Objective To compare 50-year forecasts of Australian tobacco smoking rates in relation to trends in smoking initiation and cessation and in relation to a national target of ≤5% adult daily prevalence by 2030. Methods A compartmental model of Australian population daily smoking, calibrated to the observed smoking status of 229 523 participants aged 20–99 years in 26 surveys (1962–2016) by age, sex and birth year (1910–1996), estimated smoking prevalence to 2066 using Australian Bureau of Statistics 50-year population predictions. Prevalence forecasts were compared across scenarios in which smoking initiation and cessation trends from 2017 were continued, kept constant or reversed. Results At the end of the observation period in 2016, model-estimated daily smoking prevalence was 13.7% (90% equal-tailed interval (EI) 13.4%–14.0%). When smoking initiation and cessation rates were held constant, daily smoking prevalence reached 5.2% (90% EI 4.9%–5.5%) after 50 years, in 2066. When initiation and cessation rates continued their trajectory downwards and upwards, respectively, daily smoking prevalence reached 5% by 2039 (90% EI 2037–2041). The greatest progress towards the 5% goal came from eliminating initiation among younger cohorts, with the target met by 2037 (90% EI 2036–2038) in the most optimistic scenario. Conversely, if initiation and cessation rates reversed to 2007 levels, estimated prevalence was 9.1% (90% EI 8.8%–9.4%) in 2066. Conclusion A 5% adult daily smoking prevalence target cannot be achieved by the year 2030 based on current trends. Urgent investment in concerted strategies that prevent smoking initiation and facilitate cessation is necessary to achieve 5% prevalence by 2030.

Background Aotearoa-New Zealand (A/NZ) is the first country to pass a comprehensive commercial tobacco endgame strategy into law. Key components include the denicotinisation of smoked tobacco products and a major reduction in tobacco retail outlets. Understanding the potential long-term economic impacts of these measures is important for government planning. Methods A tobacco policy simulation model that evaluated the health impacts of the A/NZ Smokefree Action Plan was extended to evaluate the economic effect of the new measures from both Government and citizen perspectives. Estimates were discounted at 3% per annum and presented in 2021 purchasing power parities US$. Findings The modelled endgame policy package generates considerable growth in income for the A/NZ population with a total cumulative gain by 2050 amounting to US$31 billion. From a government perspective, the policy results in foregone tobacco excise tax revenue with a negative net financial position estimated at US$11.5 billion by 2050. In a sensitivity analysis considering future changes to labour workforce, the government’s cumulative net position remained negative by 2050, but only by US$1.9 billion. Interpretation Our modelling suggests the Smokefree Aotearoa 2025 Action Plan is likely to produce substantial economic benefits for the A/NZ population, and modest impacts on government revenue and expenditure related to the reduction in tobacco tax and increases in aged pensions due to increased life expectancy. Such costs can be anticipated and planned for and might be largely offset by future increases in labour force and the proportion of 65+ year olds working in the formal economy. Funding This study was funded by a grant from the Australian National Health and Medical Research Council (GNT1198301) Evidence before this study Multiple countries have set targets to achieve a commercial tobacco endgame. Most simulation modelling studies have evaluated ‘traditional’ tobacco control interventions (e.g., tobacco excise tax increases, indoor smoking bans, smoking cessation health services). Very few have modelled the economic effects of endgame strategies. We searched PubMed with no language restrictions for articles published from 1 January 2000 to 8 February 2023 using the following search terms: (smoking[TW] OR tobacco[TW]) AND (endgame[TW] OR eliminat*[TW] OR “phasing out”[TW] OR “phase out”[TW] OR aboli*[TW] OR prohibit*[TW] OR ban[TW] OR “smoke free”[TW] OR “smoke-free”[TW]) AND (model*[TW] OR simulat*[TW]) AND (cost[TW] OR economic[TW]). We identified six economic evaluations of commercial tobacco endgame strategies, including different interventions and cost perspectives. Five studies modelled interventions in the Aotearoa/New Zealand (A/NZ) context and one in the UK. Four studies were conducted from a healthcare system perspective, estimating the costs to the health system associated with tobacco-related diseases. One of these studies additionally estimated ‘non-health social costs’, as the productivity loss resulting from smoking-associated morbidity and mortality. Another study estimated the cost to consumers resulting from a policy in which retail outlets selling tobacco were significantly reduced, considering both the actual cost of a pack of cigarettes and the cost of increased travel to retailers, and the last estimated excise tax revenue to the government resulting from increases to tobacco taxation (compared to no increases to current tobacco tax levels). Of the identified literature, none evaluated the effect of endgame strategies on citizen income nor the fiscal impacts to government revenue and expenditure. Added value of this study This study evaluates the economic impacts of a recently introduced commercial tobacco endgame legislation in A/NZ. We modelled the economic impacts by 2050 of a policy package that includes the four key measures in the new legislation (i.e., denicotinisation of smoked tobacco products, enhanced antismoking mass media campaigns, 90% reduction in the number of tobacco retail outlets, and a smoke-free generation law that bans sale of tobacco to anyone born after 2008). The analysis presents both a government and citizen perspective. The government fiscal impacts extend beyond health system expenditure to also include differences between business as usual (BAU) – i.e., no endgame strategy – and endgame scenarios in excise tax revenue, goods and services tax (GST) revenue, income tax revenue, and superannuation expenditure. A net government position is also calculated. The citizen perspective estimates the impact of the policy on population income and savings that may result from reduced tobacco consumption. Our model projects large economic gains for consumers from the tobacco endgame package resulting from a sharp reduction in smoking prevalence, morbidity and mortality. For the A/NZ Government, the policy is projected to result in reduced healthcare costs, and increased income tax and GST revenue. These gains are offset by increased superannuation payments resulting from a greater number of individuals living past the age at which superannuation is provided to all citizens (65 years in A/NZ and described in this article as “retirement age” for simplicity), as well as large reductions in excise tax revenue. Implication of all the available evidence Our findings support previous evidence indicating that ambitious tobacco control policies can produce large heath and economic benefits. Our model suggests that a commercial tobacco endgame strategy is likely to result in a large revenue transfer to the benefit of the A/NZ population. An endgame approach moves beyond the BAU model of incremental policy change to a deliberate strategy to permanently reduce tobacco smoking to minimal levels within a short timeframe. A logical result of such a strategy is a significant decrease in excise tax revenue for governments. Under the endgame scenario, the net position of the A/NZ Government is likely to be negative due mainly to the foregone excise tax revenue. In a sensitivity analysis of the endgame scenario that takes into account recent projections from Stats NZ of a future larger and older labour force in A/NZ, our model suggests that the net government position might become positive as early as 2036 – less than 15 years after the introduction of the endgame policy. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This study was funded by a grant from the Australia National Health and Medical Research Council (GNT1198301) ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors

Aim We aimed to combine Global Burden of Disease (GBD) Study data and local data to identify the highest priority intervention domains for preventing cardiovascular disease (CVD) in the case study country of Aotearoa New Zealand (NZ). Methods Risk factor data for CVD in NZ were extracted from the GBD using the “GBD Results Tool.” We prioritized risk factor domains based on consideration of the size of the health burden (disability-adjusted life years [DALYs]) and then by the domain-specific interventions that delivered the highest health gains and cost-savings. Results Based on the size of the CVD health burden in DALYs, the five top prioritized risk factor domains were: high systolic blood pressure (84,800 DALYs; 5400 deaths in 2019), then dietary risk factors, then high LDL cholesterol, then high BMI and then tobacco (30,400 DALYs; 1400 deaths). But if policy-makers aimed to maximize health gain and cost-savings from specific interventions that have been studied, then they would favor the dietary risk domain (e.g., a combined fruit and vegetable subsidy plus a sugar tax produced estimated lifetime savings of 894,000 health-adjusted life years and health system cost-savings of US$11.0 billion; both 3% discount rate). Other potential considerations for prioritization included the potential for total health gain that includes non-CVD health loss and potential for achieving relatively greater per capita health gain for Māori (Indigenous) to reduce health inequities. Conclusions We were able to show how CVD risk factor domains could be systematically prioritized using a mix of GBD and country-level data. Addressing high systolic blood pressure would be the top ranked domain if policy-makers focused just on the size of the health loss. But if policy-makers wished to maximize health gain and cost-savings using evaluated interventions, dietary interventions would be prioritized, e.g., food taxes and subsidies.

Objectives The objective of this longitudinal analysis was to estimate funding loss in terms of tax revenue to the New Zealand (NZ) government from disease and injury among working age adults. Methods Linked national health and tax data sets of the usually resident population between 2006 and 2016 were used to model 40 disease states simultaneously in a fixed-effects regression analysis to estimate population-level tax loss from disease and injury. To estimate tax revenue loss to the NZ government, we modeled a counterfactual scenario where all disease/injury was cause deleted. Results The estimated tax paid by all 25- to 64-year-olds in the eligible NZ population was $15 773 million (m) per annum (US dollar 2021), or $16 446 m for a counterfactual as though no one had any disease disease-related income loss (a 4.3% or $672.9 m increase in tax revenue per annum). The disease that—if it had no impact on income—generated the greatest impact was mental illness, contributing 34.7% ($233.3 m) of all disease-related tax loss, followed by cardiovascular (14.7%, $99.0 m) and endocrine (10.2%, $68.8 m). Tax revenue gains after deleting all disease/injury increased up to 65 years of age, with the largest contributor occurring among 60- to 64-year-olds ($131.7 m). Varied results were also observed among different ethnicities and differing levels of deprivation. Conclusions This study finds considerable variation by disease on worker productivity and therefore tax revenue in this high-income country. These findings strengthen the economic and government case for prevention, particularly the prevention of mental health conditions and cardiovascular disease.

Background: Cold indoor temperature (<18 C) is associated with hypertension-related and respiratory disease, depression, and anxiety. We estimate total health, health expenditure and income impacts of permanently lifting the temperature in living areas of the home to 18 C in cold homes in South-eastern Australia (N = 17 million). Methods: A proportional multistate lifetable model was used to estimate health adjusted life years (HALYs), health expenditure and income earnings, over the remainder of the lifespan of the population alive in 2021 (3% discount rate). Multiple data were integrated including the prevalence of cold housing (5.87%; mean temperature 15 C), the effect of temperature to hypertension-related, respiratory disease, depression and anxiety. Findings: Eradicating cold housing was predicted to lead to 89,600 (95% UI 47,700 to 177,000) lifetime HALYs gained over the population's remaining lifespan, nearly half of which occurred from 2021 to 2040. Respiratory disease (32.4%) and mental illness (60.6%) made large contributions to HALYs gained, but also had large uncertainty (95% UI 30.0%-42.9% and 45.1%-64.6%, respectively) due to uncertain estimates of their magnitude of causal association with cold housing. Health gains per capita were 6.1 times greater (95% UI 4.7 to 8.1) among the most compared to least deprived quintile. From 2021 to 2040, health expenditure decreased by AUD$0.87 billion (0.35-1.98) and income earnings increased by AUD$4.35 billion (1.89-9.81). Interpretation: Eliminating cold housing would lead to substantial health gains, reductions in health inequalities, savings in health expenditure, and productivity gains. Next steps require research to reduce uncertainty about the magnitude of causal associations of cold with mental and respiratory health.

A bstract Background Identifying optimal COVID-19 policies is challenging. For Victoria, Australia (6.6 million people), we evaluated 104 policy packages (two levels of stringency of public health and social measures [PHSMs], by two levels each of mask-wearing and respirator provision during large outbreaks, by 13 vaccination schedules) for nine future SARS-CoV-2 variant scenarios. Methods We used an agent-based model to estimate morbidity, mortality, and costs over 12 months from October 2022 for each scenario. The 104 policies (each averaged over the nine future variant scenarios) were ranked based on four evenly weighted criteria: cost-effectiveness from (a) health system only and (b) health system plus GDP perspectives, (c) deaths and (d) days exceeding hospital occupancy thresholds. Findings More compared to less stringent PHSMs reduced cumulative infections, hospitalisations and deaths but also increased time in stage ≥3 PHSMs. Any further vaccination from October 2022 decreased hospitalisations and deaths by 12% and 27% respectively compared to no further vaccination and was usually a cost-saving intervention from a health expenditure plus GDP perspective. High versus low vaccine coverage decreased deaths by 15% and reduced time in stage ≥3 PHSMs by 20%. The modelled mask policies had modest impacts on morbidity, mortality, and health system pressure. The highest-ranking policy combination was more stringent PHSMs, two further vaccine doses (an Omicron-targeted vaccine followed by a multivalent vaccine) for ≥30-year-olds with high uptake, and promotion of increased mask wearing (but not Government provision of respirators). Interpretation Ongoing vaccination and PHSMs continue to be key components of the COVID-19 pandemic response. Integrated epidemiologic and economic modelling, as exemplified in this paper, can be rapidly updated and used in pandemic decision making. Funding Anonymous donation, University of Melbourne funding. A bstract Background Identifying optimal COVID-19 policies is challenging. For Victoria, Australia (6.6 million people), we evaluated 104 policy packages: (a) two levels of stringency of public health and social measures (PHSMs; lower, higher), by (b) two levels each of mask wearing (low, high) and Government respirator provision (nil, yes) during large outbreaks (defined as when the projected number of people in hospital reached >270 or >130 per million population for lower and higher stringency PHSM settings respectively), by (c) 13 vaccination schedules (nil, and four combinations of low/high coverage for ≥30/60-year-olds, each with an Omicron-targeted (OT) booster in the last quarter of 2022 followed by one of: nil, another OT booster in the second quarter of 2023, or a multivalent booster in the second quarter of 2023). These policies were modelled in the setting of nine future SARS-CoV-2 variant scenarios (no major new variant of concern and one of eight variants arriving in November 2022 with different virulence, antigenic, and immune escape profiles). Methods We used an agent-based model to estimate morbidity, mortality, and costs over 12 months from October 2022 for each scenario. The 104 policies (each averaged over the nine future variant scenarios) were ranked based on four evenly weighted criteria: cost-effectiveness from (a) health system only and (b) health system plus GDP perspectives (HALYs valued at AUD 70,000; discount rate 3%), (c) deaths and (d) days exceeding hospital occupancy thresholds. Findings More compared to less stringent PHSMs reduced cumulative infections, hospitalisations and deaths by an average of 25%, 24% and 24% respectively across 468 policy comparisons (other policy and variant scenarios held constant), but also increased time in stage ≥3 (out of 5) PHSMs by an average of 42 days (23 days for low virulence and 70 days for high virulence variants). Any further vaccination from October 2022 decreased hospitalisations and deaths by 12% and 27% respectively compared to no further vaccination, however the cumulative number of infections increased by 10% due to vaccination preferentially decreasing hospitalisation rates that were used to dynamically set PHSM stages. Any further vaccination was of marginal cost-effectiveness from a health system perspective (an average of AUD 77,500 per HALY gained for vaccinating ≥60-year-olds, and AUD 41,600 for 30- to 59-year-olds incremental to ≥60-year-olds), but vaccination also resulted in 36% fewer days in Stage ≥3 PHSMs usually making it a cost-saving intervention from a health expenditure plus GDP perspective. High versus low vaccine coverage reduced deaths by 15% and reduced time in Stage ≥3 PHSMs by 20%. Promotion to increase mask wearing or government provision of respirators during large outbreaks reduced cumulative infections, hospitalisations and deaths over the 12 months by 1% to 2%, and reduced days with hospital occupancy exceeding 750 COVID-19 patients by 2% (4% to 5% in the context of highly virulent variants). The highest-ranking policy combination was more stringent PHSMs, two further vaccine doses (an Omicron-targeted vaccine followed by a multivalent vaccine) for ≥30-year-olds with high uptake, and promotion of increased mask wearing (but not Government provision of respirators). Interpretation Ongoing vaccination and PHSMs continue to be key components of the COVID-19 pandemic response. Integrated epidemiologic and economic modelling, as exemplified in this paper, can be rapidly updated and used in pandemic decision making. Funding Anonymous donation, University of Melbourne funding. R esearch in context Evidence before this study We searched Ovid MEDLINE to 28 July 2022 for studies using the terms (economic evaluation.mp. OR cost effectiveness.mp. OR health economic*.mp.) AND (simulation.mp. OR model*.mp.) AND pandemic*.mp. to identify existing simulation modelling analyses of pandemic preparedness and response that incorporated cost effectiveness considerations. All identified literature examined pandemic influenza and COVID-19 and was highly heterogeneous in terms of modelled interventions (which included school closures, masks, hand hygiene, vaccination, testing strategies, antiviral medication, physical distancing measures, indoor ventilation, and personal protective equipment), quality, context, model structure, and economic evaluation approach. Systematic reviews of COVID-19 modelling studies that include a health economic component generally indicate that SARS-CoV-2 testing, personal protective equipment, masks, and physical distancing measures are cost-effective. However, few prior studies consider optimal packages of interventions (as opposed to standalone interventions), and none explicitly account for ongoing viral evolution or accurately capture the complexities of vaccine- or natural infection-derived immunity to SARS-CoV-2. For example, a previous study integrating a dynamic SARS-CoV-2 transmission model with an economic analysis using a net monetary benefit approach published in early 2021 emphasized the combined public health and economic advantages of COVID-19 vaccination combined with physical distancing measures in the UK. However, considering current knowledge regarding the substantial waning of vaccine effectiveness and relatively low protection against infection conferred by vaccination (compared to more severe clinical outcomes), this model likely over-estimated the impact of COVID-19 vaccination on viral transmission. Scenarios that considered the emergence of SARS-CoV-2 variants of concern and thus associated changes in viral transmissibility, immune escape capacity (which has, in the case of the Omicron variant, greatly reduced protection following vaccination and prior infection) or virulence were also not modelled. Added value of this study To our knowledge, our study is the first that utilises a dynamic disease transmission model combined with an integrated economic evaluation framework to systematically compare COVID-19 policy intervention packages while accounting for ongoing SARS-CoV-2 evolution and waning population immunity. At a high-level, we found that a considerable degree of COVID-19 disease burden should be expected in the future, with modelled interventions only able to partly mitigate pandemic-associated morbidity and mortality in the medium-term. Across nine plausible future SARS-CoV-2 variant scenarios, higher stringency PHSMs notably reduced cumulative infections, hospitalisations and deaths in the 12-month period modelled but had the tradeoff of higher expected societal economic losses. Increasing community mask-wearing and substituting cloth and surgical masks for government supplied respirators during periods of high SARS-CoV-2 morbidity both reduced the number of days with hospital occupancy exceeding 750 COVID-19 patients by 2% on average across scenarios, and minimally reduced the cumulative infection, hospitalization and death burden. Compared to no further vaccines, the modelled vaccination schedules (with next-generation vaccines; one or two further doses) reduced hospitalisations by an average of 12%, and deaths by 27%. Vaccinating ≥30-year-olds was modestly superior to just vaccinating ≥60-year-olds (reducing cumulative deaths, for example, by 3.1%). Considering all policy options together, and ranking by optimality on cost-effectiveness, health system pressure and deaths, the highest ranking policy combinations tended to be a mix of higher stringency PHSMs, promotion to increase mask wearing but no Government-funded respirator provision during large outbreaks, and the administration of two booster vaccine doses within the 12-month period to ≥30-year-olds with associated high coverage (noting gains from vaccinating ≥30-year-olds compared to ≥60-year-olds were modest). Implications of all the available evidence The policy implications of this study are three-fold. Firstly, it reinforces the cost-effectiveness of ongoing vaccination of the public to mitigate morbidity and mortality associated with COVID-19. Secondly, the characteristics of emerging SARS-CoV-2 variants, outside the control of policy makers, will likely substantially influence public health outcomes associated with the pandemic in the future. Finally, at a phase of the pandemic characterised by growing intervention options urgently requiring prioritisation by decision makers alongside a large degree of ongoing uncertainty about future variants, this study provides a framework within which to systematically compare the health and economic benefits and burdens of packages of interventions that can be rapidly updated with new information (such as estimated effectiveness and waning kinetics of newly-developed vaccines) to support policy making.

Urbanization and inequalities are two of the major policy themes of our time, intersecting in large cities where social and economic inequalities are particularly pronounced. Large scale street-level images are a source of city-wide visual information and allow for comparative analyses of multiple cities. Computer vision methods based on deep learning applied to street images have been shown to successfully measure inequalities in socioeconomic and environmental features, yet existing work has been within specific geographies and have not looked at how visual environments compare across different cities and countries. In this study, we aim to apply existing methods to understand whether, and to what extent, poor and wealthy groups live in visually similar neighborhoods across cities and countries. We present novel insights on similarity of neighborhoods using street-level images and deep learning methods. We analyzed 7.2 million images from 12 cities in five high-income countries, home to more than 85 million people: Auckland (New Zealand), Sydney (Australia), Toronto and Vancouver (Canada), Atlanta, Boston, Chicago, Los Angeles, New York, San Francisco, and Washington D.C. (United States of America), and London (United Kingdom). Visual features associated with neighborhood disadvantage are more distinct and unique to each city than those associated with affluence. For example, from what is visible from street images, high density poor neighborhoods located near the city center (e.g., in London) are visually distinct from poor suburban neighborhoods characterized by lower density and lower accessibility (e.g., in Atlanta). This suggests that differences between two cities is also driven by historical factors, policies, and local geography. Our results also have implications for image-based measures of inequality in cities especially when trained on data from cities that are visually distinct from target cities. We showed that these are more prone to errors for disadvantaged areas especially when transferring across cities, suggesting more attention needs to be paid to improving methods for capturing heterogeneity in poor environment across cities around the world.

Background Although the harm to health from electronic nicotine delivery systems (ENDS) compared to smoked tobacco remains highly uncertain, society and governments still need to know the likely range of the relative harm to inform regulatory policies for ENDS and smoking. Methods We identified biomarkers with specificity of association with different disease groupings e.g., volatile organic compound (VOCs) for chronic obstructive pulmonary disease; and tobacco-specific N´-nitrosamines (TSNAs) and polycyclic aromatic hydrocarbons (PAHs) for all cancers. We conducted a review of recent studies (post January 2017) that compared these biomarkers between people exclusively using ENDS and those exclusively smoking tobacco. The percentage differences in these biomarkers, weighted by study size and adjusted for acrolein from other sources, were used as a proxy for the assumed percentage difference in disease harm between ENDS and smoking. These relative differences were applied to previously modelled estimates of smoking-related health loss (in health-adjusted life-years; HALYs). Results The respective relative biomarker levels (ENDS vs smoking) were: 28% for respiratory diseases (five results, three studies); 42% for cancers (five results, four studies); and 35% for cardiovascular (seven results, four studies). When integrated with the HALY impacts by disease, the overall harm to health from ENDS was estimated to be 33% that of smoking. Conclusions This analysis, suggests that the use of modern ENDS devices (vaping) could be a third as harmful to health as smoking in a high-income country setting. But this estimate is based on a limited number of biomarker studies and is best be considered a likely upper level of ENDS risk given potential biases in our method (i.e., the biomarkers used being correlated with more unaccounted for toxicants in smoking compared to with using ENDS).

Front-of-pack labelling (FoPL) aims to promote healthier diets by altering consumer food purchasing behaviour. We quantify the impact of the voluntary Health Star Rating (HSR) FoPL adopted by New Zealand (NZ) in 2014, on (i) the quantity of foods purchased by HSR scores and food groups and (ii) the quantities of different nutrients purchased.We used Nielsen HomeScan household purchasing panel data over 2013–2019, linked to Nutritrack packaged food composition data. Fixed effects analyses were used to estimate the association of HSR with product and nutrient purchasing. We controlled for NZ-wide purchasing trends and potential confounding at the household and product level.In 2019, HSR-labelled products accounted for 24% (2890) of 12 040 products in the dataset and 32% of purchasing volume. Of HSR-labelled products, 1339 (46%) displayed a rating of 4.0–5.0 stars and 556 (19%) displayed a rating of 0.5–2.0 stars.We found little or no association between HSR labelling and the quantities of different foods purchased. Introduction of HSR was, however, associated with lower sodium (−9%, 95% CI −13% to −5%), lower protein (−3%, 95% CI −5% to 0%) and higher fibre (5%, 95% CI 2% to 7%) purchases when purchased products carrying an HSR were compared with the same products prior to introduction of the programme.Robust evidence of HSR labelling changing consumer purchasing behaviour was not observed. The positive effect on nutrient purchasing of HSR-labelled foods likely arises from reformulation of products to achieve a better HSR label.

Immunity to SARS-CoV-2 following vaccination wanes over time in a non-linear fashion, making modelling of likely population impacts of COVID-19 policy options challenging. We observed that it was possible to mathematize non-linear waning of vaccine effectiveness (VE) on the percentage scale as linear waning on the log-odds scale, and developed a random effects logistic regression equation based on UK Health Security Agency data to model VE against Omicron following two and three doses of a COVID-19 vaccine. VE on the odds scale reduced by 47% per month for symptomatic infection after two vaccine doses, lessening to 35% per month for hospitalisation. Waning on the odds scale after triple dose vaccines was 35% per month for symptomatic disease and 19% for hospitalisation. This log-odds system for estimating waning and boosting of COVID-19 VE provides a simple solution that may be used to parametrize SARS-CoV-2 immunity over time parsimoniously in epidemiological models.

Protection against Omicron in California PrisonsUnvaccinated persons without previous Covid-19 had the highest risk of omicron infection; those who had been infected after emergence of the delta variant and had received three mRNA vaccine doses were the most protected. BackgroundInformation regarding the protection conferred by vaccination and previous infection against infection with the B.1.1.529 (omicron) variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is limited. MethodsWe evaluated the protection conferred by mRNA vaccines and previous infection against infection with the omicron variant in two high-risk populations: residents and staff in the California state prison system. We used a retrospective cohort design to analyze the risk of infection during the omicron wave using data collected from December 24, 2021, through April 14, 2022. Weighted Cox models were used to compare the effectiveness (measured as 1 minus the hazard ratio) of vaccination and previous infection across combinations of vaccination history (stratified according to the number of mRNA doses received) and infection history (none or infection before or during the period of B.1.617.2 [delta]-variant predominance). A secondary analysis used a rolling matched-cohort design to evaluate the effectiveness of three vaccine doses as compared with two doses. ResultsAmong 59,794 residents and 16,572 staff, the estimated effectiveness of previous infection against omicron infection among unvaccinated persons who had been infected before or during the period of delta predominance ranged from 16.3% (95% confidence interval [CI], 8.1 to 23.7) to 48.9% (95% CI, 41.6 to 55.3). Depending on previous infection status, the estimated effectiveness of vaccination (relative to being unvaccinated and without previous documented infection) ranged from 18.6% (95% CI, 7.7 to 28.1) to 83.2% (95% CI, 77.7 to 87.4) with two vaccine doses and from 40.9% (95% CI, 31.9 to 48.7) to 87.9% (95% CI, 76.0 to 93.9) with three vaccine doses. Incremental effectiveness estimates of a third (booster) dose (relative to two doses) ranged from 25.0% (95% CI, 16.6 to 32.5) to 57.9% (95% CI, 48.4 to 65.7) among persons who either had not had previous documented infection or had been infected before the period of delta predominance. ConclusionsOur findings in two high-risk populations suggest that mRNA vaccination and previous infection were effective against omicron infection, with lower estimates among those infected before the period of delta predominance. Three vaccine doses offered significantly more protection than two doses, including among previously infected persons.

Background Exposure to cold indoor temperature (< 18 degrees Celsius) increases cardiovascular disease (CVD) risk and has been identified by the WHO as a source of unhealthy housing. While warming homes has the potential to reduce CVD risk, the reduction in disease burden is not known. We simulated the population health gains from reduced CVD burden if the temperature in all Australian cold homes was permanently raised from their assumed average temperature of 16 degrees Celsius to 20 degrees Celsius. Methods The health effect of eradicating cold housing through reductions in CVD was simulated using proportional multistate lifetable model. The model sourced CVD burden and epidemiological data from Australian and Global Burden of Disease studies. The prevalence of cold housing in Australia was estimated from the Australian Housing Conditions Survey. The effect of cold indoor temperature on blood pressure (and in turn stroke and coronary heart disease) was estimated from published research. Results Eradication of exposure to indoor cold could achieve a gain of undiscounted one and a half weeks of additional health life per person alive in 2016 (base-year) in cold housing through CVD alone. This equates to 0.447 (uncertainty interval: 0.064, 1.34; 3% discount rate) HALYs per 1,000 persons over remainder of their lives through CVD reduction. Eight percent of the total health gains are achievable between 2016 and 2035. Although seemingly modest, the gains outperform currently recommended CVD interventions including persistent dietary advice for adults 5–9% 5 yr CVD risk (0.017 per 1000 people, UI: 0.01, 0.027) and persistent lifestyle program for adults 5–9% 5 yr CVD risk (0.024, UI: 0.01, 0.027). Conclusion Cardiovascular health gains alone achievable through eradication of cold housing are comparable with real-life lifestyle and dietary interventions. The potential health gains are even greater given cold housing eradication will also improve respiratory and mental health in addition to cardiovascular disease.

Population-level immunity to SARS-CoV-2 directly impacts the incidence of COVID-19 morbidity and mortality. Understanding how this immunity is likely to change over time in the context of future vaccination schedules and emerging SARS-CoV-2 variants is critical to inform pandemic policy. This study simulates population-level COVID-19 immunity (including relative contributions of vaccination and previous infection) in Victoria, Australia over 18 months using an agent-based model and logistic regression equations that predict immunity and waning following vaccination and/or infection. Previous infection was found to drive most immunity against infection even with ongoing regular vaccination, however a greater proportion of overall immunity against mortality was accounted for by vaccination. Although previous infection appears to be driving a substantial component of population-level COVID-19 immunity currently, improved vaccines providing longer lasting (and better sterilizing) immunity are likely to be a critical component of the future pandemic response given the risks associated with SARS-CoV-2 infection.

Simulation models of epidemiological, biological, ecological, and environmental processes are increasingly being calibrated using Bayesian statistics. The Bayesian approach provides simple rules to synthesise multiple data sources and to calculate uncertainty in model output due to uncertainty in the calibration data. As the number of tutorials and studies published grow, the solutions to common difficulties in Bayesian calibration across these fields have become more apparent, and a step-by-step process for successful calibration across all these fields is emerging. We provide a statement of the key steps in a Bayesian calibration, and we outline analyses and approaches to each step that have emerged from one or more of these applied sciences. Thus we present a synthesis of Bayesian calibration methodologies that cut across a number of scientific disciplines. To demonstrate these steps and to provide further detail on the computations involved in Bayesian calibration, we calibrated a compartmental model of tobacco smoking behaviour in Australia. We found that the proportion of a birth cohort estimated to take up smoking before they reach age 20 years in 2016 was at its lowest value since the early 20th century, and that quit rates were at their highest. As a novel outcome, we quantified the rate that ex-smokers switched to reporting as a 'never smoker' when surveyed later in life; a phenomenon that, to our knowledge, has never been quantified using cross-sectional survey data.

Background Myocardial infarction mortality has declined since the 1970s, but contemporary drivers of this trend remain unexplained. The aim of this study was to compare the contribution of trends in event rates and case fatality to declines in myocardial infarction mortality in four high-income jurisdictions from 2002-15. Methods Linked hospitalisation and mortality data were obtained from New South Wales (NSW), Australia; Ontario, Canada; New Zealand; and England, UK. People aged between 30 years and 105 years were included in the study. Age-adjusted trends in myocardial infarction event rates and case fatality were estimated from Poisson and binomial regression models, and their relative contribution to trends in myocardial infarction mortality calculated. Findings 1 947 895 myocardial infarction events from a population of 80.4 million people were identified in people aged 30 years or older. There were significant declines in myocardial infarction mortality, event rates, and case fatality in all jurisdictions. Age-standardised myocardial infarction event rates were highest in New Zealand (men 893/100 000 person-years in 2002, 536/100 000 person-years in 2015; women 482/100 000 person-years in 2002, 271/100 000 person-years in 2015) and lowest in England (men 513/100 000 person-years in 2002, 382/100 000 person-years in 2015; women 238/100 000 person-years in 2002, 173/100 000 person-years in 2015). Annual age-adjusted reductions in event rates ranged from -2.6% (95% CI -3.0 to -2.3) in men in England to -4.3% (-4.4 to -4.1) in women in Ontario. Age-standardised case fatality was highest in England in 2002 (48%), but declined at a greater rate than in the other jurisdictions (men -4.1%/year, 95% CI -4.2 to -4.0%; women -4.4%/year, -4.5 to -4.3%). Declines in myocardial infarction mortality rates ranged from -6.1%/year to -7.6%/year. Event rate declines were the greater contributor to myocardial infarction mortality reductions in Ontario (69.4% for men and women), New Zealand (men 68.4%; women 67.5%), and NSW women (60.1%), whereas reductions in case fatality were the greater contributor in England (60% in men and women) and for NSW men (54%). There were greater contributions from case fatality than event rate reductions in people younger than 55 years in all jurisdictions, with contributions to mortality declines varying by country in those aged 55-74 years. Event rate declines had a greater impact than changes in case fatality in those aged 75 years and older. Interpretation While the mortality burden of myocardial infarction has continued to fall across these four populations, the relative contribution of trends in myocardial infarction event rates and case fatality to declining mortality varied between jurisdictions, including by age and sex. Understanding the causes of this variation will enable optimisation of prevention and treatment efforts. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd.

Background 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. Methods A literature review was conducted to identify peer-reviewed evaluations (2010 to 2018) arising from the Australia Cost-Effectiveness research and NZ Burden of Disease Epidemiology, Equity and Cost-Effectiveness Programmes, or using similar methodology, with: health gains quantified as health-adjusted life years (HALYs); net health system costs and/or incremental cost-effectiveness ratio; time horizon of at least 10 years; and 3% to 5% discount rates. Results We identified 384 evaluations that met the inclusion criteria, covering 14 intervention domains: alcohol; cancer; cannabis; communicable disease; cardiovascular disease; diabetes; diet; injury; mental illness; other non-communicable diseases; overweight and obesity; physical inactivity; salt; and tobacco. There were large variations in health gain across evaluations: 33.9% gained less than 0.1 HALYs per 1000 people in the total population over the remainder of their lifespan, through to 13.0% gaining > 10 HALYs per 1000 people. Over a third (38.8%) of evaluations were cost-saving. Conclusions League tables of comparably conducted evaluations illustrate the large health gain (and cost) variations per capita between interventions, in addition to cost-effectiveness. Further work can test the utility of this league table with policy-makers and researchers.

Objective Tobacco endgame policies aim to rapidly and permanently reduce smoking to minimal levels. We reviewed evidence syntheses for: (1) endgame policies, (2) evidence gaps, and (3) future research priorities. Data sources Guided by JBI scoping review methodology, we searched five databases (PubMed, CINAHL, Scopus, Embase and Web of Science) for evidence syntheses published in English since 1990 on 12 policies, and Google for publications from key national and international organisations. Reference lists of included publications were hand searched. Study selection Two reviewers independently screened titles and abstracts. Inclusion criteria were broad to capture policy impacts (including unintended), feasibility, public and stakeholder acceptability and other aspects of policy implementation. Data extraction We report the results according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews checklist. Data synthesis Eight policies have progressed to evidence synthesis stage (49 publications): mandatory very low nicotine content (VLNC) standard (n=26); product standards to substantially reduce consumer appeal or remove the most toxic products from the market (n=1); moving consumers to reduced risk products (n=8); tobacco-free generation (n=4); ending sales (n=2); sinking lid (n=2); tax increases (n=7); and restrictions on tobacco retailers (n=10). Based on published evidence syntheses, the evidence base was most developed for a VLNC standard, with a wide range of evidence synthesised. Conclusions VLNC cigarettes have attracted the most attention, in terms of synthesised evidence. Additional focus on policies that reduce the availability of tobacco is warranted given these measures are being implemented in some jurisdictions.

Background We compared the health and economic consequences for the State of Victoria, Australia, of four COVID19 strategies: aggressive and moderate elimination, tight suppression (aiming for 1 to 5 cases per million per day) and loose suppression (5 to 25 cases per million per day). The strategies shifted up and down through five levels of policy stringency based on the number of cases per day, for one year. Methods An agent-based model (ABM) generated 100 runs of daily SARS-CoV-2 case numbers, that then fed into a proportional multistate lifetable to estimate health adjusted life years (HALYs) and costs. We used a net monetary benefit approach to estimate the optimal strategy. Findings Aggressive elimination resulted in the highest percentage of days with the lowest level of restrictions (median 31.7%, 90% simulation interval 6.6% to 64.4%). However, days in hard lockdown were similar across all four strategies (medians 27.5% to 36.1%). HALY losses (compared to a no-COVID-19 scenario) were similar for moderate elimination (286, 219 to 389) and moderate elimination (314, 228 to 413), and nearly eight and 40-times higher for tight and loose suppression. The median GDP loss was least for moderate elimination ($US41.7 billion, $29.0 to $63.6 billion), but there was substantial overlap in simulation intervals between the four strategies. From a health system perspective aggressive elimination was optimal in 64% of simulations above a willingness to pay of $15,000 per HALY, followed by moderate elimination in 35% of simulations. Moderate elimination was optimal from a partial societal perspective in half the simulations followed by aggressive elimination in a quarter. Shortening the pandemic duration to 6 months saw loose suppression become preferable under a partial societal perspective. Interpretation For this single high-income jurisdiction, elimination strategies were preferable over a 1-year pandemic duration. Funding Anonymous philanthropic donation to the University of Melbourne.