using systems thinking to understand the drivers of

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Using Systems Thinking To Understand the Drivers of Brucellosis Transmission in Jordan 1 . Abstract: Brucellosis disease leads to a significant production loss in ruminants and febrile disease in human in several places around the world particularly Africa, Asia and the Middle East. In Jordan, Brucellosis is endemic but has been increasing in the past few years. However, the only focus of the control programs is primarily the vaccination of livestock. The aim of this project is to understand the dynamic drivers of brucellosis transmission to explore policy options that aid in controlling human brucellosis in Jordan. Method : System dynamics modelling approach was used to create a causal loop diagram and a stock and flow model that suggest the dynamics of brucellosis transmission in Jordan. The model includes the age-structured “Susceptible-Infected-Vaccinated” sheep population model and “Susceptible-Infected-Recovered” human population model. Results : the model suggests four different policies to control brucellosis in Jordan other than vaccination; Sheep trade market restrictions; testing and culling infected sheep; increase farmers’ visits to the ministry of agriculture’s veterinary clinics and increase awareness of farmers. Conclusion : Current data suggest that other policies should be considered to help authorities to control brucellosis transmission. Collaboration between stakeholders is essential to achieve better outcomes. More research is needed to assess the implications of the proposed policies. 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 Years Incidence rate/100,00 Number of cases Human Brucellosis cases and incidence rate in Jordan (2004-2017) cases (MoH) Incidence rate/100,000 Phase 1 Problem Identification & structuring Phase 2 Causal loop modelling Understand behaviour of system Phase 3 Dynamic modelling Simulation & quantification Phase 4 Scenario analysis, evaluation and policy implication Research question 1 What is the problem? Research question 2 Why the problem exist? Research question 3 How can we manage the problem? Research question 4 What are the implication of managing this problem? Methods 1 Analysis of historical data BOT Analysis, Literature review Methods 2 Literature review, Semi-Interviews, Causal Loop Diagram, Archetype Methods 3 Stock & flow Model development, testing, sensitivity analysis. Methods 4 Scenario analysis, policy evaluation 2 . The Methods Figure 1: Figure: Human Brucellosis cases and incidence rate (per 100,000) in Jordan (2004-2017) 3 . The Results: Figure 3: stakeholder’s Map of brucellosis transmission in Jordan 3.3 The Causal Loop Diagram Figure 4: Presentation of overall qualitative data analysis process, participants map and Causal loop diagram building. 3.2 Building the Causal Loop Diagram Figure 5: Combined causal loop diagram of brucellosis dynamics in Jordan. 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 Reported Cases /100,000 Time Reported Human brucellosis cases by the proposed policies Current Policy Vacciantion Only Trade (Buy&Sell) Restriction Test & Cull Sheep Increase visits to Veterinary clinics Increase Awareness Combined Cull and trade restrictions Figure 6: Combined Stock and flow diagrams (The Model) of brucellosis dynamics in Jordan. Figure 7: Proposed policies for Brucellosis control and overall reported human cases per 100,000. Figure 2: Brief description of the research method 3.1 Stakeholder Analysis: The Map 3.4 The Model (Stock and Flow Diagrams) 3.5 Behaviour over time graph of reported brucellosis cases by the proposed policies References : 1. Musallam, II, Abo-Shehada MN, Guitian J. Knowledge, Attitudes, and Practices Associated with Brucellosis in Livestock Owners in Jordan. Am J Trop Med Hyg. 2015;93(6):1148-55. 2. Beauvais W, Musallam I, Guitian J. Vaccination control programs for multiple livestock host species: an age-stratified, seasonal transmission model for brucellosis control in endemic settings. Parasites & vectors. 2016;9:55. 3. Musallam, II, Abo-Shehada M, Omar M, Guitian J. Cross-sectional study of brucellosis in Jordan: Prevalence, risk factors and spatial distribution in small ruminants and cattle. Preventive veterinary medicine. 2015;118(4):387-96. 4. Sterman JD. Business dynamics: Systems thinking and modeling for a complex world. Boston: Irwin/McGraw-Hill; 2000. 5. Franc KA, Krecek RC, Hasler BN, Arenas-Gamboa AM. Brucellosis remains a neglected disease in the developing world: a call for interdisciplinary action. BMC public health. 2018;18(1):125. 6. Agriculture-Jordan Mo. MoA Jordan 2018 [Available from: http ://moa.gov.jo/ar-jo/home.aspx. Accessed 7. Zhou L, Fan M, Hou Q, Jin Z, Sun X. Transmission dynamics and optimal control of brucellosis in Inner Mongolia of China. Mathematical biosciences and engineering : MBE. 2018;15(2):543-67. Acknowledgements : I would like to appreciate the great effort put into this poster design by my lovely wife, Nermin, you are the strength that keeps me going. Additionally, I would like to thank the great inspiration, Danielle Currie for the continuous support and guidance in this project. Finally, I would like to appreciate and thank Simon Reid and Carl Smith for their guidance throughout this project. H.Taha 1 , S.Reid 2 , C.Smith 3 , J. Durham 4 , D.Currie 5 ( 1,2,3,4 The University Of Queensland 5 The Sax institute)

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Page 1: Using Systems Thinking To Understand the Drivers of

Using Systems Thinking To Understand the Drivers of

Brucellosis Transmission in Jordan

1. Abstract:

Brucellosis disease leads to a significant production loss in ruminants and febrile disease in human in several places around the world

particularly Africa, Asia and the Middle East. In Jordan, Brucellosis is endemic but has been increasing in the past few years. However, the

only focus of the control programs is primarily the vaccination of livestock. The aim of this project is to understand the dynamic drivers of

brucellosis transmission to explore policy options that aid in controlling human brucellosis in Jordan. Method: System dynamics modelling

approach was used to create a causal loop diagram and a stock and flow model that suggest the dynamics of brucellosis transmission in Jordan.

The model includes the age-structured “Susceptible-Infected-Vaccinated” sheep population model and “Susceptible-Infected-Recovered”

human population model. Results: the model suggests four different policies to control brucellosis in Jordan other than vaccination; Sheep

trade market restrictions; testing and culling infected sheep; increase farmers’ visits to the ministry of agriculture’s veterinary clinics and

increase awareness of farmers. Conclusion: Current data suggest that other policies should be considered to help authorities to control

brucellosis transmission. Collaboration between stakeholders is essential to achieve better outcomes. More research is needed to assess the

implications of the proposed policies.

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

Years

Inci

den

ce r

ate

/100,0

0

Nu

mb

er o

f ca

ses

Human Brucellosis cases and incidence rate in Jordan (2004-2017)

cases (MoH) Incidence rate/100,000

Phase 1

Problem Identification & structuring

Phase 2

Causal loop modelling

Understand behaviour of system

Phase 3

Dynamic modelling

Simulation & quantification

Phase 4

Scenario analysis, evaluation and policy

implication

Research question 1

What is the problem?

Research question 2

Why the problem exist?

Research question 3

How can we manage the

problem?

Research question 4

What are the implication of

managing this problem?

Methods 1

Analysis of historical data

BOT Analysis, Literature review

Methods 2

Literature review, Semi-Interviews, Causal

Loop Diagram, Archetype

Methods 3

Stock & flow Model development, testing,

sensitivity analysis.

Methods 4

Scenario analysis, policy evaluation

2. The Methods

Figure 1: Figure: Human Brucellosis cases and incidence rate (per 100,000) in Jordan (2004-2017)

3. The Results:

Figure 3: stakeholder’s Map of brucellosis transmission in Jordan

3.3 The Causal Loop Diagram

Figure 4: Presentation of overall qualitative data analysis process, participants map and Causal loop diagram building.

3.2 Building the Causal Loop Diagram

Figure 5: Combined causal loop diagram of brucellosis dynamics in Jordan.

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

Rep

ort

ed

Case

s /1

00,0

00

Time

Reported Human brucellosis cases by the proposed policies

Current PolicyVacciantion Only

Trade (Buy&Sell)Restriction

Test & CullSheep

Increase visits toVeterinary clinics

IncreaseAwareness

CombinedCull and trade restrictions

Figure 6: Combined Stock and flow diagrams (The Model) of brucellosis dynamics in Jordan.

Figure 7: Proposed policies for Brucellosis control and overall reported human cases per 100,000.

Figure 2: Brief description of the research method

3.1 Stakeholder Analysis: The Map

3.4 The Model (Stock and Flow Diagrams)

3.5 Behaviour over time graph of reported brucellosis cases by the proposed policies

References:

1. Musallam, II, Abo-Shehada MN, Guitian J. Knowledge, Attitudes, and Practices Associated with Brucellosis in Livestock Owners in Jordan. Am J Trop Med Hyg. 2015;93(6):1148-55.

2. Beauvais W, Musallam I, Guitian J. Vaccination control programs for multiple livestock host species: an age-stratified, seasonal transmission model for brucellosis control in endemic

settings. Parasites & vectors. 2016;9:55.

3. Musallam, II, Abo-Shehada M, Omar M, Guitian J. Cross-sectional study of brucellosis in Jordan: Prevalence, risk factors and spatial distribution in small ruminants and cattle. Preventive

veterinary medicine. 2015;118(4):387-96.

4. Sterman JD. Business dynamics: Systems thinking and modeling for a complex world. Boston: Irwin/McGraw-Hill; 2000.

5. Franc KA, Krecek RC, Hasler BN, Arenas-Gamboa AM. Brucellosis remains a neglected disease in the developing world: a call for interdisciplinary action. BMC public health.

2018;18(1):125.

6. Agriculture-Jordan Mo. MoA Jordan 2018 [Available from: http://moa.gov.jo/ar-jo/home.aspx. Accessed

7. Zhou L, Fan M, Hou Q, Jin Z, Sun X. Transmission dynamics and optimal control of brucellosis in Inner Mongolia of China. Mathematical biosciences and engineering : MBE.

2018;15(2):543-67.

Acknowledgements:

I would like to appreciate the great effort put into this poster design by my lovely wife, Nermin, you are the strength that keeps me going. Additionally, I would like to thank

the great inspiration, Danielle Currie for the continuous support and guidance in this project. Finally, I would like to appreciate and thank Simon Reid and Carl Smith for

their guidance throughout this project.

H.Taha1, S.Reid2, C.Smith3, J. Durham4, D.Currie5 (1,2,3,4 The University Of Queensland 5 The Sax institute)