Case Study of Collaborative Modeling in an Indigenous Community
Abstract
:1. Introduction
1.1. Land Acknowledgement and Positionality Statement
1.2. Context
1.3. Agent-Based Modeling
1.4. Discrete Event Simulation
1.5. System Dynamics Modeling
1.6. Objectives
- Grounded by diverse data sources, develop a model framework with ABM to assess and investigate comprehensive impacts on the community members from flooding,
- Demonstrate the capability of ABMs as an operational tool for evaluating and supporting health services and emergency planning and management measures, and,
- Contribute to the sustainability of the community and their environment by providing a tool to investigate complex interactions and feedbacks between human and natural systems and to communicate understanding of flooding impacts and improvements to mitigation measures.
2. Materials and Methods
2.1. Ethics
2.2. Community Engagement
2.3. Simulation Model
2.3.1. Model Purpose and Scope
2.3.2. Agents
2.3.3. GIS Environment
2.3.4. Flooding
2.3.5. Health Conditions
2.4. Scenarios and Parameterization
2.4.1. Scenarios
2.4.2. Parameters
2.5. Outcome Measures
2.6. Experiments
3. Results
3.1. Contaminated Truck Scenario
3.1.1. Model Outcomes
3.1.2. Ensemble Results
3.2. Pow Wow Scenario
3.2.1. Model Outcomes
3.2.2. Ensemble Results
3.3. Mobility Impacts from Flooding Scenario
3.3.1. Model Outcomes
3.3.2. Ensemble Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
Appendix A.1. Objectives
Appendix A.1.1. Purpose
Appendix A.1.2. Entities, State Variable, and Scales
Name | Description |
Person | |
Age | The person’s age in years |
Sex | The person’s sex |
Home Location | The Place representing the person’s home |
Work Location | The Place representing the person’ workplace, if any |
Care-seeking probability | Probability the person will seek care if unhealthy |
Health Conditions | Health Conditions the person has |
Place | |
Unique ID | ID of this place |
Location | Geographic location |
People Inside | Person agents inside this place |
Water Source | Water source for the place |
Water Source | |
ID | ID of this water source |
Location | Geographic location |
Source | Parent water source for the source, if any |
Reservoir Level | Level of reservoir for the source |
Secondary Sources | Water sources drawing from the source |
Water Transporter | |
Home Base | Water source where the transporter refills |
Location | Geographic location |
Reservoir Level | Level of transporter’s reservoir |
Health Condition | |
Duration | Duration of the condition |
Symptom Type | Curve shape for symptom severity vs. condition progression |
Transmission Type | Means of transmission of the condition, if any |
Transmissivity Begins | Point in progression where transmissivity begins |
Transmissivity Ends | Point in progression where transmissivity ends |
Prob of Transmission | Probability of transmission on exposure |
Full Recovery | Whether the person recover fully at end of condition progression |
Prob of Death | Probability of death from the condition |
Curable | Is the condition curable through treatment |
Treatment Symptom Mult | Multiplier on symptoms due to treatment |
Treatment Death Multiplier | Multiplier on probability of death due to treatment |
Immunity Period | Duration of immunity after recovery |
Treatment Duration | Duration of treatment |
Pond | |
Region | The GIS region associated with the pond |
Collisions | Count of the number of agents that have “collided” with the pond |
Appendix A.1.3. Process Overview and Scheduling
Appendix A.2. Design Concepts
Appendix A.2.1. Basic Principles
Appendix A.2.2. Emergence
Appendix A.2.3. Adaptation
Appendix A.2.4. Sensing
Appendix A.2.5. Interaction
Appendix A.2.6. Stochasticity
Appendix A.2.7. Collectives
Appendix A.2.8. Observation
Appendix A.3. Details
Appendix A.3.1. Initialization
Appendix A.3.2. Input Data
Appendix A.3.3. Parameters
Parameter | Default Value |
numWaterTrucks | 1 |
probability cistern contaminated by truck | 1 |
waterUsePerPersonPerDay (cistern) | 200 L/person/day [5] |
waterUsePerPersonPerDay (piped) | 500 L/person/day |
fracDiabetics | 0.02 |
isShowingBuildings | TRUE |
isShowingWaterSources | TRUE |
isShowingPeople | TRUE |
scenario | FREEFORM |
isUsingAltArt | FALSE |
isShowingLegend | TRUE |
iconScaleFactor | 1.0 |
slowForAgentMovements | FALSE |
slowTimeScale | 0.002 |
fastTimeScale | 0.1 |
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SD | DES | ABM | |
---|---|---|---|
Perspective | Top-down | Top-down | Bottom-up |
Stochasticity | Deterministic | Stochastic | Stochastic |
Building Blocks | Stocks, flows, feedback | Entities, events, queues | Agents, decision rules |
Development time | Low | High | High |
Population Scalability | Good | Poor | Poor |
Heterogeneity | Complex | Simple | Simple |
Network Effects | No | Yes | Yes |
Parameter | Baseline Value |
---|---|
Demographics | |
Population | 800 1 |
Male: Female ratio | 1.0 |
Unemployed fraction—Male | 0.5 2 |
Unemployed fraction—Female | 0.15 2 |
Prevalence of diabetes requiring dialysis | 0.02 |
Water Delivery | |
Probability contaminated truck results in contaminated cistern | 1.0 |
Waterborne Illness Natural History | |
Rate of infection by waterborne pathogen from contaminated premises | 0.75/6 h |
Latent period | 1 day |
Infectious period | 3 days |
Rate of person-to-person transmission | 0.25 per 0.1 days |
Duration of immunity | 14 days |
Clinic Operations | |
Rate ill person will seek care | 1.0/day |
Time until leaving clinic without care | 1.0–6.0 h |
Number of health care workers | 1 |
Number of beds available | 4 |
Time for appointment | 5 min |
Time using bed after appointment | 0 min |
Parameter | Baseline Value |
---|---|
Rate of person-to-person transmission | 0.25/0.1 days |
Duration of waterborne illness | 5 days |
Probability delivery truck is contaminated | 0.0 |
Truck decontamination | Never |
Rainfall | 0 mm |
Scenario | Variation | Description |
---|---|---|
Contaminated Truck | Baseline 1 | Baseline scenario |
Alt 1 | Disease is not transmissible person-to-person | |
Alt 2 | 2-day longer illness duration | |
Alt 3 | Disease is not transmissible person-to-person; 2-day longer illness duration | |
Cleaning 1 | Truck is decontaminated daily | |
Cleaning 1 Alt 1 | Truck is decontaminated daily; disease is not transmissible person-to-person | |
Cleaning 5 | Truck is decontaminated every 5 days | |
Cleaning 5 Alt 1 | Truck is decontaminated every 5 days; disease is not transmissible person-to-person | |
Pow Wow | Baseline 1 | Baseline scenario |
Alt 1 | Disease is not transmissible person-to-person | |
Alt 2 | 2-day longer illness duration | |
Alt 3 | Disease is not transmissible person-to-person; 2-day longer illness duration | |
Movement | Baseline 1 | No flooding |
10 mm | Flood due to 10 mm precipitation event | |
20 mm | Flood due to 20 mm precipitation event | |
100 mm | Flood due to 100 mm precipitation event |
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Share and Cite
McDonald, G.W.; Bradford, L.; Neapetung, M.; Osgood, N.D.; Strickert, G.; Waldner, C.L.; Belcher, K.; McLeod, L.; Bharadwaj, L. Case Study of Collaborative Modeling in an Indigenous Community. Water 2022, 14, 2601. https://doi.org/10.3390/w14172601
McDonald GW, Bradford L, Neapetung M, Osgood ND, Strickert G, Waldner CL, Belcher K, McLeod L, Bharadwaj L. Case Study of Collaborative Modeling in an Indigenous Community. Water. 2022; 14(17):2601. https://doi.org/10.3390/w14172601
Chicago/Turabian StyleMcDonald, Gavin Wade, Lori Bradford, Myron Neapetung, Nathaniel D. Osgood, Graham Strickert, Cheryl L. Waldner, Kurt Belcher, Lianne McLeod, and Lalita Bharadwaj. 2022. "Case Study of Collaborative Modeling in an Indigenous Community" Water 14, no. 17: 2601. https://doi.org/10.3390/w14172601
APA StyleMcDonald, G. W., Bradford, L., Neapetung, M., Osgood, N. D., Strickert, G., Waldner, C. L., Belcher, K., McLeod, L., & Bharadwaj, L. (2022). Case Study of Collaborative Modeling in an Indigenous Community. Water, 14(17), 2601. https://doi.org/10.3390/w14172601