To solve this problem, we need to calculate the number of days it will take for the number of recovered cases to exceed the number of new cases and the current active cases.

Here are the steps to solve this problem:

1. First, calculate the difference between the number of recovered cases and new cases per day. This will give us the net decrease in active cases per day. Let's call this value 'D'. So, D = A - B.

2. Next, divide the current active cases by 'D'. This will give us the number of days it will take for the active cases to reach zero if there were no new cases. However, since there are new cases every day, we need to add the number of days it takes for the new cases to be less than the recovered cases.

3. To find this, we divide the number of new cases by 'D'. This will give us the number of days it will take for the new cases to be less than the recovered cases.

4. Finally, we add the two values we calculated in steps 2 and 3. This will give us the minimum number of days it will take to reach zero active cases.

Here is the Python code for the above steps:

```python
def min_days(A, B, C):
D = A - B
days_for_active_cases = C // D
days_for_new_cases = B // D
return days_for_active_cases + days_for_new_cases
```

You can call this function with the given inputs to get the minimum number of days. For example, `min_days(5, 3, 1)` will return 1 and `min_days(4, 3, 2)` will return 2.

Question

To solve this problem, we need to calculate the number of days it will take for the number of recovered cases to exceed the number of new cases and the current active cases.

Here are the steps to solve this problem:

1. First, calculate the difference between the number of recovered cases and new cases per day. This will give us the net decrease in active cases per day. Let's call this value 'D'. So, D = A - B.

2. Next, divide the current active cases by 'D'. This will give us the number of days it will take for the active cases to reach zero if there were no new cases. However, since there are new cases every day, we need to add the number of days it takes for the new cases to be less than the recovered cases.

3. To find this, we divide the number of new cases by 'D'. This will give us the number of days it will take for the new cases to be less than the recovered cases.

4. Finally, we add the two values we calculated in steps 2 and 3. This will give us the minimum number of days it will take to reach zero active cases.

Here is the Python code for the above steps:

```python
def min_days(A, B, C):
    D = A - B
    days_for_active_cases = C // D
    days_for_new_cases = B // D
    return days_for_active_cases + days_for_new_cases
```

You can call this function with the given inputs to get the minimum number of days. For example, `min_days(5, 3, 1)` will return 1 and `min_days(4, 3, 2)` will return 2.

Knowee AI · Accepted Answer

To solve this problem, we need to calculate the number of days it will take for the number of recovered cases to exceed the number of new cases and the current active cases.

Here are the steps to solve this problem:

1. First, calculate the difference between the number of recovered cases and new cases per day. This will give us the net decrease in active cases per day. Let's call this value 'D'. So, D = A - B.

2. Next, divide the current active cases by 'D'. This will give us the number of days it will take for the active cases to reach zero if there were no new cases. However, since there are new cases every day, we need to add the number of days it takes for the new cases to be less than the recovered cases.

3. To find this, we divide the number of new cases by 'D'. This will give us the number of days it will take for the new cases to be less than the recovered cases.

4. Finally, we add the two values we calculated in steps 2 and 3. This will give us the minimum number of days it will take to reach zero active cases.

Here is the Python code for the above steps:

```python
def min_days(A, B, C):
    D = A - B
    days_for_active_cases = C // D
    days_for_new_cases = B // D
    return days_for_active_cases + days_for_new_cases
```

You can call this function with the given inputs to get the minimum number of days. For example, `min_days(5, 3, 1)` will return 1 and `min_days(4, 3, 2)` will return 2.

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