Advancing early warning and surveillance for zoonotic diseases under climate change: Interdisciplinary systematic perspectives

Abstract

Zoonoses account for the majority of emerging infectious diseases and pose a serious threat to human and animal health. Under global warming and climate change, zoonoses are significantly affected by influencing hosts, vectors, and pathogen dynamics as well as their interactions. Traditional zoonoses surveillance relies on molecular or serological diagnostic methods to monitor pathogens from animal or patient samples, which may miss the early warning signs of pathogens spillover from the environment. Nowadays, new technologies such as remote sensing, environment-based screening, multi-omics, and big data science facilitate comprehensive active surveillance, offering great potential for early warning and prediction. Despite the recent technological advances, there is few reviews that explores the integration of cutting-edge technologies aimed at constructing a robust early warning system. Therefore, we discussed the opportunities, barriers, and limitations of interdisciplinary emerging technologies for exploring early warning and surveillance of zoonoses. This systematic review summarized a practical framework for early surveillance integrated with a modified SEIR model for zoonoses in the context of climate change. It also outlined challenges and future prospects in terms of data sharing, early detection of unknown zoonoses and the move towards global surveillance.