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BackgroundThe novel coronavirus disease 2019 (COVID-19) has infected 1.9% of the world population by May 2, 2021. Since most previous studies that examined risk factors for mortality and severity were based on hospitalized individuals, population-based cohort studies are called for to provide evidence that can be extrapolated to the general population. Therefore, we aimed to examine the associations of comorbidities with mortality and disease severity in individuals with COVID-19 diagnosed in 2020 in Ontario, Canada.Methods and findingsWe conducted a retrospective cohort study of all individuals with COVID-19 in Ontario, Canada diagnosed between January 15 and December 31, 2020. Cases were linked to health administrative databases maintained in the ICES which covers all residents in Ontario. The primary outcome is all-cause 30-day mortality after the first COVID-19 diagnosis, and the secondary outcome is a composite severity index containing death and hospitalization. To examine the risk factors for the outcomes, we employed Cox proportional hazards regression models and logistic regression models to adjust for demographic, socio-economic variables and comorbidities. Results were also stratified by age groups. A total of 167,500 individuals were diagnosed of COVID-19 in 2020 and included in the study. About half (43.8%, n = 73,378) had at least one comorbidity. The median follow-up period were 30 days. The most common comorbidities were hypertension (24%, n = 40,154), asthma (16%, n = 26,814), and diabetes (14.7%, n = 24,662). Individuals with comorbidity had higher risk of mortality compared to those without (HR = 2.80, 95%CI 2.35–3.34; pConclusionWe found that solid organ transplant, dementia, chronic kidney disease, severe mental illness, CVD, hypertension, COPD, cancer, diabetes, rheumatoid arthritis, HIV, and asthma were associated with mortality or severity. Our study highlights that the number of comorbidities was a strong risk factor for deaths and severe outcomes among younger individuals with COVID-19. Our findings suggest that in addition of prioritizing by age, vaccination priority groups should also include younger population with multiple comorbidities.

Ambient air pollution is the leading environmental risk factor for disease globally. Air pollutants can increase the risk of some respiratory infections, but their effects on tuberculosis (TB) are unclear. In this systematic literature review, we aimed to assess epidemiological studies on the association between outdoor air pollutants and TB incidence, hospital admissions and death (collectively referred to here as ‘TB outcomes’). We sought to consolidate available evidence on this topic and propose recommendations for future studies. Following PRISMA guidelines, we searched PubMed, Web of Science, Google Scholar, and Scopus with no restrictions imposed on year of publication. A total of 11 epidemiological studies, performed in Asia, Europe and North America, met our inclusion criteria (combined sample size: 215,337 people). We extracted key study characteristics from each eligible publication, including design, exposure assessment, analytical approaches and effect estimates. The studies were assessed for overall quality and risk of bias using standard criteria. The pollutant most frequently associated with statistically significant effects on TB outcomes was fine particulate matter ( The existing epidemiological evidence is limited and shows mixed results. However, it is plausible that exposure to air pollutants, particularly PM2.5, may suppress important immune defence mechanisms, increasing an individual's susceptibility to development of active TB and TB-related mortality. Considering the small number of studies relative to the demonstrably large global health burdens of air pollution and TB, further research is required to corroborate the findings in the current literature. Based on a critical assessment of existing evidence, we conclude with methodological suggestions for future studies.

Objectives: Healthcare workers (HCWs) are at high risk of latent tuberculosis infection (LTBI), and the baseline prevalence of LTBI among frontline TB HCWs in southeastern China remains unknown. The aim of this study was to assess the prevalence of LTBI among TB HCWs and to analyze factors associated with LTBI at both the individual and institutional level. Methods: Based on a cross-sectional study design, 31 out of 89 TB-designated hospitals in Zhejiang Province of China were selected. Information on TB infection control measures was collected through field visits to each of the selected hospitals. All TB HCWs from the selected hospitals were recruited to answer a questionnaire and to undergo LTBI testing by TB interferon gamma release assay. Univariate analyses and a generalized linear mixed model were applied to analyze factors associated with LTBI at both the individual and hospital level. Results: A total of 487 TB HCWs were recruited at the 31 TB-designated hospitals; 33.9% of them tested positive for LTBI. At the institutional level, a low TB epidemic level, regular infection control training for HCWs, and regular maintenance of ultraviolet disinfection equipment were found to be significantly associated with a lower LTBI rate among HCWs. At the individual level, alcohol use, a greater number of years working on TB, and a longer weekly duration of contact with TB patients were identified as associated factors for LTBI among HCWs. Conclusions: The LTBI rate among frontline TB HCWs was found to be high in southeastern China. Factors at the institutional and individual level could both affect the prevalence of LTBI among HCWs. Keywords: Tuberculosis, Latent tuberculosis infection, Healthcare workers

Setting Shanghai is a mega city where 39% of the population comprises internal migrants. Objective To examine the different roles played by migrants and permanent residents in the transmission of multidrug-resistant tuberculosis (MDR-TB). Design We conducted a population-based cohort study to assess MDR-TB transmission in Shanghai between 1 January 2009 and 31 December 2012 using genotyping and geospatial analyses. Results A total of 367 MDR-TB cases formed the study cohort. Significant differences between MDR-TB cases who were internal migrants and those who were permanent residents were found with regard to age, sex, region, genetic characteristics and treatment outcomes. Permanent residents had a higher transmission rate than internal migrants (OR 3.36, 95%CI 1.86-6.09). Permanent residents and genotypic clustering cases had similar clusters in central downtown and some parts of suburban areas. Most of the clusters of internal migrants were found in rural areas bordering suburban areas. Clusters of genotypic non-clustering cases showed patterns that closely matched those of internal migrants, suggesting acquired drug resistance in migrants. Conclusion In Shanghai, permanent residents were significantly associated with recent transmission of MDR-TB in central downtown areas. Clustered cases of internal migrants in rural areas were most likely to have contracted MDR-TB through acquired resistance.

Background While temperature changes have been confirmed as one of the contributory factors affecting human health, the association between high-frequency temperature variability (HFTV, i.e., temperature variation at short time scales such as 1, 2, and 5 days) and the hospitalization of chronic obstructive pulmonary disease (COPD) was rarely reported. Objectives To evaluate the associations between high-frequency temperature variabilities (i.e., at 1, 2, and 5-day scales) and daily COPD hospitalization. Methods We collected daily records of COPD hospitalization and meteorological variables from 2013 to 2017 in 21 cities of Guangdong Province, South China. A quasi-Poisson regression with a distributed lag nonlinear model was first employed to quantify the effects of two HFTV measures, i.e., the day-to-day (DTD) temperature change and the intraday-interday temperature variability (IITV), on COPD morbidity for each city. Second, we used multivariate meta-analysis to pool the city-specific estimates, and stratified analyses were performed by age and sex to identify vulnerable groups. Then, the meta-regression with city-level characteristics was employed to detect the potential sources of the differences among 21 cities. Results A monotonic increasing curve of the overall exposure-response association was observed, suggesting that positive HFTV (i.e., increased DTD and IITV) will significantly increase the risk of COPD admission. Negative DTD was associated with reduced COPD morbidity while positive DTD elevated the COPD risk. An interquartile range (IQR) increase in DTD was associated with a 24% (95% CI: 12–38%) increase in COPD admissions. An IQR increase in IITV0-1 was associated with 18% (95% CI: 7–27%) increase in COPD admissions. Males and people aged 0–64 years appeared to be more vulnerable to the DTD effect than others. Potential sources of the disparity among different cities include urbanization level, sex structure, industry structure, gross domestic product (GDP), health care services, and air quality. Conclusions The increases of DTD and IITV have significant adverse impacts on COPD hospitalization. As climate change intensifies, precautions need to be taken to mitigate the impacts of high-frequency temperature changes.

Evidence for the association between fine particulate matter (PM2305 patients reported in Zhejiang and Ningxia were followed up from MDR-TB diagnosis until death, loss to follow-up or end of the study (31 December 2019), with an average follow-up of 1724 days per patient. 16-day averages of contemporaneous Normalised Difference Vegetation Index (NDVI) in the 500 m buffer of patient's residence, annual average PMHRs of 1.702 (95% CI 1.680 to 1.725) and 1.169 (1.162 to 1.175) were observed for PMIndividuals with MDR-TB could benefit from greenness by having attenuated associations between PM

Background Living closer to greenness were thought to benefit various health outcomes. We aimed to assess the association between residential greenness and mortality among patients undergoing multidrug resistant tuberculosis (MDR-TB) treatment. Methods We enrolled all local MDR-TB patients reported in Zhejiang, China from 2009 to 2017 and followed them throughout the treatment. We calculated the contemporaneous normalized difference vegetation index (NDVI) in the 250 and 500 m radius around patient’s residence. Cox proportional hazards regression models with time-varying NDVI were used to assess the impact of greenness exposure on all-cause mortality during MDR-TB treatment, adjusting for potential individual and contextual covariates. Results We ascertained 1,621 active MDR-TB cases, which contributed 3036 person-years at risk with an average follow-up of 684 days (s.d. 149 days) per patient. Among them, there were 163 deaths during follow-up, representing a crude mortality rate of 537 deaths per 10,000 person-years. Patients exposed to the second quintile (Q2) of greenness within the 500 m buffer had around 64% reduced mortality risk over the lowest quintile of greenness with hazard ratio (HR) = 0.364 (95% CI: 0.109–1.22). In lower nighttime light (NTL) areas, the hazard ratios (HR) per quintile increase in NDVI within the 500 m buffer were Q2: 0.35 (95% CI: 0.10–1.18), Q3: 0.24 (95% CI: 0.09–0.66), Q4: 0.26 (95% CI: 0.10–0.69), and Q5: 0.26 (95% CI: 0.10–0.71) relevant to the lowest quintile Q1, with a trend of p-value ≤0.01. Patients who were female, younger ( Conclusion Increasing greenness exposure along with medical treatment reduces all-cause mortality among patients living in lower NTL areas.

ObjectivesPrevious studies on geographical disparities in healthcare access have been limited by not accounting for the healthcare provider’s capacity, a key determinant of supply and demand relationships.DesignThis study proposed a spatial coverage modelling approach to evaluate disparities in hospital care access using Canadian Institute for Health Information data in 2007.SettingThis study focusses on accessibility of inpatient and emergency cares at both levels of individual hospital and the administrative regions of Local Health Integration Network (LHIN) levels.MeasuresWe integrated a set of traffic and geographical data to precisely estimate travel time as a measure of the level of accessibility to the nearest hospital by three scenarios: walking, driving and a combination of the both. We estimated population coverage rates, using hospital capacities and population in the catchments, as a measure of the level of the healthcare availability. Hospital capacities were calculated based on numbers of medical staff and beds, occupation rates and annual working hours of healthcare providers.ResultsWe observed significant disparities in hospital capacity, travel time and population coverage rate across the LHINs. This study included 25 teaching and 148 community hospitals. The teaching hospitals had stronger capacities with 489 209 inpatient and 130 773 emergency patients served in the year, while the population served in community hospitals were 2.64 times higher. Compared with north Ontario, more locations in the south could reach to hospitals within 30 min irrespective of the travel mode. Additionally, Northern Ontario has higher population coverage rates, for example, with 42.6~46.9% for inpatient and 15.7~44% for emergency cares, compared with 2.4~34.7% and 0.35~14.6% in Southern Ontario, within a 30 min catchment by driving.ConclusionCreating a comprehensive, flexible and integrated healthcare system should be considered as an effective approach to improve equity in access to care.

Background Studies differentiating the cardiorespiratory morbidity effects of PM2.5, PM10, and PM2.5∼10 (i.e. coarse PM or PMc) are still limited and inconsistent. Objective To estimate the acute, cumulative, and harvesting effects of exposure to the three size-specific PM on cardiorespiratory morbidity, and their concentration-response relations. Methods A total of 6,727,439 emergency department (ED) visits were collected from 16 public teaching hospitals in Guangzhou, from January 1st 2012 to December 31st 2015, among which over 2.1 million were asthma, COPD, pneumonia, respiratory tract infection (RTI), hypertension, stroke, and coronary heart disease (CHD). Distributed lag non-linear models (DLNM) was used to estimate the associations between the three size-specific PM and ED visits for the cardiovascular diseases. Long-term trends, seasonality, influenza epidemics, meteorological factors, and other gas pollutants, including SO2, NO2, and O3, were adjusted. We stratified the analyses by gender and age. Results Elevated PM2.5 and PM10 were significantly associated with increased ED visits for pneumonia, RTI, and CHD at both lag0 and lag0-3. A 10 μg/m3 increment of PMc (at lag0-14) was estimated to increase ED visits for pneumonia by 6.32% (95% CI, 4.19, 8.49) and for RTI by 4.72% (95% CI, 3.81, 5.63), respectively. PMc showed stronger cumulative effects on asthma in children than elderly. We observed significant harvesting effects (i.e. morbidity displacements) of the three size-specific PM on respiratory but very little on cardiovascular ED visits. The concentration-response curves suggested non-linear relations between exposures to the three different sizes of PM and respiratory morbidity. Conclusions Overall, the three size-specific PM demonstrated distinct acute and cumulative effects on the cardiorespiratory diseases. PM2.5 and PMc would have significant effects on pneumonia and RTI. Strategies should be considered to further reduce levels of ambient PM2.5 and PMc.

Inapparent avian exposure was suspected for the sporadic infection of avian influenza A(H7N9) occurring in China. This type of exposure is usually unnoticed and difficult to model and measure. Infected poultry with avian influenza H7N9 virus typically remains asymptomatic, which may facilitate infection through inapparent poultry/bird exposure, especially in a country with widespread practice of backyard poultry. The present study proposed a novel approach that integrated ecological and case-control methods to quantify the risk of inapparent avian exposure on human H7N9 infection. Significant associations of the infection with chicken and goose densities, but not with duck density, were identified after adjusting for spatial clustering effects of the H7N9 cases across multiple geographic scales of neighborhood, community, district and city levels. These exposure risks varied geographically in association with proximity to rivers and lakes that were also proxies for inapparent exposure to avian-related environment. Males, elderly people, and farmers were high-risk subgroups for the virus infection. These findings enable health officials to target educational programs and awareness training in specific locations to reduce the risks of inapparent exposure.

Background Recent biochemical studies suggest that exogenous sulfur dioxide (SO2) at low concentrations may have been beneficial in inhibiting mycobacteria tuberculosis (TB) growth. However, there is a dearth of population-based studies. Objectives To examine the association of ambient SO2 levels and initial TB outpatient visits. Methods In Ningbo, China, we collected all daily initial outpatient visits for TB and routinely air pollution monitoring data between January 2009 and December 2013. A time-series study was conducted by using generalized additive regression (GAM) with log-linear Poisson models to estimate the associations between daily initial TB outpatient visits and daily average concentration of SO2. Other traffic-related co-pollutants were adjusted. Sensitivity analyses were conducted to examine the relationship when 1% extreme SO2 concentrations excluded or if related to the early onsets of TB symptoms. Results SO2 concentrations in Ningbo were low with a daily average of 25 μg/m3 (i.e. 0.0089 ppm). Negative associations were identified between ambient SO2 concentrations and daily initial TB outpatient visits. A 10 μg/m3 increase in SO2 at lag3 and lag0-3 days were associated with −2.0% (95%CI, −3.2, −0.8) and −4.6% (95%CI, −6.8, −2.4) changes, respectively, in initial TB outpatient visits according to single-pollutant models. The negative association became stronger when nitrogen dioxide (NO2) or particulate matter with aerodynamic diameter less than 10 μm (PM10) was adjusted in two-pollutant models. This association was higher in males vs. females and in middle-aged adults vs. the elderly. We found a stronger negative association between SO2 concentration and the initial symptom occurrence. Conclusion Short-term exposure to ambient SO2 was associated with reduced risk of initial TB outpatient visits, suggesting acute protective effects of low-level ambient SO2 exposure on bacteria-induced pulmonary infections.

Recent experimental and clinical studies suggest that exogenous carbon monoxide (CO) at lower concentrations may have beneficial effects under certain circumstances, whereas population-based epidemiologic studies of environmentally relevant CO exposure generated mixed findings.To examine the acute effects of ambient CO on respiratory tract infection (RTI) hospitalizations.A time series study was conducted. Daily emergency hospital admission and air pollution data in Hong Kong were collected from January 2001 to December 2007. Log-linear Poisson models were used to estimate the associations between daily hospital admissions for RTI and daily average concentrations of CO across three background air monitoring stations and three roadside stations, respectively, controlling for other traffic-related copollutants.CO concentrations were low during the study period with a daily average of 0.6 ppm in background stations and 1.0 ppm in roadside stations. Negative associations were found between ambient CO concentrations and daily hospital admissions for RTI. One ppm increase in background CO at lag 0-2 days was associated with -5.7% (95% confidence interval, -9.2 to -2.1) change in RTI admissions from the whole population according to single-pollutant model; the negative association became stronger when nitrogen dioxide or particulate matter with aerodynamic diameter less than 10 μm was adjusted for in two-pollutant models. The negative association seemed to be stronger in the adults than in the children and elderly.Short-term exposure to ambient CO was associated with decreased risk of hospital admissions for RTI, suggesting some acute protective effects of low ambient CO exposure on respiratory infection.

Highly pathogenic avian influenza (HPAI) H5N1, a disease associated with high rates of mortality in infected human populations, poses a serious threat to public health in many parts of the world. This article reports findings from a study aimed at improving our understanding of the spatial pattern of the highly pathogenic avian influenza, H5N1, risk in East-Southeast Asia where the disease is both persistent and devastating. Though many disciplines have made important contributions to our understanding of H5N1, it remains a challenge to integrate knowledge from different disciplines. This study applies genetic analysis that identifies the evolution of the H5N1 virus in space and time, epidemiological analysis that determines socio-ecological factors associated with H5N1 occurrence, and statistical analysis that identifies outbreak clusters, and then applies a methodology to formally integrate the findings of the three sets of methodologies. The present study is novel in two respects. First it makes the initiative attempt to use genetic sequences and space-time data to create a space-time phylogenetic tree to estimate and map the virus' ability to spread. Second, by integrating the results we are able to generate insights into the space-time occurrence and spread of H5N1 that we believe have a higher level of corroboration than is possible when analysis is based on only one methodology. Our research identifies links between the occurrence of H5N1 by area and a set of socio-ecological factors including altitude, population density, poultry density, and the shortest path distances to inland water, coastlines, migrating routes, railways, and roads. This study seeks to lay a solid foundation for the interdisciplinary study of this and other influenza outbreaks. It will provide substantive information for containing H5N1 outbreaks.