “re-emergence” event as any significant recurrence of a disease that had previously been under public health control, and subjective interpretations of these events is currently the conventional practice, this has the potential to hinder effective public health responses. Defining re-emergence in this manner offers limited ability for ad hoc analysis of prevention and control measures and facilitates non-reproducible assessments of public health events of potentially high consequence. Re-emerging infectious disease alert (RED Alert) is a decision-support tool designed to address this issue by enhancing situational awareness by providing spatiotemporal context through disease incidence pattern analysis following an event that may represent a local (country-level) re-emergence. The tool’s analytics also provide users with the associated causes (socioeconomic indicators) related to the event, and guide hypothesis-generation regarding the global scenario.

Submitted by elamb on

The global strategy for eliminating tuberculosis (TB) epidemic "End TB" has been implemented in the world since 2016. Its main goal is to reduce the 2015 TB incidence rate by 90% and 2015 TB mortality rate by 95% by 2035. In Ukraine, in 2016, the incidence rate of new cases of tuberculosis among the general population was 54.7 per 100 thousand of population (2015 - 55.9), the rate of decrease was 2.1 ± 0.1%. In Donetsk Oblast (that is under control of Ukrainian authorities), the incidence rate increased by 2.4% and was 56.4 per 100 thousand of population. The mortality rates were 19 ± 0.6% in the country and 29 ± 2.5% in Donetsk Oblast. However, according to the World Health Organization (WHO) estimates, we need to enhance the annual incidence rate reduction by 10% by 2025, and TB mortality rate should be reduced to 6.5% in order to achieve the strategy-targeted values. In Ukraine, as well as globally, there is a crisis of multidrug-resistant tuberculosis (MDR-TB). According to WHO estimates, Ukraine belongs to five European countries where 2/3 of MDR-TB cases were registered; the proportion of MDR-TB cases among newly diagnosed TB cases was 16%, and 48% of repeated cases. In Ukraine, this rate is equal to 24.3% and 58.2% in Donetsk Oblast, respectively. Such results in the Donetsk region may be related to the beginning of hostilities in eastern Ukraine in 2014, which lead to the active migration of population and breakdown of the supply of anti-TB drugs. According to monitoring data, 20% of with MDR-TB on the territory of the Donetsk region controlled by Ukraine were lost and did not seek medical assistance.

Objective:

Describe the common work of Donetsk State Phthisiological Service and non-governmental organizations that has been conducted since 2014 in order to achieve the global goal for tuberculosis elimination.

Submitted by elamb on

At the Governor’s Opioid Addiction Crisis Datathon in September 2017, a team of Booz Allen data scientists participated in a two-day hackathon to develop a prototype surveillance system for business users to locate areas of high risk across multiple indicators in the State of Virginia. We addressed 1) how different geographic regions experience the opioid overdose epidemic differently by clustering similar counties by socieconomic indicators, and 2) facilitating better data sharing between health care providers and law enforcement. We believe this inexpensive, open source, surveillance approach could be applied for states across the nation, particularly those with high rates of death due to drug overdoses and those with significant increases in death.

Objective:

A team of data scientists from Booz Allen competed in an opioid hackathon and developed a prototype opioid surveillance system using data science methods. This presentation intends to 1) describe the positives and negatives of our data science approach, 2) demo the prototype applications built, and 3) discuss next steps for local implementation of a similar capability.

Submitted by elamb on

Scarlet fever is a bacterial infection caused by group A streptococcus (GAS). The clinical symptoms are usually mild. Before October, 2007, case-based surveillance of scarlet fever was conducted through notifiable infectious diseases in Taiwan, but was removed later from the list of notifiable disease because of improved medical care capacities. In 2011, Hong Kong had encountered an outbreak of scarlet fever (1,2). In response, Taiwan developed an integrated syndromic surveillance system using multiple data sources since July 2011.

Objective

To develop an integrated syndromic surveillance system for timely monitoring and early detection of unusual situations of scarlet fever in Taiwan, since Hong Kong, being so close geographically to Taiwan, had an outbreak of scarlet fever in June 2011.

 

Submitted by Magou on

There has been much interest in the use of statistical surveillance systems over the last decade, prompted by concerns over bio-terrorism, the emergence of new pathogens such as SARS and swine flu, and the persistent public health problems of infectious disease outbreaks. In the United Kingdom (UK), statistical surveillance methods have been in routine use at the Health Protection Agency (HPA) since the early 1990s and at Health Protection Scotland (HPS) since the early 2000s (1,2). These are based on a simple yet robust quasi-Poisson regression method (1). We revisit the algorithm with a view to improving its performance.

Objective

To improve the performance of the England and Wales large scale multiple statistical surveillance system for infectious disease outbreaks with a view to reducing the number of false reports, while retaining good power to detect genuine outbreaks.

 

Submitted by Magou on

Syndromic surveillance systems offer richer understanding of population health. However, because of their complexity, they are less used at small public health agencies, such as many local health departments (LHDs). The evolution of these systems has included modifying user interfaces for more efficient and effective use at the local level. The North Carolina Preparedness and Emergency Response Research Center previously evaluated use of syndromic surveillance information at LHDs in North Carolina. Since this time, both the NC DETECT system and distribution of syndromic surveillance information by the state public health agency have changed. This work describes use following these changes.

Objective

Our objective was to describe changes in use following syndromic surveillance system modifications and assess the effectiveness of these modifications.

 



 

Submitted by Magou on

Special event driven syndromic surveillance is often initiated by public health departments with limited time for development of an automated surveillance framework, which can result in heavy reliance on frontline care providers and potentially miss early signs of emerging trends. To address timelines and reliability issues, automated surveillance system are required.

Objective

To develop and implement a framework for special event surveillance using GUARDIAN, as well as document lessons learned postevent regarding design challenges and usability.



 

Submitted by Magou on

Vietnam has routinely monitored HIV sero-prevalence among key populations through its HIV sentinel surveillance system (HSS). In 2010, this system was updated to include a behavioral component (HSS+) among people who inject drugs, female sex workers, and men who have sex with men. HSS+ has historically used a paper-based questionnaire for data collection. At the end of the survey, provincial data were manually entered into computers using EpiData Entry forms (http://www.epidata.dk/) and submitted to the Vietnam Authority of HIV/AIDS Control (VAAC). As a result, feedback to provinces on data issues was not provided until after fieldwork completion. One recent survey used tablets for data collection and found that it saved time, required fewer staff, and reduced costs compared to paper-based data collection. In 2017, Vietnam introduced tablet for behavioral data collection in HSS+ to improve data quality, resource saving, and to provide more timely access to data.

Objective:

To describe the implementation process, successes, challenges, and lessons learned of the application of tablet for data collection and data system in HIV sentinel surveillance in Vietnam.

Submitted by elamb on
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