Health and related economic benefits associated with reduction in air pollution during COVID-19 outbreak in 367 cities in China

Influence of air pollution on the nonaccidental death before and after the outbreak of COVID-19

BACKGROUND

During the COVID-19 pandemic, non-therapeutic interventions (NPIs), such as traffic restrictions, work stoppages, and school suspensions, have led to a sharp decline in the concentration of air pollutants in the epidemic sites. However, few studies focused on the impact of air pollutant changes on the risk of nonaccidental death.

METHOD

We selected Yancheng City, China, as the study site and applied a Generalized Additive Model (GAM) based on the quasi-Poisson distribution to evaluate the impact of atmospheric pollutants exposure on the nonaccidental death of local residents. The time span of this study was set from January 1, 2013, to December 21, 2022, that is, before and after the outbreak of COVID-19.

RESULTS

The concentration of some air pollutants has greatly varied after the outbreak of COVID-19, with a significant decline for PM2.5 (- 43.4%), PM10 (- 38.5%), SO2 (- 62.9%), and NO2 (- 22.6%), but an increase for O3 (+ 4.3%). Comparative analysis showed that PM2.5 contributed to an increased risk of nonaccidental death after the outbreak of COVID-19. With an increase in PM2.5 by 10 µg/m³, the excess relative risks (ER) of nonaccidental death of residents increased by 1.01% (95%CI: 0.19%,1.84%). The stratified analysis revealed that air pollutants impacted nonaccidental deaths in both men and women before the outbreak of COVID-19. After the outbreak of COVID-19, PM10 had a significant effect on male nonaccidental deaths. The concentrations of PM2.5, PM10, and SO2 increased by 10 µg/m³, the ER of PM2.5, PM10, and SO2 on female nonaccidental death increased by 1.52% (0.38%,2.67%), 0.58% (0.02%,1.13%), and 15.09% (5.73%,25.28%), respectively. Before the outbreak of COVID-19, five air pollutants had an impact on the death of residents from cardiovascular disease (CVD). After the outbreak of COVID-19, only PM10 significantly affected the death risk of CVD. In addition, we discovered that PM2.5, PM10, and SO2 significantly impacted the risk of death due to respiratory diseases before and after the outbreak of COVID-19.

CONCLUSIONS

Air pollutants have different effects on nonaccidental deaths before and after the COVID-19 outbreak. A decrease in air pollutant concentration due to the NPIs for COVID-19 had a significant effect on the reduction of the risk of nonaccidental death.

Exploring the nexus of urban form, transport, environment and health in large-scale urban studies: A state-of-the-art scoping review

BACKGROUND

As the world becomes increasingly urbanised, there is recognition that public and planetary health relies upon a ubiquitous transition to sustainable cities. Disentanglement of the complex pathways of urban design, environmental exposures, and health, and the magnitude of these associations, remains a challenge. A state-of-the-art account of large-scale urban health studies is required to shape future research priorities and equity- and evidence-informed policies.

OBJECTIVES

The purpose of this review was to synthesise evidence from large-scale urban studies focused on the interaction between urban form, transport, environmental exposures, and health. This review sought to determine common methodologies applied, limitations, and future opportunities for improved research practice.

METHODS

Based on a literature search, 2958 articles were reviewed that covered three themes of: urban form; urban environmental health; and urban indicators. Studies were prioritised for inclusion that analysed at least 90 cities to ensure broad geographic representation and generalisability. Of the initially identified studies, following expert consultation and exclusion criteria, 66 were included.

RESULTS

The complexity of the urban ecosystem on health was evidenced from the context dependent effects of urban form variables on environmental exposures and health. Compact city designs were generally advantageous for reducing harmful environmental exposure and promoting health, with some exceptions. Methodological heterogeneity was indicative of key urban research challenges; notable limitations included exposure and health data at varied spatial scales and resolutions, limited availability of local-level sociodemographic data, and the lack of consensus on robust methodologies that encompass best research practice.

CONCLUSION

Future urban environmental health research for evidence-informed urban planning and policies requires a multi-faceted approach. Advances in geospatial and AI-driven techniques and urban indicators offer promising developments; however, there remains a wider call for increased data availability at local-levels, transparent and robust methodologies of large-scale urban studies, and greater exploration of urban health vulnerabilities and inequities.

Adverse Associations of Long-Term Exposure to PM2.5 and Its Components with Platelet Traits among Subway Shift-Workers without Air Purifier Use

Air purifier use, shift work, and long-term exposure to fine particulate matter (PM2.5) are linked to platelet abnormality. However, the role of air purifier use and shift work in the individual or joint associations of PM2.5 and its components with platelet indices are largely unknown. A total of 8772 participants were recruited from a population of subway workers in China. PM2.5 and its component data were obtained from the Tracking Air Pollution in China dataset. The role of air purifier use and shift work in the association between PM2.5 and its components and platelet indices were analyzed. Among shift workers without air purifier use, positive associations of PM2.5 and each component in PM2.5 with the mean platelet volume (MPV) or platelet counts (PLT) were observed, whereas negative associations of PM2.5 and each component in PM2.5 with the platelet distribution width (PDW) were observed. Furthermore, estimated changes (95%CIs) in PLT, MPV, and PDW in response to each 10th percentile increment in the mixture of PM2.5 and its components were 0.8657 (0.2496, 1.4819), 0.0192 (0.0054, 0.0329), and -0.0648 (-0.0945, -0.0351), respectively, and sulfate in PM2.5 was the major contributor to those associations. Long-term exposure to PM2.5 and its components was related to increased platelet disorders among shift workers without air purifier use, and those associations were mainly attributed to sulfate in PM2.5.

Effects of the lockdown measure amid COVID-19 pandemic on outpatient department visits associated with air pollution reduction in Thailand

We investigated the effects of COVID-19 lockdown on air quality and its consequences health and economic benefits in Thailand. The conditional Poisson regression model was applied to examine the association between air pollution and outpatient department (OPD) visits in each province and pooled the province-specific estimates using the random-effects meta-analysis to derive the national estimates. We then applied a random forest model with meteorological normalization approach to predict the concentration of air pollutants by means of business as usual during the lockdown period (April 3-May 3) in 2020 and further calculated the changes in the number of OPD visits and their consequent expenditure attributable to air pollution reduction using the obtained risk function performed earlier. The number of cardiovascular OPD visits attributed to PM10, PM2.5 and NO2 decreased by 4,414 (95% CI 982, 8,401), 4,040 (95% CI 326, 7,770), and 13,917 (95% CI 1,675, 27,278) cases, respectively, leading to reduced medical expenditure by 14,7180.21, 13,4708.31, and 46,4025.04 USD, respectively. The number of respiratory OPD visits attributed to PM10, PM2.5, NO2, and O3 reduction decreased by 2,298 (95% CI 1,223, 3,375), 2,056 (95% CI 740, 3,252), 3,326 (95% CI 542, 6,295), and 1,160 (95% CI 5,26, 1,804) cases, respectively, where the consequent medical expenditure was reduced by 76,618.48, 68,566.36, 11,0908.31, and 38,685.50 USD, respectively. Finding from this study showed that air quality during the lockdown period in Thailand was improved, contributing to the reduction of cardiovascular and respiratory OPD visits, and consequent medical service costs attributable to air pollution.

Health and Economic Benefits of Air Pollution Reductions in Vietnam During 2020-2021

Objectives: This paper explores the potential reduction in the number of deaths and the corresponding economic benefits in Vietnam that could have arisen from the decreased in concentrations of particulate matter with a diameter of 2.5 μm or less (PM2.5) and nitrogen dioxide (NO2). Methods: Using Global Exposure Mortality Models, we estimated the potential health and economic benefits on people aged 25 and above across Vietnam's 63 provinces. The counterfactual scenario assumed reducing PM2.5 and NO2 concentrations to levels observed during the two COVID-19 epidemic waves in 2021 with national lockdowns and activity restrictions. Results: In 2019, PM2.5 concentrations ranged from 12.8 to 40.8 μg/m3 while NO2 concentrations ranged between 2.9 and 36.98 μg/m3. The reduced levels of PM2.5 and NO2 resulted in 3,807 (95% CI: 2,845-4,730) and 2,451 (95% CI: 2,845-4,730) avoided deaths of adults aged 25 and above due to non-injury-related causes, respectively. Considering that every prevented death represents potential tangible and intangible cost savings, reduced levels of PM2.5 and NO2 concentrations during COVID-19 restrictions would have resulted in economic benefits of $793.0 million (95% CI: 592.7-985.4) and $510.6 million (95% CI: 381.3-634.9), respectively. Conclusion: The COVID-19 lockdown led to decreased PM2.5 and NO2 concentrations, benefiting health and economy in Vietnam. Our findings highlight the potential advantages of implementing air quality control policies in the country.

Monitoring ambient air pollution and pulmonary function in asthmatic children by mobile applications in COVID-19 pandemic

BACKGROUND

Several public health measures were implemented during the COVID-19 pandemic. However, little is known about the real-time assessment of environmental exposure on the pulmonary function of asthmatic children. Therefore, we developed a mobile phone application for capturing real-time day-to-day dynamic changes in ambient air pollution during the pandemic. We aim to explore the change in ambient air pollutants between pre-lockdown, lockdowns, and lockdowns and analyze the association between pollutants and PEF mediated by mite sensitization and seasonal change.

METHOD

A prospective cohort study was conducted among 511 asthmatic children from January 2016 to February 2022. Smartphone-app used to record daily ambient air pollution, particulate matter (PM2.5, PM10) Ozon (O₃), nitrogen dioxide (NO₂), Carbon Monoxide (CO), sulfur dioxide (SO₂), average temperature, and relative humidity, which measured and connected from 77 nearby air monitoring stations by linking to Global Positioning System (GPS)-based software. The outcome of pollutants' effect on peak expiratory flow meter (PEF) and asthma is measured by a smart peak flow meter from each patient or caregiver's phone for real-time assessment.

RESULTS

The lockdown (May 19th, 2021, to July 27th, 2021) was associated with decreased levels of all ambient air pollutants aside from SO₂ after adjusting for 2021. NO₂ and SO₂ were constantly associated with decreased levels of PEF across lag 0 (same day when the PEF was measured), lag 1 (one day before PEF was measured), and lag 2 (two days prior when the PEF was measured. Concentrations of CO were associated with PEF only in children who were sensitized to mites in lag 0, lag 1, and lag 2 in the stratification analysis for a single air pollutant model. Based on the season, spring has a higher association with the decrease of PEF in all pollutant exposure than other seasons.

CONCLUSION

Using our developed smartphone apps, we identified that NO₂, CO, and PM10 were higher at the pre-and post-COVID-19 lockdowns than during the lockdown. Our smartphone apps may help collect personal air pollution data and lung function, especially for asthmatic patients, and may guide protection against asthma attacks. It provides a new model for individualized care in the COVID era and beyond.

The positive impact of the Omicron pandemic lockdown on air quality and human health in cities around Shanghai

The Omicron pandemic broke out in Shanghai in March 2022, and some infected people spread to some cities in the Yangtze River Delta (YRD) region. To achieve the dynamic zero-COVID target as soon as possible, Shanghai and nine cities that were heavily affected by Shanghai implemented the lockdown measures. This paper aims to quantify the impact of the lockdown on air quality and human health. A difference-in-difference (DID) model was first used to measure the impact of the lockdown on air quality in these ten cities. Based on the results of the DID model, we estimated the PM2.5-related health and economic benefits using the concentration-response function and the value of statistical life method. Results showed that the lockdown has reduced the concentrations of PM2.5, PM10, SO2, NO2, and CO by 9.87 μg/m3, 17.31 μg/m3, 0.75 μg/m3, 9.03 μg/m3, and 0.07 mg/m3, respectively. The number of avoided premature deaths due to PM2.5 reduction was estimated to be 35,342. The resulting economic benefits totaled 18.86 billion US dollars. We investigated the reasons for the air quality improvement in these ten cities and found the "3 + 11" policy has had a great impact on air quality. Compared with the first COVID-19 lockdown in early 2020, the effect of the lockdown in 2022 was smaller. These findings demonstrated that reductions in anthropogenic emissions would achieve substantial air quality improvement and health benefits. This paper re-emphasized continuous efforts to improve air quality are essential to protect public health.

Effects of the COVID-19 Lockdown on Air Pollutant Levels and Associated Reductions in Ischemic Stroke Incidence in Shandong Province, China

Background

Local governments in China took restrictive measures after the outbreak of COVID-19 to control its spread, which unintentionally resulted in reduced anthropogenic emission sources of air pollutants. In this study, we intended to examine the effects of the COVID-19 lockdown policy on the concentration levels of particulate matter with aerodynamic diameters of ≤1 μm (PM₁), ≤2.5 μm (PM_2.5), and ≤10 μm (PM₁₀), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), ozone (O₃), and carbon monoxide (CO) and the potential subsequent reductions in the incidence of ischemic and hemorrhagic stroke in Shandong Province, China.

Methods

A difference-in-difference model combining the daily incidence data for ischemic and hemorrhagic stroke and air pollutant data in 126 counties was used to estimate the effect of the COVID-19 lockdown on the air pollutant levels and ischemic and hemorrhagic stroke incident counts. The avoided ischemic stroke cases related to the changes in air pollutant exposure levels were further estimated using concentration-response functions from previous studies.

Results

The PM₁, PM_2.5, PM₁₀, NO₂, and CO levels significantly decreased by −30.2, −20.9, −13.5, −46.3, and −13.1%, respectively. The O₃ level increased by 11.5% during the lockdown compared with that in the counterfactual lockdown phase of the past 2 years. There was a significant reduction in population-weighted ischemic stroke cases (−15,315, 95% confidence interval [CI]: −27,689, −2,942), representing a reduction of 27.6% (95% CI: −49.9%, −5.3%). The change in the number of hemorrhagic stroke cases was not statistically significant. The total avoided PM₁-, PM_2.5-, PM₁₀-, NO₂-, and CO–related ischemic stroke cases were 739 (95% CI: 641, 833), 509 (95% CI: 440, 575), 355 (95% CI: 304, 405), 1,132 (95% CI: 1,024, 1,240), and 289 (95% CI: 236, 340), respectively.

Conclusion

The COVID-19 lockdown indirectly reduced the concentration levels of PM₁, PM_2.5, PM₁₀, NO₂, and CO and subsequently reduced the associated ischemic stroke incidence. The health benefits due to the lockdown are temporary, and long-term measures should be implemented to increase air quality and related health benefits in the post-COVID-19 period.

Application of genetic algorithm combined with improved SEIR model in predicting the epidemic trend of COVID-19, China

Since the outbreak of the 2019 Coronavirus disease (COVID-19) at the end of 2019, it has caused great adverse effects on the whole world, and it has been hindering the global economy. It is ergent to establish an infectious disease model for the current COVID-19 epidemic to predict the trend of the epidemic. Based on the SEIR model, the improved SEIR models were established with considering the incubation period, the isolated population, and genetic algorithm (GA) parameter optimization method. The improved SEIR models can predict the trend of the epidemic situation better and obtain the more accurate epidemic-related parameters. Comparing some key parameters, it is capable to evaluate the impact of different epidemic prevention measures and the implementation of different epidemic prevention levels on the COVID-19, which has significant guidance for further epidemic prevention measures.

Food Intake and Diet Quality of Pregnant Women in China During the COVID-19 Pandemic: A National Cross-Sectional Study

Background:

Between January and April 2020, China implemented differentiated prevention and control strategies across the country, based on the severity of the COVID-19 epidemic/pandemic in different regions. These strategies included lockdowns, social distancing, and the closure of public places. These measures may have affected dietary intake to varying degrees. This study aimed to assess variations in food intake and diet quality among pregnant women according to regional severity and related control measures during the most severe period of COVID-19 restrictions in 2020.

Methods

A total of 3,678 pregnant women from 19 provinces/municipalities in mainland China were analyzed in this nationwide, multi-center study. Food intake data were obtained and assessed using a validated food frequency questionnaire (FFQ). Diet quality was quantified using the Diet Balance Index for Pregnancy (DBI-P), which included high bound score (HBS, excessive dietary intake), low bound score (LBS, insufficient dietary intake), and diet quality distance (DQD, dietary imbalance). Linear trend tests and multivariable regression analyses were performed to examine the association between food intake, DBI-P and the severity of pandemic.

Results

The median daily intake of vegetables, fruit, livestock/poultry meat, dairy, and nuts decreased (p < 0.05) according to low, moderate, and high severity of the pandemic, while no significant differences in cereals/potatoes, eggs, and fish/shrimp intake. The median daily intake of cereals/potatoes exceeded the recommended ranges, and the daily intake of eggs and fish/shrimp was below recommended ranges regardless of the pandemic severity (p < 0.05). Regarding diet quality, HBS decreased (lower excessive consumption) (p = 0.047) and LBS increased (greater insufficient consumption) (p = 0.046) with increased severity of the pandemic. On multivariable analyses, moderate and high pandemic severity were related to lower HBS risk (OR = 0.687, OR = 0.537) and higher LBS risk (β = 1.517, β = 3.020) when compared to low pandemic severity.

Conclusions

Under more severe COVID-19 pandemic conditions, pregnant women consumed less quality food, characterized by reduced consumption of vegetables, fruit, livestock/poultry meat, dairy and nuts, while the quality of the foods that pregnant women consumed in excess tended to improve, but the overconsumption of cereals/potatoes was a problem.