Control the Epidemic.
Work within your Budget.

Each team controls a different set of public health interventions. Adjust parameters, spend wisely, and observe the disease dynamics. Can you reduce malaria burden?

🛏️

Team Vector Control

Bednets & Indoor Spraying

Bednet Coverage Reduces mosquito biting rate

💰 $5 per net · ~1 net/person

IRS Coverage Indoor Residual Spraying — kills resting mosquitoes

💰 $8 per household · ~4 persons/household

Bednet Efficacy % biting reduction per net (quality)

70%

💰 +$3/net for long-lasting insecticidal nets

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Team Vaccines & Chemoprevention

RTS,S Vaccination & SMC

R21/Matrix M or RTS,S Vaccination Coverage Pre-erythrocytic vaccine, children under 5

💰 $5.0 average per dose · 4 doses required

SMC Coverage Seasonal Malaria Chemoprevention (children)

💰 $3.50 per child per season · 3 rounds

Vaccine Efficacy (%) Protection from clinical disease

39%

Fixed by biology — RTS,S field efficacy

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Team Clinical Management

Test & Treat + Prophylaxis

Treatment Rate (fT) Prob. of receiving ACT treatment when clinical

20%

💰 $2.50 per treatment course (ACT)

MDA Coverage Mass Drug Administration rounds

💰 $5 per person per round · 2 rounds/yr

Diagnostic Capacity RDT availability — increases case detection

30%

💰 $0.50 per RDT test

⚙️ Epidemiological Parameters — adjust to explore different transmission settings

EIR (inoculations/person/yr) Entomological Inoculation Rate

Seasonality 0=stable, 1=highly seasonal

0.3

Simulation Years Duration of simulation

5 yr

Mosquito Lifespan (days) Mean adult mosquito survival

7.6

Stochasticity 0=deterministic ODE · 1=full demographic noise

0.5

PfPR 2-10

—

Parasite prevalence (children)

Peak Infections / 1000

—

Highest single-day burden

Total Clinical Cases

—

Cumulative over simulation

Cases Averted

—

vs. no-intervention baseline

Cost per Case Averted

—

Intervention efficiency

Equilibrium EIR

—

Final transmission intensity

📐 Model Equations — Griffin et al. (2010) with demographic stochasticity

dS/dt = μN + rT·Tr + rU·U − Λ·S − μ·S // births + recoveries, minus new infections

dD/dt = φ(ICA)·(1−fT)·Λ·(S+A+U) − (rD+μ)·D

dA/dt = (1−φ)·Λ·(S+U) + rD·D − φ·Λ·A − (rA+μ)·A // superinfection A→D

dU/dt = rA·A − Λ·U − (rU+μ)·U // all U bites exit U → D or A

b(IB) = b₀·[b₁ + (1−b₁)/(1+(IB/IB₀)^kB)] // Griffin 2010: saturating blood immunity

φ(ICA) = φ₀·[1 − ICA^kCA/(ICA^kCA + IC₅₀^kCA)] // clinical immunity, ICA₅₀=8, never reaches zero

dIB/dt = EIR(t)/dB − IB/dB // builds with bites (dB≈142d), mean-reverts

dICA/dt= incidence/(N·dCA) − ICA/dCA // builds with clinical exposure (dCA≈662d)

SDE noise: du = f(u)dt + σ(u)·√dt·dW // Euler-Maruyama; σ²=Σ|flux rates| (demographic stochasticity)

Control the Epidemic.Work within your Budget.

📐 Model Equations — Griffin et al. (2010) with demographic stochasticity

Control the Epidemic.
Work within your Budget.