Assessing COVID-19 pandemic policies and behaviours and their economic and educational trade-offs across US states from Jan 1, 2020, to July 31, 2022: an observational analysis.

BACKGROUND: The USA struggled in responding to the COVID-19 pandemic, but not all states struggled equally. Identifying the factors associated with cross-state variation in infection and mortality rates could help to improve responses to this and future pandemics. We sought to answer five key policy-relevant questions regarding the following: 1) what roles social, economic, and racial inequities had in interstate variation in COVID-19 outcomes; 2) whether states with greater health-care and public health capacity had better outcomes; 3) how politics influenced the results; 4) whether states that imposed more policy mandates and sustained them longer had better outcomes; and 5) whether there were trade-offs between a state having fewer cumulative SARS-CoV-2 infections and total COVID-19 deaths and its economic and educational outcomes. METHODS: Data disaggregated by US state were extracted from public databases, including COVID-19 infection and mortality estimates from the Institute for Health Metrics and Evaluation's (IHME) COVID-19 database; Bureau of Economic Analysis data on state gross domestic product (GDP); Federal Reserve economic data on employment rates; National Center for Education Statistics data on student standardised test scores; and US Census Bureau data on race and ethnicity by state. We standardised infection rates for population density and death rates for age and the prevalence of major comorbidities to facilitate comparison of states' successes in mitigating the effects of COVID-19. We regressed these health outcomes on prepandemic state characteristics (such as educational attainment and health spending per capita), policies adopted by states during the pandemic (such as mask mandates and business closures), and population-level behavioural responses (such as vaccine coverage and mobility). We explored potential mechanisms connecting state-level factors to individual-level behaviours using linear regression. We quantified reductions in state GDP, employment, and student test scores during the pandemic to identify policy and behavioural responses associated with these outcomes and to assess trade-offs between these outcomes and COVID-19 outcomes. Significance was defined as p<0·05. FINDINGS: Standardised cumulative COVID-19 death rates for the period from Jan 1, 2020, to July 31, 2022 varied across the USA (national rate 372 deaths per 100 000 population [95% uncertainty interval [UI] 364-379]), with the lowest standardised rates in Hawaii (147 deaths per 100 000 [127-196]) and New Hampshire (215 per 100 000 [183-271]) and the highest in Arizona (581 per 100 000 [509-672]) and Washington, DC (526 per 100 000 [425-631]). A lower poverty rate, higher mean number of years of education, and a greater proportion of people expressing interpersonal trust were statistically associated with lower infection and death rates, and states where larger percentages of the population identify as Black (non-Hispanic) or Hispanic were associated with higher cumulative death rates. Access to quality health care (measured by the IHME's Healthcare Access and Quality Index) was associated with fewer total COVID-19 deaths and SARS-CoV-2 infections, but higher public health spending and more public health personnel per capita were not, at the state level. The political affiliation of the state governor was not associated with lower SARS-CoV-2 infection or COVID-19 death rates, but worse COVID-19 outcomes were associated with the proportion of a state's voters who voted for the 2020 Republican presidential candidate. State governments' uses of protective mandates were associated with lower infection rates, as were mask use, lower mobility, and higher vaccination rate, while vaccination rates were associated with lower death rates. State GDP and student reading test scores were not associated with state COVD-19 policy responses, infection rates, or death rates. Employment, however, had a statistically significant relationship with restaurant closures and greater infections and deaths: on average, 1574 (95% UI 884-7107) additional infections per 10 000 population were associated in states with a one percentage point increase in employment rate. Several policy mandates and protective behaviours were associated with lower fourth-grade mathematics test scores, but our study results did not find a link to state-level estimates of school closures. INTERPRETATION: COVID-19 magnified the polarisation and persistent social, economic, and racial inequities that already existed across US society, but the next pandemic threat need not do the same. US states that mitigated those structural inequalities, deployed science-based interventions such as vaccination and targeted vaccine mandates, and promoted their adoption across society were able to match the best-performing nations in minimising COVID-19 death rates. These findings could contribute to the design and targeting of clinical and policy interventions to facilitate better health outcomes in future crises. FUNDING: Bill & Melinda Gates Foundation, J Stanton, T Gillespie, J and E Nordstrom, and Bloomberg Philanthropies.

B-Cell Lymphoma Associated with COVID-19 Infection: A Case Report.

PURPOSE: Most common publications are related to COVID-19 diagnosis in hematological malignancy patients. However, here we report a case involving a patient diagnosed with B-cell lymphoma while undergoing treatment for COVID-19, including the changes in major clinical symptoms and medical examinations, then explain the probable causes of the case. CASE PRESENTATION: A 74-year-old woman with a previous history of oesophageal cancer was admitted to the hospital after having cough and sputum for 15 days. Despite the COVID-19 symptoms, this patient did not have a fever at the time of the onset. Results of routine blood tests were normal at first but then declined with persistent fever, and A whole-body C.T. examination ruled out the possibility of tumor-metastasis-related fever. This patient had no hepatosplenomegaly or regional lymphadenopathy, and there was no concrete evidence of haemophagocytic lymphohistiocytosis or lymphoma until bone marrow biopsy results confirmed the latter. CONCLUSION: We describe an uncommon case of COVID-19 who was finally diagnosed with B-cell lymphoma. An awareness of persistent fever and declined routine blood tests caused by hematological malignancies instead of COVID-19 itself can aid in providing appropriate guidelines for management and treatment.

Estimating global and regional disruptions to routine childhood vaccine coverage during the COVID-19 pandemic in 2020: a modelling study.

BACKGROUND: The COVID-19 pandemic and efforts to reduce SARS-CoV-2 transmission substantially affected health services worldwide. To better understand the impact of the pandemic on childhood routine immunisation, we estimated disruptions in vaccine coverage associated with the pandemic in 2020, globally and by Global Burden of Disease (GBD) super-region. METHODS: For this analysis we used a two-step hierarchical random spline modelling approach to estimate global and regional disruptions to routine immunisation using administrative data and reports from electronic immunisation systems, with mobility data as a model input. Paired with estimates of vaccine coverage expected in the absence of COVID-19, which were derived from vaccine coverage models from GBD 2020, Release 1 (GBD 2020 R1), we estimated the number of children who missed routinely delivered doses of the third-dose diphtheria-tetanus-pertussis (DTP3) vaccine and first-dose measles-containing vaccine (MCV1) in 2020. FINDINGS: Globally, in 2020, estimated vaccine coverage was 76·7% (95% uncertainty interval 74·3-78·6) for DTP3 and 78·9% (74·8-81·9) for MCV1, representing relative reductions of 7·7% (6·0-10·1) for DTP3 and 7·9% (5·2-11·7) for MCV1, compared to expected doses delivered in the absence of the COVID-19 pandemic. From January to December, 2020, we estimated that 30·0 million (27·6-33·1) children missed doses of DTP3 and 27·2 million (23·4-32·5) children missed MCV1 doses. Compared to expected gaps in coverage for eligible children in 2020, these estimates represented an additional 8·5 million (6·5-11·6) children not routinely vaccinated with DTP3 and an additional 8·9 million (5·7-13·7) children not routinely vaccinated with MCV1 attributable to the COVID-19 pandemic. Globally, monthly disruptions were highest in April, 2020, across all GBD super-regions, with 4·6 million (4·0-5·4) children missing doses of DTP3 and 4·4 million (3·7-5·2) children missing doses of MCV1. Every GBD super-region saw reductions in vaccine coverage in March and April, with the most severe annual impacts in north Africa and the Middle East, south Asia, and Latin America and the Caribbean. We estimated the lowest annual reductions in vaccine delivery in sub-Saharan Africa, where disruptions remained minimal throughout the year. For some super-regions, including southeast Asia, east Asia, and Oceania for both DTP3 and MCV1, the high-income super-region for DTP3, and south Asia for MCV1, estimates suggest that monthly doses were delivered at or above expected levels during the second half of 2020. INTERPRETATION: Routine immunisation services faced stark challenges in 2020, with the COVID-19 pandemic causing the most widespread and largest global disruption in recent history. Although the latest coverage trajectories point towards recovery in some regions, a combination of lagging catch-up immunisation services, continued SARS-CoV-2 transmission, and persistent gaps in vaccine coverage before the pandemic still left millions of children under-vaccinated or unvaccinated against preventable diseases at the end of 2020, and these gaps are likely to extend throughout 2021. Strengthening routine immunisation data systems and efforts to target resources and outreach will be essential to minimise the risk of vaccine-preventable disease outbreaks, reach children who missed routine vaccine doses during the pandemic, and accelerate progress towards higher and more equitable vaccination coverage over the next decade. FUNDING: Bill & Melinda Gates Foundation.

Correction：Diagnostic Accuracy of Chest Computed Tomography Scans for Suspected Patients With COVID-19: Receiver Operating Characteristic Curve Analysis.

[This corrects the article DOI: 10.2196/19424.].

Diagnostic Accuracy of Chest Computed Tomography Scans for Suspected Patients With COVID-19: Receiver Operating Characteristic Curve Analysis.

BACKGROUND: Computed tomography (CT) scans are increasingly available in clinical care globally. They enable a rapid and detailed assessment of tissue and organ involvement in disease processes that are relevant to diagnosis and management, particularly in the context of the COVID-19 pandemic. OBJECTIVE: The aim of this paper is to identify differences in the CT scan findings of patients who were COVID-19 positive (confirmed via nucleic acid testing) to patients who were confirmed COVID-19 negative. METHODS: A retrospective cohort study was proposed to compare patient clinical characteristics and CT scan findings in suspected COVID-19 cases. A multivariable logistic model with LASSO (least absolute shrinkage and selection operator) selection for variables was used to identify the good predictors from all available predictors. The area under the curve (AUC) with 95% CI was calculated for each of the selected predictors and the combined selected key predictors based on receiver operating characteristic curve analysis. RESULTS: A total of 94 (56%) patients were confirmed positive for COVID-19 from the suspected 167 patients. We found that elderly people were more likely to be infected with COVID-19. Among the 94 confirmed positive patients, 2 (2%) patients were admitted to an intensive care unit. No patients died during the study period. We found that the presence, distribution, and location of CT lesions were associated with the presence of COVID-19. White blood cell count, cough, and a travel history to Wuhan were also the top predictors for COVID-19. The overall AUC of these selected predictors is 0.97 (95% CI 0.93-1.00). CONCLUSIONS: Taken together with nucleic acid testing, we found that CT scans can allow for the rapid diagnosis of COVID-19. This study suggests that chest CT scans should be more broadly adopted along with nucleic acid testing in the initial assessment of suspected COVID-19 cases, especially for patients with nonspecific symptoms.

An Updated Understanding of the Current Emerging Respiratory Infection: COVID-19.

According to the World Health Organization (WHO), the COVID-19 pandemic has been declared as a priority disease. Some patients with COVID-19 had symptoms of multiple organ failure and death. The published articles on COVID-19 infection were reviewed. The origin of SARS-CoV-2 is still not completely established. Person-to-person transmission via droplets, probable aerosols, or close contact is considered as the main mode of transmission. With increased mortality due to SARS-CoV-2, valuable clinical indicators or treatments should be further identified and summarized. CT scanning plays an important role in the diagnosis and evaluation of COVID-19 in asymptomatic patients or those with initially negative RT-PCR results. No specific antiviral therapy is recommended, except the main supportive treatments, and effective measures should be taken into consideration to protect important organs and prevent the development of acute respiratory distress syndrome (ARDS) in patients with severe infection.

Etiology and genetic evolution of canine coronavirus circulating in five provinces of China, during 2018-2019.

As the outbreaks of COVID-19 in worldwide, coronavirus has once again caught the attention of people. Canine coronavirus is widespread among dog population, and sometimes causes even fatal cases. Here, to characterize the prevalence and evolution of current circulating canine coronavirus (CCoV) strains in China, we collected 213 fecal samples from diarrheic pet dogs between 2018 and 2019. Of the 213 samples, we found 51 (23.94%) were positive for CCoV. Co-infection with canine parvovirus (CPV), canine astrovirus (CaAstV), canine kobuvirus (CaKV), Torque teno canis virus (TTCaV) were ubiquitous existed. Mixed infection of different CCoV subtypes exists extensively. Considering the limited sequences data in recent years, we sequenced 7 nearly complete genomes and 10 complete spike gene. Phylogenetic analysis of spike gene revealed a new subtype CCoV-II Variant and CCoV-IIa was the most prevalent subtype currently circulating. Moreover, we identified strain B906_ZJ_2019 shared 93.24% nucleotide identifies with previous strain A76, and both of them clustered with CCoV-II Variant, which were not well clustered with the known subtypes. Recombination analysis of B906_ZJ_2019 indicated that strain B906_ZJ_2019 may a recombinant variant between CCoV-I and CCoV-II, which is consistent with strain A76. Furthermore, amino acid variations widely existed among current CCoV-IIa strains circulating in China and the classic CCoV-IIa strains, in spite of the unknown functions. In a word, we report a useful information as to the etiology and evolution of canine coronavirus in China based on the available sequences, which is urgent for the devise of future effective disease prevention and control strategies.