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Applications of principles to case studies focusing on non-monetary surveillance values

Häsler B., Delabouglise A., Antoine-Moussiaux N., Phan T.D., Dao D.C., Nguyen T.T., Pham H.T.T., Truong B.D., Nguyen X.N.T., Vu T.D., Nguyen K.V., Le H.T., Tatong D., Phimpraphi W., Kasemsuwan S., Peyre M.I., Martins S.B.. 2022. In : Peyre Marisa (ed.), Roger François (ed.), Goutard Flavie (ed.). Principles for evaluation of one health surveillance: the EVA book. Cham : Springer, p. 117-146.

DOI: 10.1007/978-3-030-82727-4_6

A central aspect of economic evaluations of surveillance components or systems is to estimate the value of the information that is being generated by surveillance. Importantly, the value of information is determined by the user of the information. This value is often realised through decisions on interventions that are implemented to manage disease in populations with the associated reduction of disease costs in human and animal populations including effects on the wider society. The economic efficiency of such processes can be measured within a single sector or across sectors (e.g. animal health surveillance creating benefits streams in human populations) applying standard economic evaluation techniques. Depending on the context, people may have different demands and uses for information expressed in distinct information-seeking behaviour and willingness to pay for information or knowledge. Hence, private and public stakeholders may attribute different values to surveillance depending on their decision needs. Moreover, cultural and socio-economic factors shape not only the value of surveillance, but also people's decisions around their livelihoods, income generation, prevention, and disease management strategies. Therefore it is important to understand behaviours, processes, motives, and justifications around health management and surveillance. A range of case studies are presented that describe wider benefits of surveillance and illustrate how non-monetary benefits can be assessed using stated preference elicitation methods, such as discrete choice experiment. Moreover, they demonstrate how understanding of local value systems and contexts allows appraising wider surveillance attributes that ultimately affect the performance and economic efficiency of surveillance.

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