Economic Impact Framework
MHASpread integrates epidemiological simulation with economic modeling to assess the cost-effectiveness of disease control strategies.
Overview
While MHASpread provides detailed epidemiological outputs (infected farms, animals affected, outbreak duration), downstream economic models incorporate these results to evaluate:
- Direct costs: Depopulation, vaccination, diagnosis
- Indirect costs: Market disruption, trade restrictions, lost productivity
- Benefits: Disease avoidance, prevented spread
- Cost-effectiveness: Cost per farm or animal protected
Epidemiological Outputs from MHASpread
MHASpread simulations generate outputs that feed into economic models:
Farm-Level Outcomes
- Farms depopulated: Number culled as disease control
- Farms vaccinated: Number receiving emergency ring vaccination
- Farms infected: Total farms affected by disease
- Escape farms: Uninfected farms outside control zones
Animal-Level Outcomes
By species and compartment:
- Total animals infected: Sum of $I$ compartment across all farms
- Animals recovered: Naturally immune survivors
- Animals vaccinated: Cattle receiving emergency vaccine
- Animals depopulated: Culled animals (by species)
Temporal Outcomes
- Outbreak duration: Days from index case to elimination
- Silent spread duration: Undetected pre-control phase
- Active control duration: Days with ongoing interventions
- Peak prevalence: Maximum infected animals/farms simultaneously
Network Outcomes
- Movement events blocked: Standstill-prevented trade
- Traceback links traced: Farms identified via contact tracing
- Spatial extent: Maximum distance from index farm of last case
Cost Components
Direct Costs
Depopulation Costs
\[\text{Cost}_{\text{depop}} = \sum_{\text{depopulated farms}} (\text{animal count} \times \text{value per animal}) + \text{labor} + \text{disposal}\]- Unit costs vary by species (cattle >swine > sheep)
- Example values: Cattle €500/animal, Swine €150/animal, Sheep €50/animal
- Labor/disposal: Often €1000–5000 per farm
- Total: Typically 40–60% of outbreak economic cost
Vaccination Costs
\[\text{Cost}_{\text{vax}} = \text{farms vaccinated} \times (\text{vaccine} + \text{personnel} + \text{logistics})\]- Vaccine cost: €1–2 per dose
- Personnel: Veterinarians, laborers (€10–30/hour, ~2 hours per farm)
- Logistics: Transport, equipment, cold storage (~€500–1000 per farm)
- Total per farm vaccinated: €2000–5000
Surveillance & Diagnosis
\[\text{Cost}_{\text{surv}} = \text{inspections} \times \text{cost per farm} + \text{diagnostic tests} \times \text{cost per test}\]- Farm inspection: €50–200 per farm visit
- Diagnostic test (serology, RT-PCR): €20–100 per test
- Typically 5–15% of total cost
Movement Standstill (Lost Trade)
\[\text{Cost}_{\text{standstill}} = \text{affected farms} \times \text{lost revenue per day} \times 30 \text{ days}\]- Lost revenue: Variable (dairy income, market premium loss, feed cost)
- Estimation: Average farm revenue / 365 days × number restricted farms × 30
- Can be substantial (€500–2000 per farm)
Indirect Costs
Market Disruption
- Export bans: Trade restrictions limiting market access
- Consumer confidence loss: Demand reduction post-outbreak
- Restocking delays: Time and cost to rebuild herds
Productivity Loss
- Production interruption: Farms under control have limited output
- Herd reconstruction: Time and cost to rebuild breeding stock
- Genetic loss: Valuable breeding lines culled
Cost-Effectiveness Metrics
Cost Per Farm Protected
\[\text{CER}_{\text{farm}} = \frac{\text{Total Control Cost}}{\text{Farms Prevented from Infection}}\]Example: Control cost €500,000; 50 farms prevented infection = €10,000 per farm protected
Cost Per Animal Saved
\[\text{CER}_{\text{animal}} = \frac{\text{Total Control Cost}}{\text{Animals Saved from Infection}}\]Example: Control cost €500,000; 10,000 animals saved = €50 per animal
Outbreak Cost Without Control (Counterfactual)
Estimate total cost if disease spread uncontrolled:
\[\text{Uncontrolled Cost} = \text{Infected farms} \times \text{avg farm value loss}\]Typical range: €100,000–5 million depending on region
Net Benefit
\[\text{Net Benefit} = \text{Uncontrolled Cost} - \text{Control Cost}\]Interpretation:
- Positive: Control is cost-effective (savings exceed cost)
- Negative: Control costs exceed prevented damage (rare for FMD)
Scenario Comparison Framework
Comparison of Multiple Control Strategies
Simultaneously simulate several scenarios:
| Scenario | Depop Capacity | Vax Capacity | Vax Delay | Control Cost | Farms Protected | CER |
|---|---|---|---|---|---|---|
| Conservative | 1 farm/day | 2 farms/day | 20 days | €300k | 40 | €7,500 |
| Moderate | 3 farms/day | 5 farms/day | 15 days | €450k | 52 | €8,650 |
| Aggressive | 5 farms/day | 10 farms/day | 10 days | €650k | 58 | €11,200 |
| No control | 0 | 0 | ∞ | €0 | 0 | N/A |
Insight: Moderate scenario often optimal (diminishing returns at aggressive levels).
Integration with MHASpread Outputs
Workflow
- Run MHASpread for each scenario → generates epidemiological outputs
- Export results: Farms infected, animals in each compartment, duration
- Assign unit costs to animal/farm outcomes
- Calculate total cost per scenario
- Compare across scenarios using cost-effectiveness metrics
- Sensitivity analysis: Vary cost assumptions, repeat
R-Based Integration
# After running MHASpread simulation
outbreak_results <- run_mhaspread(population, events, scenario_params)
# Extract economic inputs
depop_farms <- sum(outbreak_results$depopulation_events$count > 0)
vax_farms <- sum(outbreak_results$vaccination_events$count > 0)
infected_farm_total <- nrow(unique(outbreak_results$infected_farm_timeseries))
# Assign unit costs (€)
cost_depop <- depop_farms * 1500 # €1500 per farm depopulated
cost_vax <- vax_farms * 3000 # €3000 per farm vaccinated
cost_surveillance <- infected_farm_total * 200 # €200 per farm inspected
# Total control cost
control_cost <- cost_depop + cost_vax + cost_surveillance
# Farms protected (prevented infection)
farms_protected <- total_farms_region - infected_farm_total
# Cost-effectiveness ratio
cer <- control_cost / farms_protected
Uncertainty & Sensitivity Analysis
Parameter Sensitivity
Repeat cost-effectiveness analysis with varying cost assumptions:
| Cost Component | Low | Base | High | Impact |
|---|---|---|---|---|
| Depopulation per farm | €1000 | €1500 | €2500 | ±40% CER change |
| Vaccination per farm | €2000 | €3000 | €5000 | ±30% CER change |
| Surveillance per farm | €100 | €200 | €400 | ±10% CER change |
Output: Confidence intervals on cost-effectiveness estimates
Probabilistic Analysis
Rather than point estimates, incorporate distributions:
- Depopulation costs: Lognormal(μ=€1500, σ=€300)
- Vaccination costs: Uniform(€2000, €5000)
- Outcome uncertainty: From 100+ MHASpread replicates
Result: Posterior distribution of cost-effectiveness across scenarios
Comparative Examples
Case Study: Brazil FMD Preparedness
Region: Rio Grande do Sul (~80 cattle farms, 20 swine, 15 sheep farms)
Outbreak Scenario: Single farm infection
Uncontrolled cost: €2.5 million (estimated from cascading losses)
| Strategy | Control Cost | Farms Protected | CER |
|---|---|---|---|
| Reactive (slow depop) | €600k | 60 | €10k per farm |
| Proactive (fast depop + vax) | €850k | 95 | €9k per farm |
| Cost-effective threshold | - | - | €15k/farm |
Interpretation: Proactive strategy justified (below threshold).
Case Study: Bolivia FMD Surveillance
Region: Mixed cattle/llama system (resource-limited)
Outbreak Scenario: Two simultaneous index farms
| Strategy | Depop Capacity | Vax Efficacy | Net Benefit | Recommended? |
|---|---|---|---|---|
| Minimal intervention | 0.5 farms/day | None | -€1.2M | No |
| Realistic capacity | 2 farms/day | 85% | +€800k | Yes |
| Ideal (if funded) | 5 farms/day | 95% | +€1.5M | Yes but expensive |
Policy Implications
Break-Even Analysis
What control capacity is needed to justify costs?
Question: At what depopulation capacity does outbreak control become cost-effective?
\[\text{Depopulation capacity} \geq \frac{\text{Uncontrolled Cost}}{\text{Cost per farm depopulated}}\]Example: If uncontrolled cost €2M and depopulation costs €1500/farm:
\[\text{Required capacity} \geq 1,333 \text{ farms} = \text{Probably achievable}\]Preparedness Investment
Should a country invest in surge capacity (vans, vaccine stocks, trained personnel)?
Cost-benefit: Compare investment cost vs. expected savings across multiple outbreak scenarios.
Limitations
- Exclusion of trade bans: Model not designed to handle multi-country trade restrictions
- Longer-term impacts: Only covers acute outbreak period (~year 1)
- Indirect costs underestimated: Market disruption, consumer confidence not fully modeled
- Regional heterogeneity: Cost assumptions may vary by farm type, location
- Uncertainty propagation: Stochastic model uncertainty + cost uncertainty compounded
References & Further Reading
Key references for cost-effectiveness analysis integration:
- Cardenas et al. (2024): Integrating epidemiological and economic models to estimate the cost of simulated FMD outbreaks in Brazil
- USDA/APHIS economic impact assessments
- FAO FMD cost-benefit manuals
Next Steps
- For control strategy details, see Control Strategies
- For case study examples, see Case Studies Vignette
- For epidemiological outputs to feed this framework, see Model Overview