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.

Mortality burden due to long-term exposure to ambient PM2.5 above the new WHO air quality guideline based on 296 cities in China.

OBJECTIVE: Quantifying the spatial and socioeconomic variation of mortality burden attributable to particulate matters with aerodynamic diameter ≤ 2.5 µm (PM2.5) has important implications for pollution control policy. This study aims to examine the regional and socioeconomic disparities in the mortality burden attributable to long-term exposure to ambient PM2.5 in China. METHODS: Using data of 296 cities across China from 2015 to 2019, we estimated all-cause mortality (people aged ≥ 16 years) attributable to the long-term exposure to ambient PM2.5 above the new WHO air quality guideline (5 µg/m3). Attributed fraction (AF), attributed deaths (AD), attributed mortality rate (AMR) and total value of statistical life lost (VSL) by regional and socioeconomic levels were reported. RESULTS: Over the period of 2015-2019, 17.0% [95% confidence interval (CI): 7.4-25.2] of all-cause mortality were attributable to long-term exposure to ambient PM2.5, corresponding to 1,425.2 thousand deaths (95% CI: 622.4-2,099.6), 103.5/105 (95% CI: 44.9-153.3) AMR, and 1006.9 billion USD (95% CI: 439.8-1483.4) total VSL per year. The AMR decreased from 120.5/105 (95% CI: 52.9-176.6) to 92.7/105 (95% CI:39.9-138.5) from 2015 to 2019. The highest mortality burden was observed in the north region (annual average AF = 24.2%, 95% CI: 10.8-35.1; annual average AMR = 137.0/105, 95% CI: 60.9-198.5). The highest AD and economic loss were observed in the east region (annual average AD = 390.0 thousand persons, 95% CI: 170.3-574.6; annual total VSL = 275.6 billion USD, 95% CI: 120.3-406.0). Highest AMR was in the cities with middle level of GDP per capita (PGDP)/urbanization. The majority of the top ten cities of AF, AMR and VSL were in high and middle PGDP/urbanization regions. CONCLUSION: There were significant regional and socioeconomic disparities in PM2.5 attributed mortality burden among Chinese cities, suggesting differential mitigation policies are required for different regions in China.

Temperature-mortality association during and before the COVID-19 pandemic in Italy: A nationwide time-stratified case-crossover study.

OBJECTIVES: To identify the associations of temperature with non-COVID-19 mortality and all-cause mortality in the pandemic 2020 in comparison with the non-COVID-19 period in Italy. METHODS: The data on 3,189,790 all-cause deaths (including 3,134,137 non-COVID-19 deaths) and meteorological conditions in 107 Italian provinces between February 1st and November 30th in each year of 2015-2020 were collected. We employed a time-stratified case-crossover study design combined with the distributed lag non-linear model to investigate the relationships of temperature with all-cause and non-COVID-19 mortality in the pandemic and non-pandemic periods. RESULTS: Cold temperature exposure contributed higher risks for both all-cause and non-COVID-19 mortality in the pandemic period in 2020 than in 2015-2019. However, no different change was found for the impacts of heat. The relative risk (RR) of non-COVID-19 deaths and all-cause mortality at extremely cold (2 °C) in comparison with the estimated minimum mortality temperature (19 °C) in 2020 were 1.63 (95% CI: 1.55-1.72) and 1.45 (95%CI: 1.31-1.61) respectively, which were higher than all-cause mortality risk in 2015-2019 with RR of 1.19 (95%CI: 1.17-1.21). CONCLUSION: Cold exposure indicated stronger impacts than high temperatures on all-cause and non-COVID-19 mortality in the pandemic year 2020 compared to its counterpart period in 2015-2019 in Italy.

Vulnerability and Burden of All-Cause Mortality Associated with Particulate Air Pollution during COVID-19 Pandemic: A Nationwide Observed Study in Italy.

BACKGROUND: Limited evidence is available on the health effects of particulate matter (PM including PM2.5 with an aerodynamic diameter ≤ 2.5 µm; PM10, ≤ 10 µm; PM2.5-10, 2.5-10 µm) during the pandemic of COVID-19 in Italy. The aims of the study were to examine the associations between all-cause mortality and PM in the pandemic period and compare them to the normal periods (2015-2019). METHODS: We collected daily data regarding all-cause mortality (stratified by age and gender), and PM concentrations for 107 Italian provinces from 1 January 2015 to 31 May 2020. A time-stratified case-cross design with the distributed lag non-linear model was used to examine the association between PM and all-cause mortality. We also compared the counts and fractions of death attributable to PM in two periods. RESULTS: Italy saw an increase in daily death counts while slight decreases in PM concentrations in pandemic period. Each 10 µg/m3 increase in PM was associated with much higher increase in daily all-cause mortality during the pandemic period compared to the same months during 2015-2019 (increased mortality rate: 7.24% (95%CI: 4.84%, 9.70%) versus 1.69% (95%CI: 1.12%, 2.25%) for PM2.5; 3.45% (95%CI: 2.58%, 4.34%) versus 1.11% (95%CI: 0.79%, 1.42%) for PM10; 4.25% (95%CI: 2.99%, 5.52%) versus 1.76% (95%CI: 1.14%, 2.38%) for PM2.5-10). The counts and fractions of deaths attributable to PM were higher in 2020 for PM2.5 (attributable death counts: 20,062 versus 3927 per year in 2015-2019; attributable fractions: 10.2% versus 2.4%), PM10 (15,112 versus 3999; 7.7% versus 2.5%), and PM2.5-10 (7193 versus 2303; 3.7% versus 1.4%). CONCLUSION: COVID-19 pandemic increased the vulnerability and excess cases of all-cause mortality associated with short-term exposure to PM2.5, PM2.5-10, and PM10 in Italy, despite a decline in air pollution level.

Could the ambient higher temperature decrease the transmissibility of COVID-19 in China?

BACKGROUND: Existing literatures demonstrated that meteorological factors could be of importance in affecting the spread patterns of the respiratory infectious diseases. However, how ambient temperature may influence the transmissibility of COVID-19 remains unclear. OBJECTIVES: We explore the association between ambient temperature and transmissibility of COVID-19 in different regions across China. METHODS: The surveillance data on COVID-19 and meteorological factors were collected from 28 provincial level regions in China, and estimated the instantaneous reproductive number (Rt). The generalized additive model was used to assess the relationship between mean temperature and Rt. RESULTS: There were 12,745 COVID-19 cases collected in the study areas. We report the associated effect of temperature on Rt is likely to be negative but not of statistical significance, which holds for most Chinese regions. CONCLUSIONS: We found little statistical evidence for that the higher temperature may reduce the transmissibility of COVID-19. Since intensive control measures against the COVID-19 epidemics were implemented in China, we acknowledge this may impact the underlying effect size estimation, and thus cautiousness should be taken when interpreting our findings.