seir模型数学建模python_基于对SEIR模型的疫情发展研究（数学建模.docx）
E=zeros(7,95);
rec1=0.07;%住院康复率rec2=0.05;%自然康复率lam=0.17;%感染率aph=0.13;%潜伏者转化率die1=0.03;%住院死亡率die2=0.4;%?不住院死亡率q=0.3;%隔离比例bt=0.13;%住院隔离率m=0.07;%解除隔离比例E(1,1)=46796500;%易感人群E(2,1)=239638;%第一天患病人数E(3,1)= 1912;%潜伏者(可由1到7天新增病例得到)E(4,1)= 2396380;%隔离易感人群E(5,1)=479276;%?隔离潜伏者E(6,1)=718914;%住院观察人数E(7,1)=0;%移出者(死亡加康复)N=46796500;%总人口c=10;%平均接触人数ib=0;%疫苗接种率for i=1:95
if(i<30)
ib=0;
E(1,i 1)=E(1,i)-c*q*E(2,i)*(E(1,i)/N)-lam*(1-q)*c*E(2,i)*(E(1,i)/N) m*E(4,i)-ib*E(1,i);
E(2,i 1)=E(2,i) aph*E(3,i)-bt*E(2,i)-(rec2 die2)*E(2,i);
E(3,i 1)=E(3,i) lam*(1-q)*c*E(2,i)*(E(1,i)/N)-aph*E(3,i);
E(4,i 1)=E(4,i) c*q*(1-lam)*E(2,i)*(E(1,i)/N)-m*E(4,i)-ib*E(4,i);
E(5,i 1)=E(5,i) c*q*lam*(E(2,i)/N)-aph*E(5,i)-ib*E(5,i);
E(6,i 1)=E(6,i) bt*E(2,i) aph*E(5,i)-(rec1 die1)*E(6,i)-ib*E(6,i);
E(7,i 1)=E(7,i) (rec2 die2)*E(2,i) (rec1 die1)*E(6,i) ib*E(1,i) ib*E(4,i) ib*E(4,i) ib*E(6,i);
else
ib=0.4;
E(1,i 1)=E(1,i)-c*q*E(2,i)*(E(1,i)/N)-lam*(1-q)*c*E(2,i)*(E(1,i)/N) m*E(4,i)-ib*E(1,i);
E(2,i 1)=E(2,i) aph*E(3,i)-bt*E(2,i)-(rec2 die2)*E(2,i);
E(3,i 1)=E(3,i) lam*(1-q)*c*E(2,i)*(E(1,i)/N)-aph*E(3,i);
E(4,i 1)=E(4,i) c*q*(1-lam)*E(2,i)*(E(1,i)/N)-m*E(4,i)-ib*E(4,i);
E(5,i 1)=E(5,i) c*q*lam*(E(2,i)/N)-aph*E(5,i)-ib*E(5,i);
E(6,i 1)=E(6,i) bt*E(2,i) aph*E(5,i)-(rec1 die1)*E(6,i)-ib*E(6,i);
E(7,i 1)=E(7,i) (rec2 die2)*E(2,i) (rec1 die1)*E(6,i) ib*E(1,i) ib*E(4,i) ib*E(4,i) ib*E(6,i);
end
end
sum=E(:,1:7:95);