disabled_with_various_infected

gistfile1.txt

for (m in 1:10){
    x = m/10 #new in R so I dont know how to make steps of .1 in loops ;)
    monsterlist <- c() #This will hold the number of disabled in each sim run
    for (h in 1:1){ #Repeat simulation 1 times
        disabled <- c() #This will hold the disabled within each sim run
        population <- as.vector(c(rep(0,10000))) #The population of 10,000
        for(j in 1:30) { # Number of Years
            infected <- sample(1:length(population),floor(x*length(population))) # infect x% of the population every year
            population[infected] <- population[infected]-1 #infected get an increasingly-negative counter
            # The next 2 paragraphs control who gets LC. One should be commented out.
            # The first puts everyone in the same risk category.
            # The second creates low, medium, and high risk categories.
            for (k in 1:length(population)){ #Use this paragraph if risk to everyone of LC is equal. 
                #Use next paragraph if LC is based on low risk, medium risk, and high risk groups.
                #   #if (runif(1) <= pweibull(abs(population[k]),scale=6,shape=2)){ #Use this one if successive Covid infections increase LC risk
                if (runif(1) <= 0.1) { #Use this one if risk of LC is constant. Comment out one of these.
                    population[k] <- population[k]+ 100 #positive number means Long Covid
                }
            }
            # for (p in 1:length(population)){
            # if (p <= 3000) { #The first 3000 in the population are "low risk" for LC. 
            #     if(runif(1) <= 0.05) { #Only a 5% chance of getting LC with each infection.  
            #     population[p] <- population[p] + 100
            #     }
                
            # } else if (p >= 7000) { #High risk group for LC.
            #     if(runif(1) <= 0.25) { #This group has a 25% chance of getting LC with each infection.
            #         population[p] <- population[p] + 100
            #     }
            # } else { #This is the "medium" risk group of getting LC with each infection.
            #     if(runif(1) <= 0.1) { #This group has a 10% chance of getting LC with each infection.
            #         population[p] <- population[p] + 100
            #     }
            #     }
            # }
            for (n in 1:length(population)){ # give them a 50% chance to recover from LC this year
                if (population[n] > 0){
                    if(runif(1)>=0.5){
                    population[n] <- population[n] - 100
                    
                    }
                }
            }
            del_list <- c()
            for (m in 1:length(population)){
                if (population[m] > 0){
                    if(runif(1)>=0.9){
                    disabled <- c(disabled,population[m])
                    del_list <- c(del_list,m)
                    
                    }
                }
            }
            if (length(del_list)>0){
                population <- population[-del_list]
            }
        }
        monsterlist <- c(monsterlist,length(disabled))
        print (paste("infected:", r, " result" , sum(monsterlist)/1000, "%")) #gives the % (not the decimal) average over 100 simulations
    }
}