Point-of-Care Diagnostic Services as an Integral Part of Health Services during the Novel Coronavirus 2019 Era

Comparative analysis of loop-mediated isothermal amplification combined with microfluidic chip technology and q-PCR in the detection of clinical infectious pathogens

Background

Rapid diagnosis of infectious pathogens at an early stage is crucial to stabilize the patient's condition, reduce medical costs, and shorten hospital stays. Currently, some point‐of‐care tests have their own shortcomings. Therefore, we built a microfluidic chip based on loop‐mediated isothermal amplification to can quickly and sensitively detect infectious pathogens.

Methods

We extracted the DNA of S. aureus, MRSA, Shigella and Klebsiella pneumoniae. Then, the DNA samples were diluted by 10‐fold and examined by two methods: LAMP‐microfluidic chip and q‐PCR, the sensitivity of whom was also compared. In addition, the specificity of the two was also examined by detecting the target bacteria and other microorganisms using the same methods. Finally, we extracted and tested the DNA of clinically infected humoral samples to determine the coincidence rate between the two methods and the bacterial culture method.

Results

For S. aureus, MRSA, Shigella, and Klebsiella pneumoniae, the detection limits of the chip were 2.25 × 10³ copies/μl, 5.32 × 10³ copies/μl, 2.89 × 10³ copies/μl, 6.53 × 10² copies/μl, and the detection limits of q‐PCR were 2.25 × 10² copies/μl, 5.32 × 10¹ copies/μl, 2.89 × 10² copies/μl, 6.53 × 10¹ copies/μl, respectively. In terms of detection specificity, neither method cross‐reacted with other strains. For the detection of infectious humoral samples, the total coincidence rate between the q‐PCR and bacterial culture method was 85.7%, 95%, 95%, and 95.5%, and the total coincidence rate between the chip and bacterial culture method was 81%, 95%, 90%, and 86.4%, respectively.

Conclusion

LAMP‐microfluidic chip provides a simple, sensitive, specific, convenient, and rapid pathogen detection method for clinically infected humoral samples without relying on expensive equipment or technical personnels.

COVID-19 test sites in Victoria approaching Stage 4 restrictions: evaluating the relationship between remoteness, travel time and population serviced

OBJECTIVE

In Australia, people residing remotely typically experience increased travel time to health services, and remote health services often have unfavourable population-to-provider ratios. The state of Victoria was treated as a case study and a spatial analysis investigated the impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) point-of-care-test (POCT) site location (Major City, Inner Regional or Outer Regional) on the mean travel time for closest residents and the number of closest residents.

METHODS

A network analysis established the travel time from every mesh block in Victoria to the closest POCT site. Inferential analyses investigated the impact of POCT site location on travel time and the number of closest residents.

RESULTS

Compared to urban locations, the mean travel time for closest residents to rural POCT sites was significantly higher, while rural POCT sites had significantly fewer residents to service.

CONCLUSIONS

Findings confirm Australian health service literature suggesting that rural regions have poorer proximate availability of health services, while also contrasting to literature indicating that Australian rural regions have fewer health services per capita. Implications for public health: Localities within outer regional Victoria are candidates for a localised response to reduce unnecessary travel. Employing innovative service models may improve health service access and use and reduce population-to-provider ratios in rural locations.

COVID-19 and beyond: Use of digital technology for pandemic response in Africa

The use of technology has been ubiquitous in efforts to combat the ongoing COVID-19 pandemic. In this perspective, we review technologies and new approaches developed at the start of the pandemic; efforts earmarked by a flexible approach to problem solving, local tech entrepreneurship, and swift adoption of technology. We performed a systematic review of the use of technology during the initial wave of the COVID-19 pandemic in most African countries. We identified relevant articles by searching for mentions of technology, COVID-19, and specific country names. Articles were included if they specifically mentioned the use of technology or novel innovations in the response to the COVID-19 pandemic in an African country. The article search was conducted in August and included articles published between January and August 2020. We retrieved articles from journals, trusted news, government, and organization websites on Google, Google Scholar and PubMed. A total of 80 articles were retained and categorized under Disease Prevention (19 articles), Disease Surveillance xxx Antipoaching Tech Tracks COVID-19 Flare-Ups in South Africa - Scientific American. (2020, May 12), and Clinical Supplies and Management xxx Ethiopia's digital health response to COVID-19 - JSI. (2020, May 14). African nations used technology and innovative techniques to manage patients, monitor cases and disseminate information to counter the spread of COVID-19. The nature and outcomes of these efforts sometimes differed in Africa compared to other regions of the world due to its unique challenges and opportunities.

Civil-Military Collaboration to Facilitate Rapid Deployment of a Mobile Laboratory in Early Response to COVID-19: A High-Readiness Exercise

Rapid and adaptable diagnostic capabilities are of great importance in the face of emerging infectious diseases. In an outbreak, timely establishment of diagnostic routines is crucial to identifying cases and preventing the spread of the disease, especially when faced with high-consequence pathogens. In this article, we describe a multiagency exercise including the rapid deployment and diagnostic adaptation of the Swedish Armed Forces mobile laboratory (biological field analysis laboratory) in the context of COVID-19. This deployment was initiated as a high-readiness exercise at the end of January 2020, when the global development of the outbreak was still uncertain. Through collaboration with the Public Health Agency of Sweden and a civilian hospital, a real-time reverse transcriptase polymerase chain reaction method specific to SARS-CoV-2 was made available and adapted to the mobile laboratory, and the team established and evaluated a functional and efficient diagnostic asset along with a logistical support chain. We also organized and evaluated mobile testing teams, and the method was later used in large-scale, national, cross-sectional COVID-19 surveys in several regions of Sweden. In this article, we focus on the challenges of overbridging the civil-military interface in this context and identifying lessons learned and added values to the response during the early pandemic. We propose that the experiences from this exercise and governmental agency collaboration are valuable in preparation for future outbreaks.

Application of Artificial Intelligence in Medicine: An Overview

Artificial intelligence (AI) is a new technical discipline that uses computer technology to research and develop the theory, method, technique, and application system for the simulation, extension, and expansion of human intelligence. With the assistance of new AI technology, the traditional medical environment has changed a lot. For example, a patient's diagnosis based on radiological, pathological, endoscopic, ultrasonographic, and biochemical examinations has been effectively promoted with a higher accuracy and a lower human workload. The medical treatments during the perioperative period, including the preoperative preparation, surgical period, and postoperative recovery period, have been significantly enhanced with better surgical effects. In addition, AI technology has also played a crucial role in medical drug production, medical management, and medical education, taking them into a new direction. The purpose of this review is to introduce the application of AI in medicine and to provide an outlook of future trends.