The association between short-term exposure to ambient air pollution and the incidence of mumps in Wuhan, China: A time-series study

Air pollution, temperature and mumps: A time-series study of independent and interaction effects

Understanding the associations of air pollutants and temperature with the incidence of mumps, and exploring the interaction effects of heat index (HI) and air pollutants, are crucial for disease intervention under the context of climate change. This time-series study was conducted in Jining city using data on daily mumps cases, meteorological factors and air pollutants obtained from 2015 to 2021. Distributed lag models combined with quasi-Poisson regressions were applied to examine these associations. The findings indicated a heightened risk of mumps in correlation with elevated exposure to PM2.5, PM10, and NO2. Specifically, the precent changes in the risk of mumps were 0.6 % and 0.3 % associated with per 10 μg/m3 increment in PM2.5 and PM10 at lag0 day, respectively. The cumulative effects of temperature were significantly associated with mumps, showing a "U"-shape pattern. Compared to the minimum effect value of 4 ℃, relative risk (RRs) of mumps for high and low temperature (at the 90th and 10th percentiles) were 1.961 (1.106-3.477) and 1.058 (0.976-1.158), respectively. There were significant synergistic effects between particulate matters (PMs) and HI. Compared to the low concentrations of PMs and normal heat index (NHI), co-exposure to high PMs and high heat index (HHI) has the highest risk (RRPM2.5: 1.32 and, RRPM10: 1.30). Individuals aged over 5 years was susceptible to particulate matters (PMs). Our results suggested that mitigating both PM and high temperature exposure may bring more health benefits for mumps incidence.

Association between exposure to environmental pollutants and increased oral health risks, a comprehensive review

The burden of disease and death attributable to environmental pollution is a growing public health challenge worldwide, particularly in developing countries. While the adverse effects of environmental pollution on oral health have garnered increasing attention, a comprehensive and systematic assessment remains lacking. This article delves into the intricate relationship between environmental pollution and oral health, highlighting significant impacts on various aspects such as dental caries, periodontal diseases, oral facial clefts, cancer, as well as other oral diseases. Our results suggested that secondhand smoke, particulate matters (PM) and heavy metals are the most important risk factors affecting oral health. Additional contributors, such as radiation pollutants, electronic cigarette, phthalates, gaseous air pollutants, pesticides, solvents, wood dust, formaldehyde and excessive fluoride were investigated, though evidence for their impacts remains limited and often inconclusive. The review also explores potential mechanisms underlying these impacts, including microorganism, inflammation, oxidative stress, genetic influences, and toxicant exposures from heavy metals and other pollutants. For instance, PM2.5 may contribute to dental caries by disrupting oral pH balance and absorbing heavy metals such as lead and cadmium which have been considered as caries promoting elements. It is also associated with adverse inflammatory responses and tissue damage in periodontal tissues by causing oxidative stress, potentially leading to periodontitis. Drawing on current evidence, it provides a comprehensive analysis of these associations, offering critical insights to guide the development of preventive strategies and public health interventions. The findings highlight the pressing need for future research to validate the causal links between environmental pollution and oral diseases and to unravel the underlying biological mechanisms. Ultimately, greater attention must be directed toward addressing the relationship between environmental pollution and oral diseases, with a focus on pollution control and the reduction of preventable environmental risks to safeguard oral health on a broader scale.

An association between PM2.5 components and respiratory infectious diseases: A China's mainland-based study

The particulate matter with diameter of less than 2.5 µm (PM2.5) is an important risk factor for respiratory infectious diseases, such as scarlet fever, tuberculosis, and similar diseases. However, it is not clear which component of PM2.5 is more important for respiratory infectious diseases. Based on data from 31 provinces in mainland China obtained between 2013 and 2019, this study investigated the effects of different PM2.5 components, i.e., sulfate (SO42-), nitrate (NO3-), ammonium (NH4+), and organic matter (OM), and black carbon (BC), on respiratory infectious diseases incidence [pulmonary tuberculosis (PTB), scarlet fever (SF), influenza, hand, foot, and mouth disease (HFMD), and mumps]. Geographical probes and the Bayesian kernel machine regression (BKMR) model were used to investigate correlations, single-component effects, joint effects, and interactions between components, and subgroup analysis was used to assess regional and temporal heterogeneity. The results of geographical probes showed that the chemical components of PM2.5 were associated with the incidence of respiratory infectious diseases. BKMR results showed that the five components of PM2.5 were the main factors affecting the incidence of respiratory infectious diseases (PIP>0.5). The joint effect of influenza and mumps by co-exposure to the components showed a significant positive correlation, and the exposure-response curve for a single component was approximately linear. And single-component modelling revealed that OM and BC may be the most important factors influencing the incidence of respiratory infections. Moreover, respiratory infectious diseases in southern and southwestern China may be less affected by the PM2.5 component. This study is the first to explore the relationship between different components of PM2.5 and the incidence of five common respiratory infectious diseases in 31 provinces of mainland China, which provides a certain theoretical basis for future research.

Air pollution and upper respiratory diseases: an examination among medically insured populations in Wuhan, China

Multiple evidence has supported that air pollution exposure has detrimental effects on the cardiovascular and respiratory systems. However, most investigations focus on the general population, with limited research conducted on medically insured populations. To address this gap, the current research was designed to examine the acute effects of inhalable particulate matter (PM2.5 and PM10), nitrogen dioxide (NO2), ground-level ozone (O3), and sulfur dioxide (SO2) on the incidence of upper respiratory tract infections (URTI), utilizing medical insurance data in Wuhan, China. Data on URTI were collected from the China Medical Insurance Basic Database for Wuhan covering the period from 2014 to 2018, while air pollutant data was gathered from ten national monitoring stations situated in Wuhan city. Statistical analysis was performed using generalized additive models for quasi-Poisson distribution with a log link function. The analysis indicated that except for ozone, higher exposure to four other pollutants (NO2, SO2, PM2.5, and PM10) were significantly linked to an elevated risk of URTI, particularly during the previous 0-3 days and previous 0-4 days. Additionally, NO2 and SO2 were found to be positively linked with laryngitis. Furthermore, the effects of air pollutants on the risk of URTI were more pronounced during cold seasons than hot seasons. Notably, females and the employed population were more susceptible to infection than males and non-employed individuals. Our findings gave solid proof of the link between ambient air pollution exposure and the risk of URTI in medically insured populations.

The joint associations of ambient air pollutants and weather factors with mortality: Evidence from a national time-stratified case-crossover study in China

BACKGROUND

People in daily life are usually exposed to multiple environmental factors, but few studies have evaluated the joint health impacts of ambient air pollutants and weather factors.

OBJECTIVES

To investigate the joint associations of short-term exposures to ambient air pollutants and weather factors with mortality and estimate the mortality burden attributable to these multiple environmental exposures in China.

METHODS

We collected individual death information from six provinces (Guangdong, Yunnan, Hunan, Zhejiang, Tibet and Jilin) in China during 2013 to 2018, and applied a time-stratified case-crossover study design to estimate the joint associations of air pollutants [PM2.5 (particulate matter with an aerodynamic diameter ≤2.5 μm), O3 (ozone), NO2 (nitrogen dioxide), SO2 (sulfur dioxide), and CO (carbon monoxide)] and weather factors (temperature and relative humidity) with mortality. Air pollutant concentrations on the case day and control days were assessed using a random forest model, and the corresponding temperature and relative humidity data were assessed using a thin plate smoothing model. Excess risks (ER) of exposure to air pollutants and weather factors were estimated using Cox proportional regression models and the attributable fraction (AF) was calculated.

RESULTS

A total of 6,685,146 deaths were enrolled in this study. The overall AF of total mortality attributed to air pollutants (lag03 days) and weather factors (lag021 days) was 16.65 % (95%CI: 16.43 %, 16.87 %), in which the joint AFs attributable to air pollutants and weather factors were 5.31 % (95%CI: 5.08 %, 5.53 %) and 11.34 % (95%CI: 11.12 %, 11.56 %) respectively, and temperature contributed 56 % in the joint effects. Stratified analyses showed greater AFs in females (21.32 %) than in males (14.61 %), and in the elderly (>100 years, 42.34 %) than in young people (21-30 years, 7.67 %). The AFs of mortality from cardiovascular diseases, respiratory diseases, and pneumonia attributed to the joint exposures were 22.72 %, 24.82 % and 33.03 %, respectively.

DISCUSSION

This study provides the joint associations of short-term exposures to both air pollutants and weather factors with mortality risk in China, which has important implications in comprehensively assessing the health impacts of environmental exposures, and taking actions to protect human health.

Impact of meteorological factors on the incidence of hand-foot-mouth disease in Yangzhou from 2017 to 2022: a time series study

Background

Hand, foot, and mouth disease (HFMD) is a significant public health issue in China, and numerous studies have indicated a close association between HFMD incidence and meteorological factors. This study aims to investigate the relationship between meteorological factors and HFMD in Yangzhou City, Jiangsu Province, China.

Methods

HFMD case reports and meteorological data from Yangzhou City between 2017 and 2022 were extracted from the National Notifiable Infectious Disease Surveillance System and the Meteorological Data Sharing Service System, respectively. A generalized additive model (GAM) was employed to assess the exposure-response relationship between meteorological factors and HFMD. Subsequently, a distributed lag nonlinear model (DLNM) was used to explore the exposure-lag-effect of meteorological factors on HFMD.

Results

HFMD in Yangzhou City exhibits obvious seasonality and periodicity. There is an inverted "U" shaped relationship between average temperature and the risk of HFMD, with the maximum lag effect observed at a temperature of 25°C with lag 0 day (RR = 2.07, 95% CI: 1.74-2.47). As the duration of sunshine and relative humidity increase, the risk of HFMD continuously rises, with the maximum lag effect observed at a sunshine duration of 12.4 h with a lag of 14 days (RR = 2.10, 95% CI: 1.17-3.77), and a relative humidity of 28% with a lag of 14 days (RR = 1.21, 95% CI: 1.01-1.64). There is a "U" shaped relationship between average atmospheric pressure and the risk of HFMD, with the maximum effect observed at an atmospheric pressure of 989 hPa with no lag (RR = 1.45, 95% CI: 1.25-1.69). As precipitation increases, the risk of HFMD decreases, with the maximum effect observed at a precipitation of 151 mm with a lag of 14 days (RR = 1.45, 95% CI: 1.19-2.53).

Conclusion

Meteorological factors including average temperature, average atmospheric pressure, relative humidity, precipitation, and sunshine duration significantly influenced the risk of HFMD in Yangzhou City. Effective prevention measures for HFMD should be implemented, taking into account the local climate conditions.

Association between short-term exposure to ambient air pollution and outpatient visits for pulpitis in Hefei, China: a time series study

Evidence suggests a possible association between ambient air pollutants and oral diseases. Nevertheless, information regarding the relationship between air pollutants and pulpitis is scarce and inconclusive. In view of this, the present study aimed to investigate the relationship between short-term exposure to air pollution and outpatient visits for pulpitis. Daily data on outpatient visits for pulpitis, air pollutants, and meteorological data in Hefei, China, was collected from January 1, 2015 to December 31, 2021. The association between exposure to air pollutants and pulpitis outpatient visits was evaluated using distributed lag non-linear model (DLNM) and a generalized linear model (GLM). Furthermore, stratified analyses were performed by gender, age and season. A total of 93,324 records of outpatient visits for pulpitis were included in this study. The results showed that exposure to NO₂, PM_2.5, and CO were positively correlated with an increased risk of pulpitis outpatient visits. Each 10 μg/m³ increase in NO₂ and PM_2.5 concentration, at lag 0-2 day, was associated with a 2.4% (relative risk (RR) = 1.024, 95% confidence interval (CI): 1.014-1.035) and 0.5% (RR = 1.005, 95% CI: 1.000-1.010) increase in pulpitis outpatient visits, respectively. With a 1 mg/m³ increase in CO concentration, the risk of pulpitis outpatient visits increased by 9.1% (RR = 1.091, 95% CI: 1.031-1.154, lag 0-1 day). Intriguingly, exposure to O₃ was associated with a decreased risk of pulpitis outpatient visits (RR = 0.990, 95% CI: 0.984-0.995, lag 0-5 day). Subgroup analysis revealed that in the warm season, exposure to PM_2.5, O₃, and CO was related with a significantly higher outpatient risk of pulpitis than in the cold season. Additionally, the influence of PM_2.5 and CO exposure at age < 65 years was significantly stronger than at age ≥ 65 years. In conclusion, exposure to ambient NO₂, PM_2.5, and CO is associated with an increase in pulpitis outpatient visits in Hefei, China. Conversely, exposure to O₃ reduces the risk of outpatient visits for pulpitis. Age and season are effect modifiers of these associations.

Short-term exposure to air pollution and outpatient visits for conjunctivitis: a time-series analysis in Urumqi, China

Conjunctivitis is an inflammatory disease of the conjunctival tissue caused by a variety of causes; despite the conjunctiva being directly exposed to the external atmospheric environment, the important role of air pollution is not fully evaluated, especially in areas with poor air quality undergoing rapid economic and industrial development. Information on 59,731 outpatient conjunctivitis visits from 1 January 2013 to 31 December 2020 was obtained from the Ophthalmology Department of the First Affiliated Hospital of Xinjiang Medical University (Urumqi, Xinjiang, China), and data on six air pollutants including particulate matter with a median aerometric diameter of less than 10 and 2.5 mm (PM₁₀ and PM_2.5, respectively), carbon monoxide (CO), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and ozone (O₃) from eleven standard urban background fixed air quality monitors were also recorded. A time-series analysis design and a quasi-Poisson generalized linear regression model combined with a distributed lagged nonlinear model (DLNM) were used to fit the effect of exposure to air pollutants on the risk of conjunctivitis outpatient visits. Further subgroup analyses were conducted for gender, age, and season, as well as the type of conjunctivitis. Single and multi-pollutant models showed that exposure to PM_2.5, PM₁₀, NO₂, CO, and O₃ was associated with increased risk of outpatient conjunctivitis visits on the lag 0 day and various other lag days. Variations in the effect estimates on direction and magnitude were found in different subgroup analyses. We conducted the first time-series analysis with the longest duration as well as the largest sample size in Northwest China, which provides evidence that outpatient conjunctivitis visits is significantly associated with air pollution in Urumqi, China. Meanwhile, our results demonstrate the effectiveness of SO₂ reduction in reducing the risk of outpatient conjunctivitis visits in the Urumqi region and reaffirm the need to implement special air pollution control measures.

Association between ozone exposure and prevalence of mumps: a time-series study in a Megacity of Southwest China

In the present study, we aim to evaluate the delayed and cumulative effect of ozone (O₃) exposure on mumps in a megacity with high population density and high humidity. We took Chongqing, a megacity in Southwest China, as the research area and 2013-2017 as the research period. A total of 49,258 confirmed mumps cases were collected from 122 hospitals of Chongqing. We employed the distributed lag nonlinear models with quasi-Poisson link to investigate the relationship between prevalence of mumps and O₃ exposure after adjusting for the effects of meteorological conditions. The results show that the effect of O₃ exposure on mumps was mainly manifested in the lag of 0-7 days. The single-day ;lag effect was the most obvious on the 4th day, with the relative risk (RR) of mumps occurs of 1.006 (95% CI: 1.003-1.007) per 10 μg/m³ in the O₃ exposure. The cumulative RR within 7 days was 1.025 (95% CI: 1.013-1.038). Our results suggest that O₃ exposure can increase the risk of mumps infection, which fills the gap of relevant research in mountainous areas with high population density and high humidity.

Short-term exposure to ambient air pollution and type 2 diabetes mortality: A population-based time series study

Acute health effects of air pollution on diabetes risk have not been fully studied in developing countries and the results remain inconsistent. This study aimed to investigate the association between short-term exposure to ambient air pollution and Type 2 diabetes mellitus (T2DM) mortality in China. Data on T2DM mortality from 2013 to 2019 were obtained from the Cause of Death Reporting System (CDRS) of Wuhan Center for Disease Control and Prevention. Air pollution data for the same period were collected from 10 national air quality monitoring stations of Wuhan Ecology and Environment Institute, including daily average PM_2.5, PM₁₀, SO₂, and NO₂. Meteorological data including daily average temperature and relative humidity were collected from Wuhan Meteorological Bureau. Generalized additive models (GAM) based on quasi-Poisson distribution were applied to evaluate the association between short-term exposure to air pollution and daily T2DM deaths. A total of 9837 T2DM deaths were recorded during the study period in Wuhan. We found that short-term exposure to PM_2.5, PM₁₀, SO₂, and NO₂ were positively associated with T2DM mortality, and gaseous pollutants appeared to have greater effects than particulate matter (PM). For the largest effect, per 10 μg/m³ increment in PM_2.5 (lag 02), PM₁₀ (lag 02), SO₂ (lag 03), and NO₂ (lag 02) were significantly associated with 1.099% (95% CI: 0.451, 1.747), 1.016% (95% CI: 0.517, 1.514), 3.835% (95% CI: 1.480, 6.189), and 1.587% (95% CI: 0.646, 2.528) increase of daily T2DM deaths, respectively. Stratified analysis showed that females or elderly population aged 65 and above were more susceptible to air pollution exposure. In conclusion, short-term exposure to air pollution was significantly associated with a higher risk of T2DM mortality. Further research is required to verify our findings and elucidate the underlying mechanisms.

Association between ambient air pollution and multiple sclerosis: a systemic review and meta-analysis

Recently, increasing attention has been paid to the effects of air pollutants on autoimmune diseases. The results of relationship between ambient air pollution and multiple sclerosis (MS) showed a variety of differences. Thus, the purpose of this study is to further clarify and quantify the relationship between ambient air pollutants and MS through meta-analysis. Through electronic literature search, literature related to our research topic was collected in Cochrane Library, Embase, and PubMed till August 18, 2020, according to certain criteria. Pooled risk estimate and 95% confidence intervals (95%CI) were calculated by random-effect model analysis. After removing copies, browsing titles and abstracts, and reading full text, 6 studies were finally included. The results showed that only particulate matter (PM) with aerodynamic diameter ≤ 10 (PM₁₀) was related to MS (pooled HR = 1.058, 95% CI = 1.050-1.066), and no correlation was found between PM with aerodynamic diameter < 2.5 (PM_2.5), nitrogen dioxide (NO₂), carbon monoxide (CO), ozone (O₃), benzene (C₆H₆), major road < 50 m, and MS. There was no publication bias, and the heterogeneity analysis results were stable. PM₁₀ is correlated with the disease MS, while other pollution is not connected with MS. Therefore, it is important for MS patients to take personal protection against particulate pollution and avoid exposure to higher levels of PM.

Influence of air pollutants on varicella among adults

Little attention has been paid to the relationship between air pollutants and varicella among adults. We used data collected in Qingdao, China from 2014 to 2019. A combination of quasi-Poisson generalized linear model (GLM) and distributed lag non-linear model (DLNM) was applied to evaluate the association between exposure to air pollutants and varicella. And the effects of exposure to extremely high concentration (at 97.5th percentile) and low concentration (at 2.5th percentile) of air pollutants on varicella were also calculated. The level II of GB3095-2012 was used as the reference. A 10 μg/m³ increase of PM_2.5 was significantly associated with an increased risk of varicella (lag day: 4, 5 and 6). The negative associations were found for NO₂ per 10 μg/m³ increase from lag 15 to 19 day. The high PM_2.5 concentration (135 μg/m³) was significantly associated with the increased risk of varicella (lag day: 6, 7). For NO₂, the negative association was found at high concentration (75 μg/m³) on lag 15 to 20 day; and the positive relationship was shown at low concentration (10 μg/m³) on lag 15 to 20 day. Exposure to PM_2.5 and NO₂ were significantly associated with the risk of varicella among adults.

Association between particulate matter pollution and the incidence of mumps in 31 provinces from China

Previous studies have found that particulate matter (PM) pollution is a risk factor for respiratory disease by affecting body's immunity and carrying microorganisms. This study aimed to explore the association between PM and the incidence of mumps in 31 provinces from China. Monthly mumps cases, air pollution concentration, and meteorological factors in each province were obtained between January 2014 to December 2017. We used a generalized additive model (GAM) to investigate the associations of PM2.5 and PM10 with monthly mumps cases. We also tested the statistical significance of the differences between effect estimates in the warm season (April to September) and cold season (October to March) to explore potential effect modification. We found that a 10-μg/m3 increase (lag0) in PM2.5, and PM10 was associated with a 2.34% (95% CI: 1.32 to 3.36) and 1.90% (95% CI: 1.19 to 2.62) increase in the monthly counts of mumps cases, respectively. We also observed significant positive associations of PM2.5 and PM10 with mumps cases at lag0-1. These results were robust in our sensitivity analyses. No significant differences were found between the season-specific effects. Our results indicate that there is a positive relationship between PM and the incidence of mumps, which provides important implications for the prevention and control of mumps.

The incidence of mumps in Taiwan and its association with the meteorological parameters: An observational study

Mumps is an acute and common childhood disease caused by paramyxovirus. It has been reported that the occurrence of mumps is influenced by seasonality. However, the role of meteorological variables in the incidence of mumps remains unclear. The purpose of this study was to explore the relationship between meteorological factors and the incidence of mumps infection. Poisson regression analysis was used to study the relationship between weather variability and the incidence of mumps in Taiwan. Between 2012 and 2018, 5459 cases of mumps cases were reported to the Centers for Disease Control, Taiwan (Taiwan CDC). The occurrence of mumps virus infections revealed significant seasonality in the spring and summer seasons in Taiwan. The incidence of mumps virus infections began to increase at temperatures of 15°C and started to decline if the temperature was higher than 29°C (r2 = 0.387, P = .008). Similarly, the number of mumps cases began to increase at a relative humidity of 65% to 69% (r2 = 0.838, P < .029). The number of mumps cases was positively associated with temperature and relative humidity during the period preceding the infection. This study showed that the occurrence of mumps is significantly associated with increasing temperature and relative humidity in Taiwan. Therefore, these factors could be regarded as early warning signals and indicate the need to strengthen the intervention and prevention of mumps.

Significance between air pollutants, meteorological factors, and COVID-19 infections: probable evidences in India

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease represents the causative agent with a potentially fatal risk which is having great global human health concern. Earlier studies suggested that air pollutants and meteorological factors were considered as the risk factors for acute respiratory infection, which carries harmful pathogens and affects the immunity. The study intended to explore the correlation between air pollutants, meteorological factors, and the daily reported infected cases caused by novel coronavirus in India. The daily positive infected cases, concentrations of air pollutants, and meteorological factors in 288 districts were collected from January 30, 2020, to April 23, 2020, in India. Spearman's correlation and generalized additive model (GAM) were applied to investigate the correlations of four air pollutants (PM2.5, PM10, NO2, and SO2) and eight meteorological factors (Temp, DTR, RH, AH, AP, RF, WS, and WD) with COVID-19-infected cases. The study indicated that a 10 μg/m3 increase during (Lag0-14) in PM2.5, PM10, and NO2 resulted in 2.21% (95%CI: 1.13 to 3.29), 2.67% (95% CI: 0.33 to 5.01), and 4.56 (95% CI: 2.22 to 6.90) increase in daily counts of Coronavirus Disease 2019 (COVID 19)-infected cases respectively. However, only 1 unit increase in meteorological factor levels in case of daily mean temperature and DTR during (Lag0-14) associated with 3.78% (95%CI: 1.81 to 5.75) and 1.82% (95% CI: -1.74 to 5.38) rise of COVID-19-infected cases respectively. In addition, SO2 and relative humidity were negatively associated with COVID-19-infected cases at Lag0-14 with decrease of 7.23% (95% CI: -10.99 to -3.47) and 1.11% (95% CI: -3.45 to 1.23) for SO2 and for relative humidity respectively. The study recommended that there are significant correlations between air pollutants and meteorological factors with COVID-19-infected cases, which substantially explain the effect of national lockdown and suggested positive implications for control and prevention of the spread of SARS-CoV-2 disease.

Association between short-term ambient air pollution and outpatient visits of anxiety: A hospital-based study in northwestern China

Anxiety, a common and devastating mental disorder, has raised widespread interests. The impacts of air pollution on physical health are well known, whereas few studies have explored the association of atmospheric pollution, especially short-term air pollution exposure, with the risk of anxiety disorders. In addition, there are increasing concerns in emerging evidence supporting a possible etiological link. Therefore, our aim was to evaluate the relationship between short-term exposure to atmospheric pollutants and anxiety outpatient visits in Xi'an, a city of northwestern China and a metropolis with relatively heavy air pollution. We collected the data of both daily outpatient visits and daily air pollution (SO₂, NO₂, and PM₁₀) between January 1, 2010 and January 31, 2016 (2222 days). To clarify the association between short-term ambient atmospheric pollution exposure and anxiety outpatient visits, an over-dispersed Poisson generalized additive model was applied by adjusting the day of the week and weather conditions (including temperature, humidity, sunlight hours, and rainfalls). Positive association between gaseous air pollutants (SO₂ and NO₂) and anxiety daily outpatient visits was observed. Moreover, the largest estimated values of both SO₂ and NO₂ were evidence at lag 03 (4-day moving average lag), with 10 μg/m³ increase corresponded to the increase of outpatient anxiety visits at 4.11% (95% CI: 2.15%, 6.06%) for SO₂ and 3.97% (95% CI: 1.90%, 6.06%) for NO₂. However, there was no differences in susceptibility to air pollutants between different genders as well as different ages. Taken together, short-term exposure to ambient air pollutants, especially gaseous air pollutants (NO₂ and SO₂), can be related to higher risk of anxiety outpatient visits.

The association between short-term exposure to air pollutants and rotavirus infection in Wuhan, China

BACKGROUND

The impact of various meteorological factors on rotavirus (RV) infection has been previously studied; however, few studies have explored the association between short-term exposure to air pollutants and RV infection.

METHODS

Daily RV positive cases among children aged 0-6 years were collected from July 2014 to August 2019 in Tongji hospital (Wuhan, China). Daily data on air temperature and air pollutants were obtained from the China Meteorological Network. A distributed lag model to explore the lagged effects of short-term exposure to air pollutants and RV infection was performed. The distribution lag model was used to study the lag effect of short-term exposure to air pollutants and RV infection.

RESULTS

RV infection was negatively correlated with mean air temperature and O₃ concentration. The RV infection risk decreased by 5.2% and 0.47% for every 1℃ increase in average temperature and 1 ug/m³ increase in O₃ concentration, respectively. Increased PM_2.5 , SO₂ , and NO₂ concentrations were independent risk factors for an increase in positive rates; their relative risk values were 1.0014 (95% confidence interval [CI], 1.0013-1.0015), 1.0050 (95% CI, 1.0047-1.0053), and 1.0030 (95% CI, 1.0028-1.0032), respectively. The highest RV-positive rates were from January to March and November to December. Additionally, children <18 months of age and boys were more vulnerable to infection.

CONCLUSIONS

Air pollutants were important factors impacting the RV-positivity of children in Wuhan. These findings may help develop an early environment-based warning system to prevent and control RV infection.

Association between short-term exposure to ambient nitrogen dioxide and the risk of conjunctivitis in Hefei, China: A time-series analysis

BACKGROUND

Conjunctivitis, one of the most common ocular surface diseases, can be caused by many contributors. However, the important role of air pollution has been inadequately evaluated, particularly in countries with poor air quality. This study aims to explore the possible association of short-term ambient nitrogen dioxide (NO₂) exposure with the risk of outpatient visits for conjunctivitis.

METHODS

A total of 43,462 conjunctivitis patients from January 1, 2014 to December 31, 2018 were identified from the Department of Ophthalmology of The Second Affiliated Hospital of Anhui Medical University, Hefei, China. Such data were linked to the daily mean concentration of NO₂ at ten fixed air quality monitoring stations. A distributed lag nonlinear model (DLNM) combined with a quasi-Poisson generalized linear regression model was employed to assess the association between NO₂ exposure and the risk of outpatient visits for conjunctivitis. Stratified analyses were also performed on the basis of gender, age group and season.

RESULTS

The association of NO₂ exposure with the risk of outpatient visits for conjunctivitis was statistically significant. In the single-day lags (lag 0 to lag 11) analysis, the largest effect estimates were observed at lag 0. In the moving average exposure lags (lag 0-1 to lag 0-11) analysis, the cumulative effects were stronger than the single-day lag effects. The stratified analyses suggested that the effect of NO₂ exposure was more pronounced in females and patients aged 19-65 years and in the cold season.

CONCLUSIONS

This study confirms the evidence that short-term NO₂ exposure is associated with an increased risk of conjunctivitis outpatient visits. Our research encourages individuals to avoid outdoor activities on severe air pollution days and the government is obliged to adopt more stringent environmental policies to alleviate the effects of air pollution on human health, particularly for individuals at risk of developing conjunctivitis.

Improved ANFIS model for forecasting Wuhan City Air Quality and analysis COVID-19 lockdown impacts on air quality

In this study, we propose an improved version of the adaptive neuro-fuzzy inference system (ANFIS) for forecasting the air quality index in Wuhan City, China. We propose a hybrid optimization method to improve ANFIS performance, called PSOSMA, using a new modified meta-heuristics (MH) algorithm, Slime mould algorithm (SMA), which is improved by using the particle swarm optimizer (PSO). The proposed PSOSMA-ANFIS has been trained with air quality index time series data of three years and has been applied to forecast the fine particulate matter (PM2.5), sulfur dioxide (SO2), carbon dioxide (CO2), and nitrogen dioxide (NO2) for one year. We also compared the proposed PSOSMA to other MH algorithms used to train ANFIS. We found that the modified ANFIS using PSOSMA achieved better performance than compared algorithms. Moreover, we analyzed the impacts of the lockdown of Wuhan City on the concentrations of PM2.5, NO2, CO2, and SO2. We compared the correspondence period with previous years, and we concluded that there are significant decreases in the concentrations of PM2.5, CO2, SO2, and NO2.

SARS-CoV-2 infection, COVID-19 pathogenesis, and exposure to air pollution: What is the connection?

Exposure to air pollutants has been previously associated with respiratory viral infections, including influenza, measles, mumps, rhinovirus, and respiratory syncytial virus. Epidemiological studies have also suggested that air pollution exposure is associated with increased cases of SARS-CoV-2 infection and COVID-19-associated mortality, although the molecular mechanisms by which pollutant exposure affects viral infection and pathogenesis of COVID-19 remain unknown. In this review, we suggest potential molecular mechanisms that could account for this association. We have focused on the potential effect of exposure to nitrogen dioxide (NO2 ), ozone (O3 ), and particulate matter (PM) since there are studies investigating how exposure to these pollutants affects the life cycle of other viruses. We have concluded that pollutant exposure may affect different stages of the viral life cycle, including inhibition of mucociliary clearance, alteration of viral receptors and proteases required for entry, changes to antiviral interferon production and viral replication, changes in viral assembly mediated by autophagy, prevention of uptake by macrophages, and promotion of viral spread by increasing epithelial permeability. We believe that exposure to pollutants skews adaptive immune responses toward bacterial/allergic immune responses, as opposed to antiviral responses. Exposure to air pollutants could also predispose exposed populations toward developing COIVD-19-associated immunopathology, enhancing virus-induced tissue inflammation and damage.

Forecast and early warning of hand, foot, and mouth disease based on meteorological factors: Evidence from a multicity study of 11 meteorological geographical divisions in mainland China

BACKGROUND

Hand, foot, and mouth disease (HFMD) is a significant public health issue in China. Early warning and forecasting are one of the most cost-effective ways for HFMD control and prevention. However, relevant research is limited, especially in China with a large population and diverse climatic characteristics. This study aims to identify local specific HFMD epidemic thresholds and construct a weather-based early warning model for HFMD control and prevention across China.

METHODS

Monthly notified HFMD cases and meteorological data for 22 cities selected from different climate zones from 2014 to 2018 were extracted from the National Notifiable Disease Surveillance System and the Meteorological Data Sharing Service System, respectively. A generalized additive model (GAM) based on meteorological factors was conducted to forecast HFMD epidemics. The receiver operator characteristic curve (ROC) was generated to determine the value of optimal warning threshold.

RESULTS

The developed model was solid in forecasting the epidemic of HFMD with all R square (R²) in the 22 cities above 85%, and mean absolute percentage error (MAPE) less than 1%. The warning thresholds varied by cities with the highest threshold observed in Shenzhen (n = 7195) and the lowest threshold in Liaoyang (n = 12). The areas under the curve (AUC) was greater than 0.9 for all regions, indicating a satisfied discriminating ability in epidemics detection.

CONCLUSIONS

The weather-based HFMD forecasting and early warning model we developed for different climate zones provides needed information on occurrence time and size of HFMD epidemics. An effective early warning system for HFMD could provide sufficient time for local authorities to implement timely interventions to minimize the HFMD morbidity and mortality.

Short-term effects of ambient air pollution on the incidence of influenza in Wuhan, China: A time-series analysis

BACKGROUND

Evidence suggests that air pollution is associated with many adverse health outcomes such as cardiovascular diseases (CVD), respiratory diseases, cancer, and birth defects. Yet few studies dig into the relationship between air pollution and airborne infectious diseases.

METHODS

Daily data on influenza incidence were obtained from Hubei Provincial Center for Disease Control and Prevention (Hubei CDC). Data on air pollutants including nitrogen dioxide (NO₂), sulfur dioxide (SO₂), ground-level ozone (O₃), particulate matter (PM) with aerodynamic diameter ≤ 2.5 μm (PM_2.5), and PM with aerodynamic diameter ≤ 10 μm (PM₁₀) were retrieved from ten national air sampling stations located at Wuhan. We applied generalized additive model (GAM) to estimate the associations between air pollution and the risk of influenza in Wuhan, China during 2015-2017.

RESULTS

In the single-day lag model, the largest effect estimates were observed at lag 0. An increased relative risk (RR) of influenza was significantly associated with a 10 μg/m³ increase in SO₂ (RR: 1.099; 95% confidence interval [CI]: 1.011-1.195), NO₂ (RR: 1.039; 95% CI: 1.013-1.065), and O₃ (RR: 1.005; 95% CI: 0.994-1.016), respectively. In the multi-day lag model, concentrations of SO₂, NO₂, and O₃ were statistically significantly associated with the risk of influenza at lag 0-1. The seasonal analysis suggests that the influence of air pollution on influenza is greater in the cold season as compared in the warm season in the early lag days. The multi-pollutant model indicates that NO₂ may be a potential confounder for co-pollutants.

CONCLUSIONS

Our study shows that air pollution may be associated with the risk of influenza in a broad sense. Therefore, when formulating policies to deal with influenza outbreaks in the future, factors regarding air pollution should be taken into consideration.

Region-specific air pollutants and meteorological parameters influence COVID-19: A study from mainland China

Coronavirus disease 2019 (COVID-19) was first detected in December 2019 in Wuhan, China, with 11,669,259 positive cases and 539,906 deaths globally as of July 8, 2020. The objective of the present study was to determine whether meteorological parameters and air quality affect the transmission of COVID-19, analogous to SARS. We captured data from 29 provinces, including numbers of COVID-19 cases, meteorological parameters, air quality and population flow data, between Jan 21, 2020 and Apr 3, 2020. To evaluate the transmissibility of COVID-19, the basic reproductive ratio (R₀) was calculated with the maximum likelihood "removal" method, which is based on chain-binomial model, and the association between COVID-19 and air pollutants or meteorological parameters was estimated by correlation analyses. The mean estimated value of R₀ was 1.79 ± 0.31 in 29 provinces, ranging from 1.08 to 2.45. The correlation between R₀ and the mean relative humidity was positive, with coefficient of 0.370. In provinces with high flow, indicators such as carbon monoxide (CO) and 24-h average concentration of carbon monoxide (CO_24 h) were positively correlated with R₀, while nitrogen dioxide (NO₂), 24-h average concentration of nitrogen dioxide (NO₂_24 h) and daily maximum temperature were inversely correlated to R₀, with coefficients of 0.644, 0.661, -0.636, -0.657, -0.645, respectively. In provinces with medium flow, only the weather factors were correlated with R₀, including mean/maximum/minimum air pressure and mean wind speed, with coefficients of -0.697, -0.697, -0.697 and -0.841, respectively. There was no correlation with R₀ and meteorological parameters or air pollutants in provinces with low flow. Our findings suggest that higher ambient CO concentration is a risk factor for increased transmissibility of the novel coronavirus, while higher temperature and air pressure, and efficient ventilation reduce its transmissibility. The effect of meteorological parameters and air pollutants varies in different regions, and requires that these issues be considered in future modeling disease transmissibility.

Factors determining the diffusion of COVID-19 and suggested strategy to prevent future accelerated viral infectivity similar to COVID

This study has two goals. The first is to explain the geo-environmental determinants of the accelerated diffusion of COVID-19 that is generating a high level of deaths. The second is to suggest a strategy to cope with future epidemic threats similar to COVID-19 having an accelerated viral infectivity in society. Using data on sample of N = 55 Italian province capitals, and data of infected individuals at as of April 7th, 2020, results reveal that the accelerate and vast diffusion of COVID-19 in North Italy has a high association with air pollution of cities measured with days exceeding the limits set for PM10 (particulate matter 10 μm or less in diameter) or ozone. In particular, hinterland cities with average high number of days exceeding the limits set for PM10 (and also having a low wind speed) have a very high number of infected people on 7th April 2020 (arithmetic mean is about 2200 infected individuals, with average polluted days greater than 80 days per year), whereas coastal cities also having days exceeding the limits set for PM10 or ozone but with high wind speed have about 944.70 average infected individuals, with about 60 average polluted days per year; moreover, cities having more than 100 days of air pollution (exceeding the limits set for PM10), they have a very high average number of infected people (about 3350 infected individuals, 7th April 2020), whereas cities having less than 100 days of air pollution per year, they have a lower average number of infected people (about 1014 individuals). The findings here also suggest that to minimize the impact of future epidemics similar to COVID-19, the max number of days per year that Italian provincial capitals or similar industrialized cities can exceed the limits set for PM10 or for ozone, considering their meteorological conditions, is about 48 days. Moreover, results here reveal that the explanatory variable of air pollution in cities seems to be a more important predictor in the initial phase of diffusion of viral infectivity (on 17th March 2020, b1 = 1.27, p < 0.001) than interpersonal contacts (b2 = 0.31, p < 0.05). In the second phase of maturity of the transmission dynamics of COVID-19, air pollution reduces intensity (on 7th April 2020 with b'1 = 0.81, p < 0.001) also because of the indirect effect of lockdown, whereas regression coefficient of transmission based on interpersonal contacts has a stable level (b'2 = 0.31, p < 0.01). This result reveals that accelerated transmission dynamics of COVID-19 is due to mainly to the mechanism of "air pollution-to-human transmission" (airborne viral infectivity) rather than "human-to-human transmission". Overall, then, transmission dynamics of viral infectivity, such as COVID-19, is due to systemic causes: general factors that are the same for all regions (e.g., biological characteristics of virus, incubation period, etc.) and specific factors which are different for each region and/or city (e.g., complex interaction between air pollution, meteorological conditions and biological characteristics of viral infectivity) and health level of individuals (habits, immune system, age, sex, etc.). Lessons learned for COVID-19 in the case study here suggest that a proactive strategy to cope with future epidemics is also to apply especially an environmental and sustainable policy based on reduction of levels of air pollution mainly in hinterland and polluting cities- (having low wind speed, high percentage of moisture and number of fog days) -that seem to have an environment that foster a fast transmission dynamics of viral infectivity in society. Hence, in the presence of polluting industrialization in regions that can trigger the mechanism of air pollution-to-human transmission dynamics of viral infectivity, this study must conclude that a comprehensive strategy to prevent future epidemics similar to COVID-19 has to be also designed in environmental and socioeconomic terms, that is also based on sustainability science and environmental science, and not only in terms of biology, medicine, healthcare and health sector.

Ambient air pollution and its influence on human health and welfare: an overview

Human health is closely related to his environment. The influence of exposure to air pollutants on human health and well-being has been an interesting subject and gained much volume of research over the last 50 years. In general, polluted air is considered one of the major factors leading to many diseases such as cardiovascular and respiratory disease and lung cancer for the people. Besides, air pollution adversely affects the animals and deteriorates the plant environment. The overarching objective of this review is to explore the previous researches regarding the causes and sources of air pollution, how to control it and its detrimental effects on human health. The definition of air pollution and its sources were introduced extensively. Major air pollutants and their noxious effects were detailed. Detrimental impacts of air pollution on human health and well-being were also presented.

The association between ambient particulate matters, nitrogen dioxide, and childhood scarlet fever in Hangzhou, Eastern China, 2014-2018

BACKGROUND

The emerging cases of childhood scarlet fever (SF) and worsening air pollution problems in Chinese cities suggests a potential linkage between them. However, few studies had explored this association in a large childhood population.

METHODS

We conducted a time-series analysis using the daily count of SF and the daily concentrations of particulate matters with an aerodynamic diameter of 2.5 (PM_2.5) and 10 (PM₁₀), as well as nitrogen dioxide (NO₂) in Hangzhou, China from 2014 to 2018. Distributed lag nonlinear models were used to estimate the lag effects of PM_2.5, PM₁₀ and NO₂ for a maximum lag of 10 days, which were quantified using relative risk (RR) comparing the adjusted risks at the 2.5th (extremely low effect) and 97.5th (extremely high effect) percentiles of concentration of the three air pollutants to that at the median. Stratified RRs by sex were also reported.

RESULTS

Using the median concentration as reference, for extremely high effect, the RR was the highest on lag days 5, 6, and 3 for PM_2.5, PM₁₀, and NO₂ respectively. While on lag day 0, the RR of PM_2.5, PM₁₀, and NO₂ were 1.04 (95%CI: 0.90-1.20), 1.07 (95%CI: 0.92-1.24), and 1.08 (95%CI: 0.92-1.26) respectively, the RRs increased constantly and cumulatively to the maximum values of 1.88 (95%CI: 1.33-2.66), 1.82 (95%CI: 1.29-2.55), and 2.19 (95%CI: 1.47-3.27) for PM_2.5, PM₁₀, and NO₂ respectively on lag day 10. Subgroup analyses showed that females appeared to be more vulnerable to the three pollutants than males.

CONCLUSION

Our study provides evidence that PM_2.5, PM₁₀, and NO₂ exert delayed effects on SF infection.

The role of meteorological factors on mumps incidence among children in Guangzhou, Southern China

Mumps, a common childhood disease, has a high incidence in Guangzhou city, China. It has been proven that mumps is influenced by seasonality. However, the role of meteorological factors among children is yet to be fully ascertained. This study explored the association between meteorological factors and the incidence of mumps among children in Guangzhou. Distributed lag nonlinear models were used to evaluate the correlation between meteorological factors and the incidence of mumps among children from 2014–2018. The nonlinear lag effects of some meteorological factors were detected. Mean temperature, atmospheric pressure, and relative humidity were positively correlated with mumps incidence, contrary to that of wind speed. Extreme effects of temperature, wind speed, atmospheric pressure, and relative humidity on the incidence of mumps among children in Guangzhou were evaluated in a subgroup analysis according to gender and age. Our preliminary results offered fundamental information to better understand the epidemic trends of mumps among children to develop an early warning system, and strengthen the intervention and prevention of mumps.

Two mechanisms for accelerated diffusion of COVID-19 outbreaks in regions with high intensity of population and polluting industrialization: the air pollution-to-human and human-to-human transmission dynamics (Preprint).. [DOI: 10.2196/preprints.19331]

BACKGROUND

Coronavirus disease 2019 (COVID-19) is viral infection that generates a severe acute respiratory syndrome with serious pneumonia that may result in progressive respiratory failure and death.

OBJECTIVE

This study has two goals. The first is to explain the main factors determining the diffusion of COVID-19 that is generating a high level of deaths. The second is to suggest a strategy to cope with future epidemic threats with of accelerated viral infectivity in society.

METHODS

Correlation and regression analyses on on data of N=55 Italian province capitals, and data of infected individuals at as of April 2020.

RESULTS

The main results are: o The accelerate and vast diffusion of COVID-19 in North Italy has a high association with air pollution. o Hinterland cities have average days of exceeding the limits set for PM10 (particulate matter 10 micrometers or less in diameter) equal to 80 days, and an average number of infected more than 2,000 individuals as of April 1st, 2020, coastal cities have days of exceeding the limits set for PM10 equal to 60 days and have about 700 infected in average. o Cities that average number of 125 days exceeding the limits set for PM10, last year, they have an average number of infected individual higher than 3,200 units, whereas cities having less than 100 days (average number of 48 days) exceeding the limits set for PM10, they have an average number of about 900 infected individuals. o The results reveal that accelerated transmission dynamics of COVID-19 in specific environments is due to two mechanisms given by: air pollution-to-human transmission and human-to-human transmission; in particular, the mechanisms of air pollution-to-human transmission play a critical role rather than human-to-human transmission. o The finding here suggests that to minimize future epidemic similar to COVID-19, the max number of days per year in which cities can exceed the limits set for PM10 or for ozone, considering their meteorological condition, is less than 50 days. After this critical threshold, the analytical output here suggests that environmental inconsistencies because of the combination between air pollution and meteorological conditions (with high moisture%, low wind speed and fog) trigger a take-off of viral infectivity (accelerated epidemic diffusion) with damages for health of population, economy and society.

CONCLUSIONS

Considering the complex interaction between air pollution, meteorological conditions and biological characteristics of viral infectivity, lessons learned for COVID-19 have to be applied for a proactive socioeconomic strategy to cope with future epidemics, especially an environmental policy based on reduction of air pollution mainly in hinterland zones of countries, having low wind speed, high percentage of moisture and fog that create an environment that can damage immune system of people and foster a fast transmission of viral infectivity similar to the COVID-19.

CLINICALTRIAL

not applicable

Two mechanisms for accelerated diffusion of COVID-19 outbreaks in regions with high intensity of population and polluting industrialization: the air pollution-to-human and human-to-human transmission dynamics.. [DOI: 10.1101/2020.04.06.20055657]

What is COVID-19?

Coronavirus disease 2019 (COVID-19) is viral infection that generates a severe acute respiratory syndrome with serious pneumonia that may result in progressive respiratory failure and death.

What are the goals of this investigation?

This study explains the geo-environmental determinants of the accelerated diffusion of COVID-19 in Italy that is generating a high level of deaths and suggests general lessons learned for a strategy to cope with future epidemics similar to COVID-19 to reduce viral infectivity and negative impacts in economic systems and society.

What are the results of this study?

The main results are:

What is a socioeconomic strategy to prevent future epidemics similar to COVID-19?

Considering the complex interaction between air pollution, meteorological conditions and biological characteristics of viral infectivity, lessons learned for COVID-19 have to be applied for a proactive socioeconomic strategy to cope with future epidemics, especially an environmental policy based on reduction of air pollution mainly in hinterland zones of countries, having low wind speed, high percentage of moisture and fog that create an environment that can damage immune system of people and foster a fast transmission of viral infectivity similar to the COVID-19.

This study must conclude that a strategy to prevent future epidemics similar to COVID 19 has also to be designed in environmental and sustainability science and not only in terms of biology.

Impact of Ambient Temperature and Relative Humidity on the Incidence of Hand-Foot-Mouth Disease in Wuhan, China

Background: Few studies have previously explored the relationship between hand, foot, and mouth disease (HFMD) and meteorological factors with the effect modification of air pollution, and these studies had inconsistent findings. We therefore applied a time-series analysis assessing the effects of temperature and humidity on the incidence of HFMD in Wuhan, China to deepen our understanding of the relationship between meteorological factors and the risk of HFMD. Methods: Daily HFMD cases were retrieved from Hubei Provincial Center for Disease Control and Prevention from 1 February 2013 to 31 January 2017. Daily meteorological data including 24 h average temperature, relative humidity, wind velocity, and atmospheric pressure were obtained from Hubei Meteorological Bureau. Data on Air pollution was collected from 10 national air-monitoring stations in Wuhan city. We adopted a distributed lag non-linear model (DLNM) combined with Poisson regression and time-series analysis to estimate the effects of temperature and relative humidity on the incidence HFMD. Results: We found that the association between temperature and HFMD incidence was non-linear, exhibiting an approximate "M" shape with two peaks occurring at 2.3 °C (RR = 1.760, 95% CI: 1.218-2.542) and 27.9 °C (RR = 1.945, 95% CI: 1.570-2.408), respectively. We observed an inverted "V" shape between relative humidity and HFMD. The risk of HFMD reached a maximum value at a relative humidity of 89.2% (RR = 1.553, 95% CI: 1.322-1.824). The largest delayed cumulative effects occurred at lag 6 for temperature and lag 13 for relative humidity. Conclusions: The non-linear relationship between meteorological factors and the incidence of HFMD on different lag days could be used in the early targeted warning system of infectious diseases, reducing the possible outbreaks and burdens of HFMD among sensitive populations.