A Provocation: A Provocation: Social insects as Social insects as an experimental an experimental model of network model of network

epidemiologyepidemiologyMichael Otterstatter (CA)Michael Otterstatter (CA)

Traditional approach – Traditional approach – compartmental models; compartmental models; homogeneous homogeneous host host population, complete population, complete mixing mixing

SSI

t

ISI I

t

RI

t

β

γ

e.g., the SIR model

Of course, in real host populations patterns of contact are heterogeneous…

Modeling disease dynamicsModeling disease dynamics

A more recent approach – network models; individual-based, patterns of contact are modeled explicitly

Primary focus has been theoretical network structures; few empirical studies exist

How might we test if network models capture the epidemiology of real host populations?

Modeling disease dynamicsModeling disease dynamics

Erdos-Renyi random graph

Poisson network

amenable model of disease dynamicsamenable model of disease dynamics Social group size and transmission in ants (Hughes et al, Social group size and transmission in ants (Hughes et al, 2002)2002) Infectiousness and transmission in honey bees (Naug & Infectiousness and transmission in honey bees (Naug & Smith, 2006)Smith, 2006) Contact network structure and transmission in bumble Contact network structure and transmission in bumble bees bees (Otterstatter & Thomson, 2007)(Otterstatter & Thomson, 2007)

leafcutter ants

honey beesbumble bees

Social insectsSocial insects

Bee colony

Foraging arena with feeder

Digital camcorder

Behavioural tracking software

Donors(infected bees)

Natural bee pathogens

Inoculation during foraging

Quantifying social networks:

Introducing pathogens into social networks:

Experimental epidemiology Experimental epidemiology with beeswith bees

Bee colony

Foraging arena with feeder

Digital camcorder

Behavioural tracking software

Donors(infected bees)

Natural bee pathogens

Inoculation during foraging

Quantifying social networks:

Introducing pathogens into social networks:

Experimental epidemiology Experimental epidemiology with beeswith bees

Tracers may be artificial !

Example of an observed interaction network(node diameter ≈ degree centrality;

edge weight ≈ contact rate)

Queen

Nest workerNest worker

Forager

Forager

Nest worker

Nest worker

Experimental epidemiology Experimental epidemiology with beeswith bees

Example of an observed transmission network(node diameter ≈ risk of infection;edge weight ≈ transmission rate)

Artificiallyinfected bee

Within groups, disease spreads more quickly when network density is high (each point = 1 hive)

An individual’s risk of infection depends on its unique rate of contact with infecteds, i.e., its position in the social network (each point = 1 bee)

…from Otterstatter & Thomson, 2007

Simple (but useful) tests of Simple (but useful) tests of network theory, network theory,

using bumblejbeesusing bumblejbees