Epidemiological Modeling
To address this problem we use multiple epidemiological modeling approaches:
Compartment Model
- Deterministic, age-specific compartment model.
- Macro method models population as a whole.
- We produce the analysis based on 1000 simulation runs over a range of possible parameters.
- Inputs: Area-specific parameters (population size and demographics), Asymptomatic infection rate, Days remaining infectious, etc.
Network Model
- Stochastic, network model with SEIRS dynamics.
- People are vertices and their interactions with others are edges (including a weight for the strength of interaction).
- Our analysis is based on 3 simulation networks.
- Inputs: Area-specific parameters (population size and demographics), Relationships between the residents, Asymptomatic infection rate, Days remaining infectious, etc.
Agent-based Model
- Digital prototype of the given camp.
- 500 agents act based on rules informed by research; experts in the area outline behaviour and demographics.
- Inputs: Transmission probability, Incubation time, Infection and recovery probabilities.
Project objectives
Real time insights from our models will have impact in the following areas:
Empower NGOs
Essential supply forecasting
Serve as a tool for NGOs and grassroots organisations to mobilise action and coordinate efforts to prepare and contain COVID-19
Inform Policy Making
Decision making on the ground
Inform governments, camp management and local authorities and help them make responsible decisions in a timely manner
Save People's Lives
Reducing the spread and fatalities
Identify the most effective COVID-19 interventions designed for refugee camps and help avoid severe casualties
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