Given the risks associated with secondary spreads to zoonotic reservoirs, there is an urgent need to implement integrated surveillance programs to coordinate monitoring of SARS-CoV-2 in humans, the environment, and domestic and wild animals. However, there are several challenges in implementing integrated disease surveillance. In most countries where surveillance systems exist, separate agencies manage surveillance in humans, animals and the environment, often without intersectoral communication or coordination. In high-income countries, disease surveillance systems in humans and animals are governed by completely different regulations, policies, standards and sources of funding, making cross-sectoral collaboration difficult. In contrast, resource constraints and poor infrastructure are major barriers in most low- and middle-income countries. Regional and national governments and international organizations should implement policies that enable cross-sectoral collaboration and provide specific, long-term and international funding for continued and coordinated pathogen surveillance. Additionally, many animal producers lack the financial means or support to test their animals for target pathogens outside of funded surveillance programs and may fear economic losses and livelihoods threatened if diseases are detected. Also, few wildlife surveillance programs are mandated except for certain pathogens such as rabies and wasting disease. Therefore, comprehensive education and compensation programs will be required to improve overall knowledge and response to zoonotic diseases in livestock and wild animals, including transmission routes, symptoms, economic impacts and potential health risks. Such initiatives require government support, coordinated partnerships and collaboration with all stakeholders in food animal production, wildlife services and conservation, and large corporate and private sectors. Many in the field of disease surveillance argue that the primary reason for the distrust between institutions and the lack of inter-agency cooperation in disease surveillance is the lack of definitive guidelines on data sharing and use20. Also, data collection standards differ widely between institutions, making data integration nearly impossible. One possible solution is the development of data repositories, universal guidelines for data collection, analysis and sharing, interoperable data standards and protocols across institutions. The utility of repositories is further highlighted by their potential use for viral phenotyping and assessment of risk markers such as host cell receptor binding, viral replication, transmission, immune escape and antiviral resistance. This information turns genomic data into health intelligence, especially when combined with important ecological, behavioral and epidemiological elements . Standardization around these risk factors is also critical for knowledge synthesis and decision making. Testing all animals everywhere is not practical, feasible or necessary to gain health intelligence for mitigation and control. Instead, a rational approach to targeted surveillance, combined with laboratory experiments, is essential to confirm the zoonotic potential. To design this, we can incorporate computational models to predict and shortlist high-risk host species and locations. Molecular simulations have been used extensively to model interactions between ACE2 and its receptor binding domain to predict the susceptibility of different strains to wild-type SARS-CoV-2 and its variants2. In addition, ecological models have been developed to predict where frequent contact between humans and animals and animals increases the risk of transmission21,22. Such models can benefit from, although not include, existing knowledge of animal behavior and ecology, which generally requires specialized input from wildlife ecology and animal husbandry. In addition, links to human and environmental data allow geo-temporal prioritization based on areas with high viral activity among humans and animal exposure risk. Finally, key epidemiological parameters can inform the prioritization of surveillance by focusing on high-risk cross-border and human-animal interfaces as well as endangered animals such as some at-risk primate species. high mortality. A robust 'One Health' surveillance system for communicable diseases requires four key programmatic pillars to be in place . Surveillance of environmental samples has previously been used to monitor antimicrobial resistance23 and has been used to monitor SARS-CoV-2 . Such surveillance can act as an early detection system; for example, identification of polio virus in sewers in the UK and New York in 2022 . There has also been extensive genomic surveillance for SARS-CoV-2 more than 15 million human sourced genomes for SARS-CoV-2 strains have been deposited in the public GISAID repository 26. However, surveillance programs in humans are largely limited to healthcare-seeking patients and often target specific subsets of human pathogens, impeding the ability to detect new infectious agents. A surveillance scheme for SARS-CoV-2 based on non-targeted RNA metagenomic sequencing also provides information on the incidence and prevalence of other known zoonotic pathogens such as filoviruses or highly pathogenic avian influenza viruses and facilitates early identification. potentially zoonotic pathogens that have not yet been characterized. Extending this column to include routine surveillance of apparently healthy individuals and individuals with severe febrile respiratory syndromes of unknown etiology may help us better understand the epidemiology and potential epidemic risks of known or new infectious agents circulating in the population. Figure 2 The four pillars of genomic surveillance. Coordinated SARS-CoV-2 genomic surveillance in humans, the environment, and domestic and wild animals is critical to inform policy development for an early warning system to detect outbreaks in humans and animals. AMR, antimicrobial resistance. full size Despite the far-reaching implications of the animal reservoirs we describe for both SARS-CoV-2 and other pathogens at risk of zoonotic emergence, there is a greater gap in surveillance between the other two pillars . It is crucial that we build and integrate existing surveillance networks and support less established surveillance pillars. Such integration requires the global adoption of standardized frameworks such as the Triple Zoonosis Guide and the recently published Quadruple One Health Joint Action Plan, stakeholder engagement, and links to other One Health preparedness and response activities. Emphasis should be placed on prioritizing pathogens and populations, biocontrol strategies, early warning systems, and the development of decision support tools and triggers for action. Clear guidance forms the basis of sustainable and versatile surveillance programs that require strong, harmonized support at local, national, regional and global levels. An important lesson we should all learn from the COVID-19 pandemic is that investing in infectious disease surveillance and risk prevention strategies can minimize the devastating global economic and social damage of disease outbreaks. Most importantly, only with global coordination of current surveillance efforts can we better manage the consequences of the current pandemic and predict and prevent future outbreaks.