Quantitatively evaluating the cross-sectoral and One Health impact of interventions: A scoping review and case study of antimicrobial resistance

Current evidence of the economic value of One Health initiatives: A systematic literature review

Funding and financing for One Health initiatives at country level remain challenging as investments commonly require demonstrated evidence of economic value or returns. The objectives of this review were to i) identify, critically analyse and summarise quantitative evidence of the net economic value of One Health initiatives; ii) document methodologies commonly used in the scientific literature; and iii) describe common challenges and any evidence gaps. Scientific databases were searched for published literature following the PRISMA guidelines and an online survey and workshop with subject matter experts were used to identify relevant grey literature. Studies were included if they reported on quantitative costs and benefits (monetary and non-monetary) and were measured across at least two sectors. Relevant publications were analysed and plotted against the six action tracks of the Quadripartite One Health Joint Plan of Action to help classify the initiatives. Ninety-seven studies were included. Eighty studies involved only two sectors and 78 reported a positive economic value or return. Of those studies that reported a positive return, 49 did not compare with a sectoral counterfactual, 28 studies demonstrated an added value of using a cross-sectoral approach, and 6 studies demonstrated an added value of One Health communication, collaboration, coordination, and capacity building. Included studies most frequently related to endemic zoonotic, neglected tropical and vector-borne diseases, followed by health of the environment and food safety. However, diversity in economic analysis methodology between studies included resulted in difficulty to compare or combine findings. While there is a growing body of evidence of the value of One Health initiatives, a substantial part of the evidence still focuses on "traditional" One Health topics, particularly zoonoses. Developing a standardised and practical approach for One Health economic evaluation will facilitate assessment of the added value and gather evidence for One Health to be invested in and endorsed by multiple sectors.

Navigating One Health in research-for-development: Reflections on the design and implementation of the CGIAR Initiative on One Health

Adopting One Health approaches is key for addressing interconnected health challenges. Yet, how to best put One Health into practice in research-for-development initiatives aiming to 'deliver impacts' remains unclear. Drawing on the CGIAR Initiative on One Health - a global initiative to address zoonotic diseases, antimicrobial resistance, and food and water safety - we reflect on challenges during program conception and implementation, prompting us to suggest improvements in multisectoral collaboration, coordination, and communication. Our approach involves conducting a researcher-centered process evaluation, comprising individual interviews that are subsequently thematically analyzed and synthesized. The key takeaway is that limited time for planning processes and short program timelines compared to envisioned development impacts may impede research-for-development efforts. Yet, collaborative work can be successful when adequate time and resources are allocated for planning with minimal disruption throughout implementation. Additionally, due to the multifaceted nature of One Health initiatives, it is important to pay attention to co-benefits and trade-offs, where taking action in one aspect may yield advantages and disadvantages in another, aiding to identify sustainable One Health development pathways. Forming close partnerships with national governments and local stakeholders is essential not only to promote sustainability but also to ensure local relevance, enhancing the potential for meaningful impact. Finally, regularly assessing progress toward development goals is critical as development stands as an overarching objective.

AHHME: A model for estimating the holistic cost-effectiveness of antimicrobial resistance interventions in food animal production

Antimicrobial resistance (AMR) is considered a global priority for human health, and reducing antimicrobial use in food animals has been suggested as a key area for interventions aiming to reduce resistant infections in humans. In addition to the effect on human health, such interventions may have effects across food animal productivity, healthcare sector costs, and the broader macroeconomy, but these effects are rarely captured in the AMR health economic literature. Without being able to estimate these effects, it is difficult to understand the true cost-effectiveness of antimicrobial stewardship interventions in food animal production, or to correctly design and prioritise such interventions. We explore and demonstrate the potential use of a novel compartment-based mathematical model to estimate the holistic cost-effectiveness of AMR-related interventions in food animal production from a One Health perspective. The Agriculture Human Health Micro-Economic model (AHHME) uses Markov state transition models to model the movement of humans and food animals between health states. It assigns values to these health states utilising empiric approaches, from the perspectives of human health, food animal productivity, labour productivity and healthcare sector costs. Providing AHHME open-source code and interactive online modelling tools allow for capacity building in AMR intervention modelling. This model represents a useful framework for capturing the cost-effectiveness of AMR-related interventions in food animal production in a more holistic way: it can allow us to capture the often-overlooked benefits of such interventions in like terms while considering distributional concerns. It also demonstrates that methodological assumptions such as willingness-to-pay thresholds and discount rates can be just as important to health decision models as epidemiological parameters, and allows these assumptions to be altered. We provide example outputs, and encourage researchers and policymakers to use and adapt our code to explore, design, and prioritise AMR-related interventions in their own country contexts.

An agent-based model for collaborative learning to combat antimicrobial resistance: proof of concept based on broiler production in Senegal

Antimicrobial resistance (AMR) is a substantial global One Health problem. This paper reports on initial, proof-of-concept development of an agent-based model (ABM) as part of wider modelling efforts to support collaborations between groups interested in policy development for animal health and food systems. The model simulates AMR in poultry production in Senegal. It simultaneously addresses current policy issues, builds on existing modelling in the domain and describes AMR in the broiler chicken production cycle as seen by producers and veterinarians. This enables implementation and assessment of producer antimicrobial use and infection prevention and control strategies in terms of immediate economic incentives, potentially helping to advance conversations by addressing national policy priorities. Our model is presented as a flexible tool with promise for extension as part of AMR policy development in Senegal and West Africa, using participatory approaches. This work indicates that ABM can potentially play a useful role in fostering counter-AMR initiatives driven by food system actor behaviour in lower- and middle-income countries more generally.

The WHO costing and budgeting tool for national action plans on antimicrobial resistance-a practical addition to the WHOle toolkit

Objectives

The development of national action plans (NAPs) for antimicrobial resistance (AMR) has been promoted and supported by the WHO, with recent support in the form of costing and budgeting tools to aid in finance-allocation decisions within governments.

Methods

In this brief report we review this WHO costing and budgeting tool, discuss the strengths and weaknesses, and consider its place alongside other health economics and policy-support tools developed.

Results

We call for future analyses of the costs of AMR NAPs to consider costs beyond that of only implementation, through use of other available, open-access data and tools. These include the Global Antimicrobial Resistance and Use Surveillance System (GLASS) data and One Health tools already within the existing 'WHO toolbox'.

Conclusions

We suggest that future work on evaluating AMR along the impact pipeline use this toolbox where possible, ensuring empirical work is in turn open access.

Antimicrobial Resistance in the Global Health Network: Known Unknowns and Challenges for Efficient Responses in the 21st Century

Antimicrobial resistance (AMR) is one of the Global Health challenges of the 21st century. The inclusion of AMR on the global map parallels the scientific, technological, and organizational progress of the healthcare system and the socioeconomic changes of the last 100 years. Available knowledge about AMR has mostly come from large healthcare institutions in high-income countries and is scattered in studies across various fields, focused on patient safety (infectious diseases), transmission pathways and pathogen reservoirs (molecular epidemiology), the extent of the problem at a population level (public health), their management and cost (health economics), cultural issues (community psychology), and events associated with historical periods (history of science). However, there is little dialogue between the aspects that facilitate the development, spread, and evolution of AMR and various stakeholders (patients, clinicians, public health professionals, scientists, economic sectors, and funding agencies). This study consists of four complementary sections. The first reviews the socioeconomic factors that have contributed to building the current Global Healthcare system, the scientific framework in which AMR has traditionally been approached in such a system, and the novel scientific and organizational challenges of approaching AMR in the fourth globalization scenario. The second discusses the need to reframe AMR in the current public health and global health contexts. Given that the implementation of policies and guidelines are greatly influenced by AMR information from surveillance systems, in the third section, we review the unit of analysis ("the what" and "the who") and the indicators (the "operational units of surveillance") used in AMR and discuss the factors that affect the validity, reliability, and comparability of the information to be applied in various healthcare (primary, secondary, and tertiary), demographic, and economic contexts (local, regional, global, and inter-sectorial levels). Finally, we discuss the disparities and similarities between distinct stakeholders' objectives and the gaps and challenges of combatting AMR at various levels. In summary, this is a comprehensive but not exhaustive revision of the known unknowns about how to analyze the heterogeneities of hosts, microbes, and hospital patches, the role of surrounding ecosystems, and the challenges they represent for surveillance, antimicrobial stewardship, and infection control programs, which are the traditional cornerstones for controlling AMR in human health.

Establishment of an indicator framework for global One Health Intrinsic Drivers index based on the grounded theory and fuzzy analytical hierarchy-entropy weight method

BACKGROUND

One Health has become a global consensus to deal with complex health problems. However, the progress of One Health implementation in many countries is still relatively slow, and there is a lack of systematic evaluation index. The purpose of this study was to establish an indicator framework for global One Health Intrinsic Drivers index (GOH-IDI) to evaluate human, animal and environmental health development process globally.

METHOD

First, 82 studies were deeply analyzed by a grounded theory (GT) method, including open coding, axial coding, and selective coding, to establish a three-level indicator framework, which was composed of three selective codes, 19 axial codes, and 79 open codes. Then, through semi-structured interviews with 28 health-related experts, the indicators were further integrated and simplified according to the inclusion criteria of the indicators. Finally, the fuzzy analytical hierarchy process combined with the entropy weight method was used to assign weights to the indicators, thus, forming the evaluation indicator framework of human, animal and environmental health development process.

RESULTS

An indicator framework for GOH-IDI was formed consisting of three selective codes, 15 axial codes and 61 open codes. There were six axial codes for "Human Health", of which "Infectious Diseases" had the highest weight (19.76%) and "Injuries and Violence" had the lowest weight (11.72%). There were four axial codes for "Animal Health", of which "Animal Epidemic Disease" had the highest weight (39.28%) and "Animal Nutritional Status" had the lowest weight (11.59%). Five axial codes were set under "Environmental Health", among which, "Air Quality and Climate Change" had the highest weight (22.63%) and "Hazardous Chemicals" had the lowest weight (17.82%).

CONCLUSIONS

An indicator framework for GOH-IDI was established in this study. The framework were universal, balanced, and scientific, which hopefully to be a tool for evaluation of the joint development of human, animal and environmental health in different regions globally.

Community engagement: The key to tackling Antimicrobial Resistance (AMR) across a One Health context?

Antimicrobial resistance (AMR) is a One Health problem underpinned by complex drivers and behaviours. This is particularly so in low - and middle-income countries (LMICs), where social and systemic factors fuel (mis)use and drive AMR. Behavioural change around antimicrobial use could safeguard both existing and future treatments. However, changing behaviour necessitates engaging with people to understand their experiences. This publication describes a knowledge-exchange cluster of six LMIC-based projects who co-designed and answered a series of research questions around the usage of Community Engagement (CE) within AMR. Findings suggest that CE can facilitate AMR behaviour change, specifically in LMICs, because it is a contextualised approach which supports communities to develop locally meaningful solutions. However, current CE interventions focus on human aspects, and demand-side drivers, of AMR. Our cluster suggests that broader attention should be paid to AMR as a One Health issue. The popularity of mixed methods approaches within existing CE for AMR interventions suggests there is interdisciplinary interest in the uptake of CE. Unfortunately, the specificity and context-dependency of CE can make it difficult to evaluate and scale. Nevertheless, we suggest that in synthesising learnings from CE, we can develop a collective understanding of its scope to tackle AMR across contexts.   .

Changing food systems and infectious disease risks in low-income and middle-income countries

The emergence of COVID-19 has drawn the attention of health researchers sharply back to the role that food systems can play in generating human disease burden. But emerging pandemic threats are just one dimension of the complex relationship between agriculture and infectious disease, which is evolving rapidly, particularly in low-income and middle-income countries (LMICs) that are undergoing rapid food system transformation. We examine this changing relationship through four current disease issues. The first is that greater investment in irrigation to improve national food security raises risks of vector-borne disease, which we illustrate with the case of malaria and rice in Africa. The second is that the intensification of livestock production in LMICs brings risks of zoonotic diseases like cysticercosis, which need to be managed as consumer demand grows. The third is that the nutritional benefits of increasing supply of fresh vegetables, fruit, and animal-sourced foods in markets in LMICs pose new food-borne disease risks, which might undermine supply. The fourth issue is that the potential human health risks of antimicrobial resistance from agriculture are intensified by changing livestock production. For each disease issue, we explore how food system transition is creating unintentional infectious disease risks, and what solutions might exist for these problems. We show that successfully addressing all of these challenges requires a coordinated approach between public health and agricultural sectors, recognising the costs and benefits of disease-reducing interventions to both, and seeking win-win solutions that are most likely to attract broad policy support and uptake by food systems.

How are large-scale One Health initiatives targeting infectious diseases and antimicrobial resistance evaluated? A scoping review

While One Health initiatives are gaining in popularity, it is unclear if and how they are evaluated when implementation at scale is intended. The main purpose of this scoping review was to describe how One Health initiatives targeting infectious diseases and antimicrobial resistance at a large scale are evaluated. Secondary objectives included identifying the main facilitators and barriers to the implementation and success of these initiatives, and how their impacts were assessed. Twenty-three studies evaluating One Health initiatives were eligible. Most studies included the human (n = 22) and animal (n = 15) sectors; only four included the environment sector. The types of evaluated initiative (non-exclusive) included governance (n = 5), knowledge (n = 6), protection (n = 17), promotion (n = 16), prevention (n = 9), care (n = 8), advocacy (n = 10) and capacity (n = 10). Studies used normative (n = 4) and evaluative (n = 20) approaches to assess the One Health initiatives, the latter including impact (n = 19), implementation (n = 8), and performance (n = 7) analyses. Structural and economic, social, political, communication and coordination-related factors, as well as ontological factors, were identified as both facilitators and barriers for successful One Health initiatives. These results identified a wide range of evaluation methods and indicators used to demonstrate One Health's added values, strengths, and limitations: the inherent complexity of the One Health approach leads to the use of multiple types of evaluation. The strengths and remaining gaps in the evaluation of such initiative highlight the relevance of comprehensive, mixed-method, context-sensitive evaluation frameworks to inform and support the implementation of One Health initiatives by stakeholders in different governance settings.

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Studies evaluating One Health initiatives were scarce.

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Only One Health initiatives related to infectious diseases were evaluated.

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Evaluations were mainly conducted using quantitative approaches.

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Involvement of the community was identified as a major facilitator.

Quantifying the Relationship between Antibiotic Use in Food-Producing Animals and Antibiotic Resistance in Humans

It is commonly asserted that agricultural production systems must use fewer antibiotics in food-producing animals in order to mitigate the global spread of antimicrobial resistance (AMR). In order to assess the cost-effectiveness of such interventions, especially given the potential trade-off with rural livelihoods, we must quantify more precisely the relationship between food-producing animal antimicrobial use and AMR in humans. Here, we outline and compare methods that can be used to estimate this relationship, calling on key literature in this area. Mechanistic mathematical models have the advantage of being rooted in epidemiological theory, but may struggle to capture relevant non-epidemiological covariates which have an uncertain relationship with human AMR. We advocate greater use of panel regression models which can incorporate these factors in a flexible way, capturing both shape and scale variation. We provide recommendations for future panel regression studies to follow in order to inform cost-effectiveness analyses of AMR containment interventions across the One Health spectrum, which will be key in the age of increasing AMR.