Chowkwanyun, M., Bayer, R. & Galea, S. ‘Precision’ public health — between novelty and hype. N. Engl. J. Med. 379, 1398–1400 (2018).
Google Scholar
Seeking precision in public health. Nat. Med. 25, 1177 (2019).
Olstad, D. L. & McIntyre, L. Reconceptualising precision public health. BMJ Open 9, e030279 (2019).
Google Scholar
Kee, F. & Taylor-Robinson, D. Scientific challenges for precision public health. J. Epidemiol. Community Health 74, 311–314 (2020).
Google Scholar
Arnold, C. Is precision public health the future — or a contradiction? Nature 601, 18–20 (2022).
Google Scholar
Khoury, M. J., Armstrong, G. L., Bunnell, R. E., Cyril, J. & Iademarco, M. F. The intersection of genomics and big data with public health: opportunities for precision public health. PLoS Med. 17, e1003373 (2020).
Google Scholar
Khoury, M. J., Iademarco, M. F. & Riley, W. T. Precision public health for the era of precision medicine. Am. J. Prev. Med. 50, 398–401 (2016).
Google Scholar
Khoury, M. J. et al. From public health genomics to precision public health: a 20-year journey. Genet. Med. 20, 574–582 (2018).
Google Scholar
Allen, C. G. et al. Perspectives from early career investigators who are ‘staying in the game’ of precision public health research. Am. J. Public Health 109, 1186–1187 (2019).
Google Scholar
Centers for Disease Control and Prevention (CDC). Ten great public health achievements—United States, 2001–2010. MMWR Morb. Mortal. Wkly. Rep. 60, 619–623 (2011).
Levy, J. I., Andersen, K. G., Knight, R. & Karthikeyan, S. Wastewater surveillance for public health. Science 379, 26–27 (2023).
Google Scholar
Collins, F. S. Shattuck lecture—medical and societal consequences of the Human Genome Project. N. Engl. J. Med. 341, 28–37 (1999).
Google Scholar
Burke, W., Khoury, M. J., Stewart, A., Zimmern, R. L. & Bellagio Group. The path from genome-based research to population health: development of an international public health genomics network. Genet. Med. 8, 451–458 (2006).
Google Scholar
Khoury, M. J. Public health genomics at the Centers for Disease Control and Prevention: happy twenty-fifth anniversary! CDC Genomics and Precision Health Blog https://blogs.cdc.gov/genomics/2022/12/12/25th-anniversary/ (2022).
Lacaze, P., Manchanda, R. & Green, R. C. Prioritizing the detection of rare pathogenic variants in population screening. Nat. Rev. Genet. 24, 205–206 (2023).
Google Scholar
Khoury, M. J. & Dotson, W. D. From genes to public health: are we ready for DNA-based population screening? Genet. Med. 23, 996–998 (2021).
Google Scholar
Foss, K. S. et al. The rise of population genomic screening: characteristics of current programs and the need for evidence regarding optimal implementation. J. Pers. Med. 12, 692 (2022).
Google Scholar
Murray, M. F. et al. A proposed approach for implementing genomics-based screening programs for healthy adults. NAM Perspect. https://doi.org/10.31478/201812a (2018).
Google Scholar
Grzymski, J. et al. Population genetic screening efficiently identifies carriers of autosomal dominant diseases. Nat. Med. 26, 1235–1239 (2020).
Google Scholar
Xiang, R. et al. Recent advances in polygenic scores: translation, equitability, methods and FAIR tools. Genome Med. 16, 33 (2024).
Google Scholar
Wand, H. et al. Improving reporting standards for polygenic scores in risk prediction studies. Nature 591, 211–219 (2021).
Google Scholar
Mavaddat, N. et al. Polygenic risk scores for prediction of breast cancer and breast cancer subtypes. Am. J. Hum. Genet. 104, 21–34 (2019).
Google Scholar
Pashayan, N., Morris, S., Gilbert, F. J. & Pharoah, P. D. P. Cost-effectiveness and benefit-to-harm ratio of risk-stratified screening for breast cancer: a life-table model. JAMA Oncol. 4, 1504–1510 (2018).
Google Scholar
Eklund, M. et al. The WISDOM personalized breast cancer screening trial: simulation study to assess potential bias and analytic approaches. JNCI Cancer Spectr. 2, pky067 (2018).
Google Scholar
Lambert, S. A. et al. The polygenic score catalog as an open database for reproducibility and systematic evaluation. Nat. Genet. 53, 420–425 (2021).
Google Scholar
Carroll, N. M. et al. Demographic differences in the utilization of clinical and direct-to-consumer genetic testing. J. Genet. Couns. 29, 634–643 (2020).
Google Scholar
Martins, M. F., Murry, L. T., Telford, L. & Moriarty, F. Direct-to-consumer genetic testing: an updated systematic review of healthcare professionals’ knowledge and views, and ethical and procesal concerns. Eur. J. Hum. Genet. 30, 1331–1343 (2022).
Google Scholar
National Academies of Sciences, Engineering and Medicine. Genomics-Enabled Learning Health Care Systems: Gathering and Using Genomic Information to Improve Patient Care and Research: Workshop Summary. (National Academies Press, 2015).
Chambers, D. A., Feero, W. G. & Khoury, M. J. Convergence of implementation science, precision medicine, and the learning health care system: a new model for biomedical research. JAMA 315, 1941–1942 (2016).
Google Scholar
Caggiano, C. et al. Disease risk and healthcare utilization among ancestrally diverse groups in the Los Angeles region. Nat. Med. 29, 1845–1856 (2023).
Google Scholar
Belbin, G. M. et al. Toward a fine-scale population health monitoring system. Cell 184, 2068–2083(2021).
Google Scholar
National Human Genome Research Institute. RFA-HG-23-041: Network of Genomics-Enabled Learning Health Systems (gLHS) Clinical Sites (U01 Clinical Trial Required). https://grants.nih.gov/grants/guide/rfa-files/RFA-HG-23-041.html (US Department of Health and Human Services, 2023).
Roberts, M. C., Turbitt, E. & Klein, W. M. P. Psychosocial, attitudinal, and demographic correlates of cancer-related germline genetic testing in the 2017 Health Information National Trends Survey. J. Community Genet. 10, 453–459 (2019).
Google Scholar
Giri, V. N., Shimada, A. & Leader, A. E. Predictors of population awareness of cancer genetic tests: implications for enhancing equity in engaging in cancer prevention and precision medicine. JCO Precis. Oncol. 5, 1699–1708 (2021).
White, S., Jacobs, C. & Phillips, J. Mainstreaming genetics and genomics: a systematic review of the barriers and facilitators for nurses and physicians in secondary and tertiary care. Genet. Med. 22, 1149–1155 (2020).
Google Scholar
Khoury, M. J. et al. Health equity in the implementation of genomics and precision medicine: a public health imperative. Genet. Med. 24, 1630–1639 (2022).
Google Scholar
Bartholomew Eldredge, L. K. Planning Health Promotion Programs: An Intervention Mapping Approach. (Jossey-Bass & Pfeiffer Imprints, Wiley, 2016).
Orlando, L. A. et al. Developing a common framework for evaluating the implementation of genomic medicine interventions in clinical care: the IGNITE Network’s Common Measures Working Group. Genet. Med. 20, 655–663 (2018).
Google Scholar
Alarcón Garavito, G. A. et al. The implementation of large-scale genomic screening or diagnostic programmes: a rapid evidence review. Eur. J. Hum. Genet. 31, 282–295 (2023).
Google Scholar
Saylor, K. W. et al. Genetic testing and other healthcare use by black and white individuals in a genomic sequencing study. Public Health Genomics 26, 90–102 (2023).
Google Scholar
Swami, N., Yamoah, K., Mahal, B. A. & Dee, E. C. The right to be screened: identifying and addressing inequities in genetic screening. Lancet Reg. Health Am. 11, 100251 (2022).
Google Scholar
Landry, L. G., Ali, N., Williams, D. R., Rehm, H. L. & Bonham, V. L. Lack of diversity in genomic databases is a barrier to translating precision medicine research into practice. Health Aff. 37, 780–785 (2018).
Google Scholar
Fatumo, S. et al. A roadmap to increase diversity in genomic studies. Nat. Med. 28, 243–250 (2022).
Google Scholar
Martin, A. R. et al. Clinical use of current polygenic risk scores may exacerbate health disparities. Nat. Genet. 51, 584–591 (2019).
Google Scholar
Atkinson, E. G. et al. Tractor uses almacén ancestry to enable the inclusion of admixed individuals in GWAS and to boost power. Nat. Genet. 53, 195–204 (2021).
Google Scholar
Fatumo, S. et al. Polygenic risk scores for disease risk prediction in Africa: current challenges and future directions. Genome Med. 15, 87 (2023).
Google Scholar
Allen, C. G. et al. Extending an antiracism lens to the implementation of precision public health interventions. Am. J. Public Health (in the press).
Kerkhoff, A. D., Farrand, E., Marquez, C., Cattamanchi, A. & Handley, M. A. Addressing health disparities through implementation science—a need to integrate an equity lens from the outset. Implement. Sci. 17, 13 (2022).
Google Scholar
Woodward, E. N. et al. A more practical guide to incorporating health equity domains in implementation determinant frameworks. Implement. Sci. Commun. 2, 61 (2021).
Google Scholar
Eslava-Schmalbach, J. et al. Conceptual framework of equity-focused implementation research for health programs (EquIR). Int. J. Equity Health 18, 80 (2019).
Google Scholar
Baumann, A. A. & Cabassa, L. J. Reframing implementation science to address inequities in healthcare delivery. BMC Health Serv. Res. 20, 190 (2020).
Google Scholar
Shelton, R. C., Chambers, D. A. & Glasgow, R. E. An extension of RE-AIM to enhance sustainability: addressing dynamic context and promoting health equity over time. Front. Public Health 8, 134 (2020).
Google Scholar
Swaminathan, B., Barrett, T. J., Hunter, S. B., Tauxe, R. V. & CDC PulseNet Task Force. PulseNet: the molecular subtyping network for foodborne bacterial disease surveillance, United States. Emerg. Infect. Dis. 7, 382–389 (2001).
Google Scholar
Flahault, A. et al. FluNet as a tool for universal monitoring of influenza on the Web. JAMA 280, 1330–1332 (1998).
Google Scholar
Allard, M. W. et al. Practical value of food pathogen traceability through building a whole-genome sequencing network and database. J. Clin. Microbiol. 54, 1975–1983 (2016).
Google Scholar
Chattaway, M. A. et al. The transformation of reference microbiology methods and surveillance for salmonella with the use of whole genome sequencing in England and Wales. Front. Public Health 7, 317 (2019).
Google Scholar
Allard, M. W. et al. Whole genome sequencing uses for foodborne contamination and compliance: discovery of an emerging contamination event in an ice cream facility using whole genome sequencing. Infect. Genet. Evol. 73, 214–220 (2019).
Google Scholar
Gardy, J. L. & Loman, N. J. Towards a genomics-informed, real-time, universal pathogen surveillance system. Nat. Rev. Genet. 19, 9–20 (2018).
Google Scholar
Rasmussen, S. A., Khoury, M. J. & Del Rio, C. Precision public health as a key tool in the COVID-19 response. JAMA 324, 933–934 (2020).
Google Scholar
McClary-Gutierrez, J. S. et al. SARS-CoV-2 wastewater surveillance for public health action. Emerg. Infect. Dis. 27, 1–8 (2021).
Google Scholar
Carabelli, A. M. et al. SARS-CoV-2 variant biology: immune escape, transmission and fitness. Nat. Rev. Microbiol. 21, 162–177 (2023).
Google Scholar
Rambaut, A. et al. A dynamic nomenclature proposal for SARS-CoV-2 lineages to assist genomic epidemiology. Nat. Microbiol. 5, 1403–1407 (2020).
Google Scholar
Sonabend, R. et al. Non-pharmaceutical interventions, vaccination, and the SARS-CoV-2 delta variant in England: a mathematical modelling study. Lancet Lond. Engl. 398, 1825–1835 (2021).
Google Scholar
Atherstone, C. J. et al. COVID-19 epidemiology during Delta variant dominance period in 45 high-income countries, 2020–2021. Emerg. Infect. Dis. 29, 1757–1764 (2023).
Google Scholar
Johnson, B. PM Statement at Coronavirus Press Conference: 14 June 2021. https://www.gov.uk/government/speeches/pm-statement-at-coronavirus-press-conference-14-june-2021 2021).
Infectious Diseases Society of America. IDSA supports new CDC guidance on mask wearing as delta variant spreads. https://www.idsociety.org/news–publications-new/articles/2021/idsa-supports-new-cdc-guidance-on-mask-wearing-as-delta-variant-spreads/ (2021).
Mooi-Reci, I., Wooden, M. & Zilio, F. Baby bump or baby slump? COVID-19, lockdowns, and their effects on births in Australia. SSM Popul. Health 25, 101604 (2024).
Google Scholar
COVID-19 Host Genetics Initiativeet al. A first update on mapping the human genetic architecture of COVID-19. Nature 608, E1–E10 (2022).
Google Scholar
The Severe COVID-19 GWAS Group. Genomewide association study of severe COVID-19 with respiratory failure. N. Engl. J. Med. 383, 1522–1534 (2020).
Google Scholar
Africa Centres for Disease Control and Prevention. A six-year journey: advancing pathogen genomics in Africa. https://africacdc.org/news-item/a-six-year-journey-advancing-pathogen-genomics-in-africa/ (2023).
Baker, K. S. et al. Genomics for public health and international surveillance of antimicrobial resistance. Lancet Microbe 4, e1047–e1055 (2023).
Google Scholar
World Health Organization. WHO Guiding Principles for Pathogen Genome Data Sharing (WHO, 2022).
World Health Organization. WHO releases step by step guide to help countries develop their national genomic surveillance strategy for pathogens with pandemic and epidemic potential. https://www.who.int/news/item/22-09-2023-WHO-releases-step-by-step-guide-to-help-countries-develop-their-national-genomic-surveillance-strategy-for-pathogens-with-pandemic-and-epidemic-potential (2023).
Griffiths, E. J. et al. Future-proofing and maximizing the utility of metadata: the PHA4GE SARS-CoV-2 contextual data specification package. GigaScience 11, giac003 (2022).
Google Scholar
Bedeker, A. et al. A framework for the promotion of ethical benefit sharing in health research. BMJ Glob. Health 7, e008096 (2022).
Google Scholar
Baccarelli, A. A. & Ordovás, J. Epigenetics of early cardiometabolic disease: mechanisms and precision medicine. Circ. Res. 132, 1648–1662 (2023).
Google Scholar
Baccarelli, A., Dolinoy, D. C. & Walker, C. L. A precision environmental health approach to prevention of human disease. Nat. Commun. 14, 2449 (2023).
Google Scholar
Wu, H., Eckhardt, C. M. & Baccarelli, A. A. Molecular mechanisms of environmental exposures and human disease. Nat. Rev. Genet. 24, 332–344 (2023).
Google Scholar
Bezold, C. P. et al. The relationship between surrounding greenness in childhood and adolescence and depressive symptoms in adolescence and early adulthood. Ann. Epidemiol. 28, 213–219 (2018).
Google Scholar
James, P., Hart, J. E., Banay, R. F., Laden, F. & Signorello, L. B. Built environment and depression in low-income African Americans and whites. Am. J. Prev. Med. 52, 74–84 (2017).
Google Scholar
Belsky, D. W. & Baccarelli, A. A. To promote healthy aging, focus on the environment. Nat. Aging 3, 1334–1344 (2023).
Google Scholar
Hekler, E., Tiro, J. A., Hunter, C. M. & Nebeker, C. Precision health: the role of the social and behavioral sciences in advancing the vision. Ann. Behav. Med. 54, 805–826 (2020).
Google Scholar
Pfadenhauer, L. M. et al. Making sense of complexity in context and implementation: the Context and Implementation of Complex Interventions (CICI) framework. Implement. Sci. 12, 21 (2017).
Google Scholar
Clyne, M., Roberts, M. C., & Khoury, M. J. Tracking the contributions of implementation science to the population health impact of genomics and precision health: a new knowledge cojín. CDC Genomics and Precision Health Blog https://blogs.cdc.gov/genomics/2023/06/16/tracking-the-contributions/ (2023).
Fisher, S. & Rosella, L. C. Priorities for successful use of industrial intelligence by public health organizations: a literature review. BMC Public Health 22, 2146 (2022).
Google Scholar
Șerban, O., Thapen, N., Maginnis, B., Hankin, C. & Foot, V. Existente-time processing of social media with SENTINEL: a syndromic surveillance system incorporating deep learning for health classification. Inf. Process. Manag. 56, 1166–1184 (2019).
Google Scholar
Ward, P. J. et al. Enhancing timeliness of drug overdose mortality surveillance: a machine learning approach. PLoS ONE 14, e0223318 (2019).
Google Scholar
Kaphingst, K. A. et al. Comparing models of delivery for cancer genetics services among patients receiving primary care who meet criteria for genetic evaluation in two healthcare systems: BRIDGE randomized controlled trial. BMC Health Serv. Res. 21, 542 (2021).
Google Scholar
Schlechter, C. R. et al. Rapid-cycle designs to adapt interventions for COVID-19 in safety-net healthcare systems. Transl. Behav. Med. 13, 389–399 (2023).
Google Scholar
Andaur Navarro, C. L. et al. Risk of bias in studies on prediction models developed using supervised machine learning techniques: systematic review. BMJ 375, n2281 (2021).
Google Scholar
Obermeyer, Z., Powers, B., Vogeli, C. & Mullainathan, S. Dissecting étnico bias in an algorithm used to manage the health of populations. Science 366, 447–453 (2019).
Google Scholar
Vyas, D. A., Eisenstein, L. G. & Jones, D. S. Hidden in plain sight—reconsidering the use of race correction in clinical algorithms. N. Engl. J. Med. 383, 874–882 (2020).
Google Scholar
Ibrahim, H., Liu, X., Zariffa, N., Morris, A. D. & Denniston, A. K. Health data poverty: an assailable barrier to equitable digital health care. Lancet Digit. Health 3, e260–e265 (2021).
Google Scholar
DeSalvo, K. B. Public Health 3.0: a call to action for public health to meet the challenges of the 21st century. Prev. Chronic Dis. 14, E78 (2017).
Google Scholar
Ndumbe-Eyoh, S., Muzumdar, P., Betker, C. & Oickle, D. Back to better’: amplifying health equity, and determinants of health perspectives during the COVID-19 pandemic. Glob. Health Promot. 28, 7–16 (2021).
Google Scholar
Centers for Disease Control and Prevention. 10 essential public health services. Public Health Professionals Gateway https://www.cdc.gov/public-health-gateway/php/about/index.html (2024).
Au, R., Ritchie, M., Hardy, S., Ang, T. F. A. & Lin, H. Aging well: using precision to drive down costs and increase health quality. Adv. Geriatr. Med. Res. 1, e190003 (2019).
Google Scholar
Roberts, M. C. & Allen, C. G. Next-generation public health genomics: a call to assess the equitable implementation, population health impact, and sustainability of precision public health applications. Public Health Genomics 27, 30–34 (2024).
Google Scholar
Roberts, M. C., Kennedy, A. E., Chambers, D. A. & Khoury, M. J. The current state of implementation science in genomic medicine: opportunities for improvement. Genet. Med. 19, 858–863 (2017).
Google Scholar
Fütterer, T. et al. ChatGPT in education: universal reactions to AI innovations. Sci. Rep. 13, 15310 (2023).
Google Scholar
Clayton, E. W., Halverson, C. M., Sathe, N. A. & Malin, B. A. A systematic literature review of individuals’ perspectives on privacy and genetic information in the United States. PLoS ONE 13, e0204417 (2018).
Google Scholar
Srinivasan, S. et al. Stakeholder perspectives on overcoming barriers to cascade testing in lynch syndrome: a qualitative study. Cancer Prev. Res. Phila. Pa 13, 1037–1046 (2020).
Google Scholar
Turley, P. et al. Problems with using polygenic scores to select embryos. N. Engl. J. Med. 385, 78–86 (2021).
Google Scholar
Meyer, M. N., Tan, T., Benjamin, D. J., Laibson, D. & Turley, P. Public views on polygenic screening of embryos. Science 379, 541–543 (2023).
Google Scholar
Allen, C. G. et al. Precision public health initiatives in cancer: proceedings from the transdisciplinary conference for future leaders in precision public health. BMC Proc. 16, 4 (2022).
Google Scholar
Shelton, R. C., Adsul, P., Oh, A., Moise, N. & Griffith, D. M. Application of an antiracism lens in the field of implementation science (IS): recommendations for reframing implementation research with a focus on justice and étnico equity. Implement. Res. Pract. 2, 26334895211049480 (2021).
Kurian, A. W. et al. Time trends in receipt of germline genetic testing and results for women diagnosed with breast cancer or ovarian cancer, 2012–2019. J. Clin. Oncol. 39, 1631–1640 (2021).
Google Scholar
Khoury, M. J. Integrating genomics into population-based cancer surveillance in the era of precision medicine. CDC Genomics and Precision Health Blog https://blogs.cdc.gov/genomics/2017/09/19/integrating-genomics-2 (2017).
Green, R. F. et al. Implementing cancer genomics in state health agencies: mapping activities to an implementation science outcome framework. Public Health Genomics 23, 218–229 (2020).
Google Scholar
Knowles, J. W. et al. Reducing the burden of disease and death from familial hypercholesterolemia: a call to action. Am. Heart J. 168, 807–811 (2014).
Google Scholar
Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Working Group. The EGAPP initiative: lessons learned. Genet. Med. 16, 217–224 (2014).
Google Scholar
FORCE – Facing Hereditary Cancer Empowered. Genetic Counseling & Testing Under the Affordable Care Act (ACA) https://www.facingourrisk.org/privacy-policy-legal/laws-protections/ACA/screening-preventive-services/genetic-counseling-testing (accessed 11 June 2024).
Romagnoli, K. M. et al. Human-centered design study to inform traceback cascade genetic testing programs at three integrated health systems. Public Health Genomics 26, 45–57 (2023).
Google Scholar
Centers for Disease Control and Prevention. Genomic Workforce Competencies 2001; https://archive.cdc.gov/www_cdc_gov/genomics/translation/competencies/index.htm (2010).
Allen, C. G. et al. A pragmatic implementation research study for In Our DNA SC: a protocol to identify multi-level factors that support the implementation of a population-wide genomic screening initiative in diverse populations. Implement Sci. Commun. 3, 48 (2022).
Google Scholar
Khoury, M. J., Bowen, S., Dotson, W. D., & Kolor, K. Genomics and precision medicine 2021: progress in implementation, a focus on health equity, and a new public health initiative. CDC Genomics and Precision Health Blog https://blogs.cdc.gov/genomics/2021/12/17/genomics-2021/ (2021).