Monitoring outbreak events for disease surveillance in a data science context (MOOD)
Project leads: Andy Tatem and Shengjie Lai
Team: Eimear Cleary, Maksym Bondarenko, Fabia Le Moignan
Funding: EU Horizon 2020
Start: Jan 2020
Completion: Dec 2024
MOOD was an EU Horizon 2020 research and innovation project coordinated by CIRAD. Its original project period ran from January 2020 to December 2023, followed by a one-year no-cost extension through December 2024. The consortium developed data, analytical methods and digital tools to improve the early detection, assessment and monitoring of infectious disease threats under climate and other global changes. It combined indicator- and event-based surveillance with epidemiological, genomic, environmental, demographic, socioeconomic and mobility data in a One Health framework.
Main outputs: The project delivered the open MOOD Platform and GeoNetwork, disease profiles, standardised covariate datasets, risk maps, predictive models, visual analytics and training materials. Applications covered COVID-19, West Nile virus, tick-borne encephalitis, highly pathogenic avian influenza, dengue/chikungunya and antimicrobial resistance. The European Commission final review concluded that MOOD fully achieved its objectives and milestones and delivered exceptional results with substantial impact potential. The project reported 186 publications, including 153 peer-reviewed papers.
WorldPop and University of Southampton contributions
- Population, mobility and geospatial data. WorldPop contributed to the acquisition, processing and standardisation of demographic, socioeconomic, mobility and environmental covariates for disease modelling and risk mapping.
- Mobility-informed outbreak modelling. WorldPop developed and applied travel-network, metapopulation and social-contact models to assess COVID-19 importation and spread, transmission risks during air and rail travel, and the effects of population connectivity on epidemic trajectories. The work demonstrated the value of combining mobility, population, epidemiological and genomic data for targeted surveillance and variant-risk assessment.
- Interventions, vaccination and preparedness. Studies quantified the effects of non-pharmaceutical interventions in China, showed the importance of coordinated exit strategies across Europe, and evaluated vaccination and physical distancing jointly. A Bayesian analysis across 31 European countries estimated that vaccination and non-pharmaceutical interventions together reduced transmission by 53% by October 2021. Data, code and research outputs were shared openly where licensing permitted.
Together, these contributions demonstrated how population distribution, mobility and connectivity data can support near-real-time epidemic intelligence and public health decisions. WorldPop and the University of Southampton helped identify importation and transmission risks, assess interventions, and tailor vaccination and distancing strategies to local contexts. The evidence informed COVID-19 preparedness and response by the UK government, WHO, ECDC, US CDC, Africa CDC, China CDC and other public health authorities, and received extensive media coverage from the BBC, The Guardian and the Associated Press.
Key project, data and code resources
- Project and platform: MOOD website | CORDIS record and results | MOOD Platform
- Datasets and repositories: MOOD GeoNetwork | MOOD Zenodo community | COVID-19 mobility maps and data | WorldPop COVID-19 resources
- Open analytical code: BEARmod | Vaccine-NPIs-in-EuropeV2 | Air/train transmission analyses
Selected publications
1. Lai S, Ruktanonchai NW, Zhou L, et al. Effect of non-pharmaceutical interventions to contain COVID-19 in China. Nature 585, 410-413 (2020).
2. Ruktanonchai NW, Floyd JR, Lai S, et al. Assessing the impact of coordinated COVID-19 exit strategies across Europe. Science 369, 1465-1470 (2020).
3. Yang J, Li J, Lai S, et al. Uncovering two phases of early intercontinental COVID-19 transmission dynamics. Journal of Travel Medicine 27(8), taaa200 (2020).
4. Lai S, Ruktanonchai NW, Carioli A, et al. Assessing the effect of global travel and contact restrictions on mitigating the COVID-19 pandemic. Engineering 7(7), 914-923 (2021).
5. Huang B, Wang J, Cai J, et al. Integrated vaccination and physical distancing interventions to prevent future COVID-19 waves in Chinese cities. Nature Human Behaviour 5, 695-705 (2021).
6. Lemey P, Ruktanonchai N, Hong SL, et al. Untangling introductions and persistence in COVID-19 resurgence in Europe. Nature 595, 713-717 (2021).
7. Hu M, Lin H, Wang J, et al. Risk of severe acute respiratory syndrome coronavirus 2 transmission among air passengers in China. Clinical Infectious Diseases 75(1), e234-e240 (2022).
8. Lai S, Bogoch II, Ruktanonchai NW, et al. Assessing spread risk of COVID-19 in early 2020. Data Science and Management 5(4), 212-218 (2022).
9. Ge Y, Zhang W-B, Wu X, et al. Untangling the changing impact of non-pharmaceutical interventions and vaccination on European COVID-19 trajectories. Nature Communications 13, 3106 (2022).
10. Woods D, Cunningham A, Utazi CE, et al. Exploring methods for mapping seasonal population changes using mobile phone data. Humanities and Social Sciences Communications 9, 247 (2022).
11. Zhang D, Ge Y, Zhang W, et al. Data-driven models informed by spatiotemporal mobility patterns for understanding infectious disease dynamics. ISPRS International Journal of Geo-Information 12(7), 266 (2023).
12. van Kleef E, Van Bortel W, Arsevska E, et al. Modelling practices, data provisioning, sharing and dissemination needs for pandemic decision-making: a European survey-based modellers’ perspective, 2020 to 2022. Eurosurveillance 30(42), 2500216 (2025).
Related WorldPop projects
- Exploring the Seasonality of COVID-19
- Human mobility models to forecast disease dynamics and the effectiveness of public health interventions (MIDAS)
See also
- Covid-19 variants: Five things to know about how coronavirus is evolving in Horizon – The EU Research & Innovation Magazine
- MOnitoring Outbreaks for Disease surveillance in a data science context project website
About Us
The WorldPop research programme, based in the School of Geography and Environmental Sciences at the University of Southampton, is a multi-sectoral team of researchers, technicians and project specialists that produces data on population distributions and characteristics at high spatial resolution.
Initiated in October 2013 to combine The AfriPop Project, AsiaPop and AmeriPop projects, we have a diverse portfolio of projects, including large multi-million-pound collaborative projects with partner organisations, commercial data providers and international development organisations.
