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Exploring Trade and Health Policies Influence on Dengue Spread with an Agent-Based Model
Exploring Trade and Health Policies Influence on Dengue Spread with an Agent-Based Model
International audience; With the globalization, several free trade areas have been and are being created all around the world. They usually have positive consequences for increasing economic exchanges, but negative ecological or health side effects. These negative effects are difficult to predict or even to understand due to the complexity of the system and of the number of involved processes. In this article, we focus on the Southeast Asia free trade area (the ASEAN) and specifically in the East-West economic corridor. A significant correlation has been observed in this area between the corridor opening and dengue fever cases, without being able to establish a causality relationship. We choose to tackle this issue by building an agent-based geographically explicit model. We propose an approach coupling dengue fever dynamics, climate data, economic mobility and health policies, following a design methodology decomposing these processes in sub-models and linking them to make one integrated model. In addition, we propose a way to deal with lack of data in the modeling process. Our simulation results show that there is influence of the increase in mobility and application of different control policies on the increase of dengue cases.
- Université Paris Diderot France
- Institut de Recherche pour le Développement France
- University of Oxford United Kingdom
- University of Toulouse France
- University of Rouen France
Microsoft Academic Graph classification: Agent-based model Process (engineering) Economic mobility Causality Globalization International free trade agreement Business Economic system Free trade Health policy
Agent-based model, [SDV]Life Sciences [q-bio], Epidemiological model, Modélisation et simulation, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, Health policy, H- INFORMATIQUE, GIS data
Agent-based model, [SDV]Life Sciences [q-bio], Epidemiological model, Modélisation et simulation, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, Health policy, H- INFORMATIQUE, GIS data
Microsoft Academic Graph classification: Agent-based model Process (engineering) Economic mobility Causality Globalization International free trade agreement Business Economic system Free trade Health policy
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2. Bhatt, S., Gething, P.W., Brady, O.J., Messina, J.P., Farlow, A.W., Moyes, C.L., Myers, M.F.: The global distribution and burden of dengue. Nature (2013)
3. Gaudou, B., et al.: The MAELIA multi-agent platform for integrated analysis of interactions between agricultural land-use and low-water management strategies. In: Alam, S.J., Parunak, H.V.D. (eds.) MABS 2013. LNCS, vol. 8235, pp. 85-100. Springer, Heidelberg (2014). doi:10.1007/978-3-642-54783-6_6
4. Grignard, A., Taillandier, P., Gaudou, B., Vo, D.A., Huynh, N.Q., Drogoul, A.: GAMA 1.6: advancing the art of complex agent-based modeling and simulation. In: Boella, G., Elkind, E., Savarimuthu, B.T.R., Dignum, F., Purvis, M.K. (eds.) PRIMA 2013. LNCS (LNAI), vol. 8291, pp. 117-131. Springer, Heidelberg (2013). doi:10.1007/978-3-642-44927-7_9 [OpenAIRE]
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6. Lloyd, L.S., Beaver, C., Seng, C.M.: Managing regional public goods for health community-based dengue vector control. Technical report, Asian Development Bank, World Health Organization (2013)
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).6 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).6 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
Citations provided by BIP!Popularity provided by BIP!
- Université Paris Diderot France
- Institut de Recherche pour le Développement France
- University of Oxford United Kingdom
- University of Toulouse France
- University of Rouen France
- Can Tho University Viet Nam
- National Polytechnic Institute of Toulouse France
- Toulouse 1 Capitole University France
- Paris 13 University France
International audience; With the globalization, several free trade areas have been and are being created all around the world. They usually have positive consequences for increasing economic exchanges, but negative ecological or health side effects. These negative effects are difficult to predict or even to understand due to the complexity of the system and of the number of involved processes. In this article, we focus on the Southeast Asia free trade area (the ASEAN) and specifically in the East-West economic corridor. A significant correlation has been observed in this area between the corridor opening and dengue fever cases, without being able to establish a causality relationship. We choose to tackle this issue by building an agent-based geographically explicit model. We propose an approach coupling dengue fever dynamics, climate data, economic mobility and health policies, following a design methodology decomposing these processes in sub-models and linking them to make one integrated model. In addition, we propose a way to deal with lack of data in the modeling process. Our simulation results show that there is influence of the increase in mobility and application of different control policies on the increase of dengue cases.