Environmental and sociodemographic risk factors associated with environmentally transmitted zoonoses hospitalisations in Queensland, Australia

Risk Assessment Tools from the One Health Perspective: A Narrative Review

Background

61% of the infections around the world that have emerged to date are zoonotic. Evidence warns that the threat posed by zoonoses is on the rise, and the risk of a new pandemic is higher now than ever. Early identification of risk, populations at risk, and risk of transmission are essential steps towards a prevention, preparation and response to outbreaks. This review aims to look at the tools available for identifying and estimating risks and threats from one health perspective and finally propose a list of indicators which could assess the risk of transmission of disease at the humans, animals and the environment intersection.

Methods

The databases like PubMed, google scholar, Embase and Scopus were used to extract the relevant articles. A search was carried out using a keyword. A total of 1311 articles were listed initially after the search and reviewed. Out of 1311, only 26 tools which assessed the risk of diseases mainly infectious or were relevant to risk of transmission of any infectious diseases were included in the review.

Results

The tools included in this review involve risk assessment at the environmental, animal and human dimensions. The tools are used to evaluate the contamination of the environment due to chemicals or toxins or the risk of transmission of infection due to environmental factors like air contamination, to identify the animal diseases like bovine respiratory disease and foot and mouth disease and to estimate the human health risk at the community or individual levels.

Conclusion

Risk assessment tools are an essential part of the prevention of pandemics. These tools are helpful in assessing the risk of transmission of infections either from human to human, between human and animals, between animals and animals and so on. Thus this review gives us an insight into the existing risk assessment tools and the need for a One Health risk assessment tools to prevent outbreaks in future. It also provides a list of factors that can be included in a one health risk assessment tool.

Mapping the risk of respiratory infections using suburban district areas in a large city in Colombia

BACKGROUND

Acute respiratory infections (ARI) in Cúcuta -Colombia, have a comparatively high burden of disease associated with high public health costs. However, little is known about the epidemiology of these diseases in the city and its distribution within suburban areas. This study addresses this gap by estimating and mapping the risk of ARI in Cúcuta and identifying the most relevant risk factors.

METHODS

A spatial epidemiological analysis was designed to investigate the association of sociodemographic and environmental risk factors with the rate of ambulatory consultations of ARI in urban sections of Cúcuta, 2018. The ARI rate was calculated using a method for spatial estimation of disease rates. A Bayesian spatial model was implemented using the Integrated Nested Laplace Approximation approach and the Besag-York-Mollié specification. The risk of ARI per urban section and the hotspots of higher risk were also estimated and mapped.

RESULTS

A higher risk of IRA was found in central, south, north and west areas of Cúcuta after adjusting for sociodemographic and environmental factors, and taking into consideration the spatial distribution of the city's urban sections. An increase of one unit in the percentage of population younger than 15 years; the Index of Multidimensional Poverty and the rate of ARI in the migrant population was associated with a 1.08 (1.06-1.1); 1.04 (1.01-1.08) and 1.25 (1.22-1.27) increase of the ARI rate, respectively. Twenty-four urban sections were identified as hotspots of risk in central, south, north and west areas in Cucuta.

CONCLUSION

Sociodemographic factors and their spatial patterns are determinants of acute respiratory infections in Cúcuta. Bayesian spatial hierarchical models can be used to estimate and map the risk of these infections in suburban areas of large cities in Colombia. The methods of this study can be used globally to identify suburban areas and or specific communities at risk to support the implementation of prevention strategies and decision-making in the public and private health sectors.

Research and Innovation Opportunities to Improve Epidemiological Knowledge and Control of Environmentally Driven Zoonoses

While zoonotic diseases are defined by transmission processes between animals and humans, for many of these diseases the presence of a contaminated environmental source is the cause of transmission. Most zoonoses depend on complex environmentally driven interactions between humans and animals, which occur along an occupational and recreational environmental continuum, including farming and animal marketing systems, environmental management systems, and community leisure environments. Environmentally driven zoonoses (EDZs) are particularly challenging to diagnose and control as their reservoirs are in the natural environment and thus often escape conventional surveillance systems that rely on host monitoring. Changes in the environment as a result of climate change [1], human population density [2], and intensification of agriculture [3] have been linked to increasing transmission events for this group of infections. As such, there is a recognised need to be able to detect the presence of EDZs in the environment as a means to better anticipate transmission events and improve source attribution investigations. Finally, the recognition that a One Health approach is needed to combat these infections is signalling to governments the need to develop policy that optimises trade-offs across human, animal, and environmental health sectors. In this review, we discuss and critically appraise the main challenges relating to the epidemiology, diagnosis, and control of environmental zoonotic disease. Using a set of exemplar diseases, including avian influenza and antimicrobial resistant pathogens, we explore the epidemiological contexts (risk factors) within which these infections not only impact human health but also contribute to animal health and environmental impacts. We then critically appraise the surveillance challenges of monitoring these infections in the environment and examine the policy trade-offs for a more integrated approach to mitigating their impacts.

An argument for pandemic risk management using a multidisciplinary One Health approach to governance: an Australian case study

The emergence of SARS-CoV-2 and the subsequent COVID-19 pandemic has resulted in significant global impact. However, COVID-19 is just one of several high-impact infectious diseases that emerged from wildlife and are linked to the human relationship with nature. The rate of emergence of new zoonoses (diseases of animal origin) is increasing, driven by human-induced environmental changes that threaten biodiversity on a global scale. This increase is directly linked to environmental drivers including biodiversity loss, climate change and unsustainable resource extraction. Australia is a biodiversity hotspot and is subject to sustained and significant environmental change, increasing the risk of it being a location for pandemic origin. Moreover, the global integration of markets means that consumption trends in Australia contributes to the risk of disease spill-over in our regional neighbours in Asia-Pacific, and beyond. Despite the clear causal link between anthropogenic pressures on the environment and increasing pandemic risks, Australia’s response to the COVID-19 pandemic, like most of the world, has centred largely on public health strategies, with a clear focus on reactive management. Yet, the span of expertise and evidence relevant to the governance of pandemic risk management is much wider than public health and epidemiology. It involves animal/wildlife health, biosecurity, conservation sciences, social sciences, behavioural psychology, law, policy and economic analyses to name just a few.

The authors are a team of multidisciplinary practitioners and researchers who have worked together to analyse, synthesise, and harmonise the links between pandemic risk management approaches and issues in different disciplines to provide a holistic overview of current practice, and conclude the need for reform in Australia. We discuss the adoption of a comprehensive and interdisciplinary ‘One Health’ approach to pandemic risk management in Australia. A key goal of the One Health approach is to be proactive in countering threats of emerging infectious diseases and zoonoses through a recognition of the interdependence between human, animal, and environmental health. Developing ways to implement a One Health approach to pandemic prevention would not only reduce the risk of future pandemics emerging in or entering Australia, but also provide a model for prevention strategies around the world.

The association of wildfire air pollution with COVID-19 incidence in New South Wales, Australia

The 2020 COVID-19 outbreak in New South Wales (NSW), Australia, followed an unprecedented wildfire season that exposed large populations to wildfire smoke. Wildfires release particulate matter (PM), toxic gases and organic and non-organic chemicals that may be associated with increased incidence of COVID-19. This study estimated the association of wildfire smoke exposure with the incidence of COVID-19 in NSW. A Bayesian mixed-effect regression was used to estimate the association of either the average PM₁₀ level or the proportion of wildfire burned area as proxies of wildfire smoke exposure with COVID-19 incidence in NSW, adjusting for sociodemographic risk factors. The analysis followed an ecological design using the 129 NSW Local Government Areas (LGA) as the ecological units. A random effects model and a model including the LGA spatial distribution (spatial model) were compared. A higher proportional wildfire burned area was associated with higher COVID-19 incidence in both the random effects and spatial models after adjustment for sociodemographic factors (posterior mean = 1.32 (99% credible interval: 1.05-1.67) and 1.31 (99% credible interval: 1.03-1.65), respectively). No evidence of an association between the average PM₁₀ level and the COVID-19 incidence was found. LGAs in the greater Sydney and Hunter regions had the highest increase in the risk of COVID-19. This study identified wildfire smoke exposures were associated with increased risk of COVID-19 in NSW. Research on individual responses to specific wildfire airborne particles and pollutants needs to be conducted to further identify the causal links between SARS-Cov-2 infection and wildfire smoke. The identification of LGAs with the highest risk of COVID-19 associated with wildfire smoke exposure can be useful for public health prevention and or mitigation strategies.

Mapping the Morbidity Risk Associated with Coal Mining in Queensland, Australia

The populations in the vicinity of surface coal mining activities have a higher risk of morbidity due to diseases, such as cardiovascular, respiratory and hypertensive diseases, as well as cancer and diabetes mellitus. Despite the large and historical volume of coal production in Queensland, the main Australian coal mining state, there is little research on the association of coal mining exposures with morbidity in non-occupational populations in this region. This study explored the association of coal production (Gross Raw Output—GRO) with hospitalisations due to six disease groups in Queensland using a Bayesian spatial hierarchical analysis and considering the spatial distribution of the Local Government Areas (LGAs). There is a positive association of GRO with hospitalisations due to circulatory diseases (1.022, 99% CI: 1.002–1.043) and respiratory diseases (1.031, 95% CI: 1.001–1.062) for the whole of Queensland. A higher risk of circulatory, respiratory and chronic lower respiratory diseases is found in LGAs in northwest and central Queensland; and a higher risk of hypertensive diseases, diabetes mellitus and lung cancer is found in LGAs in north, west, and north and southeast Queensland, respectively. These findings can be used to support public health strategies to protect communities at risk. Further research is needed to identify the causal links between coal mining and morbidity in non-occupational populations in Queensland.