The graph is useful because it allows me to see the interaction between the different variables and it is interesting to relate it to differentiation to determine the changes over time. Validity of the model However, in order for the model to be valid and allow to inform government policy, it obviously needs to correspond fairly close to reality. Before checking against the graph, there are already clear advantages and disadvantages to this model: Advantages The advantages to the model include: It is very quick to model the data having found the values for the respective parameters and transition probabilities to allow immediate assessment of the condition that is present. This results in instant evaluation of the situation as well as valid prediction of the spread of disease in the future. The model is widely used and also widely understood by the medical community making it easier to explain the effects of the epidemic This model is clear and easy to understand in order to distinguish between the number of people susceptible, infected and recovered The mechanism to create the data is flexible, allowing it to be easily altered if certain values are incorrect or have changed It is computationally cheap and there are other software available with very small time intervals allowing it to be more accurate which I could not complete in excel. Disadvantages The disadvantages to the model include: The calculation of the beta values and gamma values are often inaccurate because small deviation from the can result in great changes in the overall model. For example, changing the ‘correct value’ gamma value from 0.1 to 0.3 can lead to the following changes: The data itself can be fairly unreliable especially, in countries where death counts are difficult to manage. (For the Ebola case, although the numbers seem fairly high, there is a high probability that there were far more people infected) In order for the model to be calculated correctly, you need the right form of data including the number of people infected, recovered and susceptible. This data can be very particular and calculating the
The graph is useful because it allows me to see the interaction between the different variables and it is interesting to relate it to differentiation to determine the changes over time. Validity of the model However, in order for the model to be valid and allow to inform government policy, it obviously needs to correspond fairly close to reality. Before checking against the graph, there are already clear advantages and disadvantages to this model: Advantages The advantages to the model include: It is very quick to model the data having found the values for the respective parameters and transition probabilities to allow immediate assessment of the condition that is present. This results in instant evaluation of the situation as well as valid prediction of the spread of disease in the future. The model is widely used and also widely understood by the medical community making it easier to explain the effects of the epidemic This model is clear and easy to understand in order to distinguish between the number of people susceptible, infected and recovered The mechanism to create the data is flexible, allowing it to be easily altered if certain values are incorrect or have changed It is computationally cheap and there are other software available with very small time intervals allowing it to be more accurate which I could not complete in excel. Disadvantages The disadvantages to the model include: The calculation of the beta values and gamma values are often inaccurate because small deviation from the ‘correct value’ can result in great changes in the overall model. For example, changing the gamma value from 0.1 to 0.3 can lead to the following changes: The data itself can be fairly unreliable especially, in countries where death counts are difficult to manage. (For the Ebola case, although the numbers seem fairly high, there is a high probability that there were far more people infected) In order for the model to be calculated correctly, you need the right form of data including the number of people infected, recovered and susceptible. This data can be very particular and calculating the