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Application of system dynamics and participatory spatial group model building in animal health: A case study of East Coast Fever interventions in Lundazi and Monze districts of Zambia.

Abstract East Coast Fever (ECF) is the most economically important production disease among traditional beef cattle farmers in Zambia. Despite the disease control efforts by the government, donors, and farmers, ECF cases are increasing. Why does ECF oscillate over time? Can alternative approaches such as systems thinking contribute solutions to the complex ECF problem, avoid unintended consequences, and achieve sustainable results? To answer these research questions and inform the design and implementation of ECF interventions, we qualitatively investigated the influence of dynamic socio-economic, cultural, and ecological factors. We used system dynamics modelling to specify these dynamics qualitatively, and an innovative participatory framework called spatial group model building (SGMB). SGMB uses participatory geographical information system (GIS) concepts and techniques to capture the role of spatial phenomenon in the context of complex systems, allowing stakeholders to identify spatial phenomenon directly on physical maps and integrate such information in model development. Our SGMB process convened focus groups of beef value chain stakeholders in two distinct production systems. The focus groups helped to jointly construct a series of interrelated system dynamics models that described ECF in a broader systems context. Thus, a complementary objective of this study was to demonstrate the applicability of system dynamics modelling and SGMB in animal health. The SGMB process revealed policy leverage points in the beef cattle value chain that could be targeted to improve ECF control. For example, policies that develop sustainable and stable cattle markets and improve household income availability may have positive feedback effects on investment in animal health. The results obtained from a SGMB process also demonstrated that a "one-size-fits-all" approach may not be equally effective in policing ECF in different agro-ecological zones due to the complex interactions of socio-ecological context with important, and often ignored, spatial patterns.
PMID
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Authors

Mayor MeshTerms
Keywords
Journal Title plos one
Publication Year Start




PMID- 29244862
OWN - NLM
STAT- In-Process
LR  - 20171224
IS  - 1932-6203 (Electronic)
IS  - 1932-6203 (Linking)
VI  - 12
IP  - 12
DP  - 2017
TI  - Application of system dynamics and participatory spatial group model building in 
      animal health: A case study of East Coast Fever interventions in Lundazi and
      Monze districts of Zambia.
PG  - e0189878
LID - 10.1371/journal.pone.0189878 [doi]
AB  - East Coast Fever (ECF) is the most economically important production disease
      among traditional beef cattle farmers in Zambia. Despite the disease control
      efforts by the government, donors, and farmers, ECF cases are increasing. Why
      does ECF oscillate over time? Can alternative approaches such as systems thinking
      contribute solutions to the complex ECF problem, avoid unintended consequences,
      and achieve sustainable results? To answer these research questions and inform
      the design and implementation of ECF interventions, we qualitatively investigated
      the influence of dynamic socio-economic, cultural, and ecological factors. We
      used system dynamics modelling to specify these dynamics qualitatively, and an
      innovative participatory framework called spatial group model building (SGMB).
      SGMB uses participatory geographical information system (GIS) concepts and
      techniques to capture the role of spatial phenomenon in the context of complex
      systems, allowing stakeholders to identify spatial phenomenon directly on
      physical maps and integrate such information in model development. Our SGMB
      process convened focus groups of beef value chain stakeholders in two distinct
      production systems. The focus groups helped to jointly construct a series of
      interrelated system dynamics models that described ECF in a broader systems
      context. Thus, a complementary objective of this study was to demonstrate the
      applicability of system dynamics modelling and SGMB in animal health. The SGMB
      process revealed policy leverage points in the beef cattle value chain that could
      be targeted to improve ECF control. For example, policies that develop
      sustainable and stable cattle markets and improve household income availability
      may have positive feedback effects on investment in animal health. The results
      obtained from a SGMB process also demonstrated that a "one-size-fits-all"
      approach may not be equally effective in policing ECF in different
      agro-ecological zones due to the complex interactions of socio-ecological context
      with important, and often ignored, spatial patterns.
FAU - Mumba, Chisoni
AU  - Mumba C
AUID- ORCID: http://orcid.org/0000-0002-4662-0876
AD  - The University of Zambia, School of Veterinary Medicine, Department of Disease
      Control, Lusaka, Zambia.
AD  - Norwegian University of Life Sciences, Department of Food Safety and Infection
      Biology, Section for Epidemiology and Statistics (Epicentre), Oslo, Norway.
FAU - Skjerve, Eystein
AU  - Skjerve E
AD  - Norwegian University of Life Sciences, Department of Food Safety and Infection
      Biology, Section for Epidemiology and Statistics (Epicentre), Oslo, Norway.
FAU - Rich, Magda
AU  - Rich M
AD  - University of Brighton, College of Arts and Humanities, Grand Parade, United
      Kingdom.
FAU - Rich, Karl M
AU  - Rich KM
AD  - International Livestock Research Institute (ILRI), East and Southeast Asia
      Regional Office, Ba Dinh District, Hanoi, Viet Nam.
LA  - eng
PT  - Journal Article
DEP - 20171215
PL  - United States
TA  - PLoS One
JT  - PloS one
JID - 101285081
PMC - PMC5731699
EDAT- 2017/12/16 06:00
MHDA- 2017/12/16 06:00
CRDT- 2017/12/16 06:00
PHST- 2017/06/30 00:00 [received]
PHST- 2017/12/04 00:00 [accepted]
PHST- 2017/12/16 06:00 [entrez]
PHST- 2017/12/16 06:00 [pubmed]
PHST- 2017/12/16 06:00 [medline]
AID - 10.1371/journal.pone.0189878 [doi]
AID - PONE-D-17-24752 [pii]
PST - epublish
SO  - PLoS One. 2017 Dec 15;12(12):e0189878. doi: 10.1371/journal.pone.0189878.
      eCollection 2017.