Agent-based model example
For this model, I made a few decisions for the sake of simplicity. I decided to focus solely on the prevalence of Zika infections while ignoring the effects of Zika, such as increased incidence of microcephaly. In addition, I chose to ignore human death because humans live so much longer than mosquitos, and I wanted to look at short term effects of the Zika-infected mosquito rather than long-term effects. I also do not know whether mosquitos can pass down the Zika virus to offspring, so I assumed that a certain number of offspring would become Zika carriers regardless of the source.
World:
Create X number of mosquitos
-X number of mosquitos are infected
Create X number of humans
Create X number of patches representing standing water
Agent: mosquito
Move randomly
If encounter patch, reproduce X number of mosquitos with X% chance of contracting Zika
Die after X amount of time
Agent: human
Move randomly
If encounter Zika-infected mosquito, contract virus with X% probability
If encounter patch, eliminate patch
I'd be super interested to see this in model in real life. I believe this type of modeling, agent based, is useful because you can actually see how the inputs change how the virus reacts. For example you said for your model you would assume the zika virus is passed down to the mosquito offspring, and I think it would be interesting to see what effect, if any that has on the model.
ReplyDeleteI really like this model as well! If our ultimate goal is to create a code in SLN that reflects the spread of Zika, I really like that your model incorporates a lot of the language and capabilities of SLN's computational modeling.
ReplyDeleteI really like this model as well! If our ultimate goal is to create a code in SLN that reflects the spread of Zika, I really like that your model incorporates a lot of the language and capabilities of SLN's computational modeling.
ReplyDelete