In the recent SARS-CoV-2 pandemic, public health experts have emphasized testing, tracking infected people, and tracing their contacts as an effective strategy to reduce the spread of the virus. Several diagnostic methods are reported for detecting the coronavirus in clinical, research, and public health laboratories. Some tests detect the infection directly by detecting the viral RNA and other tests detect the infection indirectly by detecting the host antibodies. A diagnostic test during the pandemic should help make an appropriate clinical decision in a short period of time. Recently reported diagnostic methods for SARS-CoV-2 have varying throughput, batching capacity, requirement of infrastructure setting, analytical performance, and turnaround times ranging from a few minutes to several hours. These factors should be considered while selecting a reliable and rapid diagnostic method to help make an appropriate decision and prompt public health interventions. This paper reviews recent SARS-CoV-2 diagnostic methods published in journals and reports released by regulatory agencies. We compared the analytical efficiency including limit of detection, sensitivity, specificity, and throughput. In addition, we also looked into ease of use, affordability, and availability of accessories. Finally, we discuss the limitations of the methods and provide our perspectives on priorities for future test development.

BackgroundLow-cost face masks made from different cloth materials are very common in developing countries. The cloth masks (CM) are usually double layered with stretchable ear loops. It is common practice to use such masks for months after multiple washing and drying cycles. If a CM is used for long time, the ear loops become stretched. The loop needs to be knotted to make the mask loop fit better on the face. It is not clear how washing and drying and stretching practices change the quality of a CM. The particulate matter (PM) filtering efficiency of a mask depends on multiple parameters, such as pore size, shape, clearance, and pore number density. It is important to understand the effect of these parameters on the filtering efficiency.MethodsWe characterized the surface of twenty different types of CMs using optical image analysis method. The filtering efficiency of selected cloth face masks was measured using the particle counting method. We also studied the effects of washing and drying and stretching on the quality of a mask.ResultsThe pore size of masks ranged from 80 to 500 μm, which was much bigger than particular matter having diameter of 2.5 μm or less (PM2.5) and 10 μm or less (PM10) size. The PM10filtering efficiency of four of the selected masks ranged from 63% to 84%. The poor filtering efficiency may have arisen from larger and open pores present in the masks. Interestingly, we found that efficiency dropped by 20% after the 4th washing and drying cycle. We observed a change in pore size and shape and a decrease in microfibers within the pores after washing. Stretching of CM surface also altered the pore size and potentially decreased the filtering efficiency. As compared to CMs, the less frequently used surgical/paper masks had complicated networks of fibers and much smaller pores in multiple layers in comparison to CMs, and therefore had better filtering efficiency. This study showed that the filtering efficiency of cloth face masks were relatively lower, and washing and drying practices deteriorated the efficiency. We believe that the findings of this study will be very helpful for increasing public awareness and help governmental agencies to make proper guidelines and policies for use of face mask.

Bulk deposition samples were collected in remote, rural village and urban areas of Beijing–Tianjin region, North China in spring, summer, fall and winter from 2007 to 2008. The annually averaged PAHs concentration and deposition flux were 11.81 ± 4.61 µg/g and 5.2 ± 3.89 µg/m2/day respectively. PHE and FLA had the highest deposition flux, accounting for 35.3% and 20.7% of total deposition flux, respectively. More exposure risk from deposition existed in the fall for the local inhabitants. In addition, the PAHs deposition flux in rural villages (3.91 µg/m2/day) and urban areas (8.28 µg/m2/day) was 3.8 and 9.1 times higher than in background area (0.82 µg/m2/day), respectively. This spatial variation of deposition fluxes of PAHs was related to the PAHs emission sources, local population density and air concentration of PAHs, and the PAHs emission sources alone can explain 36%, 49%, 21% and 30% of the spatial variation in spring, summer, fall and winter, respectively.

Forty passive air samplers were deployed to study the occurrence of gas and particulate phase PAHs in remote, rural village and urban areas of Beijing–Tianjin region, North China for four seasons (spring, summer, fall and winter) from 2007 to 2008. The influence of emissions on the spatial distribution pattern of air PAH concentrations was addressed. In addition, the air–soil gas exchange of PAHs was studied using fugacity calculations. The median gaseous and particulate phase PAH concentrations were 222 ng/m3 and 114 ng/m3, respectively, with a median total PAH concentration of 349 ng/m3. Higher PAH concentrations were measured in winter than in other seasons. Air PAH concentrations measured at the rural villages and urban sites in the northern mountain region were significantly lower than those measured at sites in the southern plain during all seasons. However, there was no significant difference in PAH concentrations between the rural villages and urban sites in the northern and southern areas. This urban–rural PAH distribution pattern was related to the location of PAH emission sources and the population distribution. The location of PAH emission sources explained 56%–77% of the spatial variation in ambient air PAH concentrations. The annual median air–soil gas exchange flux of PAHs was 42.2 ng/m2/day from soil to air. Among the 15 PAHs measured, acenaphthylene (ACY) and acenaphthene (ACE) contributed to more than half of the total exchange flux. Furthermore, the air–soil gas exchange fluxes of PAHs at the urban sites were higher than those at the remote and rural sites. In summer, more gaseous PAHs volatilized from soil to air because of higher temperatures and increased rainfall. However, in winter, more gaseous PAHs deposited from air to soil due to higher PAH emissions and lower temperatures. The soil TOC concentration had no significant influence on the air–soil gas exchange of PAHs.