Evaluation of enterovirus nucleic acids detection method based on ultra-fast real-time fluorescence RT-PCR technology - A pilot study

Ultra-Sensitive Portable Visual Paper-Based Viral Molecularly Imprinted Sensor without Autofluorescence Interference

Detection of the virus is the primary factor to discover and block the occurrence and development of the virus epidemic. Here, an ultrasensitive paper-based virus molecular imprinting sensor is developed to detect two viruses simultaneously in which the detection limit of the influenza virus (H5N1) is 16.0 aM (9.63 × 103 particles/mL) while that of the Hepatitis B Virus (HBV) is 129 fM (7.77 × 107 particles/mL). This paper-based sensor is low cost and is easy to cut, store, and carry. In addition, the visual semiquantitative detection of two viruses is achieved by using two aptamer-functionalized persistent luminescent nanoparticles as signal probes. These probes and the imprinted cavities on the paper-based material formed sandwich-type double recognition of the target viruses. This sensor has extremely high sensitivity to the H5N1 virus, which is of great value to solve the influenza epidemic with the most outbreaks in history, and also opens up a new way for the prevention and control of other virus epidemics. This cheap and portable visual sensor provides the possibility for self-service detection and can greatly reduce the pressure on medical staff and reduce the risk of virus infection caused by the concentration of people to be tested.

Analysis of the epidemiological characteristics between 2004 and 2017 and prediction of the changing pattern of other infectious diarrhea (OID) under COVID-19 in China

The study describes epidemiological features and transmission of other infectious diarrhea (OID) before and during the epidemic of COVID-19 in China, which lays a foundation for OID prevention and control. Incidence rate and mortality data of OID containing detailed epidemiological information such as date, age and region from 2004 to 2017, and total OID case number from 2018 to 2020 were obtained from the Data Center of China's Public Health Science and the National Bureau of Statistics' statistical yearbook. The Joinpoint regression model and Z test was used to analyze, while R language and ArcGIS 10.5 for drawing. The autoregressive integrated moving average model was used to predict the influence of COVID-19 on OID. The OID incidence rate increased from 31.69/10 million in 2004 to 92.42/10 million in 2017, and the mortality rate decreased from 1.82/10,000 to 0.14/10,000. The male to female incidence ratio was 1.39:1 (P < .001). The patients' age showed a decreased trend with age (P < .001). The scattered children devoted the most OID incidence rate. The bimodal distribution of OID incidence was summer peak in northern China, 2 apparent peaks in central and eastern, and winter peak in southern. The autoregressive integrated moving average model predicted 1,406,557 in 2020, comparing the actual OID cases in 2020 to 1,062,277. Affected by the epidemic control measures of COVID-19, the number of OID cases declined by 32.4% (Absolute percentage error = 32.4%). The OID incidence rate in China continuously increased and showed a bimodal distribution in summer and winter with inconspicuous regional characteristics, gender and age susceptibility differences, and occupational differences. Meanwhile, COVID-19 significantly reduced OID incidence in 2020. The discoveries might bring a beneficial effect on OID prevention and control policies.