ABSTRACT
Monitoring wastewater for SARS-CoV-2 from populations smaller than those served by wastewater treatment plants may help identify small spatial areas (subsewersheds) where COVID-19 infections are present. We sampled wastewater from three nested locations with different sized populations within the same sewer network at a university campus and quantified SARS-CoV-2 RNA using reverse transcriptase droplet digital polymerase chain reaction (PCR). SARS-CoV-2 RNA concentrations and/or concentrations normalized by PMMoV were positively associated with laboratory-confirmed COVID-19 cases for both the sewershed level and the subsewershed level. We also used an antigen-based assay to detect the nucleocapsid (N) antigen from SARS-CoV-2 in wastewater samples at the sewershed level. The N antigen was regularly detected at the sewershed level, but the results were not associated with either laboratory-confirmed COVID-19 cases or SARS-CoV-2 RNA concentrations. The results of this study indicate that wastewater monitoring based on quantification of SARS-CoV-2 RNA using PCR-based methods is associated with COVID-19 cases at multiple geographic scales within the subsewershed level and can serve to aid the public health response.
ABSTRACT
COVID 19, a furious virus, exploded across the globe in 2020. Treatment, tracing and testing are the only way to retain a normal life. But the biggest obstacle is the shortage of proper testing kits which makes life horrendous. As a consequence it demands time to ramp up the development of a suitable test kit. In this scenario we propose a kit that is made up of a two-dimensional (2-D) Si-based photonic crystal structure (PCS) that could distinguish the novel coronaviruses (n-CoV) from ordinary coronaviruses. The principle of identification relies on the reflectance, absorbance and transmittance characteristics at the signal of 412 nm wavelength obtained from a laser diode (LD);moreover, the operational mechanism deals with the manipulation of the signal with the proposed PCS structure which contains the virus solution. Finally, the output transmitted energy differentiates the viruses pertaining to their nature;for example, an output with visible light energy gives an indication of normal flu;on the other hand, output energy within the infrared (IR) range confirms the case of novel coronavirus infection.
ABSTRACT
Currently, we are in the COVID-19 pandemic situation, where the healthcare sector plays a major role to prevent the loss of life across the globe. During this COVID-19 period, the remote healthcare assistance and monitor systems show their impotence and existence. Science and technology are always associated with the healthcare sector, and it helps to diagnose the cause of bad health and helps to improve by proper treatment. The analysis of the causes plays a major role in treatment. With the advance of science and technology for the complex clinical solution in healthcare, IoHT (internet of health care things) and intelligent analytics in big data can play a bigger role in cancer detection, brain tumor, etc. The main focus of our work is to discuss a framework of intelligent analytics for big data utility to such a complex clinical problem on the IoHT platform. The digital imaging of medical imaging is playing a critical role in the clinical operation of a human in healthcare. The treatment of cancer or the brain is a very complex multistage treatment process;here, use of intelligent big data analytics and IoHT can help the doctors to provide better decision making which helps in treatment and recovery stages. So the remote healthcare sector, which is showing its utility during the COVID-19 situation, where intelligent data analytics play a major role to provide better healthcare solutions and monitoring to the human society. The intelligent medical systems for healthcare need proper data acquisition health condition, which need to analyze, store and process for each individual for clinical treatment and future reference. The past information periodically and present health condition can store and analyzed for better healthcare, this leads to an intelligent database system, where Intelligent data analytics play a big role, with the utility of the advanced platform it becomes robust and can be the backbone of the healthcare sector. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
We will present a microfluidic assay to detect SARS-CoV-2 RNA from raw nasopharyngeal swab samples in <30 min. Our method combines isotachophoresis (ITP) and state-of-the-art CRISPR Cas12-based nucleic acid detection. We show, for the first time, that electric field gradients in ITP can be used to pre-concentrate Cas12-guide RNA complex, target nucleic acids, and reporter molecules by ~1,000-fold into a ~100 pL volume on-chip. This pre-concentration accelerates target-activated CRISPR enzymatic activity on reporter molecules. We combine our ITP-CRISPR method with ITP-based nucleic acid extraction and isothermal amplification to detect Covid-19 from both contrived and clinical patient samples. © 2020 CBMS-0001