Human exposure risk assessment for infectious diseases due to temperature and air pollution: an overview of reviews

doi:10.21203/rs.3.rs-2578960/v1

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Human exposure risk assessment for infectious diseases due to temperature and air pollution: an overview of reviews

https://doi.org/10.21203/rs.3.rs-2578960/v1

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published 12 Jul, 2023

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Air pollution and global temperature change are expected to affect infectious diseases. Yet to date overview of systematic reviews assessing the exposure risk of air pollutants and temperature on infectious diseases is unavailable. PubMed, Embase, the Cochrane Library, Web of Science, and the Cumulative Index to Nursing and Allied Health Literature were searched. Systematic reviews and meta-analyses investigated the exposure risk of pollutants or temperature on infectious diseases were included. Two investigators screened literature, extracted data and performed the risk of bias assessments independently. A total of 23 articles met the inclusion criteria, which 3 (13%) were "low" quality and 20 (87%) were "critically low" quality. COVID-19 morbidity was associated with long-term exposure PM_2.5 (RR = 1.056 per 1μg/m ³, 95% CI: 1.039-1.072) and NO₂ (RR = 1.042 per 1 μg/m ³, 95% CI: 1.017-1.068). In addition, for each 1°C increase in temperature, the risk of dengue fever morbidity increased 13% (RR = 1.130 per 1°C, 95% CI: 1.120-1.150), infectious diarrhea morbidity increased 8% (RR =1.080 per 1°C, 95% CI: 1.050-1.200), and hand, foot and mouth disease (HFMD) morbidity increased 5% (RR = 1.050 per 1 °C, 95% CI: 1.020-1.080). In conclusion, PM_2.5 and NO₂ increased the risk of COVID-19 and temperatures were associated with dengue, infectious diarrhoea and HFMD morbidity. Moreover, the exposure risk of temperature on COVID-19 need to be further explored.

Pollutant

Temperature

Health

Systematic review

Air pollution is one of the most severe environmental risks affecting health (Samet et al. 2015, Yang et al. 2016, Sun and Zhu 2019), mainly including fine particles (PM_2.5), thoracic particles (pm10), ozone(O₃), nitrogen dioxide (NO₂), sulfur dioxide(SO₂) and carbon monoxide (CO) (Samet et al. 2015, Yang et al. 2016, Sun and Zhu 2019). The Global Burden of Diseases (GBD), Injuries, and Risk Factors Study indicated that air pollution ranks fourth among the global risk factors for death, with 6.67 million premature deaths due to air pollution accounting for 53% of the burden of disease (Murray et al. 2020). In addition, THE LANCET showed that air pollution ranks seventh among the global risk factors for death adjusted life-years. Air pollution mainly comes from fossil fuel combustion and industrial transportation emissions. It has a greater impact on low- and middle-income countries, which heavily rely on fossil fuels for economic development (Murray et al. 2020). The association between air pollution and non-communicable diseases, such as cardiovascular and respiratory diseases, has been confirmed. However, the global COVID-19 pandemic has changed the cognition of the risk factors for infectious diseases. Evidence of the impacts of air pollution on infectious diseases urgently needs to be analyzed (WHO 2021).

The rapid acceleration of industrialization has led to severe air pollution, and the massive emissions of greenhouse gases, such as carbon dioxide (CO₂) and methane (CH₄) has increased the global average temperature to 1.1°C higher than the pre-industrial baseline (WMO 2021). The problem of global warming continues to exacerbate, and 2019 GBD Study data has shown that extreme heat and low temperatures have significant impacts on human health. In addition, there were 1.96 million global cold-and heat-related deaths, accounting for 16% of the total burden of disease (Murray et al. 2020). More than 350,000 deaths were linked to heat in 2019 globally. A large number of epidemiological studies have shown that extreme temperatures, especially heat, increase the risks of respiratory and cardiovascular diseases. Furthermore, during 1990–2019, high temperature-related non-communicable disease burden exhibited an upward trend (Song et al. 2021). However, the evidence of extreme temperatures on infectious diseases has not been thoroughly investigated.

This study included systematic reviews and meta-analyses on the impacts of pollutants and temperatures on infectious diseases. Our study aimed to (1) summarize evidences from systematic reviews of the effects of pollutants and temperatures on infectious morbidity and mortality; and (2) evaluate the methodological quality of systematic reviews and meta-analyses evaluating the impacts of air pollutants and air temperatures on infectious diseases.

The protocol for this overview was published online and is available on PROSPERO (International Prospective Register of Systematic Reviews). The registration number is CRD42022324489.

2.1 Search strategy

PubMed, Embase, the Cochrane Library, Web of Science and the Cumulative Index to Nursing and Allied Health Literature (CINAHL) were systematically searched. Systematic reviews investigating the exposure risks of PM_2.5, PM₁₀, PM₁, CO, O₃, SO₂, CO₂, black carbon (BC) and temperatures on infectious morbidity and mortality were identified. The search was performed up to January 6th, 2022. The following U.S. National Library of Medicine’s Medical Subject Headings (MeSH) terms and keywords were used: ("heat wave*" OR "cold spell*" OR "air pollution*" OR "PM₁₀" OR "PM_2.5") AND ("health effect*" OR "morbidity" OR "hospitalization" OR "death") AND ("meta analysis" OR "systematic* review*"). Specific search strategies are provide in the appendix (Table S1 and Table S2). Additionally, the reference lists of included studies were manually searched to identify additional relevant studies.

2.2 Inclusion and exclusion criteria

Evidences from systematic reviews of the effects of pollutants and temperatures on infectious morbidity and mortality were included in this overview. According to PEOS, studies were considered eligible for inclusion if they fulfilled the following inclusion criteria (1) Population: based on the International Classification of Diseases (ICD) 10th revision, infectious diseases with ICD-10 codes A00-B99 and COVID-19 with ICD-10 code U09.100. There was no age limitation for patients. (2) Exposure: ambient temperature, high temperature, low temperature, heat wave, cold wave, PM_2.5, PM₁₀, PM₁, O₃,NO₂, SO₂, CO and BC. (3) Outcome: morbidity and mortality. (4) Study design: systematic review and meta-analysis.

Exclusion criteria were as follows: (1) Studies evaluating pollutants and temperatures in specific or indoor places. (2) Studies of which the outcome indicators were physiological and biochemical indexes. (3) Publication language is non-English.

2.3 Study selection and data extraction

Two researchers independently screened the title and abstract to identify eligible studies. Full text was screened to identify relevant studies, which were not determined by their titles and abstracts. Any conflict was resolved by a third researcher. Two researchers independently extracted data from the included systematic reviews. Study characteristics were extracted according to a standardized form, which included but was not restricted to the following items: author, year of publication, study type, exposure type, disease, outcome, databases searched, and the number of included studies. For any disagreement, a third reviewer was consulted.

2.4 Quality assessment

A MeaSurement Tool to Assess systematic Reviews 2 (AMSTAR-2), the updated version of AMSTAR, was used for assessing the methodological quality of eligible systematic reviews, and consists of 16 domains that are classified as either critical domains and non-critical domains. Items are evaluated as with “Yes”, “Partial Yes”, “No”, or “No meta-analysis conducted” (Shea et al. 2017).

2.5 Statistical analysis

Qualitative and quantitative description were used to summarize characteristics of eligible systematic reviews and meta-analyses and data were independently extracted from the latter. Summary statistics (relative risks, odds ratios, or percentages) were recalculated, and converted to relative risks (RR) per 1\({\mu }\text{g}/\text{m}\)³increase in air pollution and per 1°C increase in temperature.

\({\text{RR}}_{\text{(standardized)}}\) =\({\text{RR}}_{\text{(original)}}^{\text{Increment(1)/Increment(original)}}\)

In addition, the pollutant exposure was divided into long-term exposure and short-term exposure, and the boundary was seven days. Those with a lag of less than or equal to 7 days were considered as short-term exposure, and those with a lag of more than 7 days were considered long-term exposure (Chen et al. 2019). Forest plots combining relative risk and 95% confidence interval (CI) were constructed.

402 studies were excluded after the full-text screening. Ultimately, 23 reviews (Ramesh et al. 2013, Viana and Ignotti 2013, Fan et al. 2015, Philipsborn et al. 2016, Cheng et al. 2018, Ghazani et al. 2018, Lu et al. 2018, Bai et al. 2019, Chen et al. 2019, Coates et al. 2019, Popovic et al. 2019, Asadgol et al. 2020, Copat et al. 2020, Li et al. 2020, Villeneuve and Goldberg 2020, Katoto et al. 2021, Liang et al. 2021, Majumder and Ray 2021, Maleki et al. 2021, Meo et al. 2021, Starke et al. 2021, Xiang et al. 2021, Zang et al. 2022 ) met the inclusion criteria (Figure S1). 15 systematic reviews evaluated morbidity, 7 reviews evaluated both morbidity and mortality, and mortality was evaluated in only one review. 9 were pollutant-related, and 14 were temperature-related, covering ten infectious diseases (Table S3). Three statements were adopted in the included studies: PRISMA, MOOSE and STROBE, both Zang et al. and Asadgol et al. used PRISMA and MOOSE together, while seven studies, it was not mentioned which statement was adopted. In addition, three (13%) studies adopted the GRADE (Grading of Recommendations Assessment, Development and Evaluation).

3.1 Quality assessment of systematic reviews

As presented in Figure S2, the results of the quality assessment showed that three studies were of low quality (13%) and 20 articles were of critically low quality (87%). Item 1 (100%), item 4 (100%), Item 8 (100%), Item 11 (100%) and Item 16 (96%) denoted satisfactory results, whereas Item 3 (0%), Item 7 (0%) and Item 10 (0%) reported inadequately. Item 2 was poorly reported and most systematic reviews were not registered, however studies on COVID-19 (28.6%) and infectious diarrhea (50%) satisfied this criterion better. AMSTAR-2 scores of systematic reviews with and without meta-analyses are presented in Table S4.

3.2 Findings from the overview

3.2.1 Exposure risk assessment of short-term exposure to air pollutants on infectious diseases

Nine pollutant-related studies were included, six of which were systematic reviews (Popovic et al. 2019, Copat et al. 2020, Villeneuve and Goldberg 2020, Katoto et al. 2021, Maleki et al. 2021, Meo et al. 2021), and three were meta-analyses (Chen et al. 2019, Xiang et al. 2021, Zang et al. 2022) (Fig. 1). In addition, in nine studies, the association between short-term exposure to air pollutants and infectious morbidity and mortality was analyzed.

One meta-analysis and five systematic reviews analyzed the association between COVID-19 and pollutants: Zang et al. 2022 performed a meta-analysis on the association, which indicated that short-term exposure to NO₂ (RR 1.014 per 1 \({\mu }\text{g}/\text{m}\)³, 95% CI: 1.011–1.016), O₃ (RR 1.001 per 1 \({\mu }\text{g}/\text{m}\)³, 95% CI: 1.000-1.002), PM₁₀ (RR 1.005 per 1 \({\mu }\text{g}/\text{m}\)³, 95% CI: 1.003–1.008), PM_2.5 (RR 1.003 per 1 \({\mu }\text{g}/\text{m}\)³, 95% CI: 1.002–1.004) and SO₂ (RR 1.015 per 1 \({\mu }\text{g}/\text{m}\)³, 95% CI: 1.007–1.023) were positively associated to COVID-19 morbidity, with CO had no statistical significance.

One meta-analysis focused on the association between air pollution and conjunctivitis. It indicated that NO₂ and O₃ increased the risk of conjunctivitis morbidity (Chen et al. 2019). One meta-analysis and one systematic review analyzed the exposure risks of pollutants on tuberculosis (TB), while the results were controversial: Popovic et al.2019 showed that PM_2.5 may be associated with culture-positive TB morbidity.. Compared to the results of Xiang et al. 2021, a meta-analysis, showed that short-term exposure to pollution (PM_2.5: RR 1.003 per 1 \({\mu }\text{g}/\text{m}\)³, 95% CI: 0.998–1.008) was not associated with TB morbidity.

Figure 1 Forest plot for the effects of short-term exposure to pollutants on infectious diseases.

3.2.2 Exposure risk assessment of long-term exposure to air pollutants on infectious diseases

Eight studies (Popovic et al. 2019, Copat et al. 2020, Villeneuve and Goldberg 2020, Katoto et al. 2021, Maleki et al. 2021, Meo et al. 2021, Xiang et al. 2021, Zang et al. 2022) conducted the association between long-term exposure to air pollutants and the morbidity and mortality outcomes of infectious diseases, and two were meta-analyses (Xiang et al. 2021, Zang et al. 2022) (Fig. 2).

One meta-analysis and five systematic reviews, the association between COVID-19 and pollution was analyzed: Zang et al. 2022 showed that COVID-19 morbidity was positively associated with long-term exposure to 1 \({\mu }\text{g}/\text{m}\)³ increase in PM_2.5 (RR 1.056 per 1 \({\mu }\text{g}/\text{m}\)³, 95% CI: 1.039–1.072, I² = 94.9%), NO₂ (RR 1.042 per 1 \({\mu }\text{g}/\text{m}\)³, 95% CI: 1.017–1.068, I² = 98.3%), and SO₂ (RR 1.071 per 1 \({\mu }\text{g}/\text{m}\)³, 95% CI: 1.002–1.145, I² = 97.2%). However, COVID-19 morbidity was negatively associated with CO (RR 0.258 per 1 \({\mu }\text{g}/\text{m}\)³, 95% CI: 0.126–0.529, I² = 99.4%) and O₃ (RR 0.983 per 1 \({\mu }\text{g}/\text{m}\)³, 95% CI: 0.972–0.994, I² = 98.4%). Katoto et al. 2021 was a systematic review, which indicated a highly positive association between long-term exposure to PM_2.5 and COVID-19 morbidity.

One meta-analysis and one systematic review analyzed the association between TB and pollutants, with controversial results: Xiang et al. 2021 showed that long-term exposure to PM₁₀ (RR 1.006 per 1 \({\mu }\text{g}/\text{m}\)³, 95%CI 1.002–1.009) and NO₂ (RR 1.005 per 1 \({\mu }\text{g}/\text{m}\)³, 95%CI 1.001–1.008) was significantly associated with TB morbidity. In addition, Popovic et al. 2019 suggested that SO₂ may be a potential protective factor for TB.

3.2.3 Exposure risk assessment of temperatures on infectious diseases

Fourteen temperature-related studies were included, among which were 8 systematic reviews (Ramesh et al. 2013, Viana and Ignotti 2013, Ghazani et al. 2018, Lu et al. 2018, Bai et al. 2019, Coates et al. 2019, Asadgol et al. 2020, Starke et al. 2021) and 6 meta-analyses (Fan et al. 2015, Philipsborn et al. 2016, Cheng et al. 2018, Li et al. 2020, Liang et al. 2021, Majumder and Ray 2021) (Fig. 3).

One meta-analysis and one systematic review analyzed the association between temperatures and COVID-19: Majumder and Ray 2021 showed that temperature was associated with COVID-19 morbidity (pooled correlation = 0.230, 95% CI: 0.010–0.430). However, the correlation between temperatures and COVID-19 mortality (pooled correlation = 0.210, 95% CI: -0.140-0.520) was not statistically significant. However, a systematic review by Starke et al. 2021, indicated that an elevated temperature maybe was a protective factor for COVID-19 mortality.

Per 1°C increase in temperatures was associated with dengue, infectious diarrhoea, trachoma, hemorrhagic fever with renal syndrome and HFMD morbidity. Fan et al. 2015, Li et al. 2020 showed that dengue morbidity increased by 13% (RR = 1.130 per 1°C, 95% CI: 1.120–1.150), within the average temperature range of 23.2–27.7°C was most closely and positively correlated. The morbidity of infectious diarrhea increased 8% (RR = 1.080 per 1°C, 95% CI: 1.050–1.200), and Diarrhoeal Escherichia coli increased 10% (RR 1.100 per 1°C, 95% CI: 1.050–1.200, P < 0.0001). While increased temperatures were negatively correlated with Helicobacter pylori infection (coefficient=-0.577, P < 0.001, coefficient =-0.556, P < 0.001) (Philipsborn et al. 2016, Lu et al. 2018, Liang et al. 2021, Asadgol et al. 2020). Cheng et al. 2018 indicated that HFMD morbidity increased 5% (RR 1.050 per 1°C, 95% CI: 1.020–1.080), especially in a subtropical climate zone (RR 1.060 per 1°C, 95% CI: 1.020–1.100).

This work presents an overview of systematic reviews investigating the health exposure risks of pollutants and temperatures on infectious diseases. A comprehensive search of five electronic databases was performed using a well-defined search strategy. Ultimately, 23 systematic reviews assessing the association between pollutants, temperatures and infectious diseases morbidity or mortality were included.

4.1 PM increased the risk of transmission of respiratory infectious diseases

The effects of pollutants on COVID-19 were more definite, with short-term exposure to PM_2.5, PM₁₀, NO₂, SO₂ and long-term exposure to PM_2.5, NO₂, and SO₂ increased the risk of COVID-19 morbidity. In addition, the long-term effects acted more strongly than the short-term effects. Long-term exposure to PM_2.5 and NO₂ increased the risk of COVID-19 mortality. However, studies on COVID-19 and pollutants lack subgroup analyses of age, sex, and variant strains to identify high-risk populations that would help with better approaches for prevention and control.. Inhalation of particulate matter can impair important protective components of the lung and the body's systemic immune response to viruses, can damage the tracheal and bronchial mucosa, and disrupts the synthesis and secretion of inflammatory cytokines and disrupts the body's immune defense system (Xiang et al. 2021). Particulate matter predisposes people to COVID-19, tuberculosis-related diseases, and PM_2.5 and PM₁₀ provide a platform for the carriage of SARS-CoV-2 viruses and their transport at the lung level (Katoto et al. 2021).

The results of the systematic reviews regarding the association between pollutants and TB incidence were not fully consistent with those of the meta-analyses, and the number of studies included was limited (Popovic et al. 2019, Xiang et al. 2021). Therefore, we cannot draw a reliable conclusion on existing studies, and more research is needed to further illustrate the association further (Hiramatsu et al. 2005, Rivas-Santiago et al. 2015).

4.2 Exposure risk of temperature on COVID-19 need further assessment

Global climate change has increased the spread of viruses across species, thereby increasing the risk of infectious diseases, particularly in Africa and Asia. As global warming continues, many wild animals carrying parasites and pathogens will be forced to move their habitats into human settlements, which significantly increases the risk of virus transmission to humans, leading to new epidemics (Carlson et al. 2022). Fong and Smith 2022 showed a nonlinear correlation between COVID-19 and temperatures. The risk of COVID-19 reaches a peak at an average temperature of 15.1°C, and the risk of COVID-19 reduces when the temperatures increases or decreases. In addition, several recent studies by the Chinese CDC have shown an inverse association between temperature and COVID-19. In this overeview, a systematic review showed that a high temperature was likely to be a protective factor for COVID-19 morbidity and mortality, while a meta-analysis suggested that the increase of temperatures was associated with COVID-19 morbidity. Therefore, the link between temperatures and COVID-19 is undefined and more relevant researches are needed to explore the association.

4.3 Methodology points need to be seriously considered

The methodological quality of a systematic review is crucial to the reproducibility and credibility of results. The methodological quality will affect the recommendations in the guidelines, and thus affect the decision-making process(Shea et al. 2007, Shea et al. 2009). Several weaknesses in methodology were found, which should be addressed in the future. First, AMSTAR-2 or other principles should be followed to enhance the standardization and normalization of systematic reviews and meta-analyses, thereby clearly reporting the facilitates to get a better understanding of how the study was conducted (Moher et al. 2009, Shea et al. 2017). Second, register prior to the commencement of the study with a detailed proposal and provide registration information should be provided. A comprehensive list of systematic reviews should be provided for us at the beginning of the registeration, thus helping to avoid duplication and reduce the chance of reporting bias by comparing evaluations from completed systematic reviews with plans in the program (Shea et al. 2017). Third, the demonstration of meta on environmental epidemiology studies should be taken with caution because the reliability is poor (Young et al. 2019). Sensitivity analysis was performed on PM_2.5 and TB morbidity for the original study included in Popovic et al. 2019. Our reanalysis showed that the results were not robust and meta-analysis of the studies did not support the conclusion (Jassal et al. 2013, Hwang et al. 2014, Smith et al. 2014, Alvaro-Meca et al. 2016, Chen et al. 2016, Lai et al. 2016, Smith et al. 2016, You et al. 2016, Ge et al. 2017, Peng et al. 2017). Therefore, inappropriate statistical models and combined results with a greater heterogeneity may be unreliable. If significant heterogeneity for the pooled estimates is noticed in the meta-analysis, subgroup analysis and regression analysis should be used to analyze the sources of heterogeneity.

4.4 Significant suggestions for future research

First, the influence of temperatures on COVID-19 has not been concluded, and the results of various studies are not fully consistent. Therefore more studies are needed to face the severe epidemic situation. Second, researches on BC and greenhouse gases are also urgently needed. BC is a ubiquitous component of PM and a measured component of PM, and BC plays a potential role in the toxic fraction of PM_2.5 (Song et al. 2022). Finally, few studies mainly focus on low-and middle-income countries or resource-poor areas. Despite the progress already made on the association between air pollution and temperatures changes on infectious morbidity and mortality, the World Health Organization (WHO) states that the current pace of improvements is not fast enough for many indicators to meet the sustainable development goal (SDG) targets by 2030. Therefore, future research still needs to focus on the impact of infectious diseases on population health (WHO 2021).

4.5 Limitations

This overview consolidated assessed the exposure risk of pollutants and temperatures on COVID-19. The data also provided comprehensive and current evidence from and evaluated the methodological quality of systematic reviews assessing the exposure risk of pollutants and temperatures on infectious morbidity and mortality. Our study has some limitations that should be noted. First,this overview only included systematic reviews and meta-analyses with morbidity and mortality as the outcome, and related studies of specific biochemical indicators were not explore. Second, the low AMSTAR-2 score of the included studies increased the risk of heterogeneity and bias in the meta-analysis, which may affected the quality of the overall conclusions.

Data availability

The original contributions presented in the study are included in the article/Supplementary Appendix, further inquiries can be directed to the corresponding authors.

Conflict of interest

We declare that all authors have no competing interests.

Acknowledgements

We would like to thank the authors of the systematic review, meta-analyses and original studies for their contributions to our overview.

Funding

This work was supported by the Science and Technology Program of Gansu Province (20JR5RA262) and the Fundamental Research Funds for the Central Universities (21lzujbkyzx007).

Author Contributions Statement

YZ and XS developed the research design. XG, XS,XH and YH analyzed the data and interpreted the results. XG, XH, YZ and DW drafted manuscript. XG, YH, LJ, YZ, DW and HX did literature screening and data extraction. All of the authors contributed to drafting the manuscript. The final manuscript was approved by all authors. XS is the guarantor and accepts full responsibility for the work.

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AbstractArt.pdf
Forest plot for the effects of short-term exposure to pollutants on infectious diseases.
SupplementaryAppendix.docx
Appendix. Supplementary data Table S1Search strategy for impact of temperature on infectious diseases. Table S2Search strategy for impact of pollutants on infectious diseases. Table S3 Characteristics of included systematic reviews. Table S4 AMSTAR-2 assessment for systematic reviews with and without meta-analyses Figure S1Flow diagram of literature screening process. Figure S2 Methodological qualities of included systematic reviews.

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published 12 Jul, 2023

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Editorial decision: Major Revision
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Human exposure risk assessment for infectious diseases due to temperature and air pollution: an overview of reviews

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Abstract

Figures

1. Background

2. Method

2.1 Search strategy

2.2 Inclusion and exclusion criteria

2.3 Study selection and data extraction

2.4 Quality assessment

2.5 Statistical analysis

3. Results

3.1 Quality assessment of systematic reviews

3.2 Findings from the overview

3.2.1 Exposure risk assessment of short-term exposure to air pollutants on infectious diseases

3.2.2 Exposure risk assessment of long-term exposure to air pollutants on infectious diseases

3.2.3 Exposure risk assessment of temperatures on infectious diseases

4. Discussion

4.1 PM increased the risk of transmission of respiratory infectious diseases

4.2 Exposure risk of temperature on COVID-19 need further assessment

4.3 Methodology points need to be seriously considered

4.4 Significant suggestions for future research

4.5 Limitations

Declarations

References

Supplementary Files

Status:

Journal Publication

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