Excess emergency department visits for cardiovascular and respiratory diseases during the 2019-20 bushfire period in Australia: A two-stage interrupted time-series analysis

Residuals in space: Potential pitfalls and applications from single-institution survival analysis

In practice, survival analyses appear in pharmaceutical testing, procedural recovery environments, and registry-based epidemiological studies, each reasonably assuming a known patient population. Less commonly discussed is the additional complexity introduced by non-registry and spatially-referenced data with time-dependent covariates in observational settings. In this short report we discuss residual diagnostics and interpretation from an extended Cox proportional hazard model intended to assess the effects of wildfire evacuation on risk of a secondary cardiovascular events for patients of a specific healthcare system on the California's central coast. We describe how traditional residuals obscure important spatial patterns indicative of true geographical variation, and their impacts on model parameter estimates. We briefly discuss alternative approaches to dealing with spatial correlation in the context of Bayesian hierarchical models. Our findings/experience suggest that careful attention is needed in observational healthcare data and survival analysis contexts, but also highlights potential applications for detecting observed hospital service areas.

Climate Change, Landscape Fires, and Human Health: A Global Perspective

Landscape fires are an integral component of the Earth system and a feature of prehistoric, subsistence, and industrial economies. Specific spatiotemporal patterns of landscape fire occur in different locations around the world, shaped by the interactions between environmental and human drivers of fire activity. Seven distinct types of landscape fire emerge from these interactions: remote area fires, wildfire disasters, savanna fires, Indigenous burning, prescribed burning, agricultural burning, and deforestation fires. All can have substantial impacts on human health and well-being directly and indirectly through (a) exposure to heat flux (e.g., injuries and destructive impacts), (b) emissions (e.g., smoke-related health impacts), and (c) altered ecosystem functioning (e.g., biodiversity, amenity, water quality, and climate impacts). Minimizing the adverse effects of landscape fires on population health requires understanding how human and environmental influences on fire impacts can be modified through interventions targeted at individual, community, and regional levels.

Geospatial analysis of short-term exposure to air pollution and risk of cardiovascular diseases and mortality-A systematic review

The cardiovascular risk associated with short-term ambient air pollution exposure is well-documented. However, recent advancements in geospatial techniques have provided new insights into this risk. This systematic review focuses on short-term exposure studies that applied advanced geospatial pollution modelling to estimate cardiovascular disease (CVD) risk and accounted for additional unconventional neighbourhood-level confounders to analyse their modifier effect on the risk. Four databases were investigated to select publications between 2018 and 2023 that met the inclusion criteria of studying the effect of particulate matter (PM2.5 and PM10), SO2, NOx, CO, and O3 on CVD mortality or morbidity, utilizing pollution modelling techniques, and considering spatial and temporal confounders. Out of 3277 publications, 285 were identified for full-text review, of which 34 satisfied the inclusion criteria for qualitative analysis, and 12 of them were chosen for additional quantitative analysis. Quality assessment revealed that 28 out of 34 included articles scored 4 or above, indicating high quality. In 30 studies, advanced pollution modelling techniques were used, while in 4 only simpler methods were applied. The most pertinent confounders identified were socio-demographic variables (e.g., socio-economic status, population percentage by race or ethnicity) and neighbourhood-level built environment variables (e.g., urban/rural area, percentage of green space, proximity to healthcare), which exhibited varying modifier effects depending on the context. In the quantitative analysis, only PM 2.5 showed a significant positive association to all-cause CVD-related hospitalisation. Other pollutants did not show any significant effect, likely due to the high inter-study heterogeneity and a limited number of cases. The application of advanced geospatial measurement and modelling of air pollution exposure, as well as its risk, is increasing. This review underscores the importance of accounting for unconventional neighbourhood-level confounders to enhance the understanding of the CVD risk associated with short-term pollution exposure.

Measuring long-term exposure to wildfire PM2.5 in California: Time-varying inequities in environmental burden

Wildfires have become more frequent and intense due to climate change and outdoor wildfire fine particulate matter (PM2.5) concentrations differ from relatively smoothly varying total PM2.5. Thus, we introduced a conceptual model for computing long-term wildfire PM2.5 and assessed disproportionate exposures among marginalized communities. We used monitoring data and statistical techniques to characterize annual wildfire PM2.5 exposure based on intermittent and extreme daily wildfire PM2.5 concentrations in California census tracts (2006 to 2020). Metrics included: 1) weeks with wildfire PM2.5 < 5 μg/m3; 2) days with non-zero wildfire PM2.5; 3) mean wildfire PM2.5 during peak exposure week; 4) smoke waves (≥2 consecutive days with <15 μg/m3 wildfire PM2.5); and 5) mean annual wildfire PM2.5 concentration. We classified tracts by their racial/ethnic composition and CalEnviroScreen (CES) score, an environmental and social vulnerability composite measure. We examined associations of CES and racial/ethnic composition with the wildfire PM2.5 metrics using mixed-effects models. Averaged 2006 to 2020, we detected little difference in exposure by CES score or racial/ethnic composition, except for non-Hispanic American Indian and Alaska Native populations, where a 1-SD increase was associated with higher exposure for 4/5 metrics. CES or racial/ethnic × year interaction term models revealed exposure disparities in some years. Compared to their California-wide representation, the exposed populations of non-Hispanic American Indian and Alaska Native (1.68×, 95% CI: 1.01 to 2.81), white (1.13×, 95% CI: 0.99 to 1.32), and multiracial (1.06×, 95% CI: 0.97 to 1.23) people were over-represented from 2006 to 2020. In conclusion, during our study period in California, we detected disproportionate long-term wildfire PM2.5 exposure for several racial/ethnic groups.

Wildfire smoke exposure during pregnancy and perinatal, obstetric, and early childhood health outcomes: A systematic review and meta-analysis

BACKGROUND

Maternal exposure to air pollution during pregnancy is associated with adverse birth outcomes, although less is known for wildfire smoke. This systematic review evaluated the association between maternal exposure to wildfire smoke during pregnancy and the risk of perinatal, obstetric, and early childhood health outcomes.

METHODS

We searched CINAHL Complete, Ovid/EMBASE, Ovid/MEDLINE, ProQuest, PubMed, Scopus, Web of Science, and Google Scholar to identify relevant epidemiological observational studies indexed through September 2023. The screening of titles, abstracts, and full-texts, data extraction, and risk of bias assessment was performed by pairs of independent reviewers.

RESULTS

Our systematic search yielded 28,549 records. After duplicate removal, we screened 14,009 studies, identifying 31 for inclusion in the present review. Data extraction highlighted high methodological heterogeneity between studies, including a lack of geographic variation. Approximately 56.5% and 16% originated in the United States and Brazil, respectively, and fewer in other countries. Among the studies, wildfire smoke exposure during pregnancy was assessed using distance of residence from wildfire-affected areas (n = 15), measurement of air pollutant concentration during wildfires (n = 11), number of wildfire records (n = 3), aerosol index (n = 1), and geographic hot spots (n = 1). Pooled meta-analysis for birthweight and low birthweight were inconclusive, likely due to low number of methodologically homogenous studies. However, the reviewed studies provided suggestive evidence for an increased risk of birthweight reduction, low birthweight, preterm birth, and other adverse health outcomes.

CONCLUSIONS

This review identified 31 studies evaluating the impacts of maternal wildfire smoke exposure on maternal, infant, and child health. Although we found suggestive evidence of harm from exposure to wildfire smoke during pregnancy, more methodologically homogenous studies are required to enable future meta-analysis with greater statistical power to more accurately evaluate the association between maternal wildfire smoke and adverse birth outcomes and other health outcomes.

Climate change, environmental extremes, and human health in Australia: challenges, adaptation strategies, and policy gaps

Climate change presents a major public health concern in Australia, marked by unprecedented wildfires, heatwaves, floods, droughts, and the spread of climate-sensitive infectious diseases. Despite these challenges, Australia's response to the climate crisis has been inadequate and subject to change by politics, public sentiment, and global developments. This study illustrates the spatiotemporal patterns of selected climate-related environmental extremes (heatwaves, wildfires, floods, and droughts) across Australia during the past two decades, and summarizes climate adaptation measures and actions that have been taken by the national, state/territory, and local governments. Our findings reveal significant impacts of climate-related environmental extremes on the health and well-being of Australians. While governments have implemented various adaptation strategies, these plans must be further developed to yield concrete actions. Moreover, Indigenous Australians should not be left out in these adaptation efforts. A collaborative, comprehensive approach involving all levels of government is urgently needed to prevent, mitigate, and adapt to the health impacts of climate change.

Impacts of Climate Change on Health and Health Services in Northern New South Wales, Australia: A Rapid Review

Climate change is exposing populations to increasing temperatures and extreme weather events in many parts of Australia. To prepare for climate challenges, there is a growing need for Local Health Districts (LHDs) to identify potential health impacts in their region and strengthen the capacity of the health system to respond accordingly. This rapid review summarised existing evidence and research gaps on the impact of climate change on health and health services in Northern New South Wales (NSW)-a 'hotspot' for climate disaster declarations. We systematically searched online databases and selected 11 peer-reviewed studies published between 2012-2022 for the Northern NSW region. The most explored health outcome was mental health in the aftermath of floods and droughts, followed by increased healthcare utilisation due to respiratory, cardiovascular and mortality outcomes associated with bushfire smoke or heat waves. Future research directions were recommended to understand: the compounding impacts of extreme events on health and the health system, local data needs that can better inform models that predict future health risks and healthcare utilisation for the region, and the needs of vulnerable populations that require a whole-of-system response during the different phases of disasters. In conclusion, the review provided climate change and health research directions the LHD may undertake to inform future adaptation and mitigation policies and strategies relevant to their region.

Non-pharmaceutical interventions for COVID-19 reduced the incidence of infectious diseases: a controlled interrupted time-series study

BACKGROUND

Non-pharmaceutical interventions (NPIs) have been implemented worldwide to suppress the spread of coronavirus disease 2019 (COVID-19). However, few studies have evaluated the effect of NPIs on other infectious diseases and none has assessed the avoided disease burden associated with NPIs. We aimed to assess the effect of NPIs on the incidence of infectious diseases during the COVID-19 pandemic in 2020 and evaluate the health economic benefits related to the reduction in the incidence of infectious diseases.

METHODS

Data on 10 notifiable infectious diseases across China during 2010-2020 were extracted from the China Information System for Disease Control and Prevention. A two-stage controlled interrupted time-series design with a quasi-Poisson regression model was used to examine the impact of NPIs on the incidence of infectious diseases. The analysis was first performed at the provincial-level administrative divisions (PLADs) level in China, then the PLAD-specific estimates were pooled using a random-effect meta-analysis.

RESULTS

A total of 61,393,737 cases of 10 infectious diseases were identified. The implementation of NPIs was associated with 5.13 million (95% confidence interval [CI] 3.45‒7.42) avoided cases and USD 1.77 billion (95% CI 1.18‒2.57) avoided hospital expenditures in 2020. There were 4.52 million (95% CI 3.00‒6.63) avoided cases for children and adolescents, corresponding to 88.2% of total avoided cases. The top leading cause of avoided burden attributable to NPIs was influenza [avoided percentage (AP): 89.3%; 95% CI 84.5‒92.6]. Socioeconomic status and population density were effect modifiers.

CONCLUSIONS

NPIs for COVID-19 could effectively control the prevalence of infectious diseases, with patterns of risk varying by socioeconomic status. These findings have important implications for informing targeted strategies to prevent infectious diseases.

Long-term impacts of non-occupational wildfire exposure on human health: A systematic review

The intensity and frequency of wildfires is increasing globally. The systematic review of the current evidence on long-term impacts of non-occupational wildfire exposure on human health has not been performed yet. To provide a systematic review and identify potential knowledge gaps in the current evidence of long-term impacts of non-occupational exposure to wildfire smoke and/or wildfire impacts on human health. We conducted a systematic search of the literature via MEDLINE, Embase and Scopus from the database inception to July 05, 2022. References from the included studies and relevant reviews were also considered. The Newcastle-Ottawa Scale (NOS) and a validated quality assessment framework were used to evaluate the quality of observational studies. Study results were synthesized descriptively. A total of 36 studies were included in our systematic review. Most studies were from developed countries (11 in Australia, 9 in Canada, 7 in the United States). Studies predominantly focused on mental health (21 studies, 58.33%), while evidence on long-term impacts of wildfire exposure on health outcomes other than mental health is limited. Current evidence indicated that long-term impacts of non-occupational wildfire exposure were associated with mortality (COVID-19 mortality, cardiovascular disease mortality and acute myocardial disease mortality), morbidity (mainly respiratory diseases), mental health disorders (mainly posttraumatic stress disorder), shorter height of children, reduced lung function and poorer general health status. However, no significant associations were observed for long-term impacts of wildfire exposure on child mortality and respiratory hospitalizations. The population-based high-quality evidence with quantitative analysis on this topic is still limited. Future well-designed studies considering extensive wildfire smoke air pollutants (e.g., particulate matter, ozone, nitrogen oxides) and estimating risk coefficient values for extensive health outcomes (e.g., mortality, morbidity) are warranted to fill current knowledge gaps.

Projecting Future Climate Impact on National Australian Respiratory-Related Intensive Care Unit Demand

BACKGROUND AND AIMS

A robust climate-health projection model has the potential to improve health care resource allocation. We aim to explore the relationship between Australian intensive care unit (ICU) demand and various measures of the long-lived large-scale climate and to develop a future nationwide climate-health projection model.

METHODS

We investigated patients admitted to ICUs in Australia between January 2003 and December 2019 who were exposed to long-lived large-scale combined climatic measures of temperature and humidity. We analysed the projected demand for respiratory-related ICU average length of stay (in days) per capita (ICU_D/C) with four historical and one future projection dataset. These datasets included: i) Australian and New Zealand Intensive Care Society adult patient database, ii) Socioeconomic Data and Applications Center gridded global historical population, iii) Australian Bureau of Statistics national historical population, iv) Japanese 55-year Reanalysis historical climate (JRA55), and v) the fifth Coupled Model Inter-comparison Project future climate projections.

RESULTS

148,638 patients with respiratory issues required intensive care between 2003 and 2019. The annual growth in the population density-weighted wet-bulb-globe temperature-a combined measure of temperature and humidity-is strongly correlated with the annual per capita growth ICU_D/C for respiratory-related conditions (r=0.771; p<0.001). This relationship was applied to develop a model projecting future respiratory-related ICU demand with three possible future Representative Concentration Pathways (RCP). RCP2.6 (lowest carbon emission climate scenario) showed only a 33.4% increase in Australian ICU_D/C demand by 2090, while the RCP8.5 (highest carbon emission climate scenario) demonstrated almost two-fold higher demand (66.1%) than RCP2.6 by 2090.

CONCLUSIONS

The annual growth in population density-weighted wet-bulb-globe temperature correlates with the annual growth in Australian ICU_D/C for respiratory-related conditions. A model based on possible future climate scenarios can be developed to predict changes in ICU demand in response to CO₂ changes over the coming decades.

Toward informatics-enabled preparedness for natural hazards to minimize health impacts of climate change

Natural hazards (NHs) associated with climate change have been increasing in frequency and intensity. These acute events impact humans both directly and through their effects on social and environmental determinants of health. Rather than relying on a fully reactive incident response disposition, it is crucial to ramp up preparedness initiatives for worsening case scenarios. In this perspective, we review the landscape of NH effects for human health and explore the potential of health informatics to address associated challenges, specifically from a preparedness angle. We outline important components in a health informatics agenda for hazard preparedness involving hazard-disease associations, social determinants of health, and hazard forecasting models, and call for novel methods to integrate them toward projecting healthcare needs in the wake of a hazard. We describe potential gaps and barriers in implementing these components and propose some high-level ideas to address them.