Networks and Dynamics

Question 1

Dynamics

Answer 1

how we describe infectious disease’ movements, patterns and behaviors over time and geography

Question 2

System

Answer 2

any group of interacting things that form a whole.

Question 3

Complicated system

Answer 3

has many interacting parts that need to work correctly in a sequence to reach the desired result. However, each step of the process is completely predictable based on the step before it.

Question 4

Complex system

Answer 4

the results brought about by the interacting parts of a complex system are not directly predictable

Question 5

Emergent Properties

Answer 5

behaviors or outputs of a system that arise from 2 or more interacting components that cannot be explained by either of them on their own

Question 6

Epidemic curve

Answer 6

a graph of the number of cases or incidence rate of cases versus time.

Question 7

Propagate

Answer 7

travel

Question 8

Human ecology

Answer 8

how humans interact with and are impacted by their surrounding environment and each other

Question 9

Node

Answer 9

an individual entity in the network, like a person or a hospital

Question 10

Edge

Answer 10

What connects two nodes

Question 11

Random network

Answer 11

a lot of people/things randomly connected to each other with no rhyme or reason

Question 12

Scale-free network

Answer 12

where some nodes are more highly connected than others

Question 13

Hubs

Answer 13

nodes that are more connected than others

Question 14

Synchronous spread

Answer 14

the timing of an epidemic overlapping in multiple locations

Question 15

Concurrency

Answer 15

meaning individuals having multiple partners at the same time

Question 16

Compartmental

Answer 16

we are essentially coming up with a fake scenario in which people flow from one “compartment” or stage to another

Question 17

Deterministic

Answer 17

the model does not worry about random effects, like individual differences in susceptibility. Everyone follows the same rules of probability about what compartment they are in at any given time.

Question 18

SIR Model

Answer 18

“susceptible, infectious, and recovered.” Each person is either in the S, I or R compartment at any given time. The simplest version of the SIR model doesn’t take into account birth and death.

Question 19

Stochastic model

Answer 19

A model that takes individuality into account. They are very commonly used and based off of the same mathematical principles as deterministic models. They just use more complicated probability formulas describing whether someone will move into the next compartment, and are not deterministic.

Question 20

Agent-based models

Answer 20

helpful to study diseases that are very difficult to trace through a network to a particular infecting person (like respiratory diseases). They use computer simulations to estimate the behaviors of a real-world city, region or country. The simulations can help predict what emergent properties might occur as an infectious disease travels.

Question 21

Ro

Answer 21

the number of infected individuals one person is expected to infect while they are infectious

Question 22

herd-immunity threshold

Answer 22

the proportion of people that need to immunity in order to eradicate a disease, or prevent an outbreak

Question 23

hysterisis

Answer 23

A change in status. ex. a new emerging disease can cause an epidemic, and if not eliminated, reach a new stable equilibrium where it is now endemic.

Question 24

Rt

Answer 24

real-time or effective reproduction. Our goal when trying to prevent infectious diseases is to push Rt below 1, so that the epidemic will die out. In essence, you want to “remove” susceptible or infectious individuals from the population faster than the disease spreads. Vaccines do this very effectively.