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

ABSTRACT: 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.

SUBMITTER: Cortes-Ramirez J

PROVIDER: S-EPMC8532327 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:IntroductionExposure to high ambient temperatures and air pollution has been shown to increase the risk of spontaneous preterm birth (sPTB). Less clear are the effects of cold and the joint effects of air pollution and temperature.MethodsUsing a Cox proportional hazard regression model, we assessed the risk of independent and combined short-term exposure to ambient daily mean temperature and PM2.5 associated with sPTB in the last week before delivery on overall sPTB (weeks 23-36) and three subtypes: extremely sPTB, very sPTB, and moderate-to-late sPTB for a birth cohort of 1,318,570 births from Australia (Jan 2001-Dec 2019), while controlling for chronic exposure (i.e., throughout pregnancy except the last week before delivery) to PM2.5 and temperature. The temperature was modeled as a natural cubic spline, PM2.5 as a linear term, and the interaction effect was estimated using a multiplicative term. For short-term exposure to temperature hazard ratios reported are relative to the median temperature (18.1°C).ResultsHazard ratios at low temperature [5th percentile(11.5°C)] were 0.95 (95% CI: 0.90, 1.00), 1.08 (95% CI: 0.84, 1.4), 0.87 (95% CI: 0.71, 1.06), and 1.00 (95% CI: 0.94, 1.06) and greater for high temperature [95th percentile (24.5°C)]: 1.22 (95% CI: 1.16, 1.28), 1.27 (95% CI: 1.03, 1.57), and 1.26 (95% CI: 1.05, 1.5) and 1.05 (1.00, 1.11), respectively, for overall, extremely, very, and moderate-to-late sPTBs. While chronic exposure to PM2.5 had adverse effects on sPTB, short-term exposure to PM2.5 appeared to have a negative association with all types of sPTB, with hazard ratios ranging from 0.86 (95th CI: 0.80, 0.94) to 0.98 (95th CI: 0.97, 1.00) per 5 μg/m3 increase in PM2.5.DiscussionThe risk of sPTB was found to increase following acute exposure to hot and cold ambient temperatures. Earlier sPTB subtypes seemed to be the most vulnerable. This study adds to the evidence that short-term exposure to ambient cold and heat and longer term gestational exposure to ambient PM2.5 are associated with an elevated risk of sPTB.

Project description:BackgroundDigital proximity tracing apps were rolled out early in the COVID-19 pandemic in many countries to complement conventional contact tracing. Empirical evidence about their benefits for pandemic response remains scarce. We evaluated the effectiveness and usefulness of COVIDSafe, Australia's national smartphone-based proximity tracing app for COVID-19.MethodsIn this prospective study, done in New South Wales (NSW), Australia, we included all individuals in the state who were older than 12 years with confirmed, locally acquired SARS-CoV-2 infection between May 4 and Nov 4, 2020. We used data from the NSW Notifiable Conditions Information Management System, the national COVIDSafe database, and information from case interviews, including information on app usage, the number of app-suggested contacts, and the number of app-suggested contacts determined by public health staff to be actual close contacts. We calculated the positive predictive value and sensitivity of COVIDSafe, its additional contact yield, and the number of averted public exposure events. Semi-structured interviews with public health staff were done to assess the app's perceived usefulness.FindingsThere were 619 confirmed COVID-19 cases with more than 25 300 close contacts identified by conventional contact tracing during the study period. COVIDSafe was used by 137 (22%) cases and detected 205 contacts, 79 (39%) of whom met the close contact definition. Its positive predictive value was therefore 39%. 35 (15%) of the 236 close contacts who could have been expected to have been using the app during the study period were identified by the app, making its estimated sensitivity 15%. 79 (0·3%) of the estimated 25 300 contacts in NSW were app-suggested and met the close contact definition. The app detected 17 (<0·1%) additional close contacts who were not identified by conventional contact tracing. COVIDSafe generated a substantial additional perceived workload for public health staff and was not considered useful.InterpretationThe low uptake of the app among cases probably led to a reduced sensitivity estimate in our study, given that only contacts who were using the app could be detected. COVIDSafe was not sufficiently effective to make a meaningful contribution to the COVID-19 response in Australia's most populous state over a 6 month period. We provide an empirical evaluation of this digital contact tracing app that questions the potential benefits of digital contact tracing apps to the public health response to COVID-19. Effectiveness evaluations should be integrated into future implementations of proximity contact tracing systems to justify their investment.FundingNew South Wales Ministry of Health (Australia); National Health and Medical Research Council (Australia).

Project description:The 2019-2020 summer wildfire event on the east coast of Australia was a series of major wildfires occurring from November 2019 to end of January 2020 across the states of Queensland, New South Wales (NSW), Victoria and South Australia. The wildfires were unprecedent in scope and the extensive character of the wildfires caused smoke pollutants to be transported not only to New Zealand, but also across the Pacific Ocean to South America. At the peak of the wildfires, smoke plumes were injected into the stratosphere at a height of up to 25 km and hence transported across the globe. The meteorological and air quality Weather Research and Forecasting with Chemistry (WRF-Chem) model is used together with the air quality monitoring data collected during the bushfire period and remote sensing data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellites to determine the extent of the wildfires, the pollutant transport and their impacts on air quality and health of the exposed population in NSW. The results showed that the WRF-Chem model using Fire Emission Inventory (FINN) from National Center for Atmospheric Research (NCAR) to simulate the dispersion and transport of pollutants from wildfires predicted the daily concentration of PM2.5 having the correlation (R2) and index of agreement (IOA) from 0.6 to 0.75 and 0.61 to 0.86, respectively, when compared with the ground-based data. The impact on health endpoints such as mortality and respiratory and cardiovascular diseases hospitalizations across the modelling domain was then estimated. The estimated health impact on each of the Australian Bureau of Statistics (ABS) census districts (SA4) of New South Wales was calculated based on epidemiological assumptions of the impact function and incidence rate data from the 2016 ABS and NSW Department of Health statistical health records. Summing up all SA4 census district results over NSW, we estimated that there were 247 (CI: 89, 409) premature deaths, 437 (CI: 81, 984) cardiovascular diseases hospitalizations and 1535 (CI: 493, 2087) respiratory diseases hospitalizations in NSW over the period from 1 November 2019 to 8 January 2020. The results are comparable with a previous study based only on observation data, but the results in this study provide much more spatially and temporally detailed data with regard to the health impact from the summer 2019-2020 wildfires.

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

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