The Huck Institutes of the Life Sciences

Heterogeneities

CIDD researchers are investigating how the epidemiology and evolution of host-pathogen interactions are affected by geographical, behavioural, physiological and genetic variation in hosts and disease agents.

 

Disease in space and time

We are interested in how the spread and evolution of disease is affected by spatiotemporal heterogeneities in such variables as:

  • Intrinsic characteristics of the disease agent and the host (e.g. host immunity)
  • Extrinsic characteristics of the environment, and their effects on hosts and disease agents.  Work in Matt Ferrari’s lab has highlighted the role of seasonal variation in human movement and density on the outbreak dynamics of measles and meningitis in West Africa. Peter Hudson’s lab has shown how seasonal, and inter-annual, variation in rodent distribution affects the distribution both micro- and macro-parasites
  • Interactions between disease agents (e.g. a host's adaptive immunity may be boosted by prior infection with a related pathogen)

Mathematical modeling based on data from real epidemics allows us to identify how epidemic dynamics are affected by geographical variation in key parameters such as transmission rates. This in turn allows us to investigate the likely impact of alternative control strategies on the spread of disease.

In many host species, the frequency and nature of contacts between infected and susceptible individuals is affected by social interactions that in turn are affected by the host's environment (biotic and abiotic) — and in humans, culture and politics. All these variables may vary geographically, and through time.

We are using network models to explore the impact of host social interactions on disease spread and evolution in human societies and in wildlife populations.

 

Hetereogeneity in social space

In many host species, the frequency and nature of contacts between infected and susceptible indiduals is affected by social interactions that in turn are affected by the host's environment (biotic and abiotic) — and in humans, culture and politics. All these variables may vary geographically, and through time.

We are using network models to explore the impact of host social interactions on disease spread and evolution in human societies and in wildlife populations.

 

Differences between individual hosts

Host networks are often highly clustered, so some hosts are responsible for many more infections than others. This would be true even if all hosts were otherwise identical. However, hosts are not all the same: individuals differ from conspecifics in many ways, including gender, physiological characteristics and behavior. These differences can influence the dynamics and control of epidemics, and can affect host-pathogen coevolution.

Some hosts are much more likely to transmit infections. The existence of such superspreaders is perhaps best known in the human diseases SARS and HIV. However, superspreaders play an important role in many systems, including wildlife diseases. Superspreaders are implicated in the spread of vector-borne and emerging diseases as well as directly-transmitted and well-established ones.