Multiresolution predictive dynamics of COVID-19 risk and intervention effects
Lead Research Organisation:
Imperial College London
Department Name: School of Public Health
Abstract
SARS-CoV2 is a novel virus, and even as new data improves scientific insight, many uncertainties remain about key aspects of transmission. Throughout the pandemic, mathematical and statistical models of COVID-19 have had an important role in the analysis of epidemiological data, in forecasting incidence trends and in assessing the potential impact of different intervention strategies. Models developed by the Imperial College COVID-19 response team have been particularly influential, but the absence of detailed data on transmission patterns have necessitated important assumptions that limit their predictive performance. This project will (a) extend predictive models of transmission trends to include complex spatiotemporal correlation to better capture new seeding events and improve early identification of hotspots of transmission, (b) understand the causal effect of interventions on transmission and the limits to which this inference is possible, (c) systematically collate and analyse data on transmission in specific contexts (households, schools, workplaces and care homes) to derive specific transmission parameter estimates for those settings to be used to improve the ability of models to predict the impact of targeted non pharmaceutical interventions, (d) Understand how important epidemiological parameters are changing with time and what is driving these changes. This work will directly support the Imperial team's input into the UK COVID-19 response via the SPI-M, NERVTAG and SAGE committees and our partnerships with PHE and the Joint Biosecurity Centre (JBC).
Technical Summary
SARS-CoV2 is a novel virus, and even as new data improves scientific insight, many uncertainties
remain about key aspects of transmission. Throughout the pandemic, mathematical and statistical
models of COVID-19 have had an important role in the analysis of epidemiological data, in
forecasting incidence trends and in assessing the potential impact of different intervention
strategies. Models developed by the Imperial College COVID-19 response team have been
particularly influential, but the absence of detailed data on transmission patterns have
necessitated important assumptions that limit their predictive performance. This project will (a)
extend predictive models of transmission trends to include complex spatiotemporal correlation to
better capture new seeding events and improve early identification of hotspots of transmission,
(b) understand the causal effect of interventions on transmission and the limits to which this
inference is possible, (c) systematically collate and analyse data on transmission in specific
contexts (households, schools, workplaces and care homes) to derive specific transmission
parameter estimates for those settings to be used to improve the ability of models to predict the
impact of targeted non pharmaceutical interventions, (d) Understand how important
epidemiological parameters are changing with time and what is driving these changes. This work
will directly support the Imperial team's input into the UK COVID-19 response via the SPI-M,
NERVTAG and SAGE committees and our partnerships with PHE and the Joint Biosecurity Centre
(JBC).
remain about key aspects of transmission. Throughout the pandemic, mathematical and statistical
models of COVID-19 have had an important role in the analysis of epidemiological data, in
forecasting incidence trends and in assessing the potential impact of different intervention
strategies. Models developed by the Imperial College COVID-19 response team have been
particularly influential, but the absence of detailed data on transmission patterns have
necessitated important assumptions that limit their predictive performance. This project will (a)
extend predictive models of transmission trends to include complex spatiotemporal correlation to
better capture new seeding events and improve early identification of hotspots of transmission,
(b) understand the causal effect of interventions on transmission and the limits to which this
inference is possible, (c) systematically collate and analyse data on transmission in specific
contexts (households, schools, workplaces and care homes) to derive specific transmission
parameter estimates for those settings to be used to improve the ability of models to predict the
impact of targeted non pharmaceutical interventions, (d) Understand how important
epidemiological parameters are changing with time and what is driving these changes. This work
will directly support the Imperial team's input into the UK COVID-19 response via the SPI-M,
NERVTAG and SAGE committees and our partnerships with PHE and the Joint Biosecurity Centre
(JBC).
Publications
Ainslie K
(2020)
Evidence of initial success for China exiting COVID-19 social distancing policy after achieving containment
in Wellcome Open Research
Altman G
(2022)
A dataset of non-pharmaceutical interventions on SARS-CoV-2 in Europe.
in Scientific data
Bager P
(2022)
Risk of hospitalisation associated with infection with SARS-CoV-2 omicron variant versus delta variant in Denmark: an observational cohort study.
in The Lancet. Infectious diseases
Brito AF
(2021)
Global disparities in SARS-CoV-2 genomic surveillance.
in medRxiv : the preprint server for health sciences
Brizzi A
(2022)
Spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals.
in Nature medicine
Christensen B
(2022)
Quantifying Changes in Vaccine Coverage in Mainstream Media as a Result of the COVID-19 Outbreak: Text Mining Study.
in JMIR infodemiology
Dabrera G
(2022)
Assessment of mortality and hospital admissions associated with confirmed infection with SARS-CoV-2 Alpha variant: a matched cohort and time-to-event analysis, England, October to December 2020.
in Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin
| Description | The work on this grant has been used to directly inform UK COVID-19 policy via SPI-M, Nervtag and SAGE. The outputs which have not been published have been performed to answer specific scientific questions relevant to the UK government. Outputs from this grant have directly informed the UK COVID-19 response. |
| First Year Of Impact | 2021 |
| Sector | Healthcare,Government, Democracy and Justice |
| Impact Types | Cultural Societal Economic Policy & public services |
| Title | Data from: SARS-CoV-2 antibody dynamics in blood donors and COVID-19 epidemiology in eight Brazilian state capitals |
| Description | The COVID-19 situation in Brazil is complex due to large differences in the shape and size of regional epidemics. Here we tested monthly blood donation samples for IgG antibodies from March 2020 to March 2021 in eight of Brazil's most populous cities. The inferred attack rate of SARS-CoV-2 adjusted for seroreversion in December 2020, before the Gamma VOC was dominant, ranged from 19.3% (95% CrI 17.5% - 21.2%) in Curitiba to 75.0% (95% CrI 70.8% - 80.3%) in Manaus. Seroprevalence was consistently smaller in women and donors older than 55 years. The age-specific infection fatality rate (IFR) differed between cities and consistently increased with age. The infection hospitalisation rate (IHR) increased significantly during the Gamma-dominated second wave in Manaus, suggesting increased morbidity of the Gamma VOC compared to previous variants circulating in Manaus. The higher disease penetrance associated with the health system's collapse increased the overall IFR by a minimum factor of 2.91 (95% CrI 2.43 - 3.53). These results highlight the utility of blood donor serosurveillance to track epidemic maturity and demonstrate demographic and spatial heterogeneity in SARS-CoV-2 spread. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2022 |
| Provided To Others? | Yes |
| URL | http://datadryad.org/stash/dataset/doi:10.5061/dryad.dz08kps08 |
| Title | Governments' Responses to COVID-19 (Response2covid19) |
| Description | The Response2covid19 dataset tracks governments' responses to COVID-19 all around the world. The dataset is at the country-level and covers the January 2020 - June 2021 period; it is updated on a monthly basis. It tracks 20 measures - 13 public health measures and 7 economic measures - taken by 228 governments. The tracking of the measures allows creating an index of the rigidity of public health measures and an index of economic response to the pandemic. The objective of the dataset is both to inform citizens and to help researchers and governments in fighting the pandemic.The dataset can be downloaded and used freely. Please properly cite the name of the dataset ("Response2covid19") and the reference: Porcher, Simon "Response2covid19, a dataset of governments' responses to COVID-19 all around the world", Scientific Data, 7, 423, 2020. https://doi.org/10.1038/s41597-020-00757-y |
| Type Of Material | Database/Collection of data |
| Year Produced | 2022 |
| Provided To Others? | Yes |
| URL | https://www.openicpsr.org/openicpsr/project/119061 |
| Title | Governments' Responses to COVID-19 (Response2covid19) |
| Description | The Response2covid19 dataset tracks governments' responses to COVID-19 all around the world. The dataset is at the country-level and covers the January 2020 - June 2021 period; it is updated on a monthly basis. It tracks 20 measures - 13 public health measures and 7 economic measures - taken by 228 governments. The tracking of the measures allows creating an index of the rigidity of public health measures and an index of economic response to the pandemic. The objective of the dataset is both to inform citizens and to help researchers and governments in fighting the pandemic.The dataset can be downloaded and used freely. Please properly cite the name of the dataset ("Response2covid19") and the reference: Porcher, Simon "Response2covid19, a dataset of governments' responses to COVID-19 all around the world", Scientific Data, 7, 423, 2020. https://doi.org/10.1038/s41597-020-00757-y |
| Type Of Material | Database/Collection of data |
| Year Produced | 2022 |
| Provided To Others? | Yes |
| URL | https://www.openicpsr.org/openicpsr/project/119061/version/V7/view |
| Title | Governments' Responses to COVID-19 (Response2covid19) |
| Description | The Response2covid19 dataset tracks governments' responses to COVID-19 all around the world. The dataset is at the country-level and covers the January-July 2020 period; it is updated on a monthly basis. It tracks 20 measures - 13 public health measures and 7 economic measures - taken by 228 governments. The tracking of the measures allows creating an index of the rigidity of public health measures and an index of economic response to the pandemic. The objective of the dataset is both to inform citizens and to help researchers and governments in fighting the pandemic.The dataset can be downloaded and used freely. Please properly cite the name of the dataset ("Governments' Responses to COVID-19 (Response2covid19)") and the reference: Porcher, Simon "A novel dataset of governments' responses to COVID-19 all around the world", Chaire EPPP 2020-03 discussion paper, 2020. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2020 |
| Provided To Others? | Yes |
| URL | https://www.openicpsr.org/openicpsr/project/119061/version/V5/view?path=/openicpsr/119061/fcr:versio... |
| Title | Governments' Responses to COVID-19 (Response2covid19) |
| Description | The Response2covid19 dataset tracks governments' responses to COVID-19 all around the world. The dataset is at the country-level and covers the January-July 2020 period; it is updated on a monthly basis. It tracks 20 measures - 13 public health measures and 7 economic measures - taken by 228 governments. The tracking of the measures allows creating an index of the rigidity of public health measures and an index of economic response to the pandemic. The objective of the dataset is both to inform citizens and to help researchers and governments in fighting the pandemic.The dataset can be downloaded and used freely. Please properly cite the name of the dataset ("Governments' Responses to COVID-19 (Response2covid19)") and the reference: Porcher, Simon "A novel dataset of governments' responses to COVID-19 all around the world", Chaire EPPP 2020-03 discussion paper, 2020. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2020 |
| Provided To Others? | Yes |
| URL | https://www.openicpsr.org/openicpsr/project/119061/version/V5/view |
| Title | Governments' Responses to COVID-19 (Response2covid19) |
| Description | The Response2covid19 dataset tracks governments' responses to COVID-19 all around the world. The dataset is at the country-level and covers the January-July 2020 period; it is updated on a monthly basis. It tracks 20 measures - 13 public health measures and 7 economic measures - taken by 228 governments. The tracking of the measures allows creating an index of the rigidity of public health measures and an index of economic response to the pandemic. The objective of the dataset is both to inform citizens and to help researchers and governments in fighting the pandemic.The dataset can be downloaded and used freely. Please properly cite the name of the dataset ("Governments' Responses to COVID-19 (Response2covid19)") and the reference: Porcher, Simon "A novel dataset of governments' responses to COVID-19 all around the world", Chaire EPPP 2020-03 discussion paper, 2020. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2020 |
| Provided To Others? | Yes |
| URL | https://www.openicpsr.org/openicpsr/project/119061/version/V5/view?path=/openicpsr/119061/fcr:versio... |
| Title | Governments' Responses to COVID-19 (Response2covid19) |
| Description | The Response2covid19 dataset tracks governments' responses to COVID-19 all around the world. The dataset is at the country-level and covers the January-October 2020 period; it is updated on a monthly basis. It tracks 20 measures - 13 public health measures and 7 economic measures - taken by 228 governments. The tracking of the measures allows creating an index of the rigidity of public health measures and an index of economic response to the pandemic. The objective of the dataset is both to inform citizens and to help researchers and governments in fighting the pandemic.The dataset can be downloaded and used freely. Please properly cite the name of the dataset ("Governments' Responses to COVID-19 (Response2covid19)") and the reference: Porcher, Simon "A novel dataset of governments' responses to COVID-19 all around the world", Chaire EPPP 2020-03 discussion paper, 2020. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2020 |
| Provided To Others? | Yes |
| URL | https://www.openicpsr.org/openicpsr/project/119061/version/V6/view?path=/openicpsr/119061/fcr:versio... |
| Title | Governments' Responses to COVID-19 (Response2covid19) |
| Description | The Response2covid19 dataset tracks governments' responses to COVID-19 all around the world. The dataset is at the country-level and covers the January-October 2020 period; it is updated on a monthly basis. It tracks 20 measures - 13 public health measures and 7 economic measures - taken by 228 governments. The tracking of the measures allows creating an index of the rigidity of public health measures and an index of economic response to the pandemic. The objective of the dataset is both to inform citizens and to help researchers and governments in fighting the pandemic.The dataset can be downloaded and used freely. Please properly cite the name of the dataset ("Governments' Responses to COVID-19 (Response2covid19)") and the reference: Porcher, Simon "A novel dataset of governments' responses to COVID-19 all around the world", Chaire EPPP 2020-03 discussion paper, 2020. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2020 |
| Provided To Others? | Yes |
| URL | https://www.openicpsr.org/openicpsr/project/119061/version/V6/view |
| Title | Governments' Responses to COVID-19 (Response2covid19) |
| Description | The Response2covid19 dataset tracks governments' responses to COVID-19 all around the world. The dataset is at the country-level and covers the January-October 2020 period; it is updated on a monthly basis. It tracks 20 measures - 13 public health measures and 7 economic measures - taken by 228 governments. The tracking of the measures allows creating an index of the rigidity of public health measures and an index of economic response to the pandemic. The objective of the dataset is both to inform citizens and to help researchers and governments in fighting the pandemic.The dataset can be downloaded and used freely. Please properly cite the name of the dataset ("Governments' Responses to COVID-19 (Response2covid19)") and the reference: Porcher, Simon "A novel dataset of governments' responses to COVID-19 all around the world", Chaire EPPP 2020-03 discussion paper, 2020. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2020 |
| Provided To Others? | Yes |
| URL | https://www.openicpsr.org/openicpsr/project/119061/version/V6/view?path=/openicpsr/119061/fcr:versio... |
| Title | Governments' Responses to COVID-19 (Response2covid19) |
| Description | The Response2covid19 dataset tracks governments' responses to COVID-19 all around the world. The dataset is at the country-level and covers the January-October 2020 period; it is updated on a monthly basis. It tracks 20 measures - 13 public health measures and 7 economic measures - taken by 228 governments. The tracking of the measures allows creating an index of the rigidity of public health measures and an index of economic response to the pandemic. The objective of the dataset is both to inform citizens and to help researchers and governments in fighting the pandemic.The dataset can be downloaded and used freely. Please properly cite the name of the dataset ("Governments' Responses to COVID-19 (Response2covid19)") and the reference: Porcher, Simon "A novel dataset of governments' responses to COVID-19 all around the world", Chaire EPPP 2020-03 discussion paper, 2020. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2020 |
| Provided To Others? | Yes |
| URL | https://www.openicpsr.org/openicpsr/project/119061/version/V6/view?path=/openicpsr/119061/fcr:versio... |
| Description | Omicron severity |
| Organisation | The Statens Serum Institute (SSI) |
| Country | Denmark |
| Sector | Public |
| PI Contribution | Evaluation of data relating to Omicron severity |
| Collaborator Contribution | Provision of data |
| Impact | Paper under review in Lancet Infectious Disease |
| Start Year | 2021 |
| Description | Scientific Advisory Group for Emergencies (SAGE) |
| Organisation | Government of the UK |
| Department | Scientific Advisory Group for Emergencies (SAGE) |
| Country | United Kingdom |
| Sector | Public |
| PI Contribution | As part of SAGE, this grant was instrumental in the UK unlocking roadmap https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/963440/S1129__Unlocking__Roadmap_Scenarios_for_England_.pdf As part of SAGE, documents were published on the UK strategy for vaccinations and the removal of NPIs https://www.gov.uk/government/publications/imperial-college-london-strategies-for-gradually-lifting-npis-in-parallel-to-covid-19-vaccine-roll-out-in-the-uk-4-february-2021 https://www.gov.uk/government/publications/imperial-college-london-potential-profile-of-the-covid-19-epidemic-in-the-uk-under-different-vaccination-roll-out-strategies-13-january-2021 |
| Collaborator Contribution | Data and advisory expertise |
| Impact | https://www.gov.uk/government/publications/imperial-college-london-potential-profile-of-the-covid-19-epidemic-in-the-uk-under-different-vaccination-roll-out-strategies-13-january-2021 https://www.gov.uk/government/publications/imperial-college-london-strategies-for-gradually-lifting-npis-in-parallel-to-covid-19-vaccine-roll-out-in-the-uk-4-february-2021 https://www.gov.uk/government/publications/imperial-college-london-unlocking-roadmap-scenarios-for-england-18-february-2021 |
| Start Year | 2021 |
| Description | Branching processes for infectious diseases |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Professional Practitioners |
| Results and Impact | This was a talk in collaboration with Oxford Big data institute, statistics and computer science. |
| Year(s) Of Engagement Activity | 2022 |
| URL | https://www.stats.ox.ac.uk/events/joint-statistics-computer-science-bdi-talk-24th-feb-2022/ |
| Description | EPQ Centre Supervisor - Talk to A-Level Students |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Schools |
| Results and Impact | I was invited to give a talk about research experience and the joys of working in academia. I gave a talk around advice for a career in academia |
| Year(s) Of Engagement Activity | 2021 |
| Description | NNF Data Science Talk about Understanding cause and effect through data science and novel biomedical data sources |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Professional Practitioners |
| Results and Impact | This was a key note speech on the topic of causality in biomedical research |
| Year(s) Of Engagement Activity | 2021 |