ABSTRACT
In early 2014, the Hazelwood coalmine fire covered the regional Australian town of Morwell in smoke and ash for 45 days. One of the fires by-products, PM2.5, has been linked higher rates of COVID-19 infection to increased expression of the ACE2 receptor, which the COVID-19 virus uses to infect cells throughout the body. However, it is unclear whether the effect persists for years after exposure. In this study, we surveyed a cohort established prior to the pandemic to determine whether PM2.5 from the coalmine fire increased long-term vulnerability to COVID-19 infection and severe disease. In late 2022, 612 members of the Hazelwood Health Studys adult cohort, established in 2016/17, participated in a follow-up survey including standardised items to capture COVID-19 infections, hospitalisations, and vaccinations. Associations were evaluated in crude and adjusted logistic regression models, applying statistical weighting for survey response and multiple imputation to account for missing data, with sensitivity analyses to test the robustness of results. A total of 271 (44%) participants self-reported or met symptom criteria for at least one COVID-19 infection. All models found a positive association, with odds of infection increasing by between 4-21% for every standard deviation (12.3{micro}g/m3) increase in mine fire-related PM2.5 exposure. However, this was not statistically significant in any model. There were insufficient hospitalisations to examine severity (n=7; 1%). The findings were inconclusive in ruling out an effect of PM2.5 exposure from coalmine fire on long-term vulnerability to COVID-19 infection. Given the positive association that was robust to modelling variations as well as evidence for a causal mechanism, it would be prudent to treat PM2.5 from fire events as a risk factor for long-term COVID-19 vulnerability until more evidence accumulates.
Subject(s)
COVID-19ABSTRACT
Background and objective Ecological studies indicate ambient particulate matter [≤]2.5mm (PM2.5) air pollution is associated with poorer COVID-19 outcomes. However, these studies cannot account for individual heterogeneity and often have imprecise estimates of PM2.5 exposure. We review evidence from studies using individual-level data to determine whether PM2.5 increases risk of COVID-19 infection, severe disease, and death. Methods Systematic review of case-control and cohort studies, searching Medline, Embase, and WHO COVID-19 up to 30 June 2022. Study quality was evaluated using the Newcastle-Ottawa Scale. Results were pooled with a random effects meta-analysis, with Egger's regression, funnel plots, and leave-one-out and trim-and-fill analyses to adjust for publication bias. Results N=18 studies met inclusion criteria. A 10g/m3 increase in PM2.5 exposure was associated with 66% (95% CI: 1.31-2.11) greater odds of COVID-19 infection (N=7) and 127% (95% CI: 1.41-3.66) increase in severe illness (hospitalisation or worse) (N=6). Pooled mortality results (N=5) were positive but non-significant (OR 1.40; 0.94 to 2.10). Most studies were rated "good" quality (14/18 studies), though there were numerous methodological issues; few used individual-level data to adjust for confounders like socioeconomic status (4/18 studies), instead using area-based indicators (12/18 studies) or not adjusting for it (3/18 studies). Most severity (9/10 studies) and mortality studies (5/6 studies) were based on people already diagnosed COVID-19, potentially introducing collider bias. Conclusion There is strong evidence that ambient PM2.5 increases the risk of COVID-19 infection, and weaker evidence of increases in severe disease and mortality.
Subject(s)
COVID-19 , Kallmann Syndrome , DeathABSTRACT
The exact transmission route of many respiratory infectious diseases remains a subject for debate to date. The relative contribution ratio of each transmission route is largely undetermined, which is affected by environmental conditions, human behavior, the host and the microorganism. In this study, a detailed mathematical model is developed to investigate the relative contributions of different transmission routes to a multi-route transmitted respiratory infection. It is illustrated that all transmission routes can dominate the total transmission risk under different scenarios. Influential parameters considered include dose-response rate of different routes, droplet governing size that determines virus content in droplets, exposure distance, and virus dose transported to the hand of infector. Our multi-route transmission model provides a comprehensive but straightforward method to evaluate the transmission efficiency of different transmission routes of respiratory diseases and provides a basis for predicting the impact of individual level intervention methods such as increasing close-contact distance and wearing protective masks.