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Overview of public health surveillance systems in Australia

Discuss about the Sociodemographic and Geographical Inequalities.

Public health surveillance is the process of analysing, interpreting and dissemination health related data on specific disease and applying it in public health activities to improve the health of affected group. It may help to measure the burden of disease, guide disease prevention and control program and identify changes needed in public health practice (1). Hemolytic uraemic syndrome is a rare and serious clinical condition characterized by chronic renal failures in adults and acute kidney injury in children. The pathogenesis of HUS is mainly seen due to the infection from toxin producing strains of E.coli and Shiga toxin.  The infection results in damage to the endothelial wall and pathologic changes like hemolytic anemia and renal abnormalities (2). According to the National Surveillance report, HUS is also seriously prevalent in Australia. In response to the rise in prevalence of HUS in Australia, this essay evaluates how notification and surveillance practices for HUS is implemented in Australia. It also discusses surveillance system for HUS in Australia based on the systems attributes of the Guidelines for Evaluating Public Health Surveillance System.

Public health surveillance system has been developed in various countries to address diverse public health needs. The system of collecting and interpreting the data related to health event helps in planning and formulating specific public health program. The system of collecting data for public health surveillance may differ ranging from collecting data from single source to receiving it in complex formats (3).  In Australia, the National Notifiable Disease Surveillance System was developed in 1990 for the national surveillance of more than 50 communicable disease. The notifications about disease are given to States or Territory health authority and the notifications are collated and published on daily by the Australian Government Department of Health. The notification mainly gives detail about state identifier, disease code and data of onset of disease (4). The system of notification also varies in different state and territories because the criteria for notification of different disease varies.

According to the publication of national notifiable disease list, HUS is also a notifiable disease in western Australia which comes under the category of gastrointestinal disease. The Communicable Disease Network Australia gives the direction regarding notifying communicable disease nationally. The criteria for defining confirmed case included having clinical evidence regarding the presence of acute microangiopathic anemia on peripheral blood smear and presence of either acute renal impairment or thrombocytopenia during first week of infection (5).

Reasons and manner of notification of HUS in Australia

The main reason for annual notification of HUS to the Public Health Department in Australia is that it comes under the category of gastrointestinal disease. Gastroenteritis is regarded a major cause of illness in Australia with about one episode per year. HUS has been included under notifiable disease category of gastrointestinal disease because it is a major cause of gastroenteritis in Australia. Although the incidence of HUS due to E.coli is lower than other bacterial infection, however it has been found to cause severe illness. The large outbreak of diarrhea during HUS infection results gives great challenges to public health agencies (6). It is also a legal obligation to notify about disease as part of the Schedule 4 of Public Health and Well Being Regulations 2009. This is necessary to take adequate action to preserve health and safety of public (7). Hence, it is necessary to notify about the disease to Public Health of Australia. There are four condition grouping for method of reporting about the disease and the HUS reporting falls under Group A. This means any cases of HUS must be urgently reported to the public health agency within a few hours of first suspicion of disease (8). The usefulness of this notification is that based on the data obtained, public health department of different states and territories takes actions to prevent infection and further exposure.

The effectiveness of the public health surveillance system is dependent on its integration with the health information system. A functional surveillance system will also have a clear objective, well defined target population, specific and reliable source of data and good mechanism of information dissemination. The evaluation of the usefulness of the surveillance system can also be done based on the identifying the actions that were undertaken after the interpretation of the data published. Secondly, the system attribute of simplicity, flexibility, data quality, acceptability, sensitivity, predictive value positive, representativeness, timeliness and stability also defines the performance of the surveillance system. The following is the detail regarding each system attribute of a functional surveillance system:

Simplicity: This attribute is defined by the structure and ease of operation of the surveillance system. The simplicity of the system helps in meeting the key objectives (3). In case of the surveillance system for HUS, the simplicity may be defined by a case definition that can be easily applied. However, currently the surveillance system for HUS in Australia is complex because of the need for peripheral blood smear to confirm the case and categorization of reporting into different groups (8). The more simpler a system is, the more readily it can be accepted for public health action.

Components of an effective surveillance system for HUS

Flexibility: A public health surveillance system can be made effective if it can instantly adapt to  changing needs based on data without additional funds or time. Such system can be created if new health related events can be easily accomodated and case definitions can be revised. Currently the surveillance system of Australia is inflexible to the changing needs as no revised care definitions for HUS has been found. Secondly, changing the system will require changing multiple components like case definitions, notification criteria and response procedure (9).

Data quality: The quality of data in surveillance system is defined by the transparency and validity of the data published in the system. Low percentage of blank response in surveillance form is an indicator of high quality date. The quality might also be affected by the quality of screening test for a disease and care taken during data management process. The data quality for HUS surveillance system can be effective if effective practice exist to monitor data quality. It should give clear detail regarding the reason for surveillance, case definition, disease, notification criteria and managing single and specific situations.

Acceptability: If a person involved in working with the surveillance system readily accepts the system, it is an indicator of acceptability in the system. Hence, acceptability can be measured during evaluation by the rate of agency participation, timeliness of data reporting and good reporting rate. In case of reporting about HUS case in Australia, it has been found that the health related event is reported annually. Large proportion of reported case was also found in summer (10).

Sensitivity: The attribute of sensitivity for HUS surveillance system can be defined if appropriate proportion of disease has been identified by the surveillance system and their ability to identify changes in cases with time. Hence, active surveillance based on monitoring the quality of case reporting for HUS and tracking suspicious cases will enhance the performance of the HUS surveillance system (3).

Predictive value positive (PVP): This is defined as the percentage of reported cases for which surveillance has been started. Therefore, the proportion of investigation and number of people who actually had disease will define this attribute. The PVP for HUS can be improved if the rate of erroneous case is low and there is good communication between the reporting and the receiving agency in Australia (11).

Representativeness: Representativeness is seen in a surveillance system if the changes in disease and its distribution by place and time is regularly recorded. For developing effective component for surveillance system of HUS, there is a need to evaluate the demographic characteristics of affected person and existing practices for detecting HUS in Australia (12).

Timeliness: Timeliness is determined by the pace at which key steps of the public health surveillance system can be implemented. The timeliness in relation to surveillance system for HUS can be improved by reducing time interval in recognition and notification of disease and having access to information about control strategies to prevent HUS (13).

Stability: Stability is defined by the reliability of the data collection process and the operationability of the system. The amount of time at which HUS surveillance system is operating fully determines the effectiveness of the system. There is a need to improve the time taken in releasing data to public and working full time on reducing the rate of HUS (3).

In Australia, the surveillance system exists for different categories of disease. There is a specified notification criteria for each health related event. The main relevant factors for surveillance in Australia includes the assessment of risk, developing strategic action plan for health related event, implementing the plan and monitoring and evaluating the outcome the surveillance system. The effectiveness is also dependent on resources, process, output, outcome and impact indicator (14). Appropriate resource for surveillance system includes fundings, clear guideline and surveillance form, trained personnel and good technology for recording. Relevant process indications include the process developed for tracking activities in respond to reporting of events (15). Output indicator required for Australian surveillance system includes the number of supervision visits implemented after publishing the surveillance data. In addition, relevant outcome indicators include the quality of system reflected from completeness of reporting and good response process for outbreak. Impact of the surveillance system is defined by the changes in morbidity and mortality pattern in related to a health related event (16).

Based on the system attribute defined by the Guidelines for evaluating Public Health Surveillance, the following is the evaluation of the Australian surveillance system with respect to system attributes:

Simplicity: A surveillance system is called functional if it has a simple case definition and reporting mechanism for notifiable disease. In case of Australian surveillance system, it has been found that complex reporting mechanism exist for about more than 50 communicable disease. Notifications are required from diagnostic laboratories or clinicians (14). This limits instant action. At the national level, communicable disease surveillance is coordinated by multiple agencies.

Flexibility: In the area of flexibility, it can be said that the Australian surveillance system is inflexible to the needs for having revised case definitions and changing funding process. However, development is now seen in adapting new digital technologies for surveillance of infectious disease at risk areas (17).

Data quality: The validity of the data released in the Australian surveillance system is good because three primary stakeholder like Communicable Disease Network Australia, the National Surveillance Committee and Communicable disease intelligence is responsible for managing and disseminating the data (18).

Acceptability: One of the strength of the Australian notifiable disease surveillance system is the high acceptability of the system by the public health personnel due to the completedness of the data and the reliance on laboratory rate for notifying diseases (18).

Sensitivity: The communicable disease surveillance system is found to be effective as it focused on describing the epidemiology of rare disease that occur in state and territories, They are also vigilant regarding the actions related to quarantine activities for disease (4).

Predictive positive value: The number of non case reporting and false positive reports is very low in Australia and this is because of well defined case definitions for different disease. The Australian surveillance system has the whole list for case definition of more than 50 communicable disease (4).

Representativeness, timeliness and stability: The representativeness and timelines of the system is high as annual case reports are published regularly and accurate response action in relation to the data is present. Presence of timeliness in reporting also enhances the stability of the Australian surveillance system (19).

Conclusion:

The report summarized the purpose of public health surveillance system and reasons for regarding HUS as a notifiable disease in Australia. The specific criteria for regarding HUS as a notifiable disease and method of reporting has been discussed. Secondly, the effectiveness of the surveillance system for HUS is also evaluated based on system attributes identified by the guideline for public health surveillance system. The system attribute has also helped to evaluate the performance of the Australian surveillance system in preventing health related events.

Reference

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Webster K, Schnitzler E. Hemolytic uremic syndrome. Handbook of clinical neurology. 2014;120:1113-23.

Updated Guidelines for Evaluating Public Health Surveillance Systems. Cdc.gov. . (2017). Retrieved 31 August 2017, from https://www.cdc.gov/mmwr/preview/mmwrhtml/rr5013a1.htm

Department of Health | Introduction to the National Notifiable Diseases Surveillance System. Health.gov.au. (2017).  Retrieved 31 August 2017, from https://www.health.gov.au/internet/main/publishing.nsf/content/cda-surveil-nndss-nndssintro.htm

Department of Health | Haemolytic uraemic syndrome (HUS) case definition. Health.gov.au. (2017).  Retrieved 31 August 2017, from https://www.health.gov.au/internet/main/publishing.nsf/Content/cda-surveil-nndss-casedefs-cd_hus.htm

Vally H, Hall G, Dyda A, Raupach J, Knope K, Combs B, Desmarchelier P. Epidemiology of Shiga toxin producing Escherichia coli in Australia, 2000-2010. BMC public health. 2012 Jan 21;12(1):63.

Notification procedures. Www2.health.vic.gov.au. (2017).  Retrieved 31 August 2017, from https://www2.health.vic.gov.au/public-health/infectious-diseases/notification-procedures

Haemolytic uraemic syndrome [Internet]. Ww2.health.wa.gov.au. 2017 [cited 31 August 2017]. Available from: https://ww2.health.wa.gov.au/Articles/F_I/Haemolytic-uraemic-syndrome

Haemolytic uraemic syndrome (HUS) and shigatoxigenic E. coli infections (STEC) control guideline - Control Guidelines [Internet]. Health.nsw.gov.au. 2017 [cited 31 August 2017]. Available from: https://www.health.nsw.gov.au/Infectious/controlguideline/Pages/haemo.aspx

Hemolytic uremic syndrome | Australia | PDF | PPT| Case Reports | Symptoms | Treatment [Internet]. Omicsonline.org. 2017 [cited 31 August 2017]. Available from: https://www.omicsonline.org/australia/hemolytic-uremic-syndrome-peer-reviewed-pdf-ppt-articles/

Williamson T, Green ME, Birtwhistle R, Khan S, Garies S, Wong ST, Natarajan N, Manca D, Drummond N. Validating the 8 CPCSSN case definitions for chronic disease surveillance in a primary care database of electronic health records. The Annals of Family Medicine. 2014 Jul 1;12(4):367-72.

Haemolytic uraemic syndrome (HUS) | Queensland Health [Internet]. Health.qld.gov.au. 2017 [cited 31 August 2017]. Available from: https://www.health.qld.gov.au/cdcg/index/hus

Forde BM, McAllister LJ, Paton JC, Paton AW, Beatson S. SMRT sequencing reveals differential patterns of methylation in two O111: H-Shiga toxigenic Escherichia coli isolates from a historic hemolytic uremic syndrome outbreak in Australia. bioRxiv. 2017 Jan 1:173336.

Sloan-Gardner T, Trungove M, Corvisy R, Bright A, Konrad C, Sloan-Gardner T, Knope K, Burroughs A, Martin N, Glynn-Robinson A, Toms C. AUSTRALIA'S NOTIFIABLE DISEASE STATUS, 2014: ANNUAL REPORT OF THE NATIONAL NOTIFIABLE DISEASES SURVEILLANCE SYSTEM. COMMUNICABLE DISEASES INTELLIGENCE. 2016 Mar 1;40(1):E48-145.

Gibney KB, Cheng AC, Hall R, Leder K. Sociodemographic and geographical inequalities in notifiable infectious diseases in Australia: a retrospective analysis of 21 years of national disease surveillance data. The Lancet Infectious Diseases. 2017 Jan 1;17(1):86-97.

Communicable disease surveillance and response system [Internet]. 2017 [cited 31 August 2017]. Available from: https://www.who.int/csr/resources/publications/surveillance/WHO_CDS_EPR_LYO_2006_2.pdf

Nsoesie EO, Kluberg SA, Mekaru SR, Majumder MS, Khan K, Hay SI, Brownstein JS. New digital technologies for the surveillance of infectious diseases at mass gathering events. Clinical Microbiology and Infection. 2015 Feb 28;21(2):134-40.

Gibney KB, Cheng AC, Hall R, Leder K. Australia's National Notifiable Diseases Surveillance System 1991–2011: expanding, adapting and improving. Epidemiology & Infection. 2017 Apr;145(5):1006-17.

Groseclose SL, Buckeridge DL. Public Health Surveillance Systems: Recent Advances in Their Use and Evaluation. Annual review of public health. 2017 Mar 20;38:57-79.

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