Select Committee on Science and Technology Written Evidence

Memorandum by North of Tyne Communicable Disease Control Unit, Dr Nicol Black


    —  Surveillance information should be the life-blood that powers clinical practice and public safety. It is not.

    —  Current surveillance does not provide an effective early warning system for outbreaks.

    —  Front-line agencies need the tools to do the job of health protection.

    —  Inaction may be costly and fatal.

    —  Prototype systems are available and evaluation could commence immediately.

  Dr Black has been a full-time Consultant in Communicable Disease Control since 1989, at Regional and District level. The North of Tyne Communicable Disease Control Unit is a busy team, comprising 12 people, serving a population of 775,000 in Northumberland, Newcastle and North Tyneside. It has been innovative in developing early-warning surveillance systems, risk assessment, teaching outbreak investigation, prevention and adult immunisation.

  (i)  Current communicable disease surveillance has got itself into a conceptual backwater, which is stifling its potential to influence front-line decision-making (whether in clinical practice or public health), to make new discoveries about novel threats that arise or to exploit the vast resources of clinical data in the NHS by modern electronic technologies.

  (ii)  In general, surveillance is not "owned" by front-line staff to prioritise actions but by remote institutions, patiently answering yesterday's questions. Much surveillance is reactive, out-dated, monolithic, slow to adapt and frequently irrelevant.

  (iii)  Current surveillance does not provide an effective early warning system for outbreaks.

  (iv)  There is no point in building a better smoke-detector if the fire service cannot respond adequately. The Department of Health strategy, set out in Getting Ahead of the Curve[33], sets out proposals for a Health Protection Agency (HPA), to improve the resources and organisation available, which should improve the "fire service". Though it envisages increased surveillance, it contains no clear surveillance strategy beyond "more of the same", ie it has not been far-sighted enough to identify the need for early warning systems.

  (v)  The perspective of active, innovative, surveillance systems for early warning and local risk analysis simply is not there. This contrasts with the dramatic changes in the USA since the revision of the bioterrorist threat since 11 September 2001. At a National Syndromic Surveillance Conference in New York in September 2002, with 450 delegates, which focused on early warning systems, there was only one participant from the UK.

  (vi)  The battle for protecting the health of communities will be won or lost by the front-line agencies. They need the tools to do the job. This surveillance perspective needs urgent action to disseminate and develop if costly and fatal inaction is to be prevented.

  (vii)  In a world increasingly concerned with a deliberate bioterrorist threat, early detection of clusters of non-specific prodromal symptoms may well be the sternest test of how well designed our surveillance systems are.

  (i)  Surveillance information should be the life-blood that powers clinical practice and public safety. It is not. It should monitor changing risk factors, to allow focused prevention activities, and assessment of the effectiveness of interventions in such a timely manner as to influence them. It does not. It should be sensitive to the early appearance of new hazards as they occur, whether local or national, and be an effective alerting system. It is not.

  (ii)  Why not? Current systems are antiquated, mainly reflecting bygone needs. They have become centralised in institutions divorced from day-to-day decision-making in the field, with a gulf between them and local public health practitioners. This has led to a steady decrease in interest and participation by the very people who should be the "eyes and ears" of an alert intelligence system. Local communicable disease control systems are under-resourced, under-appreciated, marginalised and often stagnant. Surveillance should be such an essential informative component of clinical and public health practice, that not being an integral part of these activities would be unthinkable. Just as we need established knowledge (eg from books and papers) we need contemporaneous information about the nature and level of risk and about how well our care systems are functioning in practice. In short, we need to be much more data-driven than ever before.

  (i)  In general, the twin aims of surveillance of communicable disease are to detect outbreaks and monitor trends. It is a mixture of statutory clinical notification and voluntary laboratory reporting.

  (ii)  Data gets into the system by meeting a case definition, which can be explicit (as in the US) or implicit, as in a clinical diagnosis. Something is either in or not in; there is no gradation of probability (see 4.i). If a diagnostic label turns out later to be something else, there is no easy way of refining or changing it (see box 1). There is little "depth" in the current case-based systems; "best guess" clinically is indistinguishable from immutable truth.


  Measles is clinically notifiable. A few years ago, serology, by collecting gingival exudates, was introduced. More than 90 per cent of these notifications were found to be conditions other than measles. However, there is no method of re-classification and they are not de-notified, to preserve continuity with notifications from previous years. We thus have a system that has measles notifications with a caveat that they are not measles.

  (iii)  Trend analysis. Most current activity is directed towards trend analysis. To ensure comparability the data collected is very prescriptive and usually laboratory based. To ensure continuity it does not change its definitions over time. Analysis is usually at large population level and seldom gets into underlying behaviours. It is highly ritualised, slow, frequently obsolete and often divorced from decision-making. New, or enhanced, topic-based, non-statutory surveillance schemes have been introduced in recent years which are an improvement, eg TB, HIV and sexually transmitted diseases.

  (iv)  Outbreak detection. There is a clinical notification system which was designed for rapid alerting of public health. In practice it does not work very well as most busy clinicians ignore it and seldom notify except in rare or serious cases. Indeed, most notifications are post-hoc following receipt of a positive laboratory report. Laboratory results provide firm data, but their usefulness is hampered by two factors. Firstly, for many infections the efficiency of detection is likely to be very low. Of all those exposed, the numbers of those infected, who then become ill, present to their doctor, have specimens collected, which turn out to have positive isolates, which are then notified to public health progressively diminishes, eg for common enteric illnesses, to probably around 5-6 per cent. Secondly, the delay between exposure and notification is often eight to nine days, which is much too long to be effective as an alerting mechanism. Any significant hazard will have had a lot of people exposed to it by the time laboratory results become available. Laboratory reporting is, however, particularly useful for picking up rare organisms or unusual subtypes both locally and nationally.

  (v)  Only a relatively small proportion of outbreaks come to light from routine surveillance. Most come to light by complaints from the public, observations of unusual occurrences by health professionals, the media or serendipity. Why does routine surveillance not play a bigger role? The two functions of detecting outbreaks and monitoring trends have very different information needs. Outbreak detection demands timely information, which will of necessity be incomplete and provisional. Trend analysis, by contrast, needs precise, accurate, information confirmed by laboratory tests, which inevitably means it will be delayed (fig 1).

  (vi)  Current surveillance practice has emphasised trend analysis at national level, where the need for precision takes precedence over the need for promptness. As such, most surveillance activity exists to support this with local public health needs in a subordinate role. Outbreak alertness has mainly relied on informal networks of clinicians and environmental health officers to identify symptomatic people with suspicious circumstances.

  (i)  Trend analysis needs precise data, shorn of ambiguity, to make it comparable between different places and over time. The filtering by tight case-definitions, or by mandating laboratory confirmation, means much partial, but potentially useful, information is rejected and does not even enter the system (see box 2).


  A condition with a probability of 40 per cent will be rejected by a system using binary logic. Hence three (or more) cases, each with a 40 per cent probability, will all be rejected. However, in real life, three patients in the same hospital, each with a 40 per cent probability of having smallpox, would have emergency alarm bells ringing.

  (ii)  The alternative is to create a people-based rather than a case-based system, to divorce observations from inferences, to record all the observations, with confidence estimates if appropriate, and then apply whatever range of case-definitions is appropriate to the accumulated data. This is the essence of a syndromic surveillance database (see section 7). This gives great scope for manipulating indices of probability or changing the constituent components of the case definition. As always with identifiable data, good security and confidentiality safeguards are mandatory.

  (iii)  This is the epidemiological approach taken with outbreak investigations. Time, place, symptom and behaviour data are collected for everyone potentially involved in the outbreak, which is then subjected to a series of increasingly sharper case-definitions as the precise nature of the hazard becomes more clearly defined. This allows control over the degree of ambiguity in various case-definitions. Essentially, this is the basis of a syndromic database. As it has no pre-fixed data model it is hugely versatile and can be used for any type of hazard (not just microbiological) and even in novel situations where the parameters of the condition have not yet been established (see section 7).

  (i)  The main problem facing infectious disease in the UK is lack of data exploitation "at the coal-face" by health-care workers and public health professionals. Lack of contextual data blunts diagnostic and treatment precision and prevention activities lack focus. Technology is not a problem; imagination, insufficient applied research and a long-term perspective, locally and nationally, is.

  (ii)  Surveillance is divorced from local epidemiology, particularly early warning of outbreaks and recognition of non-laboratory-confirmed conditions. It does not illuminate local variation in diagnosis and treatment, which varies widely from place to place, especially antibiotic usage and resistance, whose monitoring is still embryonic. Similarly, prevention is often the Cinderella of communicable disease control, threadbare and neglected, not least because of poor focus due to inadequately identified specific risk or local transmission factors.

  (iii)  Historically, there has always been an underlying pressure to collect "the minimum data-set" ie only sufficient data for the immediate purpose intended. This was rooted in sensible principles of thrift, economy of data collection and handling and confidentiality. However, as soon as one question is elucidated, the next is waiting to take its place and parsimony has often prevented surveillance systems evolving to meet the continually developing need. The obvious alternative is the ability to "drill down" from the macro to the micro as and when required. This means exploiting existing data collected for other purposes eg clinical morbidity data or, logically, constructing future data systems with multi-use clearly borne in mind. NHS Direct was such a missed opportunity when it was initially set up (see box 3).


  When a caller contacted NHS Direct, basic demographic data (age, sex, postcode) was collected, then the person proceeded down sets of algorithms, specific to the nature of the complaint, to an outcome, which was recorded. It was possible to extract lists of these outcomes ie how many callers clinically had an influenza-like illness, but this was not linked to the demographic data. As the call centres could be receiving calls from anywhere in the UK depending on demand, no linkage could be made to a specific geographic population, hence no inferences could be made about localised incidence, such as the spread of an epidemic.

  (i)  The policy intervention with the single greatest impact on prevention and containment would be to create modern, intelligent, surveillance systems, active and visible in every locality, addressing both local and national priority issues.

  (ii)  A national surveillance strategy has never before been defined. Though Getting Ahead of the Curve33, identifies the very laudable case for "world class surveillance", 5.3-5.17, it does not articulate any strategic aims or "mission statement". If health protection is in reality to be successfully delivered, it will only be by alert, competent field teams making sound risk assessments, based on relevant, up-to-date locally applicable data. It is not clear in Ch six, section three that this is recognised. As such, it does not go far enough. It appears to be advocating "more of the same", enshrining many of the limitations of current institutionalised practice, rather than any clear-sighted vision of locally driven health protection, alert to early warning signals and responsive to locally determined variations in risk or transmission.

  (iii)  Unless such a forward-looking responsive system is put in place we will fail to deliver public protection effectively. We need the emphasis shifted towards fire-watching and fire-prevention and away from elaborately crafted post-hoc descriptions of the blaze.

  (iv)  Much of the conceptual work for this has already been done and could be ready for widespread implementation in the near future. The bedrock of successful health protection is successful risk assessment and management. A conceptual model for risk management in communicable disease control, based on a quasi-probabilistic model, has been developed by a working party with a grant from the Department of Health[34]with further work refining a dynamic risk management priority index[35]

[36]. Good risk analysis depends on information acquisition (fig 2).

Fig 2—Risk Assessment in the communicable disease control function

  (v)  Methods for detecting emerging foci of infection at local level, which dovetail with formal risk assessment, have been developed[37]. In brief, these methodologies include developing systems of early warning markers (see appendix 1) and improved space-time cluster and pattern analysis. As they are syndromic-based, they have the advantage of versatility and are adaptable for bioterrorist activities or other conditions where the case-definition is unclear, eg in newly emerging infections.

  (i)  A syndrome is a complex of signs and/or symptoms whose coexistence is recognisable without necessarily pinpointing the precise nature of the underlying disease, eg AIDS was an identifiable new syndrome before the aetiological identification of HIV infection. New diseases invariably are recognised firstly as syndromes, eg BSE, Lyme Disease, Legionnaire's Disease, etc. It follows that syndromic surveillance is a tool for identifying which signs and symptoms are found to coexist, in a given time and place, than would be expected by chance on the assumption of independence.

  (ii)  This gives unprecedented flexibility in the type of data that can be collected, at whatever level of accuracy is available and analyse it for known and unknown patterns.

  (iii)  A well-designed syndromic system will reflect public health workflow, by capturing prevailing doubt and uncertainty by dynamically coding for changing levels of confidence in individual data items and by readily changing the search criteria. This allows previously unidentified patterns to be searched for. Mathematically rigorous belief diagrams make the analysis visible and explicit. Also, it could incorporate rule-based inference to run as an automated "expert system" in the background.

  (iv)  Because it reflects public health workflow, it also provides a means of reconciling the spectrum of risk (a continuous variable) to the outcome options (a discrete variable) in an explicit, mathematically rigorous way, which is intuitively identical to the existing process of epidemiological reasoning.

  (v)  Though syndromic surveillance is a very recent development internationally[38], particularly in response to bioterrorist threats, it has been under development[39] and in use for meningococcal disease and waterborne outbreaks in a busy communicable disease control unit in the North-East of England since 1995[40]. Another application being developed there is a detailed analysis of clinical data (in meningococcal infection) for risk recognition and response[41] and its feasibility for smallpox surveillance in the US is being explored[42]. A similar application could potentially track adverse effects of vaccines or pharmaceuticals, with appropriate pattern recognition and primary care morbidity data. Its applicability to pattern recognition in unexpected situations, eg non-terrestrial environmental syndromes in astronauts is under discussion with NASA[43].

  (vi)  A major consequence of the versatility of a generic, person-based syndromic system is that a single system could cover all aspects of all infectious diseases rather than multiple specific applications, with their inevitable multiple learning and support requirements.

  (vii)  The limitation of such a system is that until it is mature as a decision-support system, ie semi-automated, it is relatively labour-intensive. This confines its deployment to teams with sufficiently sophisticated epidemiological skills and capacity to conduct the analyses. Development work is currently underway on this, but much more work is needed to simplify this process and make it more efficient.


  It is not a case of either/or. Both are needed. National/international surveillance is needed for the "big picture", ie trend monitoring. Local surveillance is needed for outbreak detection, targeting prevention and ensuring data quality. It is the local level which is data-rich; eliminating ambiguity in the data requires clarification with the information providers, ie the clinicians and laboratories. Improved interest, skill and competency in the local field teams will not only improve local performance but is essential to improve the quality and depth of nationally provided data.

  (i)  The future of infectious disease surveillance (and many other health protection activities) will be syndromic surveillance generating a risk priority index for local action.

  (ii)  The HPA surveillance strategy must be balanced between local and national needs. This means in practice being much more "bottom-up" than before.

  (iii)  As the main problem is that surveillance is not seen as an important everyday tool and is not practised by a sufficiently large number of people to illuminate operational issues, it follows that the first objective is to increase capacity and competence in the local field teams, both of which are envisaged in the proposed Health Protection Agency.

  (iv)  The second objective is motivation and enablement, which can readily be achieved with modest resources by setting up "best practice" networking, skills workshops or training placements in development units.

  (v)  At the same time, prototype systems should be fully evaluated in practice, developing sources of risk markers for early warning systems and the necessary analytical methodologies and clarifying the scope of their utility.

  (vi)  These would be enhanced by developing automated decision-support using rule-based inference. This would constitute a major advance in supporting best practice risk-management at local level and improve public safety.

  (vii)  In the long term, a strategy for linkage between surveillance systems and other sources of NHS data should be developed.


  The author gratefully acknowledges the invaluable contribution of other colleagues, particularly Dr J. Michael Smith, of Novosystems Software, and Mrs Liz Stokle, Senior Nurse Surveillance Co-ordinator, North of Tyne Communicable Disease Control Unit.

  The author also gratefully acknowledges financial support for the project from Northumbria Water plc.


  (i)  This is a system of increasing sensitivity by identifying potential early markers of infection and following up suspicious clusters by investigation, eg by active case-finding

  (ii)  There are many indicators which can be used as provisional markers of infection, (see box2).

School absenteeism Over-the-counter pharmacy sales
NHS DirectAccident/Emergency attendance
Nursing/residential home surveillanceWater utility customer complaints
Food histories from Environmental Health Officer visits
GP visits

  (iii)  Many of these are with people who have not yet seen a health-care worker. These markers have the advantage of being much more numerous than laboratory isolates and occur much earlier. As such they increase the sensitivity of the system. An aberration in one marker is inconsequential but simultaneous aberrations in multiple markers, or space-time clustering, are suspicious and warrant being analysed for consistency and corroboration and further investigation, as necessary (fig.2, p4).

  (iv)  Because of their nature, early warning markers are inherently ambiguous and the systems to store and analyse this data need special provision to cope with ambiguity, uncertainty and incompleteness. This has necessitated developing a syndromic database (see s 7).

  (v)  The early-warning systems can be used anywhere. They require no special systems. However, developing automated pattern recognition would greatly reduce the tedium of manual inspection and improve efficiency.

October 2002

33   Getting Ahead of the Curve, Department of Health 2002. Back

34   The development of a risk management model for communicable disease control in the United Kingdom. Kara-Zaitri C, Gelletlie R, Barnes H, Black N M I, Walker D, Hatton P, Schweiger M, Wilson D. Proceedings, Fifth Conference on Probabilistic Safety Assessment and Management, Vol 4, p2247-53, Universal Academic Press, 2001. Back

35   The design, development and implementation of a dynamic risk management priority index for communicable disease control in the UK. Kara-Zaitri C, Black N M I, Gelletlie R, Schweiger M, Barnes H, Walker D, Hatton P, Wilson D. Sixth Conference on Probabilistic Safety Assessment and Management, Puerto Rico, June 2002. Back

36   Dynamic risk Management in Communicable Disease Control-the further development of a Risk Management Model. Kara-Zaitri C, Black N, Barnes H, Schweiger M, Gelletlie R. PHLS Annual conference on Epidemiology and Control of Communicable Disease and Environmental Hazards (Health Protection) Nov 2002. Back

37   Implementing risk assessment of emerging foci of infection methods for early detection and evaluation. Black N M I, Stokle L, Smith J M. Sixth Conference on Probabilistic Safety Assessment and Management, Puerto Rico, June 2002. Back

38   The emerging science of very early detection of disease outbreaks. Wagner M, Tsui F-C, Espinato J, Dato V, Sittig D, Caruana R et al. Journal of Public Health Management and Practice 2001; 7;50-8. Back

39   Syndromic surveillance; sensitivity versus uncertainty and ambiguity. A local health department system in the North-East of England. Black N M I, Stokle L, Smith J M. National Syndromic Surveillance Conference, New York, Sept 2002. Back

40   Early detection of emerging foci of infection; finding a guiding star. Black NMI, Smith J M, Aldrich T E. Faculty of Public Health Medicine, July 1999, Glasgow. Back

41   Severity of meningococcal disease; a method for peri-admission risk assessment. Black N M I, Stokle L, Kara-Zaitri C. Project proposal 2001. Back

42   Personal communication, Dr Barbara Watson, Philadelphia Department of Health 2002. Back

43   Personal communication, Dr Michael Stamatelatos, Head of Safety and Reliability, NASA, 2002. Back

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