how can i get the while loop to terminate when all matrix values are <0 and create a vector based on each iteration? in python 3

Question

***I have edited the infect function and included a vaccinate function which both run and produce new matrices. However, for i==n and j==m, the infect function says that it is improperly indexed and it wont write to the right and bottom boundary of the function

import random
from copy import copy
import numpy as np


def infect(Pop,i,j,n,m, tau):
    B = copy(Pop)
    if (i==n):        #this is how I have tried to get around this matrix boundary issue
        if (j==0):    #but when I run it, the code behaves exactly as it did when this wasnt here
            is_infected = False
            for neighbor in [Pop[i-1,j],Pop[i,j+1]]:
                if neighbor:
                    B[i,j] = int(Pop[i,j] or (np.random.rand() < tau))
        if (j==m):
            is_infected = False
            for neighbor in [Pop[i-1,j],Pop[i,j-1]]:
                if neighbor:
                    B[i,j] = int(Pop[i,j] or (np.random.rand() < tau))
        if (j>0) and (j<m):
            is_infected = False
            for neighbor in [Pop[i-1,j],Pop[i,j+1],Pop[i,j-1]]:
                if neighbor:
                    B[i,j] = int(Pop[i,j] or (np.random.rand() < tau))
    if (j==m):
        if (i==0):
            is_infected = False
            for neighbor in [Pop[i+1,j],Pop[i,j-1],Pop[i-1,j]]:
                if neighbor:
                    B[i,j] = int(Pop[i,j] or (np.random.rand() < tau))

    for i in range(n):       ##changed to: for i in range(1,n-1)        #this is the part that
        for j in range(m):   ##changed to: for j in range(1,m-1)        #works excpet for the 
            is_infected = False                                         #final row and column 
            for neighbor in [Pop[i-1,j],Pop[i,j-1], Pop[i+1,j], Pop[i,j+1]]:
                if neighbor:
                    B[i,j] = int(Pop[i,j] or (np.random.rand() < tau))

    return B


def vaccinate(Pop,i,j,n,m,mu):
    V = copy(Pop)                      #since this function is purely random and doesn't rely on
    for i in range(n):                 #neighbor values, it runs fine
        for j in range(m):
            if Pop[i,j] == -2 or Pop[i,j] == -1 or Pop[i,j] > 0:
                V[i,j] = Pop[i,j]
            if Pop[i,j] == 0:
                t = (np.random.rand() < mu)
                if (t==True):
                    V[i,j] = -2               

    return V


i = 0
j = 0
n = 10
m = 10
k = int(input("How many days should it take to recover?"))
tau = 0.5
mu = 0.2
D = np.zeros((k + 1,n,m))
A = np.zeros((n,m))

n1 = random.sample(range(n),1)
m1 = random.sample(range(m),1)
A[n1,m1] = 1
print(A)


for d in range(k):
    D[d,:,:] = A                           #rather than a for loop would it be easier/better to 
    A = vaccinate(A,i,j,n,m,mu)            #implement a while loop?
    A = infect(A,i,j,n-1,m-1,tau)
    print(A)
D[k,:,:] = A

should i maybe make the entire matrix one row and column larger and just pad it with zeros? I don't actually have to present the final matrix, it is solely for computational purposes so maybe that could work. But i do have to have the simulation terminate once all values within the matrix are not equal to zero. Is there a way around this? Could I just delete the extra row and column before then or since im placing the function into a thread, will it screw everything up?

as for the while loop:

def infectAll(Pop,n,m,tau):
    Aout = copy(Pop)
    #for i in range(n):
        #for j in range(m):
    if Pop[i,j] == -2:
        Aout = Pop[i,j]
        vac = []
    if Pop[i,j] == -1:
        Aout = Pop[i,j]
    if Pop[i,j]>0 and Pop[i,j]<=k:
        Aout[i,j] = Pop[i,j] + 1
        inf = []
    if Pop[i,j]>k:
        Aout[i,j] = -1

    if Pop[i,j] == 0:
        Aout = infect(Pop,i,j,n,m,tau)
        if Aout[i,j]==0:
            Aout = vaccinate(Pop,i,j,n,m,nu)

    return Aout


A[n1,m1] = 1
d = 0
print(A)                               #i need d to count the iterations per day, but i also need
while d < 100:                         #to be able to creat 3 different vectors base on the 
     for i in range(n):                #matrix data (# total recovered, total #vaccinated and 
        for j in range(m):             #total infected per day
           if A[i,j]>=0:
              A = infectAll(A,n,m,tau)
              d = d+1 

            else:
              break