County-Level Contextual Characteristics and Disparities in Life Expectancy

Modeling the competitive transmission of the Omicron strain and Delta strain of COVID-19

Since November 2021, there have been cases of COVID-19's Omicron strain spreading in competition with Delta strains in many parts of the world. To explore how these two strains developed in this competitive spread, a new compartmentalized model was established. First, we analyzed the fundamental properties of the model, obtained the expression of the basic reproduction number, proved the local and global asymptotic stability of the disease-free equilibrium. Then by means of the cubic spline interpolation method, we obtained the data of new Omicron and Delta cases in the United States of new cases starting from December 8, 2021, to February 12, 2022. Using the weighted nonlinear least squares estimation method, we fitted six time series (cumulative confirmed cases, cumulative deaths, new cases, new deaths, new Omicron cases, and new Delta cases), got estimates of the unknown parameters, and obtained an approximation of the basic reproduction number in the United States during this time period as R 0 ≈ 1.5165 . Finally, each control strategy was evaluated by cost-effectiveness analysis to obtain the optimal control strategy under different perspectives. The results not only show the competitive transmission characteristics of the new strain and existing strain, but also provide scientific suggestions for effectively controlling the spread of these strains.

Life Expectancy and Built Environments in the U.S.: A Multilevel Analysis

INTRODUCTION

The purpose of this study is to examine the associations between built environments and life expectancy across a gradient of urbanicity in the U.S.

METHODS

Census tract‒level estimates of life expectancy between 2010 and 2015, except for Maine and Wisconsin, from the U.S. Small-Area Life Expectancy Estimates Project were analyzed in 2022. Tract-level measures of the built environment included: food, alcohol, and tobacco outlets; walkability; park and green space; housing characteristics; and air pollution. Multilevel linear models for each of the 4 urbanicity types were fitted to evaluate the associations, adjusting for population and social characteristics.

RESULTS

Old housing (built before 1979) and air pollution were important built environment predictors of life expectancy disparities across all gradients of urbanicity. Convenience stores were negatively associated with life expectancy in all urbanicity types. Healthy food options were a positive predictor of life expectancy only in high-density urban areas. Park accessibility was associated with increased life expectancy in all areas, except rural areas. Green space in neighborhoods was positively associated with life expectancy in urban areas but showed an opposite association in rural areas.

CONCLUSIONS

After adjusting for key social characteristics, several built environment characteristics were salient risk factors for decreased life expectancy in the U.S., with some measures showing differential effects by urbanicity. Planning and policy efforts should be tailored to local contexts.

Relationships between neighborhood disadvantage and cardiovascular findings at autopsy in subjects with sudden death

BACKGROUND

Neighborhood disadvantage is associated with a higher risk of sudden cardiac death. However, autopsy findings have never been investigated in this context. Here, we sought to explore associations between neighborhood disadvantage and cardiovascular findings at autopsy in cases of sudden death in the State of Maryland.

METHODS

State of Maryland investigation reports from 2,278 subjects within the CVPath Sudden Death Registry were screened for street addresses and 9-digit zip codes. Area deprivation index (ADI), used as metric for neighborhood disadvantage, was available for 1,464 subjects; 650 of whom self-identified as Black and 814 as White. The primary study outcome measurements were causes of death and gross and histopathologic findings of the heart.

RESULTS

Subjects from most disadvantaged neighborhoods (i.e., ADI ≥ 8; n = 607) died at younger age compared with subjects from less disadvantaged neighborhoods (i.e., ADI ≤ 7; n = 857; 46.07 ± 14.10 vs 47.78 ± 13.86 years; P = 0.02) and were more likely Black or women. They were less likely to die from cardiac causes of death (61.8% vs 67.7%; P = 0.02) and had less severe atherosclerotic plaque features, including plaque burden, calcification, intraplaque hemorrhage, and thin-cap fibroatheromas. In addition, subjects from most disadvantaged neighborhoods had lower frequencies of plaque rupture (18.8% vs 25.1%, P = 0.004). However, these associations were omitted after adjustment for traditional risk factors and race.

CONCLUSION

Neighborhood disadvantage did not associate with cause of death or coronary histopathology after adjustment for cardiovascular risk factors and race, implying that social determinants of health other than neighborhood disadvantage play a more prominent role in sudden cardiac death.

Ambient particulate matter pollution of different sizes associated with recurrent stroke hospitalization in China: A cohort study of 1.07 million stroke patients

BACKGROUND

To estimate the associations between ambient particulate matter (PM) pollution of different sizes (PM₁, PM_2.5, and PM₁₀) and risk of rehospitalization among stroke patients, as well as the attributable burden in China.

METHODS

We built a cohort of 1,066,752 participants with an index stroke hospitalization in Sichuan, China from 2017 to 2019. Seven-day and annual average exposures to PM pollution prior to the date of the index hospitalization were linked with residential address using a bilinear interpolation approach. Cox proportional hazard models were constructed to assess the association between ambient PM and the risk of rehospitalization. The burden of stroke rehospitalization was estimated using a counterfactual approach.

RESULTS

245,457 (23.0 %) participants experienced rehospitalization during a mean of 1.15 years (SD: 0.90 years) of follow-up. Seven-day average concentrations of PM were associated with increased risk of rehospitalization: the hazard ratios (HRs) per 10 μg/m³ were 1.034 (95 % confidence interval [CI]: 1.029-1.038) for PM₁, 1.033 (1.031-1.036) for PM_2.5, and 1.030 (1.028-1.031) for PM₁₀; the hazard ratios were larger for annual average concentrations: 1.082 (1.074-1.090) for PM₁, 1.109 (1.104-1.114) for PM_2.5, and 1.103 (1.099-1.106) for PM₁₀. The associations were stronger in participants who were female, of minority ethnicity (non-Han Chinese), who suffered from an ischemic stroke, and those admitted under normal conditions. Population attributable fractions for stroke rehospitalization ranged from 4.66 % (95 % CI: 1.69 % to 7.63 %) for the 7-day average of PM₁ to 17.05 % (14.27 % to 19.83 %) for the annual average of PM₁₀; the reducible average cost of rehospitalization per participant attributable to PM ranged from 492.09 (178.19 to 806) RMB for the 7-day average of PM₁ to 1801.65 (1507.89 to 2095.41) RMB for the annual average of PM₁₀.

CONCLUSIONS

Ambient PM pollution may increase the risk of rehospitalization in stroke patients and is responsible for a significant burden of stroke rehospitalization.

Association of Ambient Particulate Matter Pollution of Different Sizes With In-Hospital Case Fatality Among Stroke Patients in China

BACKGROUND AND OBJECTIVES

To characterize the association of ambient particulate matter (PM) pollution of different sizes (PM ≤1 µm in aerodynamic diameter [PM1], PM2.5, and PM10) with in-hospital case fatality among patients with stroke in China.

METHODS

We collected hospitalizations due to stroke in 4 provinces in China from 2013 to 2019. Seven-day and annual averages of PM prior to hospitalization were estimated using bilinear interpolation and residential addresses. Associations with in-hospital case fatality were estimated using random-effects logistic regression models. Potential reducible fraction and the number of fatalities attributed to PM were estimated using a counterfactual approach.

RESULTS

Among 3,109,634 stroke hospitalizations (mean age 67.23 years [SD 12.22]; 1,765,644 [56.78%] male), we identified 32,140 in-hospital stroke fatalities (case fatality rate 1.03%). Each 10 µg/m3 increase in 7-day average (short-term) exposure to PM was associated with increased in-hospital case fatality: odds ratios (ORs) were 1.058 (95% CI 1.047-1.068) for PM1, 1.037 (95% CI 1.031-1.043) for PM2.5, and 1.025 (95% CI 1.021-1.029) for PM10. Similar but larger ORs were observed for annual averages (long-term): 1.240 (95% CI 1.217-1.265) for PM1, 1.105 (95% CI 1.094-1.116) for PM2.5, and 1.090 (95% CI 1.082-1.099) for PM10. In counterfactual analyses, PM10 was associated with the largest potential reducible fraction in in-hospital case fatality (10% [95% CI 8.3-11.7] for short-term exposure and 21.1% [19.1%-23%] for long-term exposure), followed by PM1 and PM2.5.

DISCUSSION

PM pollution is a risk factor for in-hospital stroke-related deaths. Strategies that target reducing PM pollution may improve the health outcomes of patients with stroke.

Risks and burdens of incident diabetes in long COVID: a cohort study

BACKGROUND

There is growing evidence suggesting that beyond the acute phase of SARS-CoV-2 infection, people with COVID-19 could experience a wide range of post-acute sequelae, including diabetes. However, the risks and burdens of diabetes in the post-acute phase of the disease have not yet been comprehensively characterised. To address this knowledge gap, we aimed to examine the post-acute risk and burden of incident diabetes in people who survived the first 30 days of SARS-CoV-2 infection.

METHODS

In this cohort study, we used the national databases of the US Department of Veterans Affairs to build a cohort of 181 280 participants who had a positive COVID-19 test between March 1, 2020, and Sept 30, 2021, and survived the first 30 days of COVID-19; a contemporary control (n=4 118 441) that enrolled participants between March 1, 2020, and Sept 30, 2021; and a historical control (n=4 286 911) that enrolled participants between March 1, 2018, and Sept 30, 2019. Both control groups had no evidence of SARS-CoV-2 infection. Participants in all three comparison groups were free of diabetes before cohort entry and were followed up for a median of 352 days (IQR 245-406). We used inverse probability weighted survival analyses, including predefined and algorithmically selected high dimensional variables, to estimate post-acute COVID-19 risks of incident diabetes, antihyperglycaemic use, and a composite of the two outcomes. We reported two measures of risk: hazard ratio (HR) and burden per 1000 people at 12 months.

FINDINGS

In the post-acute phase of the disease, compared with the contemporary control group, people with COVID-19 exhibited an increased risk (HR 1·40, 95% CI 1·36-1·44) and excess burden (13·46, 95% CI 12·11-14·84, per 1000 people at 12 months) of incident diabetes; and an increased risk (1·85, 1·78-1·92) and excess burden (12·35, 11·36-13·38) of incident antihyperglycaemic use. Additionally, analyses to estimate the risk of a composite endpoint of incident diabetes or antihyperglycaemic use yielded a HR of 1·46 (95% CI 1·43-1·50) and an excess burden of 18·03 (95% CI 16·59-19·51) per 1000 people at 12 months. Risks and burdens of post-acute outcomes increased in a graded fashion according to the severity of the acute phase of COVID-19 (whether patients were non-hospitalised, hospitalised, or admitted to intensive care). All the results were consistent in analyses using the historical control as the reference category.

INTERPRETATION

In the post-acute phase, we report increased risks and 12-month burdens of incident diabetes and antihyperglycaemic use in people with COVID-19 compared with a contemporary control group of people who were enrolled during the same period and had not contracted SARS-CoV-2, and a historical control group from a pre-pandemic era. Post-acute COVID-19 care should involve identification and management of diabetes.

FUNDING

US Department of Veterans Affairs and the American Society of Nephrology.

Risks of mental health outcomes in people with covid-19: cohort study

OBJECTIVE

To estimate the risks of incident mental health disorders in survivors of the acute phase of covid-19.

DESIGN

Cohort study.

SETTING

US Department of Veterans Affairs.

PARTICIPANTS

Cohort comprising 153 848 people who survived the first 30 days of SARS-CoV-2 infection, and two control groups: a contemporary group (n=5 637 840) with no evidence of SARS-CoV-2, and a historical control group (n=5 859 251) that predated the covid-19 pandemic.

MAIN OUTCOMES MEASURES

Risks of prespecified incident mental health outcomes, calculated as hazard ratio and absolute risk difference per 1000 people at one year, with corresponding 95% confidence intervals. Predefined covariates and algorithmically selected high dimensional covariates were used to balance the covid-19 and control groups through inverse weighting.

RESULTS

The covid-19 group showed an increased risk of incident anxiety disorders (hazard ratio 1.35 (95% confidence interval 1.30 to 1.39); risk difference 11.06 (95% confidence interval 9.64 to 12.53) per 1000 people at one year), depressive disorders (1.39 (1.34 to 1.43); 15.12 (13.38 to 16.91) per 1000 people at one year), stress and adjustment disorders (1.38 (1.34 to 1.43); 13.29 (11.71 to 14.92) per 1000 people at one year), and use of antidepressants (1.55 (1.50 to 1.60); 21.59 (19.63 to 23.60) per 1000 people at one year) and benzodiazepines (1.65 (1.58 to 1.72); 10.46 (9.37 to 11.61) per 1000 people at one year). The risk of incident opioid prescriptions also increased (1.76 (1.71 to 1.81); 35.90 (33.61 to 38.25) per 1000 people at one year), opioid use disorders (1.34 (1.21 to 1.48); 0.96 (0.59 to 1.37) per 1000 people at one year), and other (non-opioid) substance use disorders (1.20 (1.15 to 1.26); 4.34 (3.22 to 5.51) per 1000 people at one year). The covid-19 group also showed an increased risk of incident neurocognitive decline (1.80 (1.72 to 1.89); 10.75 (9.65 to 11.91) per 1000 people at one year) and sleep disorders (1.41 (1.38 to 1.45); 23.80 (21.65 to 26.00) per 1000 people at one year). The risk of any incident mental health diagnosis or prescription was increased (1.60 (1.55 to 1.66); 64.38 (58.90 to 70.01) per 1000 people at one year). The risks of examined outcomes were increased even among people who were not admitted to hospital and were highest among those who were admitted to hospital during the acute phase of covid-19. Results were consistent with those in the historical control group. The risk of incident mental health disorders was consistently higher in the covid-19 group in comparisons of people with covid-19 not admitted to hospital versus those not admitted to hospital for seasonal influenza, admitted to hospital with covid-19 versus admitted to hospital with seasonal influenza, and admitted to hospital with covid-19 versus admitted to hospital for any other cause.

CONCLUSIONS

The findings suggest that people who survive the acute phase of covid-19 are at increased risk of an array of incident mental health disorders. Tackling mental health disorders among survivors of covid-19 should be a priority.

Kidney Outcomes in Long COVID

BACKGROUND

COVID-19 is associated with increased risk of post-acute sequelae involving pulmonary and extrapulmonary organ systems-referred to as long COVID. However, a detailed assessment of kidney outcomes in long COVID is not yet available.

METHODS

We built a cohort of 1,726,683 US Veterans identified from March 1, 2020 to March 15, 2021, including 89,216 patients who were 30-day survivors of COVID-19 and 1,637,467 non-infected controls. We examined risks of AKI, eGFR decline, ESKD, and major adverse kidney events (MAKE). MAKE was defined as eGFR decline ≥50%, ESKD, or all-cause mortality. We used inverse probability-weighted survival regression, adjusting for predefined demographic and health characteristics, and algorithmically selected high-dimensional covariates, including diagnoses, medications, and laboratory tests. Linear mixed models characterized intra-individual eGFR trajectory.

RESULTS

Beyond the acute illness, 30-day survivors of COVID-19 exhibited a higher risk of AKI (aHR, 1.94; 95% CI, 1.86 to 2.04), eGFR decline ≥30% (aHR, 1.25; 95% CI, 1.14 to 1.37), eGFR decline ≥40% (aHR, 1.44; 95% CI, 1.37 to 1.51), eGFR decline ≥50% (aHR, 1.62; 95% CI, 1.51 to 1.74), ESKD (aHR, 2.96; 95% CI, 2.49 to 3.51), and MAKE (aHR, 1.66; 95% CI, 1.58 to 1.74). Increase in risks of post-acute kidney outcomes was graded according to the severity of the acute infection (whether patients were non-hospitalized, hospitalized, or admitted to intensive care). Compared with non-infected controls, 30-day survivors of COVID-19 exhibited excess eGFR decline (95% CI) of -3.26 (-3.58 to -2.94), -5.20 (-6.24 to -4.16), and -7.69 (-8.27 to -7.12) ml/min per 1.73 m² per year, respectively, in non-hospitalized, hospitalized, and those admitted to intensive care during the acute phase of COVID-19 infection.

CONCLUSIONS

Patients who survived COVID-19 exhibited increased risk of kidney outcomes in the post-acute phase of the disease. Post-acute COVID-19 care should include attention to kidney disease.

Ambient fine particulate matter air pollution and the risk of hospitalization among COVID-19 positive individuals: Cohort study

BACKGROUND

Ecologic analyses suggest that living in areas with higher levels of ambient fine particulate matter air pollution (PM2.5) is associated with higher risk of adverse COVID-19 outcomes. Studies accounting for individual-level health characteristics are lacking.

METHODS

We leveraged the breadth and depth of the US Department of Veterans Affairs national healthcare databases and built a national cohort of 169,102 COVID-19 positive United States Veterans, enrolled between March 2, 2020 and January 31, 2021, and followed them through February 15, 2021. Annual average 2018 PM2.5 exposure, at an approximately 1 km2 resolution, was linked with residential street address at the year prior to COVID-19 positive test. COVID-19 hospitalization was defined as first hospital admission between 7 days prior to, and 15 days after, the first COVID-19 positive date. Adjusted Poisson regression assessed the association of PM2.5 with risk of hospitalization.

RESULTS

There were 25,422 (15.0%) hospitalizations; 5,448 (11.9%), 5,056 (13.0%), 7,159 (16.1%), and 7,759 (19.4%) were in the lowest to highest PM2.5 quartile, respectively. In models adjusted for State, demographic and behavioral factors, contextual characteristics, and characteristics of the pandemic a one interquartile range increase in PM2.5 (1.9 µg/m3) was associated with a 10% (95% CI: 8%-12%) increase in risk of hospitalization. The association of PM2.5 and risk of hospitalization among COVID-19 individuals was present in each wave of the pandemic. Models of non-linear exposure-response suggested increased risk at PM2.5 concentrations below the national standard 12 µg/m3. Formal effect modification analyses suggested higher risk of hospitalization associated with PM2.5 in Black people compared to White people (p = 0.045), and in those living in socioeconomically disadvantaged neighborhoods (p < 0.001).

CONCLUSIONS

Exposure to higher levels of PM2.5 was associated with increased risk of hospitalization among COVID-19 infected individuals. The risk was evident at PM2.5 levels below the regulatory standards. The analysis identified those of Black race and those living in disadvantaged neighborhoods as population groups that may be more susceptible to the untoward effect of PM2.5 on risk of hospitalization in the setting of COVID-19.

Temporal trends of COVID-19 mortality and hospitalisation rates: an observational cohort study from the US Department of Veterans Affairs

OBJECTIVES

To investigate the temporal trends of 30-day mortality and hospitalisation in US Veterans with COVID-19 and 30-day mortality in hospitalised veterans with COVID-19 and to decompose the contribution of changes in the underlying characteristics of affected populations to these temporal changes.

DESIGN

Observational cohort study.

SETTING

US Department of Veterans Affairs.

PARTICIPANTS

49 238 US veterans with a positive COVID-19 test between 20 March 2020 and 19 September 2020; and 9428 US veterans hospitalised with a positive COVID-19 test during the same period.

OUTCOME MEASURES

30-day mortality rate and hospitalisation rate.

RESULTS

Between 20 March 2020 and 19 September 2020 and in COVID-19 positive individuals, 30-day mortality rate dropped by 9.2% from 13.6% to 4.4%; hospitalisation rate dropped by 16.8% from 33.8% to 17.0%. In hospitalised COVID-19 individuals, 30-day mortality rate dropped by 12.7% from 23.5% to 10.8%. Among COVID-19 positive individuals, decomposition analyses suggested that changes in demographic, health and contextual characteristics, COVID-19 testing capacity, and hospital occupancy rates accounted for 40.2% and 33.3% of the decline in 30-day mortality and hospitalisation, respectively. Changes in the underlying characteristics of hospitalised COVID-19 individuals accounted for 29.9% of the decline in 30-day mortality.

CONCLUSION

Between March and September 2020, changes in demographic and health characteristics of people infected with COVID-19 contributed measurably to the substantial decline in 30-day mortality and hospitalisation.