Antimicrobial resistance in the South East Asian food system: A participatory, One Health study

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 Shannon MajowiczDownload button
Shannon Majowicz
School of Public Health Sciences

Introduction

Antimicrobials have modernized medicine and increased agricultural food production, but their inappropriate use has contributed to antimicrobial resistance (AMR) development and spread across human, animal, agricultural and environmental systems. With antimicrobial use projected to increase, South East Asia (SEA) is at high risk of experiencing disproportionate health, social and economic burdens from AMR.

While AMR mitigation actions from high-income regions are commonly applied in low-middle income regions, South East Asia (SEA) remains a hotspot, suggesting a need to understand the regional context to determine how to effectively intervene. A One Health approach that engages participants from human, animal and environment sectors to understand the web of connections that give rise to AMR has been promoted as an appropriate method. The study objective therefore was to apply a One Health approach in engaging diverse stakeholders to identify factors influencing AMR in SEA’s food system and leverage points for intervention to inform policy and management decisions.

Methodology

Eighteen participants from research, academic, healthcare, not-for-profit, government and private sectors participated in the study. Participants represented the following areas of expertise: environmental technologies and water quality; human and animal medicine; clinical microbiology; veterinarian; aquaculture; animal health policy and economics; animal welfare; pharmacology; medicine use and safety; health systems and economics; food aid; food safety; nutrition; and tropical pest management in agricultural plants. Nine participants were from Malaysia with the remaining from Thailand, Indonesia, Laos, Singapore, Sri Lanka, India and Ethiopia.

Two 6.5 hour in-person workshops were conducted. Participants were shown an existing causal loop diagram (CLD) of AMR in the Canadian food system and tasked to adapt it to reflect the SEA food system. Factors influencing AMR were defined and the direction and nature of connections between factors were identified. Through small group discussions, participants identified leverage points in the CLD to target interventions with the potential to change behaviors in ways that could mitigate AMR.

Resulting CLDs were open coded, triangulated and thematically analyzed using NVivo 12, while all factors and connections were entered into Vensim Professional 8.0.4 Double Precision to yield two CLDs, one for each workshop, which were then combined because of their similarities. The leverage points for intervention were classified as “shallow” (places where interventions are easier to implement but may have less potential to transform the behavior of the whole system) or “deep” (places in the system that are more difficult to alter yet have greater potential to change the behavior of the whole system).

Outcomes

The CLD of AMR in the SEA food system contained 98 factors interlinked by 362 connections. CLD factors were grouped into eight sub-areas of the One Health spectrum (Figure 1). Seven themes emerged from workshop discussions that described the key CLD dynamics (Table 1). In addition, participants identified six overarching factors not included in the CLD because they exerted broad impacts on the entire system (Table 2).

Ninety-eight CLD factors grouped into eight One Health sub-areas

Figure 1. Ninety-eight CLD factors grouped into eight One Health sub-areas.

Open image in a separate tab to zoom in.

Theme

Description

Antimicrobial and pesticide use and AMR spread

The role of human behavior in AMR development and spread in animals, people and the environment, such as inappropriate antimicrobial, pesticide and/or chemical use; poor infection prevention and control measures; poor sanitation and waste management; and the transport of people and animals across porous borders.

Agricultural food production systems

How regulated and unregulated food production systems use antimicrobials, pesticides and chemicals to produce food quickly to  meet market demands, and how low animal welfare standards can contribute to AMR, and the challenges farmers face in implementing good farm practices.

Consumer demand

How consumer demand for food and antibiotics influences the use of antibiotics, fungicides, pesticides and chemicals and the factors (e.g., religious and cultural practices, finances) that shape these demands.

Access to antimicrobials, diagnostics and alternatives

How public and privatized healthcare, over the counter and online sales of antimicrobials, and access to alternative health providers enable access to different types of antimicrobials (including counterfeit antimicrobials) depending on what people can access or afford, and how a lack of availability of appropriate diagnostics or alternatives to antimicrobials impact clinical diagnosis and/or antibiotic prescribing practices.

Food safety

The influence of cultural, religious and food safety practices in SEA on potential food borne illnesses, and how improper use of antimicrobial compounds along the food chain can contribute to AMR.

Population growth
and migration

How increased population growth and migration of people from rural to urban areas for employment opportunities and animals for cross-border trade contribute to infectious disease and AMR spread. Also highlights how migration of people impacts resources (e.g., access to clean water) and the food chain based on changing lifestyles and consumption patterns.

Awareness and understanding of AMR

How awareness of issues relevant to AMR (e.g., what antimicrobials to use, when, and how; food safety; and alternatives to antimicrobials) have on AMU practices and AMR spread.

Table 1: Themes based on participant discussions.

Overarching factor

Description

Drive to survive

How food insecurity, poverty and environmental conditions (e.g., pollution, pests, bacterial, viral and zoonotic diseases) can impact human and animal health and alter markets and trade and drive people, businesses and leaders to do what they need to survive even if it leads to unintended consequences that can impact AMR.

Leadership priorities

How leadership, particularly national government’ decisions to spur economic development and improve food security have ripple effects on antibiotic, pesticide, or chemical use, the microbiome, economic security, and livelihoods and nutritional intake of citizens.

Changing socio-economic structures

How economic development in the SEA region is increasing wealth and changing consumer lifestyles and demands that can impact nutritional intake, health, and immunity. How changing socioeconomic structures leads to fewer people choosing careers in agricultural food production, creating increased labour costs to produce foods in systems that already rely on antimicrobials, pesticides, and chemicals to meet market demands.

Governance, regulations and enforcement

Governance mechanisms that exist to address AMR in SEA and challenges with implementation which may contribute to mass, potentially illegal and inappropriate AMU and AMR development and spread.

Climate change

How global warming will increase heat stress in animals, increase pests and insects and potentially impact the acidity of oceans that in turn could impact food production and supply, change food consumption patterns, cause disease, and impact AMR.

Underlying intent driving system behavior

How the underlying values and goals of economic prosperity that drive system behavior and in turn global problems like AMR and climate change and a lack of systems thinking contribute to short-term solutions that may not effectively mitigate AMR over time.

Table 2: Overarching factors based on participant discussions.

Participants identified eight CLD factors and two overarching factors as leverage points and identified potential interventions, while the research team classified and characterized each leverage point as “shallow” or “deep” (Tables 3, 4). Given the complexity of the densely interconnected CLD structure, it is highly likely that identified leverage points fall on multiple feedback loops, increasing the potential for interventions to create unpredictable consequences (positive or negative) that can affect the sustainability and effectiveness of interventions to tackle AMR.

SHALLOW LEVERAGE POINTS: Places for intervention that have less potential to change the entire system’s behavior to mitigate AMR

Leverage point for intervention identified
by participants

Example suggested intervention or action identified by participants

National budget, money, funding, and subsidies (CLD factor)

  • Invest in research and development (e.g., developing alternatives to antimicrobials, such as vaccines).

Resistance in the wider environment
(CLD factor)

  • Install green buffers around farms and water bodies to reduce diffuse pollution, accumulation of antimicrobial residues, and AMR spread.

Table 3: Shallow leverage points and suggested actions

DEEP LEVERAGE POINTS: Places for intervention that have potential to change system behavior to mitigate AMR

Leverage point for intervention identified by participants

Example of an intervention or action identified by participants

Governance, regulations and enforcement

(Overarching factor)

  • Enforce ban on over the counter antibiotic sales while ensuring equitable access to antibiotics and antibiotic alternatives.

Prescribing, diagnosing, treatment practices

(CLD factor)

  • Implement hospital stewardship policies, health professional trainings and audits to ensure quality care and appropriate prescribing practices.

Treatment of waste and wastewater

(CLD factor)

  • Improve wastewater management to reduce the accumulation of antimicrobials in city wastewater.

Understanding and awareness

(CLD factor)

  • Educate and train food chain actors to implement higher animal welfare systems and biosecurity measures.

Good farm practices

(CLD factor)

  • Foster multisectoral collaborations to share knowledge and resources that improve farm practices.

Development, access, and availability of alternatives to antimicrobials

(CLD factor)

  • Disseminate and use autogenous vaccines (e.g., for aquatic animals) made with local pathogens.

Research, development and innovation

(CLD factor)

  • Research crop ecosystems and microflora and develop narrow spectrum antibiotics for crops.

Underlying intent driving the system

(Overarching factor)

  • Ensure global collaboration to change the underlying “consumptive economy” (day 2 workshop) that drives system behavior and AMR.

Table 4: Deep leverage points and suggested actions

Conclusions

Using a social-ecological systems framework, the study produced a CLD that illustrated numerous and complex interconnecting and overarching factors that influence AMR across the One Health spectrum in the SEA food system. The study identified several leverage points for intervention across human, animal and environment sectors that if comprehensively targeted with multi-pronged actions may have potential to change system behaviors in ways that help to mitigate AMR. Targeting select leverage points, such as increasing investments in research and capacity building and setting and enforcing regulations to control antimicrobial supply, demand, and use, could shift attitudes that lead to changes in more difficult to alter leverage points in ways that transform antimicrobial use and sustainably mitigate AMR.

Study limitations included a lack of representation from several SEA countries and from areas of expertise. Future research would benefit from the participation of more females native to SEA to broaden understanding of gender-related influences on AMR and identify tailored intervention needs. While participants validated the CLD model via feedback, the study did not verify their statements against existing literature nor did participants identify the relative importance of factors in the SEA context, which warrant future investigation.

Reference

Lambraki, I. A., Chadag, M. V., Cousins, M., Graells, T., Léger, A., Henriksson, P. J. G., Troell, M. F., Harbarth, S., Wernli, D., Jørgensen, P. S., Carson, C. A., Parmley, E. J., Majowicz, S. E. Factors impacting antimicrobial resistance in the South East Asian food system and potential places to intervene: A participatory, one health study. Frontiers in Microbiology, January 2023. doi.org/10.3389/fmicb.2022.992507


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Chicken Farm photo by Amisom Public Information on Flickr.