[Coordination of sentinel nets and new stages of epidemiological surveillance]

Guía de principios y métodos de las redes centinelas sanitarias en España

Health sentinel networks are being increasingly used in the study of health-related problems. The present article aims to provide a methodological guide - designed by regional sentinel network managers and based on the results of a Delphi study - that can be used to set up and develop a health sentinel network. The main topics in the guide are the following: definition of a health sentinel network; network description: aims and structure; methods for the selection of sentinel participants; description of health processes suitable for study through this methodology: incidence, case definition, exclusion and inclusion criteria; description of the target population: the denominator for incidence rates estimates; quality indicators; periodicity of data collection; dissemination of the information: periodicity and methods, and incorporation of the participants in the decision-making process through multidisciplinary commissions. This guide aims to contribute to the development of sentinel networks in the autonomous communities by providing a common methodology, which could be highly useful when introducing new networks in Spain. Finally, we conclude that it is important to raise awareness of the concept of health sentinel networks, disseminate the information generated, and promote its use by public health administration.

Redes centinela sanitarias en España. Consenso para una guía de principios y métodos

Since the eighties, health sentinel networks have been active in our country, but with a variety of objectives, methods and different development levels in the autonomous communities. The necessity of standardising the management and harmonising the indicators has concluded in a research project on the Spanish health sentinel networks, one of whose objectives is to establish a guide for work principles and methods. A panel of 23 experts has made a study using the Delphi method to agree, in three consecutive phases, a definition of sentinel network, the objectives and the management principles and other aspects related to the organisation and functioning. Altogether, 41 questions were gathered from a previous draft which needed 80% of consensus in the first phase and 70% in the second. All the experts participated in the first phase, 22 in the second and 20 in the third. A consensus was achieved on 36 questions in the first phase and in 4 of the remaining ones in the second. In the third phase the shape of the guide document was given. The Delphi consensus method has been extremely useful in the resolution of discrepancies and divergences. The experts who were selected outside of the sentinel networks contributed with a wider vision on the objectives and applicability of the health sentinel networks in Spain.

[Incorporation of geostatistical methodology for influenza surveillance in a sentinel network]

OBJECTIVES

To evaluate geostatistical description of influenza data from the Valencian Sentinel Network (VSN) in Spain using the kringing method and to assess the possibility of incorporating this method into routine surveillance.

METHODS

We use influenza surveillance data on three influenza seasons (1997-1998, 1998-1999 and 1999-2000) from the VSN to construct a geocodified data matrix of the incidence of this disease. The geographic distribution was studied using the kringing method, which enables estimation of the incidence in a few strategically distributed points. Influenza isoincidence maps for each week were plotted. Cross validation was used to evaluate the method.

RESULTS

In most of the weeks, the values of reduced standard deviation and reduced mean were close to the optimal values (0 and 1, respectively). Out of range reduced standard deviation values were found in 12 of 20 weeks in the last season only. The estimation of rates in all three seasons showed coherence in spatial distribution and temporal evolution.

CONCLUSIONS

In most situations the results were acceptable. The method does not require extra computer resources or an excessive amount of time and requires only annual adaptation. Because it is easy to use, the technique is appropriate for routine use but the accuracy of estimations could be improved by increasing the complexity of the model.