Uncomfortable science: How mathematical models, and consensus, come to be in public policy

'There's too much power in this number. It's freaking the whole response out': The views of key informants on evidence and targets to achieve hepatitis C elimination goals in Australia

Enumeration of disease is a key management tool. Setting of targets, like for hepatitis C elimination, have deep meaning and effect. We use the case of elimination in New South Wales (NSW), Australia to examine key informants' understandings of the use of targets, and the evidence that informs them, to drive action in elimination. Twenty-eight key informants working in NSW, elsewhere in Australia and internationally in high-income countries participated in a semi-structured qualitative interview in 2022. Analysis was informed by scholarship calling for examination of the ways in which science constructs what is thought possible in action. Participants pointed to the power of quantified evidence and targets and their complex effects, and questioned the usefulness and certainty derived from these at the "pointy end" of elimination. Although a range of targets exist in global and local strategies, reaching testing targets was the assumed solution to achieving elimination. Achieving elimination was thought to require "off piste" and experimental approaches that went beyond available evidence. The different types of work that participants felt necessary for late-stage elimination may require additional metrics to explain return on investment ratios. What threshold would be used to reduce efforts in elimination was a major concern. These data indicate that understandings of the evidence underpinning elimination targets and how to achieve them are far from settled. At this point, elimination efforts may need to rely on locally produced and community-driven evidence and shift from evidence-based to evidence-making paradigm.

Evaluation of the use of modelling in resource allocation decisions for HIV and TB

INTRODUCTION

Globally, resources for health spending, including HIV and tuberculosis (TB), are constrained, and a substantial gap exists between spending and estimated needs. Optima is an allocative efficiency modelling tool that has been used since 2010 in over 50 settings to generate evidence for country-level HIV and TB resource allocation decisions. This evaluation assessed the utilisation of modelling to inform financing priorities from the perspective of country stakeholders and their international partners.

METHODS

In October to December 2021, the World Bank and Burnet Institute led 16 semi-structured small-group virtual interviews with 54 representatives from national governments and international health and funding organisations. Interviews probed participants' roles and satisfaction with Optima analyses and how model findings have had been used and impacted resource allocation. Interviewed stakeholders represented nine countries and 11 different disease programme-country contexts with prior Optima modelling analyses. Interview notes were thematically analysed to assess factors influencing the utilisation of modelling evidence in health policy and outcomes.

RESULTS

Common influences on utilisation of Optima findings encompassed the perceived validity of findings, health system financing mechanisms, the extent of stakeholder participation in the modelling process-including engagement of funding organisations, sociopolitical context and timeliness of the analysis. Using workshops can facilitate effective stakeholder engagement and collaboration. Model findings were often used conceptually to localise global evidence and facilitate discussion. Secondary outputs included informing strategic and financial planning, funding advocacy, grant proposals and influencing investment shifts.

CONCLUSION

Allocative efficiency modelling has supported evidence-informed decision-making in numerous contexts and enhanced the conceptual and practical understanding of allocative efficiency. Most immediately, greater involvement of country stakeholders in modelling studies and timing studies to key strategic and financial planning decisions may increase the impact on decision-making. Better consideration for integrated disease modelling, equity goals and financing constraints may improve relevance and utilisation of modelling findings.

Early warnings and slow deaths: A sociology of outbreak and overdose

In this paper, we offer a sociological analysis of early warning and outbreak in the field of drug policy, focusing on opioid overdose. We trace how 'outbreak' is enacted as a rupturing event which enables rapid reflex responses of precautionary control, based largely on short-term and proximal early warning indicators. We make the case for an alternative view of early warning and outbreak. We argue that practices of detection and projection that help to materialise drug-related outbreaks are too focused on the proximal and short-term. Engaging with epidemiological and sociological work investigating epidemics of opioid overdose, we show how the short-termism and rapid reflex response of outbreak fails to appreciate the slow violent pasts of epidemics indicative of an ongoing need and care for structural and societal change. Accordingly, we gather together ideas of 'slow emergency' (Ben Anderson), 'slow death' (Lauren Berlant) and 'slow violence' (Rob Nixon), to re-assemble outbreaks in 'long view'. This locates opioid overdose in long-term attritional processes of deindustrialisation, pharmaceuticalisation, and other forms of structural violence, including the criminalisation and problematisation of people who use drugs. Outbreaks evolve in relation to their slow violent pasts. To ignore this can perpetuate harm. Attending to the social conditions that create the possibilities for outbreak invites early warning that goes 'beyond outbreak' and 'beyond epidemic' as generally configured.

Undoing elimination: Modelling Australia's way out of the COVID-19 pandemic

In the middle of 2020, with its borders tightly closed to the rest of the world, Australia almost achieved the local elimination of COVID-19 and subsequently maintained 'COVID-zero' in most parts of the country for the following year. Australia has since faced the relatively unique challenge of deliberately 'undoing' these achievements by progressively easing restrictions and reopening. Exploring the role of mathematical modelling in navigating a course through the pandemic through qualitative interviews with modellers and others working closely with modelling, we argue that each of these two significant phases of Australia's COVID-19 experience can be understood as distinct forms of 'model society'. This refers at once to the society enacted through the governance of risk, and to the visions of societal outcomes - whether to be sought or to be avoided - that are offered up by models. Each of the two model societies came about through a reflexive engagement with risk facilitated by models, and the iterative relationship between the representations of society enacted within models and the possibilities that these representations generate in the material world beyond them.