Reshaping surveillance for infectious diseases: less chasing of pathogens and more monitoring of drivers


J.A. Drewe, J. George & B. Häsler

Animal health surveillance, despite its name, tends to focus on looking for disease. Often this involves searching for cases of infection with known pathogens (‘pathogen chasing’). Such an approach is both resource-intensive and limited by the requirement for prior knowledge of disease likelihood. In this paper we propose the gradual reshaping of surveillance towards the systems level, focusing on the processes (‘drivers’) that promote disease or health, rather than on the presence or absence of specific pathogens. Examples of relevant drivers are land-use change, increasing global interconnectedness, and finance and capital flows. Importantly, we suggest the focus of surveillance should be on the detection of changes in patterns or quantities relating to such drivers. This would generate systems-level risk-based surveillance information to identify areas where additional attention may be needed, and, over time, inform the implementation of prevention efforts. The collection, integration and analysis of data on drivers is likely to require investment in improving data infrastructures. A period of overlap would allow the two systems (traditional surveillance and driver monitoring) to be compared and calibrated. This would also lead to a better understanding of the drivers and their linkages, and thereby generate new knowledge that can improve surveillance and inform mitigation efforts. Since surveillance of drivers may give signals at the level of the system when changes are occurring, which could act as alerts and enable targeted mitigation, this might even enable disease to be prevented before it happens by intervening directly on the drivers themselves. Surveillance focused on drivers such as these would be expected to bring co-benefits because many diseases are promoted by the same drivers. Further, focusing on drivers rather than pathogens should allow for controlling currently unknown diseases, making this approach particularly timely given the increasing risk of emergence of new diseases.

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