COVID-19 research with ongoing local and international impact
A Te Herenga Waka—Victoria University of Wellington researcher has been awarded funding from the Ministry of Health for a project that will improve current and future COVID-19 responses and vaccination programmes.
Internationally-recognised epidemiologist and Associate Dean—Research and Innovation Colin Simpson from the Wellington Faculty of Health—Te Wāhanga Tātai Hauora has won a Ministry of Health RFP for an evaluation of Aotearoa’s COVID-19 vaccination programme - the COVE project.
Professor Simpson will be the Primary Investigator (PI) for the project which will use data analysis to inform improvements to current and future vaccination programmes, and seek to provide better access and care, particularly for the country’s most vulnerable populations.
The COVE project is aligned with the National Immunisation Programme and includes collaborators ESR, Massey University, Precision Data Ltd, and iNZight Analytics Ltd. The project seeks to inform improvements in vaccination coverage, effectiveness, and equity in the context of rapidly changing infection epidemiology and emerging viral variants. The project will look at creating new ways for the timely use and reporting of linked data in Aotearoa.
The COVE project is co-led by Māori biostatistician Andrew Sporle (Ngāti Apa, Rangitāne, Te Rarawa) from iNZight Analytics, and includes a focus on Māori health access, quality, and outcomes, using robust Māori data that builds on work currently underway by Māori data scientists.
Professor Simpson will also be a co-investigator for another project, led by the University of Otago, which will further investigate and describe the epidemiology of the COVID-19 pandemic and its impacts.
This follows on the back of a successful HRC-funded project Professor Simpson led last year which will also continue to inform responses to infectious diseases in the future.
The project, Predict and Prevent COVID-19: a data driven innovation project, which featured in a case study in the Ministry of Business, Innovation, and Employment’s COVID-19 Research Response Report 2022 published last month, used advanced data science methods to improve understanding of how infectious diseases can move through a population.
The team undertook modelling work to understand the possible impact of Covid-19 on the Aotearoa New Zealand population (including Māori and Pasifika populations). Under a scenario with an effective vaccine and the Covid-19 Delta variant, the project found that very high uptake amongst most age groups was required to prevent outbreak (a population immunity threshold).
Higher vaccination rates with a strategy of targeting high risk groups (older ages) leads to lower rates of peak hospitalisations and deaths. A strategy to target younger age groups to minimise the spread of disease leads to lower cases.
Genomic sequencing of COVID-19 cases has been a key tool in Aotearoa's COVID response, Professor Simpson says.
“The work done with this grant helped us to interpret the data from genomic sequencing in real time so that it could rapidly inform the public health response.”
“We have developed and refined methods to link cases to clusters, monitor how many cases are coming across the border, uncover cryptic chains of transmission, and track how fast the virus is spreading in the community. The tools and techniques developed here are being used in the ongoing fight against COVID-19 and can be applied to other virus infections such as influenza.”
“We created new approaches to use genomic data to understand the spread of this disease through the population and incorporate new data in near real-time,” Professor Simpson says. “We also used detailed human movement and location data to independently model the structure of the population.”
Professor Simpson says surveillance of infectious disease (genomic and forecast modelling) is a rapidly growing area that has been accelerated by the pandemic.
“The knowledge gained here indicates that real-time genomic surveillance and infectious disease forecasting can be practical and useful for a wide range of infectious disease outbreaks, and the tools for rapid analysis, inference and visualisation need further development to improve scale, precision, and automation.”
The results were well received internationally, including a paper published in Nature Communications (with an Altmetric score of 2251 - top 5% of all outputs), and another paper on Covid-19 modelling published in Lancet Regional Western Pacific, listed as one of the journal’s most-read.
The team worked closely with the Ministry of Health and Government policy makers throughout the Covid-19 pandemic to ensure their findings were broadly understood and had maximum health impact. The results also featured widely in national media.
The University team included data science machine learning expert Dr Binh Nguyen from the School of Economics and Finance, and Professor of Network Engineering in the School of Engineering and Computer Science, Winston Seah.
The research was a collaboration with the University of Auckland, University of Otago, Massey University and ESR, and also drew upon Māori Data Science experts (Andrew Sporle) and expertise from industry (iNZight Analytics Ltd.).
The funding was from the HRC’s Emerging Infectious Diseases Grant established to address New Zealand’s evidence needs in relation to COVID-19, while also contributing to global efforts.