A set of training materials for professionals working in intervention epidemiology, public health microbiology and infection control and hospital hygiene.
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Surveillance should be directly relevant to control needs, and as such the criteria for deciding whether to undertake surveillance of a particular hazard, exposure or event are closely aligned to those for deciding whether to undertake control measures in respect of that hazard, exposure or event. The major criteria for determining the case for surveillance are therefore:
There are additional considerations in respect of decisions about what type or form of surveillance might be undertaken, and these will be discussed later.
The public health importance of a problem, and the priority for control and prevention, is determined by a variety of factors, the most important of which is usually the overall burden on the population. Other factors, such as the potential for epidemic spread, political or media interest, the availability and cost-benefit ratio of interventions, and national or international disease control targets may also be influential in determining the priority given to the control and surveillance of a public health problem. An example of how priorities can change, and as a result investment in surveillance can be influenced, can be seen in respect of sexually transmitted infections in the UK in the second half of the 20th century. Investment in the control, and surveillance, of sexually transmitted infections in the UK declined during the 1950's and 1960's, as it was perceived that the post war peak in gonorrhoea and syphilis had been successfully controlled. Despite rises in the incidence of these diseases in the 1960's and 1970's it was not until the advent of AIDS in the 1980's that significant investment in improved surveillance, as part of a major new programme of control and prevention, took place . These improved surveillance systems provided much of the information, and identified cases for research, that enabled targeted and effective control measures to be implemented before HIV had been identified. More recently, the rise in antimicrobial resistance has resulted in significant investment in many countries in surveillance systems for monitoring MRSA , antibiotic resistant gonorrhoea  and other important resistant bacterial infections.
The decision to undertake surveillance, and more particularly the decision as to what type of surveillance should be undertaken, should take into account the strategy for prevention and control of the disease, hazard or exposure that is to be monitored, and also the types of intervention that are to make up the control programme. Potential points for intervention to control or prevent infectious disease are outlined in figure 1.
The development of a new intervention may introduce the requirement for new surveillance systems to inform and monitor the application of that intervention. Thus the introduction of pneumococcal vaccination in the UK, initially among high risk groups and subsequently as part of the routine childhood immunisation programme, has prompted the development of enhanced surveillance systems for pneumococcal infection, including monitoring of serotypes causing invasive illness and monitoring of vaccine uptake among high risk groups, which has informed policy (in respect of choice of vaccine) and enabled programme delivery to be assessed .
New opportunities for the development of surveillance may also arise as a result of changes in the feasibility of collecting data that would inform control and prevention activities. These opportunities might arise because of the introduction of a new health service that is able to provide information that would previously not have been available or prohibitively costly to obtain, or because of the introduction of new technology that significantly reduces the costs, and hence the cost-benefit, of data collection for surveillance purposes. An example of the former are the surveillance systems that have been developed to make use of data recorded by telephone health advisory services, in the UK  and the USA . Examples of surveillance that has been established because of opportunities provided by new technology include primary care surveillance systems recently introduced in the UK .
1. Catchpole MA. The Role of Epidemiology and Surveillance Systems in the Control of Sexually Transmitted Diseases. Genitourinary Medicine 1996; 72: 321
2. Griffiths C, et al. Trends in MRSA in England and Wales: analysis of morbidity and mortality data for 1993-2002. Health Stat Q 2004;21:15-22
3. Paine T, Herring A, Turner A, et al. GRASP: a new national sentinel surveillance initiative for monitoring gonococcal antimicrobial resistance in England and Wales. Sex Transm Infect 2001; 77:398-401
4. Health Protection Agency. Surveillance of the impact of the pneumococcal conjugate (PCV) vaccination programme for children in England and Wales and protocol for investigation of vaccine failures. (July 2006). http://www.hpa.org.uk/infections/topics_az/pneumococcal/PneumococcalGuidanceSurveillance.htm
5. Cooper DL, Smith GE, Baker M, Chinemana F, Verlander N, Gerard E, Hollyoak V, Griffiths R. A national symptom surveillance system in the UK using calls to a telephone health advice service. MMWR 2004: 53(Suppl);179-183.
6. Steven F. Magruder, J. Henry, M. Snyder. Linked Analysis for Definition of Nurse Advice Line Syndrome Groups, and Comparison to Encounters. MMWR 2005: 54(Suppl);93-97
7. Health Protection Agency. Primary Care Surveillance - QResearch (July 2006) http://www.hpa.org.uk/infections/topics_az/primary_care_surveillance/QResearch.htm
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aLambrou posted on 9/30/2015 4:31:20 PM:Some proposed changes in the following sentences in the text:
1. “Adding a p-value to the description of our study results is useful since it suggests how high or low the probability is that the difference that we observed between the groups was due to chance.” to “Adding a p-value to the description of our study results is useful since it suggests how high or low the probability is that the observed difference between the groups or a more extreme one was due to chance”
2. “Please note that again it is a common convention to chose 95% as a confidence interval, but this might as well have been 90%, 99% or even 93.37%: it is a matter of choice” to “Please note that again it is a common convention to choose 95% as a confidence level, but this might as well have been 90%, 99% or even 93.37%; it is a matter of choice.”
3. “The deviation comprises the Standard Error”…Actually, the deviation is expressed as “critical value (of a distribution) plus or minus the standard error”. Some more elaboration here would be beneficial...
4. “If the Null Hypothesis is included within the CI, then we should consider it non-significant. For example, in case of a relative risk, the null hypothesis is that RR=1.0 (and the same goes for Odds Ratio).” What about writing this “If the null value is included within the CI, we will consider that the result is not statistically significant. For example, in case of a relative risk, the null value is 1.0 (RR=1.0) based on the null hypothesis that the exposure under study is not associated with the outcome under study (and the same goes for Odds Ratio).”?
5. “Most analytical software will give the confidence intervals automatically, together with the point estimates and p-value.” to “Most analytical software will provide the confidence intervals automatically, together with the point estimates and p-values.”
6. “This can be interpreted that the true relative risk for olive eating and botulism is with 95% probability between 1.17 and 11.07.” can maybe be rephrased to “The true relative risk lies between 1.17 and 11.07 with 95% confidence. That is, the data are also consistent with hypotheses of a relative risk between 1.17 and 11.07.”
7. “A confidence interval represents the range of effects that are compatible with the data. The CI provides
• the magnitude of the measured effect
• the the range in which the effect of our interest is most likely to be
• the direction of the effect (risk factor or protective factor)”
“A confidence interval represents the range of hypotheses that are compatible with the data.
The CI provides information on:
• the magnitude of the measured effect or else the strength of the association
• the range in which the effect of our interest is most likely to be
• the direction of the effect (risk factor or protective factor)
A separate part on the interpretation of the confidence intervals (as a headline) can also be useful. One may also include the results from the botulism outbreak example in this part.
It might also be preferable to use the terms wide and narrow instead of large and small when commenting on the width of confidence intervals. For example, “In principle, high data variability will lead to wide confidence intervals. The larger the sample size, the narrower the confidence interval. And finally, the higher the confidence level chosen, the wider the interval will be.”
There are some typos in the following sentences:
- “If we want to answer to this question, we can calculate the confidence interval around or estimated effect” to “If we want to answer to this question, we can calculate the confidence interval around our estimated effect”
- “Please note that again it is a common convention to chose 95% as a confidence interval, but this might as well have been 90%, 99% or even 93.37%: it is a matter of choice.” to “Please note that again it is a common convention to choose 95% as a confidence interval, but this might as well have been 90%, 99% or even 93.37%: it is a matter of choice.”
Arnold Bosman replied on 9/30/2015 5:30:55 PM: These are very good comments !
Thanks for this. I would like to suggest to modify the article accordingly (please feel free to use the 'edit' button on top of this article.
Alternatively I would also be happy to do so, if you experience technical obstacles to modifying the article.
Thanks again, this is highly valuable.
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