Why do we need to evaluate health surveillance systems?
The need to set up efficient and sustainable surveillance systems has become a major concern particularly in recent years, following SARS, H1N1 influenza, and Covid19 pandemics. The recent crisis has highlighted the importance to early detect new emerging diseases, including zoonosis such as coronavirus, MERs-CoV, and Ebola. To ensure implementation of the best surveillance strate- gies and make optimal use of available resources, it is critical to perform timely and relevant evaluations of such systems both at planning and operational steps of the process. The evaluation must provide a robust scientific foundation to inform decision-makers and meet their demand for simple and practical evalua- tion guidance. The aim of this chapter is to provide a better understanding on the need and challenges for such evaluation of health surveillance systems to ensure quality and reliability of the data generated.
Main Authors: | , , |
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Format: | book_section biblioteca |
Language: | eng |
Published: |
Springer
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Online Access: | http://agritrop.cirad.fr/601595/ http://agritrop.cirad.fr/601595/1/ID601595.pdf |
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Summary: | The need to set up efficient and sustainable surveillance systems has become a major concern particularly in recent years, following SARS, H1N1 influenza, and Covid19 pandemics. The recent crisis has highlighted the importance to early detect new emerging diseases, including zoonosis such as coronavirus, MERs-CoV, and Ebola. To ensure implementation of the best surveillance strate- gies and make optimal use of available resources, it is critical to perform timely and relevant evaluations of such systems both at planning and operational steps of the process. The evaluation must provide a robust scientific foundation to inform decision-makers and meet their demand for simple and practical evalua- tion guidance. The aim of this chapter is to provide a better understanding on the need and challenges for such evaluation of health surveillance systems to ensure quality and reliability of the data generated. |
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