Research from a study funded by the Centre for Biodiversity Analysis' Ignition Grant program, Biodiversity change: A risk factor for human health?, has found linkages between patterns of infections disease risk and rainfall and land-use changes.

The ANU, CSIRO and QUT authors, with expertise spanning population health, mathematical sciences and macroecological modelling, found that an increased risk of cryptosporidiosis is uniquely associated with rainfall and habitat measures.

Over 60% of infectious diseases in humans have originated from animals, and human changes to wildlife habitat may increase the risk of zoonotic disease transmission. One such zoonotic pathogen is Cryptosporidium spp, a leading cause of diarrhoea in humans and animals worldwide. Cryptosporidiosis is easily spread through water and is associated with changes in rainfall, temperature, history of flooding and drought.

The study, just published in Science of The Total Environment, developed a Bayesian spatio-temporal model for disease risk using reported cryptosporidiosis in Australia between  2001 and 2018.

The research found, as previously reported, higher case numbers of cryptosporidiosis are predicted for more vulnerable age groups and those with higher levels of socio-economic disadvantage.

However, for the first time in Australia, their models also found an increased disease risk for those living in areas with a greater proportion of natural habitat remaining and higher-than-average annual rainfall.

Land use changes such as deforestation, fragmentation and agricultural development may increase the risk of disease transmission from animals to humans as settlements increasingly encroach on wildlife habitat. Heavy rainfall can flush animal and human faeces into surface drinking water sources, contaminating them and increasing the risk of illness.

The results demonstrate the importance of including perspectives from land and water management experts for policy making and public health responses to manage environmentally mediated diseases such as cryptosporidiosis.

Owen Forbes, Rose Hosking, Karel Mokany, Aparna Lal. 2021. Bayesian spatio-temporal modelling to assess the role of extreme weather, land use change and socio-economic trends on cryptosporidiosis in Australia, 2001–2018. Science of The Total Environment,
791. (https://doi.org/10.1016/j.scitotenv.2021.148243).