Policymakers are exploring the use of big data for precision public health which combines traditional data with technologies from fields including genomics.
Real-time surveillance – especially in low- and middle- income countries – can be improved using genomic technologies to improve real-time surveillance consistent with the International Health Regulation (2005).
With the UK National Institute for Health Research, CGPS has supported four countries – Colombia, India, Nigeria and the Philippines – to enhance their use of genomic methods, using tools and innovation to provide real-time surveillance and epidemiology within their national policies and health systems.
There is increased recognition that innovation in both science and technology is the best solution to keep up with the spread of disease[i] . In this era of fast-paced outbreaks, tools that improve disease surveillance can be considered a national as well as a global public good[ii].
Policymakers are exploring the use of big data for precision public health which combines traditional data with technologies from fields including genomics[iii].
Modern public health programs can achieve new levels of speed and accuracy not plausible a decade ago[iv]; with new analytical models, data sources, and stakeholders creating an evolving ecosystem[v]. Genomics has become an important foundation for real-time surveillance, disease pathogenesis, diagnoses and treatments, and drug and vaccine development, as witnessed in the recent SARS-CoV-2 pandemic.
To facilitate modern pathogen analysis and reporting, surveillance systems – especially those in low- and middle- income countries – must be strengthened consistent with the International Health Regulation (2005) and other public health frameworks such as the Global Action Plan for AMR, so that detection and communication can be as fast-paced as the movement of the outbreak[i].
National Partnership and Action Plans
National partnerships work to realize the ambitions of national action plans and promote national partnerships and coordination for real-time surveillance. Partnering with the UK’s National Institute for Health Research, CGPS helped to support National Units in Colombia, India, Nigeria, and the Philippines. These sites occupy strategic positions around the world, acting as gateways to understanding the landscape of antibiotic resistance in their respective continents.
Every country has a different context and organizational model for surveillance systems. National Action Plans for AMR are an important aspect in establishing the contribution of data science and genomics to surveillance for AMR.
Nigeria’s National Action Plan for Antimicrobial Resistance, 2017-2022 (NAP-AMR), for example, has an explicit focus on the use of genomic methods as part of its surveillance activities, including utilizing gene sequencing techniques in identifying AMR mechanisms, and investment in establishing an integrated national gene bank[vii].
Global Guidance and Ecosystems
With WHO guidelines[viii] and publicly-accessible tools available giving countries real-time access to global pathogen information, countries have an opportunity to consider how genomic methods can be implemented as part of their broader surveillance systems.
Each of the country units has contributed back into the global ecosystem, contributing to WHO guidelines[viii], and hosting regional and inter-agency conferences and workshops.
Technical and policy leadership has been an important role taken by country units. International leadership is a central strategy in India’s National Action Plan on AMR, and the Bangalore unit has been an expert reviewer for the WHO Technical Guidance[viii], and has led the establishment of the WHONET network across Bangalore city. Likewise, the country unit in Colombia has been active in establishing One Health partnerships and providing technical advice to the Ministry of Health and regional partners.
At the national level, the outcomes from these partnerships and activities have strengthened local healthcare systems and public health research by enabling more refined identification of microbial pathogens which in turn impacts infection control and the time taken to identify outbreaks, directly benefiting patients and the general population.
As the Philippines Department of Health noted in its Annual Report:
‘…Aside from generating sequence data to inform public policy, the project aims to provide resourcing and local capacity development. With the developing capacity for genomic sequencing and bioinformatics in the reference laboratory, the DOH-ARSP stakeholders can look forward to the provision of genomic data to better characterize high-risk bacterial lineages for better management and control[ix]
References[i] Davies, S. 2020. Reporting Disease Outbreaks in a World with No Digital Borders. In: McInnes, C., Lee, K., and Youde, J., 2020. The Oxford Handbook of Global Health Politics. Oxford University Press, United Kingdom.
[ii] Bettcher, D. et al. 2017. International Efforts to Promote Public Health. In Detels, R., et al. (eds) 2017. Oxford Textbook of Global Public Health, Volume 1. Oxford University Press
[iii] OECD 2019. Health Data in the 21st Century. OECD Paris
[iv] Dolloy 2018. Big Data’s Role in Precision Public Health. Front. Public Health, 07 March 2018
[v] Vayena et al. 2018. Policy implications of big data in the health sector. Bull World Health Organ 2018;96:
[vii] Nigeria Federal Ministries of Agriculture, Environment and Health 2017. National Action Plan for Antimicrobial Resistance, 2017-2022. Government of Nigeria.
[viii] WHO GLASS 2019. Molecular methods for antimicrobial resistance (AMR) diagnostics to enhance the Global Antimicrobial Resistance Surveillance System. WHO Geneva.
[ix] hilippines Department of Health, Antimicrobial Resistance Surveillance Program – 2018 Annual Report. https://arsp.com.ph/arsp-2018-annual-report-data-summary-is-now-available-for-download/