Shuqiong Huang

Background: The coronavirus disease 2019 (Covid-19) spreads rapidly around the world. Objective: To evaluate the association between comorbidities and the risk of death in patients with COVID-19, and to further explore potential sex-specific differences. Methods: We analyzed the data from 18,465 laboratory-confirmed cases that completed an epidemiological investigation in Hubei Province as of February 27, 2020. Information on death was obtained from the Infectious Disease Information System. The Cox proportional hazards model was used to estimate the association between comorbidities and the risk of death in patients with COVID-19. Results: The median age for COVID-19 patients was 50.5 years. 8828(47.81%) patients were females. Severe cases accounted for 20.11% of the study population. As of March 7, 2020, a total of 919 cases deceased from COVID-19 for a fatality rate of 4.98%. Hypertension (13.87%), diabetes (5.53%), and cardiovascular and cerebrovascular diseases (CBVDs) (4.45%) were the most prevalent comorbidities, and 27.37% of patients with COVID-19 reported having at least one comorbidity. After adjustment for age, gender, address, and clinical severity, patients with hypertension (HR 1.55, 95%CI 1.35-1.78), diabetes (HR 1.35, 95%CI 1.13-1.62), CBVDs (HR 1.70, 95%CI 1.43-2.02), chronic kidney diseases (HR 2.09, 95%CI 1.47-2.98), and at least two comorbidities (HR 1.84, 95%CI 1.55-2.18) had significant increased risks of death. And the association between diabetes and the risk of death from COVID-19 was prominent in women (HR 1.69, 95%CI 1.27-2.25) than in men (HR 1.16, 95%CI 0.91-1.46) ( P for interaction = 0.036). Conclusion: Among laboratory-confirmed cases of COVID-19 in Hubei province, China, patients with hypertension, diabetes, CBVDs, chronic kidney diseases were significantly associated with increased risk of death. The association between diabetes and the risk of death tended to be stronger in women than in men. Clinicians should increase their awareness of the increased risk of death in COVID-19 patients with comorbidities.

Tuberculosis (TB) has a very high mortality rate worldwide. However, only a few studies have examined the associations between short-term exposure to air pollution and TB incidence. Our objectives were to estimate associations between short-term exposure to air pollutants and TB incidence in Wuhan city, China, during the 2015–2016 period. We applied a generalized additive model to access the short-term association of air pollution with TB. Daily exposure to each air pollutant in Wuhan was determined using ordinary kriging. The air pollutants included in the analysis were particulate matter (PM) with an aerodynamic diameter less than or equal to 2.5 micrometers (PM_2.5), PM with an aerodynamic diameter less than or equal to 10 micrometers (PM₁₀), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), carbon monoxide (CO), and ground-level ozone (O₃). Daily incident cases of TB were obtained from the Hubei Provincial Center for Disease Control and Prevention (Hubei CDC). Both single- and multiple-pollutant models were used to examine the associations between air pollution and TB. Seasonal variation was assessed by splitting the all-year data into warm (May–October) and cold (November–April) seasons. In the single-pollutant model, for a 10 μg/m³ increase in PM_2.5, PM₁₀, and O₃ at lag 7, the associated TB risk increased by 17.03% (95% CI: 6.39, 28.74), 11.08% (95% CI: 6.39, 28.74), and 16.15% (95% CI: 1.88, 32.42), respectively. In the multi-pollutant model, the effect of PM_2.5 on TB remained statistically significant, while the effects of other pollutants were attenuated. The seasonal analysis showed that there was not much difference regarding the impact of air pollution on TB between the warm season and the cold season. Our study reveals that the mechanism linking air pollution and TB is still complex. Further research is warranted to explore the interaction of air pollution and TB.

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.

We examined the associations of daily mean concentrations of ambient air pollutants (particulate matter (PM₁₀), sulfur dioxide (SO₂), nitric oxide (NO₂)) and daily cardiovascular diseases (CVD) mortality in Wuhan, China using a case-crossover design to analyze four years of data (2006–2009) collected from the Hubei Provincial Center for Disease Control and Prevention and the Wuhan Environmental Protection Bureau. From 2006 to 2009, daily average concentrations of PM₁₀, SO₂ and NO₂ were 115.60 µg/m³, 53.21 µg/m³ and 53.08 µg/m³, respectively. After adjusting for temperature and relative humidity, a 10 µg/m³ increase in SO₂ and NO₂ over a 24-h period was associated with CVD mortality relative risk (R.R.) of 1.010 (95% CI: 1.000, 1.020) for SO₂ and 1.019 (95% CI: 1.005, 1.033) for NO₂, but there was no significant association between increases in PM₁₀ and mortality. Subgroup analysis on by gender showed a significant association of 1.026 (95% CI: 1.007, 1.045) between NO₂ and CVD among males, while no significant statistical effect was shown among females. Subgroup analysis by age showed that for those older than 65 years, every 10 µg/m³ increase in NO₂ was associated with a 1.6% (95% CI: 0.1%, 3.1%) increase in CVD mortality. Subgroup analysis on different types of CVD showed that every 10 µg/m³ increase in PM₁₀ and SO₂ were significantly associated with an approximately 1.012 (95% CI: 1.002, 1.022) and 1.021 (95% CI: 1.002, 1.040) increase, respectively, in ischemic heart disease (ICH) mortality. In conclusion, exposure to NO₂ is significantly associated with CVD mortality. Larger, multi-center studies in Chinese cities are being currently conducted to validate these findings.