Optimization of Multi Two-Level Batch Testing

As the COVID-19 pandemic continues to spread, rapid testing could help curb asymptomatic transmission. Thus, it is paramount that the most efficient testing method be identified and implemented, as to reduce the strain on the medical community. This project introduces a novel batch testing method called multi two-level batch testing, which was hypothesized to increase the efficiency of batch testing in terms of minimizing the number of tests performed for a given population. While Dorfman’s two-level and Li’s multi-level batch testing methods already exist, this method offers a novel strategy distinct from existing methods. A Java simulation was created to iteratively compute the number of tests required for each testing method at various percentages of population infection rate, batch sizes, and other parameters specific to each method. Based on this simulation, it can be shown that the multi two-level procedure is more efficient than both the two-level and the multi-level procedures at an infection rate of 0.01, which is the anticipated rate at the University of Florida during the Spring 2021 semester. Additionally, at infection rates between 0.05 and 0.30, the multi two-level batch testing method slightly outperforms multi-level. When the infection rate exceeds 0.30, all methods are unviable and begin to require more tests than necessary to test each person in the population individually. If laboratories implement multi two-level batch testing, they may reduce costs and labor. Additionally, the novel batch testing procedure can be applied to other diseases and future pandemics.

How to draw the line – Raman spectroscopy as a tool for the assessment of biomedicines

Biomedicines are complex biochemical formulations with multiple components that require extensive quality control during manufacturing and in subsequent batch testing. A proof-of-concept study has shown that an application of Raman spectroscopy can be beneficial for a classification of vaccines. However, the complexity of biomedicines introduces new challenges to spectroscopic methodology that require advanced experimental protocols. We further show the impact of analytical protocols on vaccine classification using R as an Open Source data analysis platform. In conclusion, we advocate for standardized and transparent experimental and analytical procedures and discuss current findings and open challenges.

A Polynomial-Time Approximation Scheme for Sequential Batch Testing of Series Systems

The paper studies a recently introduced generalization of the classic sequential testing problem for series systems, consisting of multiple stochastic components. The conventional assumption in such settings is that the overall system state can be expressed as an AND function, defined with respect to the states of individual components. However, unlike the classic setting, rather than testing components separately, one after the other, we allow aggregating multiple tests to be conducted simultaneously, while incurring an additional set-up cost. This feature is present in numerous practical applications, where decision makers are incentivized to exploit economy of scale by testing subsets of components in batches. The main contribution of this paper is to devise a polynomial-time approximation scheme for the sequential batch-testing problem, by leveraging a number of techniques in approximate dynamic programming, based on a synthesis of ideas related to efficient enumeration methods, state-space collapse, and charging schemes.

Discharge curve-based formation of retired power batteries for secondary use

To address the problem of optional group formation in the process of retired power batteries for secondary use, a detection method based on the ampere-time integration method is used for batch testing of retired power batteries. The dynamic time-bending dynamic time warping distance between different batteries is calculated by comparing the discharge curves during the testing process. Combining the remaining capacity, open circuit voltage and internal resistance of the battery as a common battery classification condition, each condition is normalised and a density canopy + K-means clustering algorithm is applied to regroup the retired power batteries. This method improves the regrouping technique for the retired batteries and improves the performance of the regrouped battery modules in terms of capacity and consistency.

Molecular diagnosis for the novel coronavirus SARS-CoV-2: lessons learnt from the Ghana experience

Background: A novel coronavirus, SARS-CoV-2 is currently causing a worldwide pandemic. The first cases of SARS-CoV-2 infection were recorded in Ghana on March 12, 2020. Since then, the country has been combatting countrywide community spread. This report describes how the Virology Department, Noguchi Memorial Institute for Medical Research (NMIMR) is supporting the Ghana Health Service (GHS) to diagnose infections with this virus in Ghana.Methods: The National Influenza Centre (NIC) in the Virology Department of the NMIMR, adopted real-time Polymerase Chain Reaction (rRT-PCR) assays for the diagnosis of the SARS-CoV-2 in January 2020. Samples from suspected cases and contact tracing across Ghana were received and processed for SARS-CoV-2. Samples were ‘pooled’ to enable simultaneous batch testing of samples without reduced sensitivity.Outcomes: From February 3 to August 21, the NMIMR processed 283 946 (10%) samples. Highest number of cases were reported in June when the GHS embarked on targeted contact tracing which led to an increase in number of samples processed daily, peaking at over 7,000 samples daily. There were several issues to overcome including rapid consumption of reagents and consumables. Testing however continued successfully due to revised procedures, additional equipment and improved pipeline of laboratory supplies. Test results are now provided within 24 to 48 hours of sample submission enabling more effective response and containment.Conclusion: Following the identification of the first cases of SARS-CoV-2infection by the NMIMR, the Institute has trained other centres and supported the ramping up of molecular testing capacity in Ghana. This provides a blueprint to enable Ghana to mitigate further epidemics and pandemics.

Assessing the potential impact on health of the UK's future relationship agreement with the EU: analysis of the negotiating positions

While policy attention is understandably diverted to COVID-19, the end of the UK's post-Brexit ‘transition period’ remains 31 December 2020. All forms of future EU−UK relationship are worse for health than EU membership, but analysis of the negotiating texts shows some forms are better than others. The likely outcomes involve major negative effects for NHS staffing, funding for health and social care, and capital financing for the NHS; and for UK global leadership and influence. We expect minor negative effects for cross border healthcare (except in Northern Ireland); research collaboration; and data sharing, such as the Early Warning and Response System for health threats. Despite political narratives, the legal texts show that the UK seeks de facto continuity in selected key areas for pharmaceuticals, medical devices, and equipment [including personal protective equipment (PPE)], especially clinical trials, pharmacovigilance, and batch-testing. The UK will be excluded from economies of scale of EU membership, e.g. joint procurement programmes as used recently for PPE. Above all, there is a major risk of reaching an agreement with significant adverse effects for health, without meaningful oversight by or input from the UK Parliament, or other health policy stakeholders.