Analysis of infection status and infection risk factors of caregivers of COVID-19 patients (preprint)

Background: Omicron infection often occurs in a family cluster, therefore, infection among caregivers of patients with COVID-19 is an important health concern. To explore the spread and risk factors of infection among caregivers of patients with COVID-19 and provide a theoretical basis for the scientific prevention and control of susceptible infections. Methods: We recruited 66 caregivers of patients with COVID-19 who were admitted to the medicine department of Jilin Provincial Hospital of Hepatobiliary Diseases supported by the First Hospital of Jilin University, between April 9, 2022 and April 30, 2022. We analyzed the impact of age, sex, vaccination history, positive conversion time, and some basic disease on the occurrence of infection among caregivers. Results: At one week after discharge of the admitted COVID-19 patients, 54 of the enrolled caregivers (including 22 males and 32 females) turned positive, while the remaining 12 did not. Among the patients with positive conversion, 79.63% had underlying diseases, 83.33% had positive conversion within 3 days after admission, and 46.30% had received the last vaccination more than 200 days. The positive conversion time, was significantly longer in women than in men. Additionally, the positive conversion time in those with underlying disease was longer than in those without. Conclusion: An understanding of the prevalence and risk factors for secondary infection among caregivers of COVID-19 patients would be useful in developing strategies for the prevention of infection in the of COVID-19-susceptible population and help improve the monitoring of various susceptible factors.

The relationship between green bonds and conventional financial markets: Evidence from quantile-on-quantile and quantile coherence approaches

Financial markets evolve continuously and become increasingly complex with the steady stream of financial innovations, among which recent emergence of green bonds breathes life into and poses challenges on conventional financial markets. Relevant studies rarely consider market conditions and time frequencies, and fail to cover the 2020 market recession. We examine their relationships at various quantiles and frequencies with novel quantile-based approaches using daily data of five representative markets involving the period of the COVID-19 pandemic. Our results reveal positive dependence of green bonds on fixed-income markets, indicating the diversifier role of green bonds, being most effective at the extreme lower quantiles of the treasury market and green bonds, which raises concern about their price transmission especially in recession. Hedging properties of green bonds for currency and stock markets are strongest in the medium term. In addition, we conduct the portfolio analysis, verifying hedging and diversification benefits of green bonds.

Application of time series model and deep learning method in measuring the impact of COVID-19 on agriculture in Hubei, China

Taking the agricultural situation of Hubei Province as the research object, this paper uses the time series ARIMA model, ARMA model and deep learning LSTM neural network model to explore the impact of COVID-19 on the agriculture of Hubei Province. Three main indicators are screened out to measure the development of agricultural economy, that is, gross regional product, gross output value of agriculture, forestry, animal husbandry and fishery, agricultural product production price index. Based on the quarterly data of indicators from 2001 to 2019 from the National Bureau of Statistics, three indicators in Hubei Province in the first quarter and the second quarter of 2020 are predicted by using the deep learning-based time series ARIMA model, ARMA model and LSTM neural network model. By comparing the predicted data with the real data, the impact of COVID-19 is measured on the agricultural situation of Hubei Province. It was found that COVID-19 had a great impact on the agricultural situation of Hubei Province in both of the first and second quarters of 2020, with the impact in the first quarter being greater than that in the second quarter. At the same time, the prediction accuracy of the two methods is compared to find that the time series model is more effective and reliable in predicting the agricultural product price index. The LSTM neural network model with a long and short term memory has a good prediction effect on the regional gross product and the total output value of agriculture, forestry, animal husbandry and fishery.

A case report of moderate COVID-19 with an extremely long-term viral shedding period in China (preprint)

BackgroundAn ongoing outbreak of novel coronavirus disease 2019 (COVID-19) from Wuhan, China, is currently recognized as a global public health emergency, which has subsequently spread to the rest of China and other countries. The WHO raised the COVID-19 alert to the highest level. The virus is a new highly contagious via human-to-human transmission. The median duration of viral shedding is 20.0 days. We report that the longest duration of viral shedding was 32.0 days from illness onset in a patient with moderate COVID-19 admitted to QianJiang Central Hospital.Case presentationA 37-year-old male sought medical advice while suffering from fever, dry cough, fatigue, dizziness, runny nose and diarrhoea. Five days before the visit, he had a history of travel from affected geographic areas. The patient had a positive RT-PCR test, and chest CT images showed multiple nodules and mixed ground-glass opacification with consolidation in both lungs. Laboratory findings showed that his lymphocyte and CD4+ counts were below the normal range. The patient was given antiviral treatment, including arbidol, lopinavir, IFN-α, and traditional Chinese medicine, and other necessary support care. All clinical symptoms and CT imaging manifestation abnormalities resolved during the course of therapy.ConclusionAlthough the positive RT-PCR tests were verified in consecutive upper respiratory specimens, the clinical symptoms, CT imaging findings, CD4 + lymphocyte counts, and IgG antibody levels had obviously improved. Positive tests may be detecting pieces of inactive viruses, which would not be transmissible in individual cases.

A case report of moderate COVID-19 with an extremely long-term viral shedding period in China (preprint)

Background: An ongoing outbreak of novel coronavirus disease 2019 (COVID-19) from Wuhan, China, is currently recognized as a global public health emergency, which has subsequently spread to the rest of China and other countries. The WHO raised the COVID-19 alert to the highest level. The virus is a new highly contagious via human-to-human transmission. The median duration of viral shedding is 20.0 days. We report that the longest duration of viral shedding was 32.0 days from illness onset in a patient with moderate COVID-19 admitted to QianJiang Central Hospital.Case presentation: A 37-year-old male sought medical advice while suffering from fever, dry cough, fatigue, dizziness, runny nose and diarrhoea. Five days before the visit, he had a history of travel from affected geographic areas. The patient had a positive RT-PCR test, and chest CT images showed multiple nodules and mixed ground-glass opacification with consolidation in both lungs. Laboratory findings showed that his lymphocyte and CD4+ counts were below the normal range. The patient was given antiviral treatment, including arbidol, lopinavir, IFN-α, and traditional Chinese medicine, and other necessary support care. All clinical symptoms and CT imaging manifestation abnormalities resolved during the course of therapy.Conclusion: Although the positive RT-PCR tests were verified in consecutive upper respiratory specimens, the clinical symptoms, CT imaging findings, CD4+ lymphocyte counts, and IgG antibody levels had obviously improved. Positive tests may be detecting pieces of inactive viruses, which would not be transmissible in individual cases.