How clinical data and biodiversity measurements will be integrated to examine spatial relationships between ecology and health. Solid arrows indicate work to be undertaken in the project and the dashed arrow indicates extensions of this work.

Ignition Grant Round 7 (July 2017)

• Aparna Lal ANU
• Karel Mokany, CSIRO

Patterns of biodiversity and human infectious diseases are expected to change over the coming century in response to anthropogenic environmental forcings. Despite the high environmental, socio-economic and health costs associated with environmental extremes, little is known about how changes in biodiversity are related with human infections spread from animals to humans. This knowledge gap limits our ability to anticipate how impending change will shape the future of the planet and her people.

Over 70% of infectious diseases in humans have originated from animals. One such zoonotic pathogen is Cryptosporidium spp, a leading cause of diarrhoea in humans and animals worldwide.

Australia reports the second highest rate of Cryptosporidium illness in humans across developed nations with the risk of reported infection highest in remote areas. Children under five years old living in very remote regions are at nearly 8 times higher risk of reported infection compared to urban dwelling pre-schoolers. 

We need to understand the distribution of Cryptosporidium spp. to limit cross-species spread, a current challenge for land use managers and public health agencies. However, there are only scattered reports of Cryptosporidium in wild animals and livestock from Australia which almost surely underestimate the full range of the environmental burden of this parasite and makes it difficult to put observed human infection patterns into a useful practical context. For example, recent modelling work has shown that human cryptosporidiosis patterns are linked to rainfall variability and natural resource management regions are better at explaining disease patterns compared to the scale at which health resources are allocated (Lal, Wilford under review).

Given the potential for native and introduced vertebrates to act as hosts of Cryptosporidium, the abundance and diversity of vertebrates may play an important role in influencing human infection. Greater species’ diversity has shown to have a protective effect on the risk of human vector-borne infections. Does this suggest that we can manage natural resources and biodiversity to protect populations from non-vector borne zoonotic infections like cryptosporidiosis?

The proposed project will address this by examining the spatial relationship between observed patterns of human illness and estimates of biodiversity at a high spatial resolution (see above Figure). 

The aim of this project is to model the spatial relationships between patterns of human cryptosporidiosis and biodiversity and can be further delineated through three specific objectives:

1. To undertake data preparation and cleaning that will include coding illnesses and associated patient characteristics (Indigenous status, demographic and personal characteristics, and co-morbidity) and ensuring completion of geocoding. 
2. To examine how spatial patterns of cryptosporidiosis relate to different measures of biodiversity at a high spatial resolution.
3. To examine how the relationship between measures of biodiversity and cryptosporidiosis are influenced by demographic and personal characteristics, and co-morbidity.

References

1. Lal A, Hashizume M, Hales S. 2017. The Indian Ocean Dipole and cryptosporidiosis in Australia: Short-term and non-linear associations. Environmental Science and Technology. https://doi:/10.1021/acs.est.6b05146.