Publications

We regularly publish high-quality and influential research in top peer-reviewed journals

Our publications

SHINE research seeks to synthesise techniques from epidemiology, mathematics, and data science to conduct sophisticated simulation modelling analyses of public health interventions. Our research efforts are broadly grouped into five themes: SHINE infrastructure, COVID-19 modelling, dietary modelling, tobacco modelling, and housing modelling.  Explore publications relevant to each theme below.

Our research

Theme 1: SHINE Infrastructure

This research theme comprises all publications that have contributed to the development of the general ecosystem of SHINE simulation modelling: from the proportional multistate lifetable (PMSLT) simulation modelling framework, to input data used in simulation models, to end-user tools that visualise and compare results of health interventions.

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(1.1) Comparing health gains, costs and cost-effectiveness of 100s of interventions in Australia and New Zealand: an online interactive league table

This study compares the health gains, costs, and cost-effectiveness of hundreds of Australian and New Zealand (NZ) health interventions conducted with comparable methods in an online interactive league table designed to inform policy (ANZ-HILT).

Carvalho, Natalie, et al. "Comparing health gains, costs and cost-effectiveness of 100s of interventions in Australia and New Zealand: an online interactive league table." Population health metrics 20.1 (2022): 1-10.

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(1.2) Proportional multistate lifetable modelling of preventive interventions: concepts, code and worked examples

This tutorial-style methodology paper explains how SHINE proportional multistate lifetable (PMSLT) modelling quantifies intervention impacts, using comparisons between three tobacco control case studies [eradication of tobacco, tobacco-free generation i.e. the age at which tobacco can be legally purchased is lifted by 1 year of age for each calendar year) and tobacco tax].

Blakely, Tony, et al. "Proportional multistate lifetable modelling of preventive interventions: concepts, code and worked examples." International journal of epidemiology 49.5 (2020): 1624-1636.

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(1.3) Disease-related income and economic productivity loss in New Zealand: A longitudinal analysis of linked individual-level data

This study estimates individual-level income loss for 40 conditions simultaneously by phase of diagnosis, and the total income loss at the population level (a function of how common the disease is and the individual-level income loss if one has the disease). These inputs feed into SHINE simulation modelling to generate productivity estimates for simulated interventions.

Blakely, Tony, et al. "Disease-related income and economic productivity loss in New Zealand: A longitudinal analysis of linked individual-level data." PLoS medicine 18.11 (2021): e1003848.

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(1.4) Disaggregating proportional multistate lifetables by population heterogeneity to estimate intervention impacts on inequalities

Simulation models can be used to quantify the projected health impact of interventions. Quantifying heterogeneity in these impacts, for example by socioeconomic status, is important to understand impacts on health inequalities. This study develops the heterogeneity disaggregation algorithm used in SHINE modelling, that iteratively rescales mortality, incidence and case-fatality rates by time-step of the model to ensure correct total population counts were retained at each step.

Andersen, Patrick, et al. "Disaggregating proportional multistate lifetables by population heterogeneity to estimate intervention impacts on inequalities." Population health metrics 20.1 (2022): 1-17.

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(1.5) Health system costs for individual and comorbid noncommunicable diseases: An analysis of publicly funded health events from New Zealand

The objective of this study was to use statistical methods to disaggregate all publicly funded health expenditure by disease, disease phase, and comorbidities. SHINE modelling implements these relativities by disease phase to disaggregate Australian and other country disease expenditure for inputting to PMSLT modelling.

Blakely, Tony, et al. "Health system costs for individual and comorbid noncommunicable diseases: An analysis of publicly funded health events from New Zealand." PLoS medicine 16.1 (2019): e1002716.

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Theme 2: COVID-19 Modelling

This research theme comprises applications of our simulation modelling to the COVID-19 pandemic in Australia, and internationally. Research efforts in this sphere have occurred in collaboration with various government and private organisations, both domestically and abroad. These efforts are developed simultaneously with our online pandemic trade-offs interactive tools to visualise and communicate key modelling results.

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(2.1) An integrated epidemiologic and economic model to assess optimal COVID-19 pandemic policy (preprint)

This study employs an agent-based model to estimate morbidity, mortality, and costs over 18 months from 1 April 2022 for for 44 policy packages (two levels of stringency of public health and social measures [PHSMs]; providing respirators during infection surges; 11 vaccination schedules of current and next-generation vaccines), and across 64 future SARS-CoV-2 variants (combinations of transmissibility, virulence, immune escape, and incursion date). Policies were ranked on cost-effectiveness (health system only and health system plus GDP perspectives), deaths and days exceeding hospital occupancy thresholds.

Szanyi, Joshua, et al. "An integrated epidemiologic and economic model to assess optimal COVID-19 pandemic policy." medRxiv (2022).

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(2.2) A log-odds system for waning and boosting of COVID-19 vaccine effectiveness

This study describes a log odds system for generating vaccine effectiveness by number of doses, time since last dose, and severity (i.e. protection against any infection through to death). This method is at the heart of our recent SHINE-COVID-19 policy modelling:

Szanyi, Joshua, et al. "A log-odds system for waning and boosting of COVID-19 vaccine effectiveness." Vaccine (2022).

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(2.3) The health impact of long COVID during the 2021-2022 Omicron wave in Australia: a quantitative burden of disease study (preprint)

This study quantifies the morbidity (years lived with disability; YLDs) of long COVID in Australia during the 2021-2022 Omicron BA.1/BA.2 wave, with an aim to compare long COVID YLDs with: acute SARS-CoV-2 infection YLDs; years of life lost (YLLs) from SARS-CoV-2; and health loss from other diseases.

Howe, Samantha, et al. "The health impact of long COVID during the 2021-2022 Omicron wave in Australia: a quantitative burden of disease study." medRxiv (2022).

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(2.4) 2022 will be better: COVID-19 Pandemic Tradeoffs modelling (report)

This study employs an agent-based model to simulate virus transmission, and assess how it varies with factors we cannot control, such as the true reproductive rate (R0) of the virus, and factors we can at least partially control, such as our public-health response. 

Blakely, Tony, et al. "2022 will be better: COVID-19 Pandemic Tradeoffs Modelling". Population Interventions Unit, Melbourne School of Population and Global Health.

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(2.5) Association of Simulated COVID-19 Policy Responses for Social Restrictions and Lockdowns With Health-Adjusted Life-Years and Costs in Victoria, Australia

This study analyses 4 policy responses to the COVID-19 pandemic (aggressive elimination, moderate elimination, tight suppression, and loose suppression) n the state of Victoria, Australia, to identify the policy response with the least health losses and is the most cost-effective of.

Blakely, Tony, et al. "Association of Simulated COVID-19 Policy Responses for Social Restrictions and Lockdowns With Health-Adjusted Life-Years and Costs in Victoria, Australia." JAMA Health Forum. Vol. 2. No. 7. American Medical Association, 2021.

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(2.6) The probability of the 6-week lockdown in Victoria (commencing 9 July 2020) achieving elimination of community transmission of SARS-CoV-2

This study estimates the probability of achieving elimination of community transmission of COVID-19, in Victoria, Australia. This study was pivotal in strengthening the case for Australasia to follow an elimination strategy in 2020:

Blakely, Tony, et al. "The probability of the 6‐week lockdown in Victoria (commencing 9 July 2020) achieving elimination of community transmission of SARS‐CoV‐2." Medical Journal of Australia 213.8 (2020): 349-351.

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Theme 3: Diet

This research theme encompasses our extensive research efforts with dietary modelling in New Zealand, Australia, and the United Kingdom. The next generation of SHINE modelling with extend these analyses in collaboration with other research groups.

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(3.1) The effect of food taxes and subsidies on population health and health costs: a modelling study

This study estimates the health and cost impacts of various food taxes and subsidies in New Zealand, and summarises a large body of NZ work in the Burden of Disease Epidemiology, Equity and Cost-Effectiveness Program (BODE3) on food taxes and subsidies, propagated through PMSLT modelling to quantify health gains and costs:

Blakely, Tony, et al. "The effect of food taxes and subsidies on population health and health costs: a modelling study." The Lancet Public Health 5.7 (2020): e404-e413.

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(3.2) The impact of voluntary front-of-pack nutrition labelling on packaged food reformulation: A difference-in-differences analysis of the Australasian Health Star Rating scheme

Front-of-pack nutrition labelling (FoPL) of packaged foods can promote healthier diets. Australia and New Zealand (NZ) adopted the voluntary Health Star Rating (HSR) scheme in 2014. This study estimates the impact of voluntary adoption of health star rating (HSR) on food reformulation relative to unlabelled foods and examined differential impacts for more-versus-less healthy foods.

Jones, Alexandra, et al. "The performance and potential of the Australasian Health Star Rating system: a four‐year review using the RE‐AIM framework." Australian and New Zealand journal of public health 43.4 (2019): 355-365.

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Theme 4: Tobacco

This research theme encompasses the applications of our proportional multistate lifetable (PMSLT) simulation modelling framework to tobacco interventions in New Zealand. Research in this domain has occurred in collaboration with international government agencies, and is currently being adapted to different countries.

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(4.1) Tobacco endgame intervention impacts on health gains and Māori:non-Māori health inequity: a simulation study of the Aotearoa-New Zealand Tobacco Action Plan

This study  seeks to estimate the health gains and Māori:non-Māori health inequality reductions of the Aotearoa/New Zealand Government’s proposed endgame strategy, reporting on modelling commissioned by the NZ Government of forecast heath gains and health inequality impacts of the world-leading Aotearoa New Zealand tobacco endgame strategy (denicotinising tobacco, massive reductions in retail, tobacco-free generation).

Ouakrim, Driss Ait, et al. "Tobacco endgame intervention impacts on health gains and Māori: non-Māori health inequity: a simulation study of the Aotearoa-New Zealand Tobacco Action Plan." medRxiv (2022).

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(4.2) Impact of tax and tobacco-free generation on health-adjusted life years in the Solomon Islands: a multistate life table simulation

This study represents a ‘proof of principle’, applying tobacco PMSLT modelling to the Solomon Islands, drawing on Global Burden of Disease data – an example of ‘scaling out’ in SHINE. In this study, we seek to estimate health-adjusted life years (HALY) gained in the Solomon Islands for the 2016 population over the remainder of their lives, for three interventions: hypothetical eradication of cigarettes; 25% annual tax increases to 2025 such that tax represents 70% of sales price of tobacco; and a tobacco-free generation (TFG).

Singh, Ankur, et al. "Impact of tax and tobacco-free generation on health-adjusted life years in the Solomon Islands: a multistate life table simulation." Tobacco Control 29.4 (2020): 388-397.

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(4.3) Potential Country-level Health and Cost Impacts of Legalizing Domestic Sale of Vaporized Nicotine Products

This study presents an application of PMSLT modelling to e-cigarette liberalisation in New Zealand. In this study, we seek to estimate the net impact on population health and health system costs of vaporised nicotine products. We model, with uncertainty, the health and cost impacts of liberalising the vaporised nicotine market for a high-income country, New Zealand (NZ).

Petrovic-van der Deen, Frederieke S., et al. "Potential country-level health and cost impacts of legalizing domestic sale of vaporized nicotine products." Epidemiology 30.3 (2019): 396-404.

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(4.4) Simulating future public health benefits of tobacco control interventions: a systematic review of models

This study presents a critique of existing tobacco intervention modelling, thereby identifying the criteria we look for in robust and comparable modelling. We applied a Medline search with keywords intersecting modelling and tobacco, and undertook a systematic review of tobacco intervention simulation models to assess model structure and input variations that may render model outputs non-comparable.

Singh, Ankur, Nick Wilson, and Tony Blakely. "Simulating future public health benefits of tobacco control interventions: a systematic review of models." Tobacco Control 30.4 (2021): 460-470.

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Theme 5: Housing

This research theme encompasses applications of our proportional multistate lifetable (PMSLT) simulation modelling framework to housing interventions domestically, and abroad. Research in this domain has occurred in collaboration with the Healthy Housing CRE.

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(5.1) The Health Gains and Cost Savings of Eradicating Cold Housing in Australia (preprint)

This study applies the SHINE proportional multistate lifetable (PMSLT) simulation modelling framework to estimate the health, health inequality, health expenditure and income impacts of lifting the temperature in living areas of the home to 18 degrees Celsius in cold homes in the south-eastern States of Australia (N= 17 million).

Mishra, Shiva Raj, et al. "The Health Gains and Cost Savings of Eradicating Cold Housing in Australia." Available at SSRN 4165606.

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