1. Problem B The Next Plague?

2. Simple analysis
150
Nearby villages
and islands 15

3. Simple analysis We want to get the following results Allocate the
scarce resources
Classification of
types & severity
If an epidemic
is contained or not
Appropriate measures
Epidemic analysis problem
Disease control problems

4. Simple analysis Kink 4 Stage Theory 1st stage:The asymptomatic period．
Unnoticed、lower morbidity
2nd stage:outbreak and spreading phase．
Begin to take measures、higher morbidity
3rd stage:Peak period．
Strict measures、controlled、stable
4th stage:recession and effectively control period．
Patient numbers fell
Develop a model to show the four stages
use the model to predict the epidemic changes
建立的模型就应该体现4个不同时期下疫情的发展过程，并能够在此基础上准确预测疫情变化情况，提出切实可行的控制措施.考虑在经典传染病SIR模型基础上，通过机理分析，加入合理的实际因素，建立适合分段微分方程模型，称为SIR改进模型

5. Proper useful model Classification problem Analytic Hierarchy Process
Cluster analysis
Decision-making tree

6. Proper useful model Assignment problem
Infectious Disease Diffusion Model
Integer Programming Theory
Cluster Theory
Genetic Algorithms

7. Tips
Reasonable distribution principles
Clustering the victims
Non-dimensional treatment

8. Classical SIR model I(t) --Infectives S(t)--Susceptibles R(t)—Removed
N=S+I+R

9. Classical SIR model Solution: Increase，then decrease to 0
Diseases spread
Keep decreasing to 0
Not spread

10. More complex cases

11. Some other model
Branching process
Reed
Logistic model
Infectious disease network model and the compartment model
Complex network model（neighborhood）
More complex models
Treatment model 
Quarantine and isolation model（SEIR）
Infectious kinetics model (SEIDR)
IF we take measures，when it comes to different stages，
we can develop a model group！

12. For example Take borderline cases into consideration No control
SE：ΔE=I(t)*r*Δt r：Contacting number
EQ：ΔQ=ΔE*λ λ ：rate of virus carrier
QI：ΔI=(1-(1-1/(a2-a1))exp(-t)*ΔQ*Δt Assumption: Exponential growth
IR：ΔR=(1-1/a3))exp(-t)*I(t)*Δt a3:removed rate

13. For example
Similarly，
Under control function：。。。。
after
before

14. Solving
numerical analysis
Fitting
Iterative
。。。

15. Thank you！