[en] While climate is often presented as a key factor influencing the seasonality of diseases, the importance of anthropogenic factors is less commonly evaluated. Using a combination of methods - wavelet analysis, economic analysis, statistical and disease transmission modelling - we aimed to explore the influence of climatic and economic factors on the seasonality of H5N1 Highly Pathogenic Avian Influenza in the domestic poultry population of Vietnam. We found that while climatic variables are associated with seasonal variation in the incidence of avian influenza outbreaks in the North of the country, this is not the case in the Centre and the South. In contrast, temporal patterns of H5N1 incidence are similar across these 3 regions: periods of high H5N1 incidence coincide with Lunar New Year festival, occurring in January-February, in the 3 climatic regions for 5 out of the 8 study years. Yet, daily poultry meat consumption drastically increases during Lunar New Year festival throughout the country. To meet this rise in demand, poultry production and trade are expected to peak around the festival period, promoting viral spread, which we demonstrated using a stochastic disease transmission model. This study illustrates the way in which economic factors may influence the dynamics of livestock pathogens.
Disciplines :
Veterinary medicine & animal health
Author, co-author :
Delabouglise, Alexis
Choisy, Marc
Phan, Thang D.
Antoine-Moussiaux, Nicolas ; Université de Liège > Département des productions animales (DPA) > Biostatistique, économie, sélection animale
Peyre, Marisa
Vu, Ton D.
Pfeiffer, Dirk U.
Fournie, Guillaume
Language :
English
Title :
Economic factors influencing zoonotic disease dynamics: demand for poultry meat and seasonal transmission of avian influenza in Vietnam.
Lipsitch, M. & Viboud, C. Influenza seasonality: Lifting the fog. Proc. Natl. Acad. Sci. USA 106, 3645-3646, doi:10.1073/pnas.0900933106 (2009).
Thai, P. Q. et al. Seasonality of absolute humidity explains seasonality of influenza-like illness in Vietnam. Epidemics 13, 65-73, doi:10.1016/j.epidem.2015.06.002 (2015).
Tamerius, J. et al. Global Influenza Seasonality: Reconciling Patterns across Temperate and Tropical Regions. Environ. Health Perspect. 119, 439-445, doi:10.1289/ehp.1002383 (2010).
Shaman, J. & Kohn, M. Absolute humidity modulates influenza survival, transmission, and seasonality. Proc. Natl. Acad. Sci. USA 106, 3243-3248, doi:10.1073/pnas.0806852106 (2009).
FAO. Approaches to controlling, preventing and eliminating H5N1 Highly Pathogenic Avian Influenza in endemic countries. (Food and Agriculture Organization of the United Nations, 2011).
FAO. EMPRES-I, Global Animal Disease Information System. http://empres-i.fao.org/eipws3g/(2014) (date of access: 05/05/2015).
WHO. Avian Influenza. http://www.who.int/mediacentre/factsheets/avian-influenza/en/(2014) (date of access: 10/10/2015).
Imai, M. et al. Experimental adaptation of an influenza H5 HA confers respiratory droplet transmission to a reassortant H5 HA/H1N1 virus in ferrets. Nature 486, 420-428, doi:10.1038/nature10831 (2012).
Durand, L. O. et al. Timing of influenza A(H5N1) in poultry and humans and seasonal influenza activity worldwide, 2004-2013. Emerg. Infect. Dis. 21, 202-208, doi:10.3201/eid2102.140877 (2015).
Park, A. W. & Glass, K. Dynamic patterns of avian and human influenza in east and southeast Asia. Lancet Infect. Dis. 7, 543-548, doi:10.1016/s1473-3099(07)70186-x (2007).
Murray, E. J. & Morse, S. S. Seasonal oscillation of human infection with influenza A/H5N1 in Egypt and Indonesia. PLoS One 6, e24042, doi:10.1371/journal.pone.0024042 (2011).
Fang, L. Q. et al. Environmental factors contributing to the spread of H5N1 avian influenza in mainland China. PLoS One 3, e2268, doi:10.1371/journal.pone.0002268 (2008).
Loth, L., Gilbert, M., Osmani, M. G., Kalam, A. M. & Xiao, X. Risk factors and clusters of Highly Pathogenic Avian Influenza H5N1 outbreaks in Bangladesh. Prev. Vet. Med. 96, 104-113, doi:10.1016/j.prevetmed.2010.05.013 (2010).
Pfeiffer, D. U., Minh, P. Q., Martin, V., Epprecht, M. & Otte, M. J. An analysis of the spatial and temporal patterns of highly pathogenic avian influenza occurrence in Vietnam using national surveillance data. Vet. J. 174, 302-309, doi:10.1016/j. tvjl.2007.05.010 (2007).
Gilbert, M. et al. Mapping H5N1 highly pathogenic avian influenza risk in Southeast Asia. Proc. Natl. Acad. Sci. USA 105, 4769-4774, doi:10.1073/pnas.0710581105 (2008).
Gilbert, M. et al. Free-grazing ducks and highly pathogenic avian influenza, Thailand. Emerg. Infect. Dis. 12, 227-234, doi:10.3201/eid1202.050640 (2006).
Ahmed, S. S. et al. Ecological determinants of highly pathogenic avian influenza (H5N1) outbreaks in Bangladesh. PLoS One 7, e33938, doi:10.1371/journal.pone.0033938 (2012).
Desvaux, S. et al. Risk Factors of Highly Pathogenic Avian Influenza H5N1 Occurrence at the Village and Farm Levels in the Red River Delta Region in Vietnam. Transbound. Emerg. Dis. 58, 492-502, doi:10.1111/j.1865-1682.2011.01227.x (2011).
Fournie, G. et al. Interventions for avian influenza A (H5N1) risk management in live bird market networks. Proc. Natl. Acad. Sci. USA 110, 9177-9182, doi:10.1073/pnas.1220815110 (2013).
Colman, D. & Young, G. Product supply and input demand in Principles of Agricultural Economics (eds D. Colman & G. Young) 30-48 (Cambridge University Press, 1989).
Ward, C. E. Vertical Integration Comparison: Beef, Pork, and Poultry. 15 (Oklahoma State University, 1997).
General Statistics Office of Vietnam. Results of the Vietnam Living Standards Survey 2004. (Vietnam Statistical Publishing House, 2004).
Minh, P. Q. et al. Spatio-temporal epidemiology of highly pathogenic avian influenza outbreaks in the two deltas of Vietnam during 2003-2007. Prev. Vet. Med. 89, 16-24, doi:10.1016/j.prevetmed.2009.01.004 (2009).
Hong Hanh, P. T., Burgos, S. & Roland-Holst, D. The Poultry Sector in Viet Nam: Prospects for Smallholder Producers in the Aftermath of the HPAI Crisis. Pro-Poor Livestock Policy Initiative Research Report. (Food and Agriculture Organisation of the United Nations, 2007).
AAC. Vietnam's Market for Imported Meat and Poultry. A guide for Canadian Exporters. (Agriculture and Agri-Food Canada, 2010).
Epprecht, M. Geographic Dimensions of Livestock Holdings in Vietnam. Spatial Relationships among Poverty, Infrastructure and the Environment. (Ministry of Agriculture and Rural Development of Vietnam, 2005).
Delabouglise, A. et al. The Perceived Value of Passive Animal Health Surveillance: The Case of Highly Pathogenic Avian Influenza in Vietnam. Zoonoses Public Health 63, 112-128, doi:10.1111/zph.12212 (2016).
Soares Magalhaes, R. J. et al. Live poultry trade in Southern China provinces and HPAIV H5N1 infection in humans and poultry: the role of Chinese New Year festivities. PLoS One 7, e49712, doi:10.1371/journal.pone.0049712 (2012).
Phan, D. T., Vu, D. T., Dogot, T. & Lebailly, P. Financial analysis of poultry commodity chains in Hanoi Suburb, North of Vietnam in Proceedings of Scientific Research Results-Institutional University Cooperation Program 2008-2012 (ed Hanoi University of Agriculture Francophone Joint University Council (CIUF)) 101-106 (Hanoi University of Agriculture, 2013).
Desvaux, S. et al. Risk of Introduction in Northern Vietnam of HPAI Viruses from China: Description, Patterns and Drivers of Illegal Poultry Trade. Transbound. Emerg. Dis. doi:10.1111/tbed.12279 (2014).
Davis, C. T. et al. Detection and Characterization of Clade 7 High Pathogenicity Avian Influenza H5N1 Viruses in Chickens Seized at Ports of Entry and Live Poultry Markets in Vietnam. Avian Dis. 54, 307-312, doi:10.1637/8801-040109-ResNote.1 (2010).
Minh, P. Q., Stevenson, M. A., Jewell, C., French, N. & Schauer, B. Spatio-temporal analyses of highly pathogenic avian influenza H5N1 outbreaks in the Mekong River Delta, Vietnam, 2009. Spat. Spatiotemporal Epidemiol. 2, 49-57 (2011).
Khanh Hoa Journal. Lĩnh vuc chǎn nuôi heo, gà: Môt nǎm khôn dôn [Pig and poultry husbandry sectors: a cursed year]. http://www. baokhanhhoa.com.vn/kinh-te/201212/linh-vuc-chan-nuoi-heo-ga-mot-nam-khon-don-2207388/(2012) (date of access: 20/06/2016).
The Pig Site. Vietnam: Hog Markets. http://www.thepigsite.com/swinenews/35734/viet-nam-hog-markets/(2012) (date of access: 20/06/2016).
Greenfeed Vietnam. Chǎn nuôi gà bán công nghiêp & gà tha vuon: Xu huong kinh doanh moi [Industrial and backyard poultry farming: recent business tendency]. http://www.greenfeed.com.vn/en/news/222/chan-nu.html (2012) (date of access: 20/06/2016).
Nguyen, L. Nguy co "sôt" thi truong thit lon, gà cuôi nǎm [Risk of pork and poultry meat market fever on the end of the year]. http://toquoc.vn/kinh-te-viet-nam/nguy-co-sot-thi-truong-thit-lon-ga-cuoi-nam-108681.html (2012) (date of access: 20/06/2016).
Ministry of Agriculture and Rural Development of Vietnam. Agricultural prices database. http://agro.gov.vn/news/nguonwmy.aspx (2016) (date of access: 14/08/2016).
ACI. Poultry Sector Rehabilitation Project-Phase I: The Impact of Avian Influenza on Poultry Sector Restructuring and its Socioeconomic Effects. Prepared for the Food and Agriculture Organization of the United Nations. (Agrifood Consulting International, 2006).
Department of Animal Health of Vietnam. Official Guide of avian influenza surveillance in years 2011-2012. (Department of Animal Health of Vietnam, 2011).
Tung, P. D. & Nugyen, P. Vietnam Household Living Standard Survey (VHLSS) 2002 and 2004. Basic Information. (Social and Environment Statistics Department, General Statistics Office of Vietnam, 2005).
Jain, A. K., Murty, M. N. & Flynn, P. J. Data Clustering: A Review. ACM Comput. Surv. 31, 264-323 (1999).
Badr, H. S., Zaitchik, B. F. & Dezfuli, A. K. A tool for hierarchical climate regionalization. Earth Sci. Inform. 8, 949-958, doi:10.1007/s12145-015-0221-7 (2015).
Murtagh, F. & Legendre, P. Ward's Hierarchical Agglomerative Clustering Method: Which Algorithms Implement Ward's Criterion? J. Classif. 31, 274-295, doi:10.1007/s00357-014-9161-z (2014).
Cazelles, B. et al. Wavelet analysis of ecological time series. Oecologia 156, 287-304, doi:10.1007/s00442-008-0993-2 (2008).
Morris, A. et al. Complex temporal climate signals drive the emergence of human water-borne disease. Emerg. Microbes Infect. 3, e56, doi:10.1038/emi.2014.56 (2014).
Gouhier, T. biwavelet: conduct univariate and bivariate wavelet analyses (version 0.17.4). http://github.com/tgouhier/biwavelet (2014) (date of access: 11/07/2015).
Schlattmann, P. Medical Applications of Finite Mixture Models. 252 (Springer, 2009).
Biernacki, C., Celeux, G. & Govaert, G. Assessing a mixture model for clustering with the integrated completed likelihood. IEEE Trans. Pattern Anal. Mach. Intell. 22, 719-725, doi:10.1109/34.865189 (2000).
Baudry, J. P., Raftery, A. E., Celeux, G., Lo, K. & Gottardo, R. Combining Mixture Components for Clustering. J. Comput. Graph. Stat. 9, 332-353, doi:10.1198/jcgs.2010.08111 (2010).
De Boer, P. T., Kroese, D. P., Mannor, S. & Rubinstein, R. Y. A tutorial on the cross-entropy method. Ann Oper Res 134, 19-67, doi:10.1007/s10479-005-5724-z (2005).
Stuart, A. & Ord, K. Kendall's Advanced Theory of Statistics. Volume 2A, Classical Inference and the Linear Model. 6th Edition. (Edward Arnold, 1998).
Wears, L. R. Advanced Statistics: Statistical Methods for Analyzing Cluster and Cluster-randomized Data. Acad. Emerg. Med. 9, 330-341 (2002).
General Statistics Office of Vietnam. Results of the 2006 Rural, Agriculture and Fishery Census. (Vietnam Statistical Publishing House, 2007).
Toni, T., Welch, D., Strelkowa, N., Ipsen, A. & Stumpf, M. P. H. Approximate Bayesian computation scheme for parameter inference and model selection in dynamical systems. J. R. Soc. Interface 6, 187-202, doi:10.1098/rsif.2008.0172 (2009).
R core team. R: a language and environment for statistical computing. http://www.R-project.org/(2014) (date of access: 08/10/2012).