Lessons Learned from the Australian Bushfires: Climate Change, Air Pollution, and Public Health

How researchers can translate health evidence into books for children

The health promotion literature that considers how scientific evidence can be effectively communicated tends to focus on evaluating the effectiveness of communication materials. This has resulted in a knowledge gap regarding effective knowledge translation processes. This study explores the process, reasoning and practices for developing books for children that incorporate evidence-based information to aid understanding of scientific evidence about health and environmental or natural disasters. This study is informed by a systematic review of the literature combined with responses to an email interview with authors of books for children. Nine published studies were included in the systematic review. Twenty-two authors responded to the email survey (25% response rate, following 86 invitations). We report seven key findings to guide the development of health-promoting books for children: (i) understand the needs and expectations of the audience, (ii) articulate the topic and research evidence, (iii) assemble a team with a mix of content knowledge and creative expertise, (iv) format should be chosen to suit the user group and guided by the creative team, (v) early testing with children and their support system is crucial, (vi) develop a dissemination strategy to reach the user group and (vii) engage in reflexivity through evaluation of effectiveness of messaging. The current investigation can guide the process, reasoning and practice of developing books for children that incorporate evidence about health and environmental disasters.

The influence of the brand image of green agriculture products on China's consumption intention--The mediating role of perceived value

Green agriculture can minimize the negative impact of agriculture on the environment. As countries around the world strongly advocate green production and green life style, not only is consumers' awareness about green consumption rising, but the demand for green agricultural products at home and abroad is gradually increasing as well. Brand image has been a crucial factor for consumers to make their final purchasing decisions, thus playing a critical role in influencing the purchasing decisions of consumers. Based on the theory of the brand image, this paper undergoes a comprehensive theoretical and positive analysis and explores the influence mechanism of brand image of green agricultural products on consumers' purchasing intention. A hypothetical model with perceived value as mediators is constructed by us to examine the influence of brand image of green agricultural products on consumers' purchasing intention. A quantitative study was conducted for a random sample of 341 consumers who purchased green agricultural products in China according to a questionnaire-based survey using a cluster random sampling technique. The study showed that the overall image of agribusiness, the image of agricultural products, the social image of agribusiness, and the image of consumers are all positively related to consumption intention. The overall image of agribusiness, the image of agricultural products, the social image of agribusiness, and the image of consumers have a positive influence on perceived value. Moreover, perceived value plays a part in the mediating role in the influence of the overall image of agribusiness, the image of agricultural products, the social image of agribusiness, and the image of consumers on consumption intention. These findings shed lights on enterprises in establishing a scientific and effective brand strategy and building an excellent brand image. The research conclusion can provide new insight into how to enhance the consumption willingness for green agricultural products and promote sustainable development.

Recognising the importance of chronic lung disease: a consensus statement from the Global Alliance for Chronic Diseases (Lung Diseases group)

BACKGROUND

Chronic respiratory diseases are disorders of the airways and other structures of the lung, and include chronic obstructive pulmonary disease (COPD), lung cancer, asthma, bronchiectasis, interstitial lung diseases, occupational lung diseases and pulmonary hypertension. Through this article we take a broad view of chronic lung disease while highlighting (1) the complex interactions of lung diseases with environmental factors (e.g. climate change, smoking and vaping) and multimorbidity and (2) proposed areas to strengthen for better global patient outcomes.

CONCLUSION

We suggest new directions for the research agenda in high-priority populations and those experiencing health disparities. We call for lung disease to be made a research priority with greater funding allocation globally.

A Wildfire Smoke Detection System Using Unmanned Aerial Vehicle Images Based on the Optimized YOLOv5

Wildfire is one of the most significant dangers and the most serious natural catastrophe, endangering forest resources, animal life, and the human economy. Recent years have witnessed a rise in wildfire incidents. The two main factors are persistent human interference with the natural environment and global warming. Early detection of fire ignition from initial smoke can help firefighters react to such blazes before they become difficult to handle. Previous deep-learning approaches for wildfire smoke detection have been hampered by small or untrustworthy datasets, making it challenging to extrapolate the performances to real-world scenarios. In this study, we propose an early wildfire smoke detection system using unmanned aerial vehicle (UAV) images based on an improved YOLOv5. First, we curated a 6000-wildfire image dataset using existing UAV images. Second, we optimized the anchor box clustering using the K-mean++ technique to reduce classification errors. Then, we improved the network's backbone using a spatial pyramid pooling fast-plus layer to concentrate small-sized wildfire smoke regions. Third, a bidirectional feature pyramid network was applied to obtain a more accessible and faster multi-scale feature fusion. Finally, network pruning and transfer learning approaches were implemented to refine the network architecture and detection speed, and correctly identify small-scale wildfire smoke areas. The experimental results proved that the proposed method achieved an average precision of 73.6% and outperformed other one- and two-stage object detectors on a custom image dataset.

Double jeopardy-pregnancy and birth during a catastrophic bushfire event followed by a pandemic lockdown, a natural experiment

BACKGROUND

From November 2019 to January 2020, eastern Australia experienced the worst bushfires in recorded history. Two months later, Sydney and surrounds were placed into lockdown for six weeks due to the COVID-19 pandemic, followed by ongoing restrictions. Many pregnant women at this time were exposed to both the bushfires and COVID-19 restrictions.

OBJECTIVE

To assess the impact of exposure to bushfires and pandemic restrictions on perinatal outcomes.

METHODS

The study included 60 054 pregnant women who gave birth between November 2017 and December 2020 in South Sydney. Exposure cohorts were based on conception and birthing dates: 1) bushfire late pregnancy, born before lockdown; 2) bushfires in early-mid pregnancy, born during lockdown or soon after; 3) conceived during bushfires, lockdown in second trimester; 4) conceived after bushfires, pregnancy during restrictions. Exposure cohorts were compared with pregnancies in the matching periods in the two years prior. Associations between exposure cohorts and gestational diabetes, preeclampsia, hypertension, stillbirth, mode of birth, birthweight, preterm birth and small for gestational age were assessed using generalised estimating equations, adjusting for covariates.

RESULTS

A decrease in low birth weight was observed for cohort 1 (aOR 0.81, 95%CI 0.69, 0.95). Conversely, cohort 2 showed an increase in low birth weight, and increases in prelabour rupture of membranes, and caesarean sections (aOR 1.18, 95%CI 1.03, 1.37; aOR 1.21, 95%CI 1.07, 1.37; aOR 1.10 (1.02, 1.18) respectively). Cohort 3 showed an increase in unplanned caesarean sections and high birth weight babies (aOR 1.15, 95%CI 1.04, 1.27 and aOR 1.16, 95%CI 1.02, 1.31 respectively), and a decrease in gestational diabetes mellitus was observed for both cohorts 3 and 4.

CONCLUSION

Pregnancies exposed to both severe climate events and pandemic disruptions appear to have increased risk of adverse perinatal outcomes beyond only experiencing one event, but further research is needed.

FFireNet: Deep Learning Based Forest Fire Classification and Detection in Smart Cities

Forests are a vital natural resource that directly influences the ecosystem. Recently, forest fire has been a serious issue due to natural and man-made climate effects. For early forest fire detection, an artificial intelligence-based forest fire detection method in smart city application is presented to avoid major disasters. This research presents a review of the vision-based forest fire localization and classification methods. Furthermore, this work makes use of the forest fire detection dataset, which solves the classification problem of discriminating fire and no-fire images. This work proposes a deep learning method named FFireNet, by leveraging the pre-trained convolutional base of the MobileNetV2 model and adding fully connected layers to solve the new task, that is, the forest fire recognition problem, which helps in classifying images as forest fires based on extracted features which are symmetrical. The performance of the proposed solution for classifying fire and no-fire was evaluated using different performance metrics and compared with other CNN models. The results show that the proposed approach achieves 98.42% accuracy, 1.58% error rate, 99.47% recall, and 97.42% precision in classifying the fire and no-fire images. The outcomes of the proposed approach are promising for the forest fire classification problem considering the unique forest fire detection dataset.

Bushfire Smoke and Children's Health-Exploring a Communication Gap

The "Black Summer" bushfires of 2019/2020 in Australia generated smoke that persisted for over three months, mainly affecting Eastern Australia. Most communication strategies focused on the fire itself, revealing a knowledge gap in effective communication of the impact of bushfire smoke on health, especially for children and those living in non-English speaking minority groups. To address this, semi-structured qualitative interviews were undertaken with sixteen adults with caring (n = 11) or educational (n = 5) responsibilities for primary-school aged children (5-12 years, with some also having children up to 16 years) who had direct experience of the "Black Summer" bushfires. Overall, 43% (n = 7) of the sample spoke English as a first language, 25% (n = 4) spoke Turkish, with the remainder speaking Persian, Arabic, and Spanish. Thematic inductive qualitative content analysis revealed predominant themes of the role of parents and caregivers as conduits and curators of information. Air quality apps were the most common source of information. Language barriers and the lack of child-friendly methods of communication were highlighted as particular challenges. This qualitative study provides evidence for future development of communication strategies to better serve culturally and linguistically diverse individuals and the children in their care.

Government Actions and Their Relation to Resilience in Healthcare During the COVID-19 Pandemic in New South Wales, Australia and Ontario, Canada

BACKGROUND

Resilience, a system's ability to maintain a desired level of performance when circumstances disturb its functioning, is an increasingly important concept in healthcare. However, empirical investigations of resilience in healthcare (RiH) remain uncommon, particularly those that examine how government actions contribute to the capacity for resilient performance in the healthcare setting. We sought to investigate how governmental actions during the coronavirus disease 2019 (COVID-19) pandemic related to the concept of resilience, how these actions contributed to the potential for resilient performance in healthcare, and what opportunities exist for governments to foster resilience within healthcare systems.

METHODS

We conducted case studies of government actions pertaining to the COVID-19 pandemic in New South Wales, Australia and Ontario, Canada. Using media releases issued by each government between December 2019 and August 2020, we performed qualitative content analysis to identify themes relevant to the resilience potentials (anticipate, monitor, respond, learn) and RiH.

RESULTS

Direct references to the term 'resilience' appeared in the media releases of both governments. However, these references focused on the reactive aspects of resilience. While actions that constitute the resilience potentials were evident, the media releases also revealed opportunities to enhance learning (eg, a need to capitalize on opportunities for double-loop learning and identify strategies appropriate for complex systems) and anticipating (eg, incorporating the concept of hedging into frameworks of RiH).

CONCLUSION

Though fostering RiH through government action remains a challenge, this study suggests opportunities to realize this goal. Articulating a proactive vision of resilience and recognizing the complex nature of current systems could enhance governments' ability to coordinate resilient performance in healthcare. Reflection on how anticipation relates to resilience appears necessary at both the practical and conceptual levels to further develop the capacity for RiH.

Air pollution and health outcomes: Evidence from Black Saturday Bushfires in Australia

This paper presents new evidence of the causal effect of air pollution on Australian health outcomes, using the Black Saturday bushfires (BSB) in 2009 as a natural experiment. This event was one of the largest bushfires in Australian history and emitted approximately four million tonnes of CO₂ into the atmosphere. We use data from the Household Income and Labour Dynamic Australia (HILDA) panel and compare the health status of individuals who were living in affected and unaffected regions before and after the event. Using a triple differences procedure, we further examine whether a difference in vulnerability to bushfire smoke exists comparing people living in urban or regional areas. We find that ambient air pollution had significant negative effects on health and that the magnitudes were actually larger for individuals residing in urban areas.

Pandemic and the Nature-Alienated Self

This consideration of COVID-19 places the pandemic in the larger context of our present-day ontology and the environmentally destructive human–nature relationship that characterizes it, exploring it in three parts. First, it sets out the problematic conceptualization of nature in the modern social imaginary by focusing upon the self in terms of its sense of identity, agency and authority. Second, it sets out how the pandemic fundamentally disrupts these three facets of the self in terms of the fragilization of economic values, the notion of unique human agency, and the limitation of the authority of discursive reason. Finally, it concludes by outlining the opportunity for a renewed relationship with nature by proposing the recovery of the premodern concepts of metaphysical participation, teleology, and rational intuition. In doing so, the pandemic crisis is considered in the wider context of the ecological crisis of the modern age, and as an opportunity for rethinking our collective concept of nature, and the place of our selves within it.

Bushfire Smoke in Our Eyes: Community Perceptions and Responses to an Intense Smoke Event in Canberra, Australia

The 2019–20 bushfires that raged in eastern Australia were an overwhelming natural disaster leading to lives lost or upended, and communities destroyed. For almost a month, Canberra, Australia's capital city in the Australian Capital Territory (ACT), was obscured by smoke from fires which threatened the outer suburbs. While smoke itself is experientially different from many natural disasters, it nevertheless poses a significant public health threat. As the impact of extended bushfire smoke in an urban setting is relatively unexplored we aimed to capture the individual and community-level experiences of the event and their importance for community and social functioning. We responded rapidly by conducting semi-structured interviews with a range of Canberra residents who, due to their personal or social circumstances, were potentially vulnerable to the effects of the smoke. Three major themes emerging from the narratives depicted disruption to daily life, physical and psychological effects, and shifting social connectedness. This study highlighted the ambiguous yet impactful nature of a bushfire smoke event, and identified four simple key messages that may be critically relevant to policy making in preparation for similar smoke events in the future.

Efficacy of Communication Techniques and Health Outcomes of Bushfire Smoke Exposure: A Scoping Review

Public health officials communicate the relevant risks of bushfire smoke exposure and associated health protection measures to affected populations. Increasing global bushfire incidence in the context of climate change motivated this scoping review. English-language publications related to adverse health outcomes following bushfire smoke exposure and publications relating to communication during natural disasters were included. Bushfire smoke events potentially increase healthcare contact, especially presentations triggered by respiratory illness. At-risk populations include those with underlying cardiorespiratory disease, elderly, paediatric, pregnant persons, and First Nations people. We found that social media, television, and radio are among the most common information sources utilised in bushfire smoke events. Message style, content, and method of delivery can directly influence message uptake and behaviour modification. Age, rurality, and geographical location influence information source preferences. Culturally and linguistically diverse groups and those with hearing, vision, and mobility-related disabilities may benefit from targeted health recommendations. This review emphasises the health effects of bushfire smoke exposure and related communication recommendations during and after bushfire smoke events. Additional investigation may further clarify the health effects of bushfire smoke exposure and efficacy of related health messaging, particularly in at-risk populations. Quantitative comparison of communication methods may yield more specific recommendations for future bushfire smoke events.

Environmental Air Pollutants Inhaled during Pregnancy Are Associated with Altered Cord Blood Immune Cell Profiles

Air pollution exposure during pregnancy may be a risk factor for altered immune maturation in the offspring. We investigated the association between ambient air pollutants during pregnancy and cell populations in cord blood from babies born to mothers with asthma enrolled in the Breathing for Life Trial. For each patient (n = 91), daily mean ambient air pollutant levels were extracted during their entire pregnancy for sulfur dioxide (SO₂), nitric oxide, nitrogen dioxide, carbon monoxide, ozone, particulate matter <10 μm (PM₁₀) or <2.5 μm (PM_2.5), humidity, and temperature. Ninety-one cord blood samples were collected, stained, and assessed using fluorescence-activated cell sorting (FACS). Principal Component (PC) analyses of both air pollutants and cell types with linear regression were employed to define associations. Considering risk factors and correlations between PCs, only one PC from air pollutants and two from cell types were statistically significant. PCs from air pollutants were characterized by higher PM_2.5 and lower SO₂ levels. PCs from cell types were characterized by high numbers of CD8 T cells, low numbers of CD4 T cells, and by high numbers of plasmacytoid dendritic cells (pDC) and low numbers of myeloid DCs (mDCs). PM_2.5 levels during pregnancy were significantly associated with high numbers of pDCs (p = 0.006), and SO₂ with high numbers of CD8 T cells (p = 0.002) and low numbers of CD4 T cells (p = 0.011) and mDCs (p = 4.43 × 10⁻⁶) in cord blood. These data suggest that ambient SO₂ and PM_2.5 exposure are associated with shifts in cord blood cell types that are known to play significant roles in inflammatory respiratory disease in childhood.

Policy Implications for Protecting Health from the Hazards of Fire Smoke. A Panel Discussion Report from the Workshop Landscape Fire Smoke: Protecting Health in an Era of Escalating Fire Risk

Globally, and nationally in Australia, bushfires are expected to increase in frequency and intensity due to climate change. To date, protection of human health from fire smoke has largely relied on individual-level actions. Recent bushfires experienced during the Australian summer of 2019–2020 occurred over a prolonged period and encompassed far larger geographical areas than previously experienced, resulting in extreme levels of smoke for extended periods of time. This particular bushfire season resulted in highly challenging conditions, where many people were unable to protect themselves from smoke exposures. The Centre for Air pollution, energy and health Research (CAR), an Australian research centre, hosted a two-day symposium, Landscape Fire Smoke: Protecting health in an era of escalating fire risk, on 8 and 9 October 2020. One component of the symposium was a dedicated panel discussion where invited experts were asked to examine alternative policy settings for protecting health from fire smoke hazards with specific reference to interventions to minimise exposure, protection of outdoor workers, and current systems for communicating health risk. This paper documents the proceedings of the expert panel and participant discussion held during the workshop.

Impact of exposure to mine fire emitted PM2.5 on ambulance attendances: A time series analysis from the Hazelwood Health Study

BACKGROUND

For six weeks from February 9, 2014, smoke and ash from a fire in the Morwell open cut brown coal mine adjacent to the Hazelwood power station covered parts of the Latrobe Valley, in south eastern Australia.

AIMS

To evaluate the health impact of the mine fire, daily counts of ambulance attendances from July 2010 to March 2015 were analysed.

METHODS

Time series models were used to evaluate the relative risk of ambulance attendances during the mine fire, in comparison with the remainder of the analysis period, and to also assess the risk of ambulance attendances associated with lagged effects of exposure to mine fire-related PM_2.5 levels. The models controlled for factors likely to influence ambulance attendances including seasonality, long-term temporal trends, day of the week, daily maximum temperature and public holidays.

RESULTS

A 10 μg/m³ increase in fire-related PM_2.5 was found to be associated with a 42% (95%CI: 14-76%) increase in ambulance attendances for respiratory conditions and a 7% (0-14%) increase in all ambulance attendances over a 20-day lag period. A smaller effect associated with exposure to fire-related PM_2.5 was identified when assuming shorter lag effects. Similar results were identified when assessing whether ambulance attendances increased during the 30-day mine fire period. There was a 15% (8-21%) increased risk of ambulance attendances for all conditions and a 47% (19-81%) increased risk for respiratory conditions during the mine fire period.

CONCLUSIONS

Exposure to smoke and ash from a fire in an open cut brown coal mine was associated with increased ambulance attendances, particularly for respiratory conditions. These findings guide the development and implementation of effective and timely strategies and health service planning to respond and mitigate health risks that arise in affected communities during future major air pollution episodes.

Air quality and health impact of 2019-20 Black Summer megafires and COVID-19 lockdown in Melbourne and Sydney, Australia

Poor air quality is an emerging problem in Australia primarily due to ozone pollution events and lengthening and more severe wildfire seasons. A significant deterioration in air quality was experienced in Australia's most populous cities, Melbourne and Sydney, as a result of fires during the so-called Black Summer which ran from November 2019 through to February 2020. Following this period, social, mobility and economic restrictions to curb the spread of the COVID-19 pandemic were implemented in Australia. We quantify the air quality impact of these contrasting periods in the south-eastern states of Victoria and New South Wales (NSW) using a meteorological normalisation approach. A Random Forest (RF) machine learning algorithm was used to compute baseline time series' of nitrogen dioxide (NO₂), ozone (O₃), carbon monoxide CO and particulate matter with diameter < 2.5 μm (PM_2.5), based on a 19 year, detrended training dataset. Across Victorian sites, large increases in CO (188%), PM_2.5 (322%) and ozone (22%) were observed over the RF prediction in January 2020. In NSW, smaller pollutant increases above the RF prediction were seen (CO 58%, PM_2.5 80%, ozone 19%). This can be partly explained by the RF predictions being high compared to the mean of previous months, due to high temperatures and strong wind speeds, highlighting the importance of meteorological normalisation in attributing pollution changes to specific events. From the daily observation-RF prediction differences we estimated 249.8 (95% CI: 156.6-343.) excess deaths and 3490.0 (95% CI 1325.9-5653.5) additional hospitalisations were likely as a result of PM_2.5 and O₃ exposure in Victoria and NSW. During April 2019, when COVID-19 restrictions were in place, on average NO₂ decreased by 21.5 and 8% in Victoria and NSW respectively. O₃ and PM_2.5 remained effectively unchanged in Victoria on average but increased by 20 and 24% in NSW respectively, supporting the suggestion that community mobility reduced more in Victoria than NSW. Overall the air quality change during the COVID-19 lockdown had a negligible impact on the calculated health outcomes.

Exploratory Analysis of Driving Force of Wildfires in Australia: An Application of Machine Learning within Google Earth Engine

Recent studies have suggested that due to climate change, the number of wildfires across the globe have been increasing and continue to grow even more. The recent massive wildfires, which hit Australia during the 2019–2020 summer season, raised questions to what extent the risk of wildfires can be linked to various climate, environmental, topographical, and social factors and how to predict fire occurrences to take preventive measures. Hence, the main objective of this study was to develop an automatized and cloud-based workflow for generating a training dataset of fire events at a continental level using freely available remote sensing data with a reasonable computational expense for injecting into machine learning models. As a result, a data-driven model was set up in Google Earth Engine platform, which is publicly accessible and open for further adjustments. The training dataset was applied to different machine learning algorithms, i.e., Random Forest, Naïve Bayes, and Classification and Regression Tree. The findings show that Random Forest outperformed other algorithms and hence it was used further to explore the driving factors using variable importance analysis. The study indicates the probability of fire occurrences across Australia as well as identifies the potential driving factors of Australian wildfires for the 2019–2020 summer season. The methodical approach and achieved results and drawn conclusions can be of great importance to policymakers, environmentalists, and climate change researchers, among others.