Temporal variation of excess deaths from diabetes during the COVID-19 pandemic in the United States.

BACKGROUND: Although the COVID-19 pandemic has persisted for more than two years with the evident excess mortality from diabetes, few studies have investigated its temporal patterns. This study aims to estimate the excess deaths from diabetes in the United States (US) during the COVID-19 pandemic and evaluate the excess deaths by spatiotemporal pattern, age groups, sex, and race/ethnicity. METHODS: Diabetes as one of multiple causes of death or an underlying cause of death were both considered into analyses. The Poisson log-linear regression model was used to estimate weekly expected counts of deaths during the pandemic with adjustments for long-term trend and seasonality. Excess deaths were measured by the difference between observed and expected death counts, including weekly average excess deaths, excess death rate, and excess risk. We calculated the excess estimates by pandemic wave, US state, and demographic characteristic. RESULTS: From March 2020 to March 2022, deaths that diabetes as one of multiple causes of death and an underlying cause of death were about 47.6 % and 18.4 % higher than the expected. The excess deaths of diabetes had evident temporal patterns with two large percentage increases observed during March 2020, to June 2020, and June 2021 to November 2021. The regional heterogeneity and underlying age and racial/ethnic disparities of the excess deaths were also clearly observed. CONCLUSIONS: This study highlighted the increased risks of diabetes mortality, heterogeneous spatiotemporal patterns, and associated demographic disparities during the pandemic. Practical actions are warranted to monitor disease progression, and lessen health disparities in patients with diabetes during the COVID-19 pandemic.

Comparison of the prevalence of opioid use among U.S. adults with cardiac conditions before and during the COVID-19 pandemic.

Limited data are available on the prevalence of prescription opioid use among patients with cardiac conditions who were exposed to increased risks of cardiac events including myocardial failure and cardiac arrest. According to the U.S. National Health Interview Survey, we evaluated the prevalence of opioid use in patients with cardiac conditions who reported prescription opioid use in the past 12 months and 3 months in 2019 and 2020, respectively, and further estimated the prevalence of opioid use for acute pain or chronic pain. We also analyzed the stratified prevalence by demographical characteristics. Our results showed that there was no statistically significant change in the prevalence of opioid use in the past 12 months (26.5% in 2019 vs. 25.7% in 2020) or the past 3 months (66.6% in 2019 vs. 62.5% in 2020) before and during the COVID-19 pandemic. However, there was a significant decline in the prevalence of opioid use for acute pain, from 64.2% (95% confidence interval [CI] 57.6% to 70.3%) in 2019 to 49.6% (95% CI 40.1% to 59.0%) in 2020 (P = 0.012), particularly in the subgroups of men, non-Hispanic white people, adults with education below high school, those with an income-to-poverty ratio ranging from 1.0 to 1.9, and those covered with health insurance. Our findings suggest that monitoring opioid use in the era of living with COVID-19 is important, which will help inform healthcare providers to develop care strategies to reduce health loss for vulnerable individuals.

Excess deaths from Alzheimer's disease and Parkinson's disease during the COVID-19 pandemic in the USA.

BACKGROUND: COVID-19 pandemic has indirect impacts on patients with chronic medical conditions, which may increase mortality risks for various non-COVID-19 causes. This study updates excess death statistics for Alzheimer's disease (AD) and Parkinson's disease (PD) up to 2022 and evaluates their demographic and spatial disparities in the USA. METHODS: This is an ecological time-series analysis of AD and PD mortality in the USA from January 2018 to March 2022. Poisson log-linear regressions were utilised to fit the weekly death data. Excess deaths were calculated with the difference between the observed and expected deaths under a counterfactual scenario of pandemic absence. RESULTS: From March 2020 to March 2022, we observed 41,115 and 10,328 excess deaths for AD and PD, respectively. The largest percentage increases in excess AD and PD deaths were found in the initial pandemic wave. For people aged ≥85 years, excess mortalities of AD and PD (per million persons) were 3946.0 (95% confidence interval [CI]: 2954.3, 4892.3) and 624.3 (95% CI: 369.4, 862.5), which were about 23 and 9 times higher than those aged 55-84 years, respectively. Females had a three-time higher excess mortality of AD than males (182.6 vs. 67.7 per million persons). The non-Hispanic Black people experienced larger increases in AD or PD deaths (excess percentage: 31.8% for AD and 34.6% for PD) than the non-Hispanic White population (17.1% for AD and 14.7% for PD). CONCLUSION: Under the continuing threats of COVID-19, efforts should be made to optimise health care capacity for patients with AD and PD.

Towards a global One Health index: a potential assessment tool for One Health performance.

BACKGROUND: A One Health approach has been increasingly mainstreamed by the international community, as it provides for holistic thinking in recognizing the close links and inter-dependence of the health of humans, animals and the environment. However, the dearth of real-world evidence has hampered application of a One Health approach in shaping policies and practice. This study proposes the development of a potential evaluation tool for One Health performance, in order to contribute to the scientific measurement of One Health approach and the identification of gaps where One Health capacity building is most urgently needed. METHODS: We describe five steps towards a global One Health index (GOHI), including (i) framework formulation; (ii) indicator selection; (iii) database building; (iv) weight determination; and (v) GOHI scores calculation. A cell-like framework for GOHI is proposed, which comprises an external drivers index (EDI), an intrinsic drivers index (IDI) and a core drivers index (CDI). We construct the indicator scheme for GOHI based on this framework after multiple rounds of panel discussions with our expert advisory committee. A fuzzy analytical hierarchy process is adopted to determine the weights for each of the indicators. RESULTS: The weighted indicator scheme of GOHI comprises three first-level indicators, 13 second-level indicators, and 57 third-level indicators. According to the pilot analysis based on the data from more than 200 countries/territories the GOHI scores overall are far from ideal (the highest score of 65.0 out of a maximum score of 100), and we found considerable variations among different countries/territories (31.8-65.0). The results from the pilot analysis are consistent with the results from a literature review, which suggests that a GOHI as a potential tool for the assessment of One Health performance might be feasible. CONCLUSIONS: GOHI-subject to rigorous validation-would represent the world's first evaluation tool that constructs the conceptual framework from a holistic perspective of One Health. Future application of GOHI might promote a common understanding of a strong One Health approach and provide reference for promoting effective measures to strengthen One Health capacity building. With further adaptations under various scenarios, GOHI, along with its technical protocols and databases, will be updated regularly to address current technical limitations, and capture new knowledge.

The non-pharmaceutical interventions may affect the advantage in transmission of mutated variants during epidemics: A conceptual model for COVID-19.

As the COVID-19 pandemic continues, genetic mutations in SARS-CoV-2 emerge, and some of them are found more contagious than the previously identified strains, acting as the major mechanism for many large-scale epidemics. The transmission advantage of mutated variants is widely believed as an innate biological feature that is difficult to be altered by artificial factors. In this study, we explore how non-pharmaceutical interventions (NPI) may affect transmission advantage. A two-strain compartmental epidemic model is proposed and simulated to investigate the biological mechanism of the relationships among different NPIs, the changes in transmissibility of each strain and transmission advantage. Although the NPIs are effective in flattening the epidemic curve, we demonstrate that NPIs probably lead to a decline in transmission advantage, which is likely to occur if the NPIs become intensive. Our findings uncover the mechanistic relationship between NPIs and transmission advantage dynamically, and highlight the important role of NPIs not only in controlling the intensity of epidemics but also in slowing or even containing the growth of the proportion of variants.

The non-pharmaceutical interventions may affect the advantage in transmission of mutated variants during epidemics: A conceptual model for COVID-19

As the COVID-19 pandemic continues, genetic mutations in SARS-CoV-2 emerge, and some of them are found more contagious than the previously identified strains, acting as the major mechanism for many large-scale epidemics. The transmission advantage of mutated variants is widely believed as an innate biological feature that cannot be altered by artificial factors. In this study, we explore how non-pharmaceutical interventions (NPI) may affect transmission advantage. A two-strain compartmental epidemic model is proposed and simulated to investigate the biological mechanism of the relationships among different NPIs, the changes in transmissibility of each strain and transmission advantage. Although the NPIs are effective in flattening the epidemic curve, we demonstrate that NPIs probably lead to a decline in transmission advantage, which is likely to occur if the NPIs become intensive. Our findings uncover the mechanistic relationship between NPIs and transmission advantage dynamically, and highlight the important role of NPIs not only in controlling the intensity of epidemics but also in showing or even containing the growth of the proportion of mutated variants.

The co-circulating transmission dynamics of SARS-CoV-2 Alpha and Eta variants in Nigeria: A retrospective modeling study of COVID-19.

BACKGROUND: The COVID-19 pandemic poses serious threats to public health globally, and the emerging mutations in SARS-CoV-2 genomes has become one of the major challenges of disease control. In the second epidemic wave in Nigeria, the roles of co-circulating SARS-CoV-2 Alpha (ie, B.1.1.7) and Eta (ie, B.1.525) variants in contributing to the epidemiological outcomes were of public health concerns for investigation. METHODS: We developed a mathematical model to capture the transmission dynamics of different types of strains in Nigeria. By fitting to the national-wide COVID-19 surveillance data, the transmission advantages of SARS-CoV-2 variants were estimated by likelihood-based inference framework. RESULTS: The reproduction numbers were estimated to decrease steadily from 1.5 to 0.8 in the second epidemic wave. In December 2020, when both Alpha and Eta variants were at low prevalent levels, their transmission advantages (against the wild type) were estimated at 1.51 (95% credible intervals (CrI) = 1.48, 1.54), and 1.56 (95% CrI = 1.54, 1.59), respectively. In January 2021, when the original variants almost vanished, we estimated a weak but significant transmission advantage of Eta against Alpha variants with 1.14 (95% CrI = 1.11, 1.16). CONCLUSIONS: Our findings suggested evidence of the transmission advantages for both Alpha and Eta variants, of which Eta appeared slightly more infectious than Alpha. We highlighted the critical importance of COVID-19 control measures in mitigating the outbreak size and relaxing the burdens to health care systems in Nigeria.

Exploring the Interaction between E484K and N501Y Substitutions of SARS-CoV-2 in Shaping the Transmission Advantage of COVID-19 in Brazil: A Modeling Study.

The COVID-19 pandemic poses serious threats to global health, and the emerging mutation in SARS-CoV-2 genomes is one of the major challenges of disease control. Considering the growth of epidemic curve and the circulating SARS-CoV-2 variants in Brazil, the role of locally prevalent E484K and N501Y substitutions in contributing to the epidemiological outcomes is of public health interest for investigation. We developed a likelihood-based statistical framework to reconstruct reproduction numbers, estimate transmission advantage associated with different SARS-CoV-2 variants regarding the marking (identifying) 484K and 501Y substitutions (including Alpha, Zeta, and Gamma variants) in Brazil, and explored the interactive effects of genetic activities on transmission advantage marked by these two mutations. We found a significant transmission advantage associated with the 484K/501Y variants (including P.1 or Gamma variants), which increased the infectivity significantly by 23%. In contrast and by comparison to Gamma variants, E484K or N501Y (including Alpha or Zeta variants) substitution alone appeared less likely to secure a concrete transmission advantage in Brazil. Our finding indicates that the combined impact of genetic activities on transmission advantage marked by 484K/501Y outperforms their independent contributions in Brazil, which implies an interactive effect in shaping the increase in the infectivity of COVID-19. Future studies are needed to investigate the mechanisms of how E484K and N501Y mutations and the complex genetic mutation activities marked by them in SARS-CoV-2 affect the transmissibility of COVID-19.

How Transportation Restriction Shapes the Relationship Between Ambient Nitrogen Dioxide and COVID-19 Transmissibility: An Exploratory Analysis.

Background: Several recent studies reported a positive (statistical) association between ambient nitrogen dioxide (NO2) and COVID-19 transmissibility. However, considering the intensive transportation restriction due to lockdown measures that would lead to declines in both ambient NO2 concentration and COVID-19 spread, the crude or insufficiently adjusted associations between NO2 and COVID-19 transmissibility might be confounded. This study aimed to investigate whether transportation restriction confounded, mediated, or modified the association between ambient NO2 and COVID-19 transmissibility. Methods: The time-varying reproduction number (Rt ) was calculated to quantify the instantaneous COVID-19 transmissibility in 31 Chinese cities from January 1, 2020, to February 29, 2020. For each city, we evaluated the relationships between ambient NO2, transportation restriction, and COVID-19 transmission under three scenarios, including simple linear regression, mediation analysis, and adjusting transportation restriction as a confounder. The statistical significance (p-value < 0.05) of the three scenarios in 31 cities was summarized. Results: We repeated the crude correlational analysis, and also found the significantly positive association between NO2 and COVID-19 transmissibility. We found that little evidence supported NO2 as a mediator between transportation restriction and COVID-19 transmissibility. The association between NO2 and COVID-19 transmissibility appears less likely after adjusting the effects of transportation restriction. Conclusions: Our findings suggest that the crude association between NO2 and COVID-19 transmissibility is likely confounded by the transportation restriction in the early COVID-19 outbreak. After adjusting the confounders, the association between NO2 and COVID-19 transmissibility appears unlikely. Further studies are warranted to validate the findings in other regions.

Maternal and Neonatal Outcomes of Pregnant Women With Coronavirus Disease 2019 (COVID-19) Pneumonia: A Case-Control Study.

BACKGROUND: The ongoing pandemic of coronavirus disease 2019 (COVID-19) has caused serious concerns about its potential adverse effects on pregnancy. There are limited data on maternal and neonatal outcomes of pregnant women with COVID-19 pneumonia. METHODS: We conducted a case-control study to compare clinical characteristics and maternal and neonatal outcomes of pregnant women with and without COVID-19 pneumonia. RESULTS: During the period 24 January-29 February 2020, there were 16 pregnant women with confirmed COVID-19 pneumonia and 18 suspected cases who were admitted to labor in the third trimester. Two had vaginal delivery and the rest were cesarean delivery. Few patients presented respiratory symptoms (fever and cough) on admission, but most had typical chest computed tomographic images of COVID-19 pneumonia. Compared to the controls, patients with COVID-19 pneumonia had lower counts of white blood cells (WBCs), neutrophils, C-reactive protein (CRP), and alanine aminotransferase on admission. Increased levels of WBCs, neutrophils, eosinophils, and CRP were found in postpartum blood tests of pneumonia patients. Three (18.8%) of the mothers with confirmed COVID-19 pneumonia and 3 (16.7%) with suspected COVID-19 pneumonia had preterm delivery due to maternal complications, which were significantly higher than in the control group. None experienced respiratory failure during their hospital stay. COVID-19 infection was not found in the newborns, and none developed severe neonatal complications. CONCLUSIONS: Severe maternal and neonatal complications were not observed in pregnant women with COVID-19 pneumonia who had vaginal or cesarean delivery. Mild respiratory symptoms of pregnant women with COVID-19 pneumonia highlight the need of effective screening on admission.

The changing patterns of COVID-19 transmissibility during the social unrest in the United States: A nationwide ecological study with a before-and-after comparison.

Nationwide mass social unrest has emerged in the US since May 25 and raised broad concerns about its impacts on the local COVID-19 epidemics. We compared the COVID-19 transmissibility between May 19-May 25 and May 29-June 4 for each state of the US. We found that social unrest is likely associated with the rebound of the COVID-19 transmissibility, which might raise difficulties in the pandemic control.

The shortage of hospital beds for COVID-19 and non-COVID-19 patients during the lockdown of Wuhan, China.

BACKGROUND: The 76-day lockdown of Wuhan city has successfully contained the first wave of the coronavirus disease 2019 (COVID-19) outbreak. However, to date few studies have evaluated the hospital bed shortage for COVID-19 during the lockdown and none for non-COVID-19 patients, although such data are important for better preparedness of the future outbreak. METHODS: We built a compartmental model to estimate the daily numbers of hospital bed shortage for patients with mild, severe and critical COVID-19, taking account of underreport and diagnosis delay. RESULTS: The maximal daily shortage of inpatient beds for mild, severe and critical COVID-19 patients was 43,960 (95% confidence interval: 35,246, 52,929), 2,779 (1,395, 4,163) and 196 (143, 250) beds in early February 2020. An earlier or later lockdown would have greatly increased the shortage of hospital beds in Wuhan. The overwhelmed healthcare system might have delayed the provision of health care to both COVID-19 and non-COVID-19 patients during the lockdown. The second wave in Wuhan could have occurred in June 2020 if social distancing measures had waned in early March 2020. The hospital bed shortage was estimated much smaller in the potential second wave than in the first one. CONCLUSIONS: Our findings suggest that the timing and strength of lockdown is important for the containment of the COVID-19 outbreaks. The healthcare needs of non-COVID-19 patients in the pandemic warrant more investigations.

Obesity and COVID-19 in Adult Patients With Diabetes.

Obesity has caused wide concerns due to its high prevalence in patients with severe coronavirus disease 2019 (COVID-19). Coexistence of diabetes and obesity could cause an even higher risk of severe outcomes due to immunity dysfunction. We conducted a retrospective study in 1,637 adult patients who were admitted into an acute hospital in Wuhan, China. Propensity score-matched logistic regression was used to estimate the risks of severe pneumonia and requiring in-hospital oxygen therapy associated with obesity. After adjustment for age, sex, and comorbidities, obesity was significantly associated with higher odds of severe pneumonia (odds ratio [OR] 1.47 [95% CI 1.15-1.88]; P = 0.002) and oxygen therapy (OR 1.40 [95% CI 1.10-1.79]; P = 0.007). Higher ORs of severe pneumonia due to obesity were observed in men, older adults, and those with diabetes. Among patients with diabetes, overweight increased the odds of requiring in-hospital oxygen therapy by 0.68 times (P = 0.014) and obesity increased the odds by 1.06 times (P = 0.028). A linear dose-response curve between BMI and severe outcomes was observed in all patients, whereas a U-shaped curve was observed in those with diabetes. Our findings provide important evidence to support obesity as an independent risk factor for severe outcomes of COVID-19 infection in the early phase of the ongoing pandemic.

Initial COVID-19 Transmissibility and Three Gaseous Air Pollutants (NO2, SO2, and CO): A Nationwide Ecological Study in China.

In this study, we conducted an ecological study to examine their effects in the early phase of the pandemic (from December 2019 to February 2020) in China. We found that the associations between the average concentrations of NO2, SO2, and CO and the COVID-19 transmissibility are not statistically clear.

Blood pressure control and adverse outcomes of COVID-19 infection in patients with concomitant hypertension in Wuhan, China.

Hypertension is a common comorbidity in hospitalized patients with COVID-19 infection. This study aimed to estimate the risks of adverse events associated with in-hospital blood pressure (BP) control and the effects of angiotensin II receptor blocker (ARB) prescription in COVID-19 patients with concomitant hypertension. In this retrospective cohort study, the anonymized medical records of COVID-19 patients were retrieved from an acute field hospital in Wuhan, China. Clinical data, drug prescriptions, and laboratory investigations were collected for individual patients with diagnosed hypertension on admission. Cox proportional hazards models were used to estimate the risks of adverse outcomes associated with BP control during the hospital stay. Of 803 hypertensive patients, 67 (8.3%) were admitted to the ICU, 30 (3.7%) had respiratory failure, 26 (3.2%) had heart failure, and 35 (4.8%) died. After adjustment for confounders, the significant predictors of heart failure were average systolic blood pressure (SBP) (hazard ratio (HR) per 10 mmHg 1.89, 95% confidence interval (CI): 1.15, 3.13) and pulse pressure (HR per 10 mmHg 2.71, 95% CI: 1.39, 5.29). The standard deviations of SBP and diastolic BP were independently associated with mortality and ICU admission. The risk estimates of poor BP control were comparable between patients receiving ARBs and those not receiving ARBs, with the only exception of a high risk of heart failure in the non-ARB group. Poor BP control was independently associated with higher risks of adverse outcomes of COVID-19. ARB drugs did not increase the risks of adverse events in hypertensive patients.

Air and surface contamination by SARS-CoV-2 virus in a tertiary hospital in Wuhan, China.

BACKGROUND: Few studies have explored air and surface contamination by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in healthcare settings. METHODS: Air and surface samples were collected from the isolation wards and intensive care units designated for coronavirus disease 2019 (COVID-19) patients. Clinical data and the results of nasopharyngeal specimen and serum antibody testing were also collected for the patient sample. RESULTS: A total of 367 air and surface swab samples were collected from the patient care areas of 15 patients with mild COVID-19 and nine patients with severe/critical COVID-19. Only one air sample taken during the intubation procedure tested positive. High-touch surfaces were slightly more likely to be contaminated with SARS-CoV-2 RNA than low-touch surfaces. Contamination rates were slightly higher near severe/critical patients than near mild patients, although this difference was not statistically significant (p > 0.05). Surface contamination was still found near the patients with both positive IgG and IgM. CONCLUSIONS: Air and surface contamination with viral RNA was relatively low in these healthcare settings after the enhancement of infection prevention and control. Environmental contamination could still be found near seroconverted patients, suggesting the need to maintain constant vigilance in healthcare settings to reduce healthcare-associated infection during the COVID-19 pandemic.