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Virol J ; 18(1): 209, 2021 10 21.
Article in English | MEDLINE | ID: covidwho-1484316


BACKGROUND: Porcine vesicular disease is caused by the Seneca Valley virus (SVV), it is a novel Picornaviridae, which is prevalent in several countries. However, the pathogenicity of SVV on 5-6 week old pigs and the transmission routes of SVV remain unknown. METHODS: This research mainly focuses on the pathogenicity of the CH-GX-01-2019 strain and the possible vector of SVV. In this study, 5-6 week old pigs infected with SVV (CH-GX-01-2019) and its clinical symptoms (including rectal temperatures and other clinical symptoms) were monitored, qRT-PCR were used to detect the viremia and virus distribution. Neutralization antibody assay was set up during this research. Mosquitoes and Culicoides were collected from pigsties after pigs challenge with SVV, and SVV detection within mosquitoes and Culicoides was done via RT-PCR. RESULTS: The challenged pigs presented with low fevers and mild lethargy on 5-8 days post infection. The viremia lasted more than 14 days. SVV was detected in almost all tissues on the 14th day following the challenge, and it was significantly higher in the hoofs (vesicles) and lymph nodes in comparison with other tissues. Neutralizing antibodies were also detected and could persist for more than 28 days, in addition neutralizing antibody titers ranged from 1:128 to 1:512. Mosquitoes and Culicoides were collected from the pigsty environments following SVV infection. Although SVV was not detected in the mosquitoes, it was present in the Culicoides, however SVV could not be isolated from the positive Culicoides. CONCLUSIONS: Our work has enriched the knowledge relating to SVV pathogenicity and possible transmission routes, which may lay the foundation for further research into the prevention and control of this virus.

Ceratopogonidae , Picornaviridae Infections , Picornaviridae , Swine Diseases , Animals , Farms , Mosquito Vectors , Picornaviridae Infections/veterinary , Swine , Virulence
SSRN; 2020.
Preprint | SSRN | ID: ppcovidwho-4401


The coronavirus (COVID-19) pandemic has interrupted many industries, with restaurants being one of the hardest-hit businesses. On-demand delivery platforms such as DoorDash, Grubhub, and Uber Eats have been a valuable option for consumers, but whether and to what extent these platforms benefit restaurants remain under-investigated. This paper studies the impact of delivery platforms on restaurant demand and staffing. Empirical analysis shows that restaurants that are on delivery platforms are less negatively affected by the pandemic: both consumer demand and restaurant staffing are higher than restaurants that are not on these platforms. However, such positive platform effects are substantially heterogeneous across different types of restaurants: the demand enhancement effect for fast-food chains is four times larger than that of independent restaurants. This disparity suggests that delivery platforms can widen the performance gap between national chains and independent restaurants, which may drive more independent restaurants to close. Further, we find that changes in customers’ price sensitivity may explain why fast-food chains disproportionally benefit from delivery platforms. While the use of delivery platforms increases during the pandemic, consumers on these platforms are more price sensitive as these platforms reduce geographic frictions and facilitate price comparisons. Therefore, consumers on the platforms are more likely to choose the relatively low-priced fast-food chains over independent restaurants. These findings deepen our understanding of the effects of delivery platforms on restaurants and have implications for restaurants and policy makers.

Ann Intern Med ; 173(10): 773-781, 2020 11 17.
Article in English | MEDLINE | ID: covidwho-714329


BACKGROUND: Obesity, race/ethnicity, and other correlated characteristics have emerged as high-profile risk factors for adverse coronavirus disease 2019 (COVID-19)-associated outcomes, yet studies have not adequately disentangled their effects. OBJECTIVE: To determine the adjusted effect of body mass index (BMI), associated comorbidities, time, neighborhood-level sociodemographic factors, and other factors on risk for death due to COVID-19. DESIGN: Retrospective cohort study. SETTING: Kaiser Permanente Southern California, a large integrated health care organization. PATIENTS: Kaiser Permanente Southern California members diagnosed with COVID-19 from 13 February to 2 May 2020. MEASUREMENTS: Multivariable Poisson regression estimated the adjusted effect of BMI and other factors on risk for death at 21 days; models were also stratified by age and sex. RESULTS: Among 6916 patients with COVID-19, there was a J-shaped association between BMI and risk for death, even after adjustment for obesity-related comorbidities. Compared with patients with a BMI of 18.5 to 24 kg/m2, those with BMIs of 40 to 44 kg/m2 and greater than 45 kg/m2 had relative risks of 2.68 (95% CI, 1.43 to 5.04) and 4.18 (CI, 2.12 to 8.26), respectively. This risk was most striking among those aged 60 years or younger and men. Increased risk for death associated with Black or Latino race/ethnicity or other sociodemographic characteristics was not detected. LIMITATION: Deaths occurring outside a health care setting and not captured in membership files may have been missed. CONCLUSION: Obesity plays a profound role in risk for death from COVID-19, particularly in male patients and younger populations. Our capitated system with more equalized health care access may explain the absence of effect of racial/ethnic and socioeconomic disparities on death. Our data highlight the leading role of severe obesity over correlated risk factors, providing a target for early intervention. PRIMARY FUNDING SOURCE: Roche-Genentech.

Betacoronavirus , Coronavirus Infections/mortality , Obesity/epidemiology , Pneumonia, Viral/mortality , Adult , Age Factors , Aged , Aged, 80 and over , Asthma/epidemiology , Body Mass Index , COVID-19 , California/epidemiology , Cohort Studies , Comorbidity , Delivery of Health Care, Integrated , Diabetes Mellitus/epidemiology , Female , Humans , Hyperlipidemias/epidemiology , Hypertension/epidemiology , Male , Middle Aged , Pandemics , Retrospective Studies , Risk Factors , SARS-CoV-2 , Sex Factors , Young Adult