Demographic and Psychosocial Factors associated with Internet Addiction among the Pakistani Population during COVID-19: A Web-Based Survey.

This study aims to determine the burden of COVID19-induced internet addiction and related psychosocial factors among the Pakistani sample. A web-based cross-sectional survey was conducted from January to March 2021. An analytical cross-sectional survey was broadcast on the internet via a Google form completed by 1145 Pakistanis. Individuals aged 13 years and above with competency to comprehend English or Urdu language, currently residing in any province of Pakistan, having access to the questionnaire, and willing to participate were eligible to participate. Overseas Pakistanis were excluded from the study. The outcome is COVID19-induced internet addiction was measured using the validated tool Young's Internet Addiction Test (IAT). In addition, symptoms of depression, anxiety, stress, and other psychosocial factors were assessed using the validated tool Depression, Anxiety, and Stress Scale-21 (DASS-21). Adjusted odds ratios with a 95% confidence interval were reported using multinomial logistic regression. Most participants were females and youth (between 20 and 24 years). The prevalence of problematic internet users (PIU) and addictive internet users (AIU) was 27.3% and 11.3%, respectively. The odds of extremely severe anxiety among AIU were approximately three times (Adj OR: 2.6 (1.1-7.1), followed by the odds of having extremely severe stress being about five times higher among AIU (Adj OR: 5.4 (1.6-17.6)) as compared to normal internet users (NIU). Amid COVID-19, the burden of internet addiction has surged among the Pakistani populace. This study identified that gender, marital status, depression, stress, anxiety, work situation, and mood changes during the COVID-19 pandemic are significantly correlated with problematic and addictive internet use. Preventative measures against the addictive use of the internet are needed to avoid or mitigate any serious mental health problems.

Integration of RT-LAMP and Microfluidic Technology for Detection of SARS-CoV-2 in Wastewater as an Advanced Point-of-Care Platform.

Development of lab-on-a-chip (LOC) system based on integration of reverse transcription loop-mediated isothermal amplification (RT-LAMP) and microfluidic technology is expected to speed up SARS-CoV-2 diagnostics allowing early intervention. In the current work, reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) and RT-LAMP assays were performed on extracted RNA of seven wastewater samples from COVID-19 hotspots. RT­LAMP assay was also performed on wastewater samples without RNA extraction. Current detection of SARS-CoV-2 is mainly by RT-qPCR of ORF (ORF1ab) and N genes so we targeted both to find the best target gene for SARS-CoV-2 detection. We also performed RT-LAMP with/without RNA extraction inside microfluidic device to target both genes. Positivity rates of RT-qPCR and RT-LAMP performed on extracted RNA were 100.0% (7/7) and 85.7% (6/7), respectively. RT-qPCR results revealed that all 7 wastewater samples were positive for N gene (Ct range 37-39), and negative for ORF1ab, suggesting that N gene could be the best target gene for SARS-CoV-2 detection. RT-LAMP of N and ORF (ORF1a) genes performed on wastewater samples without RNA extraction indicated that all 7 samples remains pink (negative). The color remains pink in all microchannels except microchannels which subjected to RT-LAMP for targeting N region after RNA extraction (yellow color) in 6 out of 7 samples. This study shows that SARS-CoV-2 was successfully detected from wastewater samples using RT-LAMP in microfluidic chips. This study brings the novelty involving the use of wastewater samples for detection of SARS-CoV-2 without previous virus concentration and with/without RNA extraction.

Co-movement of energy prices and stock market return: environmental wavelet nexus of COVID-19 pandemic from the USA, Europe, and China.

This work aims to study the time-frequency relationship between the recent COVID-19 pandemic and instabilities in oil price and the stock market, geopolitical risks, and uncertainty in the economic policy in the USA, Europe, and China. The coherence wavelet method and the wavelet-based Granger causality tests are applied to the data (31st December 2019 to 1st August 2020) based on daily COVID-19 observations, oil prices, US-EPU, the US geopolitical risk index, and the US stock price index. The short- and long-term COVID-19 consequences are depicted differently and may initially be viewed as an economic crisis. The results illustrate the reduced industrial productivity, which intensifies with the increase in the pandemic's severeness (i.e., a 10.57% decrease in the productivity index with a 1% increase in the pandemic severeness). Similarly, indices for oil demand, stock market, GDP growth, and electricity demand decrease significantly with an increase in the pandemic severeness index (i.e., a 1% increase in the pandemic severeness results in a 0.9%, 0.67%, 1.12%, and 0.65% decrease, respectively). However, the oil market shows low co-movement with the stock exchange, exchange rate, and gold markets. Therefore, investors and the government are recommended to invest in the oil market to generate revenue during the sanctions period.