Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Review Article
  • Published:

Viral emergence and pandemic preparedness in a One Health framework

Nature Reviews Microbiology (2025)Cite this article

Subjects

This article has been updated

Abstract

The risk of viral pathogen transmission between humans and animals (spillover events) and subsequent spread has been increasing due to human impacts on the planet, which lead to changes in the interactions between humans, animals, ecosystems and their pathogens. Key factors (drivers) that increase the risk of disease emergence include climate change, urbanization, land-use changes and global travel, all of which can alter human–animal–environment interactions and increase the likelihood of zoonotic spillovers and vector-borne diseases. Incorporating data on these drivers (such as ecological shifts and patterns of animal movement) into disease surveillance systems can help identify hot spots for disease emergence, which could in theory enable earlier detection of outbreaks and, in turn, increase the effectiveness of intervention strategies. A One Health approach, emphasizing the interconnectedness of human, animal and environmental health, is advocated for addressing these complex challenges. Although conceptually clear and widely endorsed, implementation of One Health approaches towards primary prevention of spillovers is extremely challenging. Here, we summarize current knowledge on disease emergence and its drivers, and discuss how this knowledge could be used towards primary prevention and for the development of risk-targeted One Health early warning surveillance. We consider integrating innovative tools for diagnostics, surveillance and virus characterization, and propose an outlook towards more integrated prevention, early warning and control of emerging infections at the human–animal interface.

Access through your institution
Buy or subscribe

This is a preview of subscription content, access via your institution

Access options

Access through your institution

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Viral emergence and its key drivers.
Fig. 2: One Health surveillance to monitor drivers and disease.
Fig. 3: Examples of regional One Health surveillance: WNV and rabies virus.

Similar content being viewed by others

Change history

  • 14 October 2025

    In the version of the article initially published, the Acknowledgements section was inadvertently omitted and has now been added to the HTML and PDF versions of the article.

References

  1. Adepoju, P. Mpox declared a public health emergency. Lancet 404, e1–e2 (2024).

    Article  PubMed  Google Scholar 

  2. Lawrence, O. G., Ashish, K. J. & Alexandra, F. The Mpox global health emergency — a time for solidarity and equity. N. Engl. J. Med. 391, 1265–1267 (2024).

    Article  Google Scholar 

  3. Taylor, L. PAHO: Americas report record dengue and Oropouche cases. BMJ 387, q2808 (2024).

    Article  PubMed  Google Scholar 

  4. Caserta, L. C. et al. Spillover of highly pathogenic avian influenza H5N1 virus to dairy cattle. Nature 634, 669–676 (2024). This study reports the unprecedented spillover and cow-to-cow transmission of HPAI H5N1 in US dairy cattle, highlighting a critical shift in the host range of the virus.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Banyard, A. C. et al. Detection and spread of high pathogenicity avian influenza virus H5N1 in the Antarctic region. Nat. Commun. 15, 7433 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Authority, E. F. S. et al. Avian influenza overview December 2024–March 2025. EFSA J. 23, e9352 (2025).

    Google Scholar 

  7. Krammer, F. & Schultz-Cherry, S. We need to keep an eye on avian influenza. Nat. Rev. Immunol. 23, 267–268 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Sah, R. et al. Concerns on H5N1 avian influenza given the outbreak in U.S. dairy cattle. Lancet Reg. Health Am. 35, 100785 (2024).

    PubMed  PubMed Central  Google Scholar 

  9. Kuiken, T., Fouchier, R. A. M. & Koopmans, M. P. G. Being ready for the next influenza pandemic? Lancet Infect. Dis. 23, 398–399 (2023).

    Article  PubMed  Google Scholar 

  10. Adisasmito, W. B. et al. One Health: a new definition for a sustainable and healthy future. PLoS Pathog. 18, e1010537 (2022). In this paper the OHHLEP presents an updated definition of One Health, which is now widely adopted.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Machalaba, C. M. & Karesh, W. B. Emerging infectious disease risk: shared drivers with environmental change. Rev. Sci. Tech. 36, 435–444 (2017).

    Article  CAS  PubMed  Google Scholar 

  12. Engering, A., Hogerwerf, L. & Slingenbergh, J. Pathogen–host–environment interplay and disease emergence. Emerg. Microbes Infect. 2, 1–7 (2013).

    Article  Google Scholar 

  13. Jones, K. E. et al. Global trends in emerging infectious diseases. Nature 451, 990–993 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. European Commission: Group of Chief Scientific Advisors and Directorate-General for Research and Innovation. One Health Governance in the European Union (Publications Office of the European Union, 2024).

  15. Mora, C. et al. Over half of known human pathogenic diseases can be aggravated by climate change. Nat. Clim. Change 12, 869–875 (2022). This study presents a systematic review of peer reviewed publications that study the effects of climate change on infectious diseases that impact humans.

    Article  Google Scholar 

  16. IPCC Climate Change 2022: Impacts, Adaptation, and Vulnerability (eds Pörtner, H.-O. et al.) (Cambridge Univ. Press, 2022).

  17. Carlson, C. J. et al. Climate change increases cross-species viral transmission risk. Nature 607, 555–562 (2022). This review highlights that climate change impacts interactions and spillover events not only at the human–animal interface but also between animal species.

    Article  CAS  PubMed  Google Scholar 

  18. Greenville, A. C., Wardle, G. M. & Dickman, C. R. Extreme climatic events drive mammal irruptions: regression analysis of 100-year trends in desert rainfall and temperature. Ecol. Evol. 2, 2645–2658 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  19. Rushing, C. S., Royle, J. A., Ziolkowski, D. J. & Pardieck, K. L. Migratory behavior and winter geography drive differential range shifts of eastern birds in response to recent climate change. Proc. Natl Acad. Sci. USA 117, 12897–12903 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Perry, A. L., Low, P. J., Ellis, J. R. & Reynolds, J. D. Climate change and distribution shifts in marine fishes. Science 308, 1912–1915 (2005).

    Article  CAS  PubMed  Google Scholar 

  21. Musmanni, G. D. The delta blues: why climate change adaptation is crucial in the world’s deltas. Global Centre of Adaptation https://gca.org/the-delta-blues-why-climate-change-adaptation-is-crucial-in-the-worlds-deltas/ (2022).

  22. European Environment Agency. Urban Adaptation in Europe: What Works? (EEA, 2024).

  23. Geneletti, D. & Zardo, L. Ecosystem-based adaptation in cities: an analysis of European urban climate adaptation plans. Land Use Policy 50, 38–47 (2016).

    Article  Google Scholar 

  24. Lindsay, S. W., Wilson, A., Golding, N., Scott, T. W. & Takken, W. Improving the built environment in urban areas to control Aedes aegypti-borne diseases. Bull. World Health Organ. 95, 607–608 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  25. Rocklöv, J. et al. Decision-support tools to build climate resilience against emerging infectious diseases in Europe and beyond. Lancet Reg. Health Eur. 32, 100701 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  26. de Cock, M. P., Esser, H. J., van der Poel, W. H. M., Sprong, H. & Maas, M. Higher rat abundance in greener urban areas. Urban Ecosystems 27, 1389–1401 (2024).

    Article  Google Scholar 

  27. Traweger, D., Travnitzky, R., Moser, C., Walzer, C. & Bernatzky, G. Habitat preferences and distribution of the brown rat (Rattus norvegicus Berk.) in the city of Salzburg (Austria): implications for an urban rat management. J. Pest. Sci. 79, 113–125 (2006).

    Article  Google Scholar 

  28. de Cock, M. P. et al. Increased rat-borne zoonotic disease hazard in greener urban areas. Sci. Total. Environ. 896, 165069 (2023).

    Article  PubMed  Google Scholar 

  29. Kibret, S., McCartney, M., Lautze, J., Nhamo, L. & Yan, G. The impact of large and small dams on malaria transmission in four basins in Africa. Sci. Rep. 11, 13355 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. de Souza, W. M. & Weaver, S. C. Effects of climate change and human activities on vector-borne diseases. Nat. Rev. Microbiol. 22, 476–491 (2024).

    Article  PubMed  Google Scholar 

  31. Mordecai, E. A., Ryan, S. J., Caldwell, J. M., Shah, M. M. & LaBeaud, A. D. Climate change could shift disease burden from malaria to arboviruses in Africa. Lancet Planet. Health 4, e416–e423 (2020). This study shows how climate change may have different effects across regions, vectors and pathogens.

    Article  PubMed  PubMed Central  Google Scholar 

  32. FAOSTAT. Land Use Statistics and Indicators 2000–2021. Global, Regional and Country Trends Analytical Brief 71 (FAO, 2023).

  33. Ellis, E. C., Klein Goldewijk, K., Siebert, S., Lightman, D. & Ramankutty, N. Anthropogenic transformation of the biomes, 1700 to 2000. Glob. Ecol. Biogeogr. 19, 589–606 (2010).

    Article  Google Scholar 

  34. Livestock, Environment and Development Initiative. Livestock’s Long Shadow: Environmental Issues and Options (LEAD & FAO, 2006).

  35. Greenspoon, L. et al. The global biomass of wild mammals. Proc. Natl Acad. Sci. USA 120, e2204892120 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Wegner, G. I. et al. Averting wildlife-borne infectious disease epidemics requires a focus on socio-ecological drivers and a redesign of the global food system. eClinicalMedicine 47, 101386 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  37. Sikkema, R. S. et al. Risks of SARS-CoV-2 transmission between free-ranging animals and captive mink in the Netherlands. Transbound. Emerg. Dis. 69, 3339–3349 (2022).

    Article  CAS  PubMed  Google Scholar 

  38. Isabella, M. et al. Emergence of a highly pathogenic avian influenza virus from a low-pathogenic progenitor. J. Virol. 88, 4375–4388 (2014).

    Article  Google Scholar 

  39. Agüero, M. et al. Highly pathogenic avian influenza A (H5N1) virus infection in farmed minks, Spain, October 2022. Eurosurveillance 28, 2300001 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  40. Domańska-Blicharz, K. et al. Cryptic SARS-CoV-2 lineage identified on two mink farms as a possible result of long-term undetected circulation in an unknown animal reservoir, Poland, November 2022 to January 2023. Eurosurveillance 28, 2300188 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  41. Pendrill, F. et al. Disentangling the numbers behind agriculture-driven tropical deforestation. Science 377, eabm9267 (2022).

    Article  CAS  PubMed  Google Scholar 

  42. Faust, C. L. et al. Pathogen spillover during land conversion. Ecol. Lett. 21, 471–483 (2018).

    Article  PubMed  Google Scholar 

  43. Walsh, M. G., Mor, S. M., Maity, H. & Hossain, S. Forest loss shapes the landscape suitability of Kyasanur Forest disease in the biodiversity hotspots of the Western Ghats, India. Int. J. Epidemiol. 48, 1804–1814 (2019).

    PubMed  Google Scholar 

  44. Green, J., Schmidt-Burbach, J. & Elwin, A. Taking stock of wildlife farming: a global perspective. Glob. Ecol. Conserv. 43, e02452 (2023).

    Google Scholar 

  45. Biao, K. et al. Molecular evolution analysis and geographic investigation of severe acute respiratory syndrome coronavirus-like virus in palm civets at an animal market and on farms. J. Virol. 79, 11892–11900 (2005).

    Article  Google Scholar 

  46. Nelson, M. I. et al. Global migration of influenza A viruses in swine. Nat. Commun. 6, 1–11 (2015).

    Article  Google Scholar 

  47. Brown, V. R. et al. Risks of introduction and economic consequences associated with African swine fever, classical swine fever and foot-and-mouth disease: a review of the literature. Transbound. Emerg. Dis. 68, 1910–1965 (2021).

    Article  PubMed  Google Scholar 

  48. Moyen, N. et al. Avian influenza transmission risk along live poultry trading networks in Bangladesh. Sci. Rep. 11, 19962 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Lankau, E. W. et al. Prevention and control of rabies in an age of global travel: a review of travel- and trade-associated rabies events—US, 1986–2012. Zoonoses Public. Health 61, 305–316 (2014).

    Article  CAS  PubMed  Google Scholar 

  50. Worobey, M. et al. The Huanan market was the early epicenter of SARS-CoV-2 emergence. Science 377, 951–959 (2022).

    Article  CAS  PubMed  Google Scholar 

  51. Aguirre, A. A., Catherina, R., Frye, H. & Shelley, L. Illicit wildlife trade, wet markets, and COVID-19: preventing future pandemics. World Med. Health Policy 12, 256–265 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  52. Zhou, P. et al. Avian influenza A (H7N9) virus and mixed live poultry–animal markets in Guangdong province: a perfect storm in the making? Emerg. Microbes Infect. 4, 1–3 (2015).

    Article  CAS  Google Scholar 

  53. Milbank, C. & Vira, B. Wildmeat consumption and zoonotic spillover: contextualising disease emergence and policy responses. Lancet Planet. Health 6, e439–e448 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  54. Xia, W., Hughes, J., Robertson, D. & Jiang, X. How one pandemic led to another: was African swine fever virus (ASFV) the disruption contributing to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emergence? Preprint at Preprints.org https://doi.org/10.20944/preprints202102.0590.v2 (2022).

  55. Lytras, S., Xia, W., Hughes, J., Jiang, X. & Robertson, D. L. The animal origin of SARS-CoV-2. Science 373, 968–970 (2021).

    Article  CAS  PubMed  Google Scholar 

  56. Kowarik, I. Novel urban ecosystems, biodiversity, and conservation. Environ. Pollut. 159, 1974–1983 (2011).

    Article  CAS  PubMed  Google Scholar 

  57. Johnson, M. T. J. & Munshi-South, J. Evolution of life in urban environments. Science 358, eaam8327 (2017). This review describes and analyses the effects of urbanization on the evolution of microorganisms, plants and animals, and how this affects interactions with humans.

    Article  PubMed  Google Scholar 

  58. Bradley, C. A. & Altizer, S. Urbanization and the ecology of wildlife diseases. Trends Ecol. Evolution 22, 95–102 (2007).

    Article  Google Scholar 

  59. Egan, S., Barbosa, A. D., Feng, Y., Xiao, L. & Ryan, U. Critters and contamination: zoonotic protozoans in urban rodents and water quality. Water Res. 251, 121165 (2024).

    Article  CAS  PubMed  Google Scholar 

  60. Akhtardanesh, B. et al. Survey of common infectious diseases in urban foxes (Vulpes spp.) in southeastern Iran. J. Wildl. Dis. 60, 77–85 (2024).

    Article  PubMed  Google Scholar 

  61. Naderi, S. et al. Zooanthroponotic transmission of SARS-CoV-2 and host-specific viral mutations revealed by genome-wide phylogenetic analysis. eLife 12, e83685 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Gibb, R. et al. Zoonotic host diversity increases in human-dominated ecosystems. Nature 584, 398–402 (2020).

    Article  CAS  PubMed  Google Scholar 

  63. United Nations Department of Economic and Social Affairs. World Urbanization Prospects: The 2018 Revision (United Nations, 2018).

  64. Seto, K. C., Sánchez-Rodríguez, R. & Fragkias, M. The new geography of contemporary urbanization and the environment. Annu. Rev. Environ. Resour. 35, 167–194 (2010).

    Article  Google Scholar 

  65. Schneider, A., Friedl, M. A. & Potere, D. A new map of global urban extent from MODIS satellite data. Environ. Res. Lett. 4, 044003 (2009).

    Article  Google Scholar 

  66. United Nations Human Settlements Programme. World Cities Report 2022: Envisaging the Future of Cities (UN Habitat, 2022).

  67. Coltart, C. E. M., Lindsey, B., Ghinai, I., Johnson, A. M. & Heymann, D. L. The Ebola outbreak, 2013–2016: old lessons for new epidemics. Philos. Trans. R. Soc. B: Biol. Sci. 372, 20160297 (2017).

    Article  Google Scholar 

  68. Dellicour, S. et al. Phylodynamic assessment of intervention strategies for the West African Ebola virus outbreak. Nat. Commun. 9, 2222 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  69. Dudas, G. et al. Virus genomes reveal factors that spread and sustained the Ebola epidemic. Nature 544, 309–315 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. World Health Organization & United Nations Human Settlements Programme. Hidden Cities: Unmasking and Overcoming Health Inequities in Urban Settings (WHO & UN Habitat, 2010).

  71. Levin, A. T. et al. Assessing the burden of COVID-19 in developing countries: systematic review, meta-analysis and public policy implications. BMJ Glob. Health 7, e008477 (2022).

    Article  PubMed  Google Scholar 

  72. Wachtler, B. et al. Socioeconomic inequalities and COVID-19—a review of the current international literature. J. Health Monit. 5, 3–17 (2020).

    PubMed  PubMed Central  Google Scholar 

  73. Parolin, Z. & Lee, E. K. The role of poverty and racial discrimination in exacerbating the health consequences of COVID-19. Lancet Reg. Health Am. 7, 100178 (2022).

    PubMed  PubMed Central  Google Scholar 

  74. Van Damme, P. et al. Hepatitis A virus infection. Nat. Rev. Dis. Primers 9, 51 (2023).

    Article  PubMed  Google Scholar 

  75. Boussaa, S., Pesson, B. & Boumezzough, A. Phlebotomine sandflies (Diptera: Psychodidae) of Marrakech city, Morocco. Ann. Tropical Med. Parasitol. 101, 715–724 (2007).

    Article  CAS  Google Scholar 

  76. Kabaria, C. W., Gilbert, M., Noor, A. M., Snow, R. W. & Linard, C. The impact of urbanization and population density on childhood Plasmodium falciparum parasite prevalence rates in Africa. Malar. J. 16, 1–10 (2017).

    Article  Google Scholar 

  77. Giles, J. R. et al. The duration of travel impacts the spatial dynamics of infectious diseases. Proc. Natl Acad. Sci. USA 117, 22572–22579 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Liu, K. et al. Population movement, city closure in Wuhan, and geographical expansion of the COVID-19 infection in China in January 2020. Clin. Infect. Dis. 71, 2045–2051 (2020).

    Article  CAS  PubMed  Google Scholar 

  79. Volz, E. et al. Evaluating the effects of SARS-CoV-2 spike mutation D614G on transmissibility and pathogenicity. Cell 184, 64–75.e11 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Castelli, F. & Sulis, G. Migration and infectious diseases. Clin. Microbiol. Infect. 23, 283–289 (2017).

    Article  CAS  PubMed  Google Scholar 

  81. World Health Organization. SARS outbreak contained worldwide. WHO https://www.who.int/news/item/05-07-2003-sars-outbreak-contained-worldwide (2003).

  82. Bell, D. M. & World Health Organization Working Group on International and Community Transmission of SARS. Public health interventions and SARS spread, 2003. Emerg. Infect. Dis. 10, 1900–1906 (2004).

    Article  PubMed  PubMed Central  Google Scholar 

  83. Stegeman, A. et al. Avian influenza A virus (H7N7) epidemic in the Netherlands in 2003: course of the epidemic and effectiveness of control measures. J. Infect. Dis. 190, 2088–2095 (2004).

    Article  PubMed  Google Scholar 

  84. World Health Organization. Strengthening Health Emergency Prevention, Preparedness, Response and Resilience (HEPR & WHO, 2023).

  85. Singer, B. J. et al. Development of prediction models to identify hotspots of schistosomiasis in endemic regions to guide mass drug administration. Proc. Natl Acad. Sci. USA 121, e2315463120 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  86. Kasbergen, L. M. R. et al. Multi-antigen serology and a diagnostic algorithm for the detection of arbovirus infections as novel tools for arbovirus preparedness in southeast Europe (MERMAIDS-ARBO): a prospective observational study. Lancet Infect. Dis. 25, 678–689 (2025).

    Article  PubMed  Google Scholar 

  87. Sigfrid, L. et al. Prevalence, clinical management, and outcomes of adults hospitalised with endemic arbovirus illness in southeast Europe (MERMAIDS-ARBO): a prospective observational study. Lancet Infect. Dis. 25, 690–700 (2025).

    Article  PubMed  Google Scholar 

  88. Schmidt, T. L. et al. Incursion pathways of the Asian tiger mosquito (Aedes albopictus) into Australia contrast sharply with those of the yellow fever mosquito (Aedes aegypti). Pest. Manag. Sci. 76, 4202–4209 (2020).

    Article  CAS  PubMed  Google Scholar 

  89. Oliveira, S., Rocha, J., Sousa, C. A. & Capinha, C. Wide and increasing suitability for Aedes albopictus in Europe is congruent across distribution models. Sci. Rep. 11, 9916 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. Nakase, T., Giovanetti, M., Obolski, U. & Lourenço, J. Global transmission suitability maps for dengue virus transmitted by Aedes aegypti from 1981 to 2019. Sci Data 10, 275 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  91. Dagostin, F. et al. Ecological and environmental factors affecting the risk of tick-borne encephalitis in Europe, 2017 to 2021. Euro. Surveill. 28, 2300121 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  92. Farooq, Z. et al. European projections of West Nile virus transmission under climate change scenarios. One Health 16, 100509 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  93. Romero-Alvarez, D., Escobar, L. E., Auguste, A. J., Del Valle, S. Y. & Manore, C. A. Transmission risk of Oropouche fever across the Americas. Infect. Dis. Poverty 12, 47 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  94. Kjær, L. J. et al. Potential drivers of human tick-borne encephalitis in the Örebro region of Sweden, 2010–2021. Sci. Rep. 13, 7685 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  95. Chemison, A., Ramstein, G., Jones, A., Morse, A. & Caminade, C. Ability of a dynamical climate sensitive disease model to reproduce historical Rift valley fever outbreaks over Africa. Sci. Rep. 14, 3904 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  96. Nabi, G. et al. Bats and birds as viral reservoirs: a physiological and ecological perspective. Sci. Total. Env. 754, 142372 (2021).

    Article  CAS  Google Scholar 

  97. Guth, S. et al. Bats host the most virulent—but not the most dangerous—zoonotic viruses. Proc. Natl Acad. Sci. USA 119, e2113628119 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. Mollentze, N. & Streicker, D. G. Viral zoonotic risk is homogenous among taxonomic orders of mammalian and avian reservoir hosts. Proc. Natl Acad. Sci. USA 117, 9423–9430 (2020). This study proposes a host-neutral explanation for differences in the number of zoonotic pathogens among animal groups.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  99. Ribeiro, R. et al. Incorporating environmental heterogeneity and observation effort to predict host distribution and viral spillover from a bat reservoir. Proc. Biol. Sci. 290, 20231739 (2023).

    PubMed  PubMed Central  Google Scholar 

  100. Beyer, R. M., Manica, A. & Mora, C. Shifts in global bat diversity suggest a possible role of climate change in the emergence of SARS-CoV-1 and SARS-CoV-2. Sci. Total. Env. 767, 145413 (2021).

    Article  CAS  Google Scholar 

  101. Forero-Muñoz, N. R. et al. The coevolutionary mosaic of bat betacoronavirus emergence risk. Virus Evol. 10, vead079 (2024). This study shows that predicted virus hot spots based on the combined presence and richness of bat species may not be correct when they are compared with coronavirus co-evolution patterns.

    Article  PubMed  Google Scholar 

  102. Warmuth, V. M., Metzler, D. & Zamora-Gutierrez, V. Human disturbance increases coronavirus prevalence in bats. Sci. Adv. 9, eadd0688 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  103. Rulli, M. C., D’Odorico, P., Galli, N. & Hayman, D. T. S. Land-use change and the livestock revolution increase the risk of zoonotic coronavirus transmission from rhinolophid bats. Nat. Food 2, 409–416 (2021).

    Article  CAS  PubMed  Google Scholar 

  104. Nyakarahuka, L. et al. Ecological niche modeling for filoviruses: a risk map for Ebola and marburg virus disease outbreaks in Uganda. PLoS Curr. https://doi.org/10.1371/currents.outbreaks.07992a87522e1f229c7cb023270a2af1 (2017).

  105. Muylaert, R. L. et al. Using drivers and transmission pathways to identify SARS-like coronavirus spillover risk hotspots. Nat. Commun. 14, 6854 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  106. Sánchez, C. A. et al. A strategy to assess spillover risk of bat SARS-related coronaviruses in Southeast Asia. Nat. Commun. 13, 4380 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  107. Horigan, V. et al. Assessing the quality of data for drivers of disease emergence. Sci. Tech. Rev. 42, 90–102 (2023).

    Article  CAS  Google Scholar 

  108. Si, Y., Xin, Q., Prins, H. H. T., de Boer, W. F. & Gong, P. Improving the quantification of waterfowl migration with remote sensing and bird tracking. Sci. Bull. 60, 1984–1993 (2015).

    Article  Google Scholar 

  109. Johnson, E. et al. Applications and advances in acoustic monitoring for infectious disease epidemiology. Trends Parasitol. 39, 386–399 (2023). This study highlights the promise of integrating ecological methodologies in infectious disease research.

    Article  PubMed  Google Scholar 

  110. González-Pérez, M. I. et al. Field evaluation of an automated mosquito surveillance system which classifies Aedes and Culex mosquitoes by genus and sex. Parasites Vectors 17, 97 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  111. Ruppert, K. M., Kline, R. J. & Rahman, M. S. Past, present, and future perspectives of environmental DNA (eDNA) metabarcoding: a systematic review in methods, monitoring, and applications of global eDNA. Glob. Ecol. Conserv. 17, e00547 (2019).

    Google Scholar 

  112. Park, H.-A., Jung, H., On, J., Park, S. K. & Kang, H. Digital epidemiology: use of digital data collected for non-epidemiological purposes in epidemiological studies. Healthc. Inform. Res. 24, 253–262 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  113. Dugas, A. F. et al. Influenza forecasting with Google Flu trends. PLoS ONE 8, e56176 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  114. Rocklöv, J. et al. Using big data to monitor the introduction and spread of Chikungunya, Europe, 2017. Emerg. Infect. Dis. 25, 1041 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  115. Wu, J. et al. Mobile health technology combats COVID-19 in China. J. Infect. 82, 159–198 (2021).

    PubMed  Google Scholar 

  116. Brownstein, J. S., Rader, B., Astley, C. M. & Tian, H. Advances in artificial intelligence for infectious-disease surveillance. N. Engl. J. Med. 388, 1597–1607 (2023).

    Article  CAS  PubMed  Google Scholar 

  117. Maganga, G. D. et al. Genetic diversity and ecology of coronaviruses hosted by cave-dwelling bats in Gabon. Sci. Rep. 10, 1–13 (2020).

    Article  Google Scholar 

  118. Bai, R. et al. Exploring utility of genomic epidemiology to trace origins of highly pathogenic influenza A/H7N9 in Guangdong. Virus Evol. 6, veaa097 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  119. Atama, N. C. et al. Evaluation of the use of alternative sample types for mosquito-borne flavivirus surveillance: using Usutu virus as a model. One Health 15, 100456 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  120. Hotta, K. et al. Antibody survey on avian influenza viruses using egg yolks of ducks in Hanoi between 2010 and 2012. Vet. Microbiol. 166, 179–183 (2013).

    Article  CAS  PubMed  Google Scholar 

  121. de Rooij, M. M. T. et al. Occupational and environmental exposure to SARS-CoV-2 in and around infected mink farms. Occup. Env. Med. 78, 893–899 (2021).

    Article  Google Scholar 

  122. Hendriksen, R. S. et al. Global monitoring of antimicrobial resistance based on metagenomics analyses of urban sewage. Nat. Commun. 10, 1124 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  123. Nieuwenhuijse, D. F. et al. Setting a baseline for global urban virome surveillance in sewage. Sci. Rep. 10, 13748 (2020). This study shows the potential of environmental samples that may benefit pandemic preparedness.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  124. Lu, J. et al. Capturing noroviruses circulating in the population: sewage surveillance in Guangdong, China (2013–2018). Water Res. 196, 116990 (2021).

    Article  CAS  PubMed  Google Scholar 

  125. Tisza, M. et al. Wastewater sequencing reveals community and variant dynamics of the collective human virome. Nat. Commun. 14, 6878 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  126. Kutter, J. S. et al. Small quantities of respiratory syncytial virus RNA only in large droplets around infants hospitalized with acute respiratory infections. Antimicrob. Resist. Infect. Control. 10, 100 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  127. Grayson, S. A., Griffiths, P. S., Perez, M. K. & Piedimonte, G. Detection of airborne respiratory syncytial virus in a pediatric acute care clinic. Pediatr. Pulmonol. 52, 684–688 (2017).

    Article  PubMed  Google Scholar 

  128. Gaide, N. et al. Viral tropism and detection of clade 2.3.4.4b H5N8 highly pathogenic avian influenza viruses in feathers of ducks and geese. Sci. Rep. 11, 5928 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  129. Cheung, P. P. et al. Identifying the species-origin of faecal droppings used for avian influenza virus surveillance in wild-birds. J. Clin. Virol. 46, 90–93 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  130. Smith, S. E. et al. Emerging technologies in the study of the virome. Curr. Opin. Virol. 54, 101231 (2022).

    Article  CAS  PubMed  Google Scholar 

  131. Kwok, K. T. T., Nieuwenhuijse, D. F., Phan, M. V. T. & Koopmans, M. P. G. Virus metagenomics in farm animals: a systematic review. Viruses 12, 107 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  132. Jumper, J. et al. Highly accurate protein structure prediction with AlphaFold. Nature 596, 583–589 (2021). This work presents a key artificial intelligence tool that has transformed timely prediction of pathogen properties.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  133. Madani, A. et al. Large language models generate functional protein sequences across diverse families. Nat. Biotechnol. 41, 1099–1106 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  134. Plowright, R. K. et al. Pathways to zoonotic spillover. Nat. Rev. Microbiol. 15, 502–510 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  135. Warren, C. J. & Sawyer, S. L. Identifying animal viruses in humans. Science 379, 982–983 (2023).

    Article  CAS  PubMed  Google Scholar 

  136. One Health High-Level Expert Panel. Prevention of zoonotic spillover: from relying on response to reducing the risk at source. PLoS Pathog. 19, e1011504 (2023). In this work the OHHLEP advocates for primary prevention.

    Article  Google Scholar 

  137. Fritz, S. et al. Citizen science and the United Nations Sustainable Development Goals. Nat. Sustain. 2, 922–930 (2019).

    Article  Google Scholar 

  138. Pocock, M. J. O., Tweddle, J. C., Savage, J., Robinson, L. D. & Roy, H. E. The diversity and evolution of ecological and environmental citizen science. PLoS ONE 12, e0172579 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  139. Palmer, J. R. B. et al. Citizen science provides a reliable and scalable tool to track disease-carrying mosquitoes. Nat. Commun. 8, 916 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  140. Cohnstaedt, L. W., Ladner, J., Campbell, L. R., Busch, N. & Barrera, R. Determining mosquito distribution from egg data: the role of the citizen scientist. Am. Biol. Teach. 78, 317–322 (2016).

    Article  Google Scholar 

  141. Murindahabi, M. M. et al. Citizen science for monitoring the spatial and temporal dynamics of malaria vectors in relation to environmental risk factors in Ruhuha, Rwanda. Malar. J. 20, 1–18 (2021).

    Article  Google Scholar 

  142. Kampen, H. et al. Approaches to passive mosquito surveillance in the EU. Parasites Vectors 8, 1–13 (2015).

    Article  Google Scholar 

  143. Larsen, L. Why citizen scientists are gathering DNA from hundreds of lakes-on the same day. Nature https://www.nature.com/articles/d41586-024-00520-y (2024).

  144. Poen, M. J. et al. Local amplification of highly pathogenic avian influenza H5N8 viruses in wild birds in the Netherlands, 2016 to 2017. Eurosurveillance 23, 17-00449 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  145. Münger, E. et al. One Health approach uncovers emergence and dynamics of Usutu and West Nile viruses in the Netherlands. Nat. Commun. 16, 7883 (2025). This extensive study describes how collaboration between different expertise, as well as involvement of citizen science, can lead to important insights in zoonotic virus ecology.

    Article  PubMed  PubMed Central  Google Scholar 

  146. World Health Organizaton. mHealth: New Horizons for Health Through Mobile Technologies (WHO, 2011).

  147. Kaarj, K., Akarapipad, P. & Yoon, J.-Y. Simpler, faster, and sensitive Zika virus assay using smartphone detection of loop-mediated isothermal amplification on paper microfluidic chips. Sci. Rep. 8, 1–11 (2018).

    Article  CAS  Google Scholar 

  148. Geneviève, L. D. et al. Participatory disease surveillance systems: ethical framework. J. Med. Internet Res. 21, e12273 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  149. Koppeschaar, C. E. et al. Influenzanet: citizens among 10 countries collaborating to monitor influenza in Europe. JMIR Public. Health Surveill. 3, e7429 (2017).

    Article  Google Scholar 

  150. Elliot, A. J. et al. Self-sampling for community respiratory illness: a new tool for national virological surveillance. Eurosurveillance 20, 21058 (2015).

    Article  CAS  PubMed  Google Scholar 

  151. Su, X. et al. A novel internet sampling for HIV surveillance: feasibility of self-sampling and preparation of DBS for delivery detection of HIV total nucleic acid and complementarity to sentinel surveillance. BMC Infect. Dis. 23, 509 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  152. Karesh, W. B. et al. Ecology of zoonoses: natural and unnatural histories. Lancet 380, 1936–1945 (2012). This key study proposes a framework of disease emergence.

    Article  PubMed  PubMed Central  Google Scholar 

  153. Corman, V. M. et al. Detection of 2019 novel coronavirus (2019-nCoV) by real-time RT-PCR. Euro. Surveill. 25, 2000045 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  154. Wille, M., Geoghegan, J. L. & Holmes, E. C. How accurately can we assess zoonotic risk? PLoS Biol. 19, e3001135 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  155. Wasik, B. R. et al. Onward transmission of viruses: how do viruses emerge to cause epidemics after spillover? Philos. Trans. R. Soc. B 374, 20190017 (2019).

    Article  CAS  Google Scholar 

  156. Zhang, X.-A. et al. A zoonotic Henipavirus in febrile patients in China. N. Engl. J. Med. 387, 470–472 (2022). This study is an example of how a human risk population can serve as the sentinel for novel zoonotic viruses.

    Article  PubMed  Google Scholar 

  157. Porta, M. S., Greenland, S., Hernán, M., dos Santos Silva, I. & Last, J. M. A Dictionary of Epidemiology (Oxford Univ. Press, 2014).

  158. Hui, D. S. et al. Middle East respiratory syndrome coronavirus: risk factors and determinants of primary, household, and nosocomial transmission. Lancet Infect. Dis. 18, e217–e227 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  159. Wang, H., de Paulo, K. J. I. d. A., Gültzow, T., Zimmermann, H. M. L. & Jonas, K. J. Brief report: determinants of potential sexual activity reduction in the face of the mpox epidemic. Int. J. Behav. Med. 32, 308–324 (2024).

    Article  PubMed  Google Scholar 

  160. Wilkinson, A., Parker, M., Martineau, F. & Leach, M. Engaging ‘communities’: anthropological insights from the West African Ebola epidemic. Philos. Trans. R. Soc. B: Biol. Sci. 372, 20160305 (2017).

    Article  Google Scholar 

  161. Tan, C. C. S. et al. Transmission of SARS-CoV-2 from humans to animals and potential host adaptation. Nat. Commun. 13, 2988 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  162. Koopmans, M. SARS-CoV-2 and the human–animal interface: outbreaks on mink farms. Lancet Infect. Dis. 21, 18–19 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  163. Hallmaier-Wacker, L. K., Munster, V. J. & Knauf, S. Disease reservoirs: from conceptual frameworks to applicable criteria. Emerg. Microbes Infect. 6, 1–5 (2017).

    Article  Google Scholar 

  164. Food and Agriculture Organization, World Organisation for Animal Health & World Health Orgaization. Joint statement on the prioritization of monitoring SARS-CoV-2 infection in wildlife and preventing the formation of animal reservoirs. WHO https://www.who.int/news/item/07-03-2022-joint-statement-on-the-prioritization-of-monitoring-sars-cov-2-infection-in-wildlife-and-preventing-the-formation-of-animal-reservoirs (2022).

  165. Hoffmann, M. et al. SARS-CoV-2 mutations acquired in mink reduce antibody-mediated neutralization. Cell Rep. 35, 109017 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  166. Hayman, D. T. S. et al. Developing One Health surveillance systems. One Health 17, 100617 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  167. Bordier, M., Uea-Anuwong, T., Binot, A., Hendrikx, P. & Goutard, F. L. Characteristics of One Health surveillance systems: a systematic literature review. Preventive Vet. Med. 181, 104560 (2020).

    Article  Google Scholar 

  168. Vredenberg, I. et al. Assessing the use of different surveillance components to detect highly pathogenic avian influenza outbreaks in poultry in the Netherlands in low-and high-risk years. Transbound. Emerg. Dis. 2025, 7441785 (2025).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  169. Errecaborde, K. M. et al. Factors that enable effective One Health collaborations — a scoping review of the literature. PLoS ONE 14, e0224660 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  170. Sikkema, R. & Koopmans, M. One Health training and research activities in Western Europe. Infect. Ecol. Epidemiol. 6, 33703 (2016).

    PubMed  Google Scholar 

  171. World Health Organization. WHO Pandemic Agreement (WHO, 2025). This work presents the adoption of the WHO Pandemic Agreement, an important milestone towards coordinated, fair preparation and response to future pandemics.

  172. Stephen, C. & Berezowski, J. Reflective practice is a prerequisite for One Health development. One Health Outlook 6, 13 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  173. Halpin, K., Graham, K. & Durr, P. A. Sero-monitoring of horses demonstrates the Equivac® HeV Hendra virus vaccine to be highly effective in inducing neutralising antibody titres. Vaccines 9, 731 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  174. Manyweathers, J. et al. Risk mitigation of emerging zoonoses: Hendra virus and non-vaccinating horse owners. Transbound. Emerg. Dis. 64, 1898–1911 (2017).

    Article  CAS  PubMed  Google Scholar 

  175. International Monetary Fund. World Economic Outlook: Countering the Cost-of-living Crisis (IMF, 2022).

  176. Fan, V. Y., Jamison, D. T. & Summers, L. H. Pandemic risk: how large are the expected losses? Bull. World Health Organ. 96, 129 (2018).

    Article  PubMed  Google Scholar 

  177. World Bank. Putting Pandemics Behind Us: Investing in One Health to Reduce Risks of Emerging Infectious Diseases (World Bank, 2022).

  178. Dobson, A. P. et al. Ecology and economics for pandemic prevention. Science 369, 379–381 (2020). This study attempts to quantify the costs and benefits of pandemic preparedness.

    Article  CAS  PubMed  Google Scholar 

  179. Butt, E. W. et al. Amazon deforestation causes strong regional warming. Proc. Natl Acad. Sci. USA 120, e2309123120 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  180. Montanarella, L., Scholes, R. & Brainich, A. The Assessment Report on Land Degradation and Restoration: Summary for Policymakers (IPBES, 2018).

  181. Pike, J., Bogich, T., Elwood, S., Finnoff, D. C. & Daszak, P. Economic optimization of a global strategy to address the pandemic threat. Proc. Natl Acad. Sci. USA 111, 18519–18523 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  182. Sirleaf, E. J. & Clark, H. Report of the Independent Panel for Pandemic Preparedness and Response: making COVID-19 the last pandemic. Lancet 398, 101–103 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  183. Sikkema, R. S. et al. Detection of West Nile virus in a common whitethroat (Curruca communis) and Culex mosquitoes in the Netherlands, 2020. Eurosurveillance 25, 2001704 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  184. de Saint Lary, C.dB. et al. Assessing West Nile virus (WNV) and Usutu virus (USUV) exposure in bird ringers in the Netherlands: a high-risk group for WNV and USUV infection? One Health 16, 100533 (2023).

    Article  Google Scholar 

  185. Streng, K. et al. Sentinel chicken surveillance reveals previously undetected circulation of West Nile virus in the Netherlands. Emerg. Microbes Infect. 13, 2406278 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  186. Streng, K. et al. Orthoflavivirus surveillance in the Netherlands: insights from a serosurvey in horses & dogs and a questionnaire among horse owners. Zoonoses Public. Health 71, 900–910 (2024).

    Article  PubMed  Google Scholar 

  187. Tao, X., Liu, S., Zhu, W. & Rayner, S. Rabies surveillance and control in China over the last twenty years. Biosaf. Health 3, 142–147 (2021).

    Article  Google Scholar 

  188. Liu, H. et al. Rabies viruses in specific wild fur animals in northern China, 2017–2019. Transbound. Emerg. Dis. 67, 2307–2312 (2020).

    Article  CAS  PubMed  Google Scholar 

  189. Oude Munnink, B. B. et al. The next phase of SARS-CoV-2 surveillance: real-time molecular epidemiology. Nat. Med. 27, 1518–1524 (2021).

    Article  CAS  PubMed  Google Scholar 

  190. Holmes, E. C. et al. The origins of SARS-CoV-2: a critical review. Cell 184, 4848–4856 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  191. Alm, E. et al. Geographical and temporal distribution of SARS-CoV-2 clades in the WHO European region, January to June 2020. Eurosurveillance 25, 2001410 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  192. Voeten, H. et al. Unravelling the modes of transmission of SARS-CoV-2 during a nursing home outbreak: looking beyond the church super-spread event. Clin. Infect. Dis. 73, S163–S169 (2020).

    Article  Google Scholar 

  193. Lu, L. et al. Adaptation, spread and transmission of SARS-CoV-2 in farmed minks and associated humans in the Netherlands. Nat. Commun. 12, 6802 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  194. Mulder, M. et al. Reinfection of severe acute respiratory syndrome coronavirus 2 in an immunocompromised patient: a case report. Clin. Infect. Dis. 73, e2841–e2842 (2021).

    Article  CAS  PubMed  Google Scholar 

  195. Lu, L. et al. West Nile virus spread in Europe: phylogeographic pattern analysis and key drivers. PLoS Pathog. 20, e1011880 (2024). This work presents an extensive multi-institute phylogenetic analysis of WNV in Europe, identifying possible drivers for spread.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  196. Attwood, S. W., Hill, S. C., Aanensen, D. M., Connor, T. R. & Pybus, O. G. Phylogenetic and phylodynamic approaches to understanding and combating the early SARS-CoV-2 pandemic. Nat. Rev. Genet. 23, 547–562 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  197. Vaughan, T. G. et al. Estimating epidemic incidence and prevalence from genomic data. Mol. Biol. Evol. 36, 1804–1816 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  198. Roosenhoff, R. et al. Influenza A/H3N2 virus infection in immunocompromised ferrets and emergence of antiviral resistance. PLoS ONE 13, e0200849 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  199. Bai, R. et al. Antigenic variation of avian influenza A (H5N6) viruses, Guangdong province, China, 2014–2018. Emerg. Infect. Dis. 25, 1932 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  200. Harvey, W. T. et al. SARS-CoV-2 variants, spike mutations and immune escape. Nat. Rev. Microbiol. 19, 409–424 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  201. Luca, B. et al. Highly pathogenic avian influenza H5N1 virus infections in wild red foxes (Vulpes vulpes) show neurotropism and adaptive virus mutations. Microbiol. Spectr. 11, e0286722 (2023).

    Article  Google Scholar 

  202. Simmonds, P. & Aiewsakun, P. Virus classification—where do you draw the line? Arch. Virol. 163, 2037–2046 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  203. Wang, J. et al. Individual bat virome analysis reveals co-infection and spillover among bats and virus zoonotic potential. Nat. Commun. 14, 4079 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  204. Geoghegan, J. L. & Holmes, E. C. Predicting virus emergence amid evolutionary noise. Open. Biol. 7, 170189 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  205. Suttie, A. et al. Inventory of molecular markers affecting biological characteristics of avian influenza A viruses. Virus Genes. 55, 739–768 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  206. Potocnakova, L., Bhide, M. & Pulzova, L. B. An introduction to B-cell epitope mapping and in silico epitope prediction. J. Immunol. Res. 2016, 6760830 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  207. Joana, D. et al. Broad host range of SARS-CoV-2 predicted by comparative and structural analysis of ACE2 in vertebrates. Proc. Natl Acad. Sci. USA 117, 22311–22322 (2020).

    Article  Google Scholar 

  208. Borkenhagen, L. K., Allen, M. W. & Runstadler, J. A. Influenza virus genotype to phenotype predictions through machine learning: a systematic review: computational prediction of influenza phenotype. Emerg. Microbes Infect. 10, 1896–1907 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  209. Zhou, L. et al. Retrospective detection and phylogenetic analysis of swine acute diarrhoea syndrome coronavirus in pigs in southern China. Transbound. Emerg. Dis. 66, 687–695 (2019).

    Article  CAS  PubMed  Google Scholar 

  210. Edwards, C. E. et al. Swine acute diarrhea syndrome coronavirus replication in primary human cells reveals potential susceptibility to infection. Proc. Natl Acad. Sci. USA 117, 26915–26925 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  211. Li, H. et al. Human–animal interactions and bat coronavirus spillover potential among rural residents in southern China. Biosaf. Health 1, 84–90 (2019).

    Article  PubMed  Google Scholar 

  212. Schriml, L. M. et al. COVID-19 pandemic reveals the peril of ignoring metadata standards. Sci. Data 7, 188 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  213. Chen, Z. et al. Global landscape of SARS-CoV-2 genomic surveillance and data sharing. Nat. Genet. 54, 499–507 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  214. Murray, K. et al. A morbillivirus that caused fatal disease in horses and humans. Science 268, 94–97 (1995).

    Article  CAS  PubMed  Google Scholar 

  215. Plowright, R. K. et al. Ecological dynamics of emerging bat virus spillover. Proc. R. Soc. B: Biol. Sci. 282, 20142124 (2015).

    Article  Google Scholar 

  216. Eby, P. et al. Pathogen spillover driven by rapid changes in bat ecology. Nature 613, 340–344 (2023). This work presents an extensive 25-year study of bat virus spillover in Australia, providing a knowledge base for the development of interventions for primary prevention of spillover.

    Article  CAS  PubMed  Google Scholar 

  217. Becker, D. J., Eby, P., Madden, W., Peel, A. J. & Plowright, R. K. Ecological conditions predict the intensity of Hendra virus excretion over space and time from bat reservoir hosts. Ecol. Lett. 26, 23–36 (2023).

    Article  PubMed  Google Scholar 

  218. World Health Organization. SARS-CoV-2 in Animals Used for Fur Farming: GLEWS+ Risk Assessment (FAO, WOAH & WHO, 2021).

  219. Guan, Y. et al. Isolation and characterization of viruses related to the SARS coronavirus from animals in southern China. Science 302, 276–278 (2003).

    Article  CAS  PubMed  Google Scholar 

  220. Oude Munnink, B. B. et al. Transmission of SARS-CoV-2 on mink farms between humans and mink and back to humans. Science 371, 172–177 (2020). This work is the first report of large-scale spillover and spill-back of SARS-CoV-2 between humans and animals.

    Article  PubMed  PubMed Central  Google Scholar 

  221. Lindh, E. et al. Highly pathogenic avian influenza A (H5N1) virus infection on multiple fur farms in the South and Central Ostrobothnia regions of Finland, July 2023. Eurosurveillance 28, 2300400 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  222. Zhao, J. et al. Farmed fur animals harbour viruses with zoonotic spillover potential. Nature 634, 228–233 (2024). This study shows that farmed fur animals can be a reservoir for novel zoonotic viruses, in addition to known risks of SARS-CoV-2 and avian influenza virus infections and adaptation.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  223. European Food Safety Authority et al. Drivers for a pandemic due to avian influenza and options for One Health mitigation measures. EFSA J. 22, e8735 (2024).

    Google Scholar 

  224. European Food Safety Authoity. SARS-CoV-2 in animals: susceptibility of animal species, risk for animal and public health, monitoring, prevention and control. EFSA J. 21, e07822 (2023).

    Google Scholar 

  225. Halstead, S. B. Three dengue vaccines—what now. N. Engl. J. Med. 390, 464–465 (2024).

    Article  PubMed  Google Scholar 

  226. Weber, W. C. et al. The approved live-attenuated Chikungunya virus vaccine (IXCHIQ®) elicits cross-neutralizing antibody breadth extending to multiple arthritogenic alphaviruses similar to the antibody breadth following natural infection. Vaccines 12, 893 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  227. World Health Organization. Global Vector Control Response 2017–2030 (WHO & TDR, 2017).

  228. Hickmann, M. Plant-covered residential towers in Chengdu attract mosquitos, repel tenants. The Architect's Newspaper https://www.archpaper.com/2020/09/plant-covered-residential-towers-chengdu-attract-mosquitos-repel-tenants/ (2020).

  229. Walshe, D. P., Garner, P., Adeel, A. A., Pyke, G. H. & Burkot, T. R. Larvivorous fish for preventing malaria transmission. Cochrane Database Syst. Rev. 12, CD008090 (2017).

    PubMed  Google Scholar 

  230. Willott, E. Restoring nature, without mosquitoes? Restor. Ecol. 12, 147–153 (2004).

    Article  Google Scholar 

Download references

Acknowledgements

R.S. and M.K. receive funding for One Health research through European Union’s Horizon 2020 research and innovation programme under grant agreement no. 874735 (VEO - Versatile emerging infectious disease observatory) and EU HERA/HADEA under grant agreement no. 101102733 (DURABLE).

Author information

Authors and Affiliations

  1. Viroscience Department, Erasmus MC, Rotterdam, The Netherlands

    Reina S. Sikkema & Marion Koopmans

  2. Pandemic and Disaster Preparedness Research Centre, Erasmus MC, Rotterdam, The Netherlands

    Reina S. Sikkema & Marion Koopmans

Authors
  1. Reina S. Sikkema
    View author publications

    Search author on:PubMed Google Scholar

  2. Marion Koopmans
    View author publications

    Search author on:PubMed Google Scholar

Contributions

The authors contributed equally to all aspects of the article.

Corresponding authors

Correspondence to Reina S. Sikkema or Marion Koopmans.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Reviews Microbiology thanks Gregory Gray, who co-reviewed with Franciso Guerra; and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Related links

European countries banned fur farming: https://www.furfreealliance.com/fur-bans/

Reported human infections in the United States: https://www.cdc.gov/bird-flu/situation-summary/index.html

World Bank Pandemic Fund: https://www.thepandemicfund.org/

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sikkema, R.S., Koopmans, M. Viral emergence and pandemic preparedness in a One Health framework. Nat Rev Microbiol (2025). https://doi.org/10.1038/s41579-025-01243-1

Download citation

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s41579-025-01243-1

Search

Advanced search

Quick links

Nature Briefing Microbiology

Sign up for the Nature Briefing: Microbiology newsletter — what matters in microbiology research, free to your inbox weekly.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing: Microbiology