Solve a linear system of equation using ODE45 in MATLAB - function

Question

I have written a function plus a script to determine the variables. My variables name are "S E I1 I2 R Q H" which I named them in my function as x(1) to x(7). The total number of population equals to N which also equals to x(1)+x(2)+x(3)+x(4)+x(5). The problem is that when I try to run the script MATLAB gives me error and can not solve the linear system of ordinary differential equations. The worse problem is that MATLAB does not tell me where I'm wrong. It just tell me that the error comes from the eight line of my function. Can anyone help me with it ?
function Variables_rate = COVID_FUN(t,x) %#ok
NV = 7; % Number of Variables
global beta1 beta2 kessi ro1 ro2 alpha theta1 theta2 gamma1 gamma2 say phi lambda delta
% The Whole Number of community (N) equals to : N = S + E + I + R
N = x(1) + x(2) + x(3) + x(4) + x(5); % Total Number of people
%% This function will Model the COVID-19 Dynamical System Based on input Variables which are as follows :
% S: Suceptible Class corrosponds to {x1}
% E : Exposed Corrosponds to {x2}
% I1 : Infectious without intervention Corrosponds to {x3}
% I2 : Infectious with intervention corrosponds to {x4}
% R : Recovered corrosponds to {x5}
% Q : Quarantined corrosponds to {x6}
% H : Hospitalized corrosponds to {x7}
%% Model The Dynamic of the System with Differential Equations
Variables_rate = zeros(NV,1);
Variables_rate(1) = (-x(1)./N)*(beta1*x(3)+beta2*x(4)+kessi*x(2))+ro1*x(6)-ro2*x(1)+alpha*x(5); % Sdot
Variables_rate(2) = (x(1)./N)*(beta1*x(3)+beta2*x(4)+kessi*x(2))-theta1*x(2)-theta2*x(2); % Edot
Variables_rate(3) = theta1*x(2)-gamma1*x(3); % I1dot
Variables_rate(4) = theta2*x(2)-gamma2*x(4)-say*x(4)+lambda*(delta+x(6)); % I2dot
Variables_rate(5) = gamma1*x(3)+gamma2*x(4)+phi*x(7)-alpha*x(5); % Rdot
Variables_rate(6) = say*x(4)-phi*x(7); % Qdot
Variables_rate(7) = delta+ro2*x(1)-lambda*(delta+x(6))-ro1*x(6); % Hdot
end
Also the following is my main script :
clc;clear;close all;
% { COVID-19 Main Script Based on the written function }
global beta1 beta2 kessi ro1 ro2 alpha theta1 theta2 gamma1 gamma2 phi lambda delta say
%% According to TABLE 5 the Values of the Global Parameters are as follows :
beta1 = 1.0538*1e-1; % Contact rate of transmission per contact with infected class
beta2 = beta1; % Infection rate of transmission per contact with infected class
kessi = 1.6221*1e-1; % Probability of transmission per contact from exposed individuals
ro1 = 2.8133*1e-3; % Transition rate of quarantined exposed between the quarantined infected class and wider community
ro2 = 1.2668*1e-1; % Transition rate of quarantined exposed between the quarantined infected class and wider community
alpha = 1.2048*1e-4; % Temporary Immunity Rate
theta1 = 9.5*1e-4; % Transition rate of exposed individuals to the infected class
theta2 = 3.5412*1e-2; % Transition rate of exposed individuals to the infected class
gamma1 = 8.5*1e-3; % Recovery rate of symptomatic Infected Individuals to recovered
gamma2 =1.0037*1e-3; % Recovery rate of symptomatic Infected Individuals to recovered
say = 0.291; % Rate of Infectious with symptoms Hospitalized
phi = 0.0107; % Recovered rate of Quarantined infected individuals
lambda = 9.4522*1e-2; % Recovered rate of Quarantined Class to the recovered class
delta = 10; % External Input from the foreign countries
%% Time Vector and Initial Conditions
t = linspace(0,5,5);
Ics = [59717.71 5077 7.29 729 32 4711 658]';
%% Solve the Linear System Using ODE45 function
[~,States] = ode45(#(t,x)COVID_FUN,t,Ics)