On the Corrosion Fatigue of Magnesium Alloys Aimed at Biomedical Applications: New Insights from the Influence of Testing Frequency and Surface Modification of the Alloy ZK60

Magnesium alloys are contemporary candidates for many structural applications of which medical applications, such as bioresorbable implants, are of significant interest to the community and a challenge to materials scientists. The generally poor resistance of magnesium alloys to environmentally assisted fracture, resulting, in particular, in faster-than-desired bio-corrosion degradation in body fluids, strongly impedes their broad uptake in clinical practice. Since temporary structures implanted to support osteosynthesis or healing tissues may experience variable loading, the resistance to bio-corrosion fatigue is a critical issue that has yet to be understood in order to maintain the structural integrity and to prevent the premature failure of implants. In the present communication, we address several aspects of the corrosion fatigue behaviour of magnesium alloys, using the popular commercial ZK60 Mg-Zn-Zr alloy as a representative example. Specifically, the effects of the testing frequency, surface roughness and metallic coatings are discussed in conjunction with the fatigue fractography after the testing of miniature specimens in air and simulated body fluid. It is demonstrated that accelerated environmentally assisted degradation under cyclic loading occurs due to a complicated interplay between corrosion damage, stress corrosion cracking and cyclic loads. The occurrence of corrosion fatigue in Mg alloys is exaggerated by the significant sensitivity to the testing frequency. The fatigue life or strength reduced remarkably with a decrease in the test frequency.

Pooled testing efficiency increases with test frequency

Pooled testing increases efficiency by grouping individual samples and testing the combined sample, such that many individuals can be cleared with one negative test. This short paper demonstrates that pooled testing is particularly advantageous in the setting of pandemics, given repeated testing, rapid spread, and uncertain risk. Repeated testing mechanically lowers the infection probability at the time of the next test by removing positives from the population. This effect alone means that increasing frequency by x times only increases expected tests by around x. However, this calculation omits a further benefit of frequent testing: Removing infections from the population lowers intragroup transmission, which lowers infection probability and generates further efficiency. For this reason, increasing testing frequency can paradoxically reduce total testing cost. Our calculations are based on the assumption that infection rates are known, but predicting these rates is challenging in a fast-moving pandemic. However, given that frequent testing naturally suppresses the mean and variance of infection rates, we show that our results are very robust to uncertainty and misprediction. Finally, we note that efficiency further increases given natural sampling pools (e.g., workplaces, classrooms) that induce correlated risk via local transmission. We conclude that frequent pooled testing using natural groupings is a cost-effective way to provide consistent testing of a population to suppress infection risk in a pandemic.

Can we check serum lithium levels less often without compromising patient safety?

Background Lithium is viewed as the first-line long-term treatment for prevention of relapse in people with bipolar disorder. Aims This study examined factors associated with the likelihood of maintaining serum lithium levels within the recommended range and explored whether the monitoring interval could be extended in some cases. Method We included 46 555 lithium rest requests in 3371 individuals over 7 years from three UK centres. Using lithium results in four categories (<0.4 mmol/L; 0.40–0.79 mmol/L; 0.80–0.99 mmol/L; ≥1.0 mmol/L), we determined the proportion of instances where lithium results remained stable or switched category on subsequent testing, considering the effects of age, duration of lithium therapy and testing history. Results For tests within the recommended range (0.40–0.99 mmol/L categories), 84.5% of subsequent tests remained within this range. Overall, 3 monthly testing was associated with 90% of lithium results remaining within range, compared with 85% at 6 monthly intervals. In cases where the lithium level in the previous 12 months was on target (0.40–0.79 mmol/L; British National Formulary/National Institute for Health and Care Excellence criteria), 90% remained within the target range at 6 months. Neither age nor duration of lithium therapy had any significant effect on lithium level stability. Levels within the 0.80–0.99 mmol/L category were linked to a higher probability of moving to the ≥1.0 mmol/L category (10%) compared with those in the 0.4–0.79 mmol/L group (2%), irrespective of testing frequency. Conclusion We propose that for those who achieve 12 months of lithium tests within the 0.40–0.79 mmol/L range, the interval between tests could increase to 6 months, irrespective of age. Where lithium levels are 0.80–0.99 mmol/L, the test interval should remain at 3 months. This could reduce lithium test numbers by 15% and costs by ~$0.4 m p.a.

Requirements for the containment of COVID-19 disease outbreaks through periodic testing, isolation, and quarantine

We employ individual-based Monte Carlo computer simulations of a stochastic SEIR model variant on a two-dimensional Newman-Watts small-world network to investigate the control of epidemic outbreaks through periodic testing and isolation of infectious individuals, and subsequent quarantine of their immediate contacts. Using disease parameters informed by the COVID-19 pandemic, we investigate the effects of various crucial mitigation features on the epidemic spreading: fraction of the infectious population that is identifiable through the tests; testing frequency; time delay between testing and isolation of positively tested individuals; and the further time delay until quarantining their contacts as well as the quarantine duration. We thus determine the required ranges for these intervention parameters to yield effective control of the disease through both considerable delaying the epidemic peak and massively reducing the total number of sustained infections.

Detection and abundance of SARS-CoV-2 in wastewater in Liechtenstein, and the estimation of prevalence and impact of the B.1.1.7 variant

The new coronavirus 2 (SARS-CoV-2) is known to be also shed through feces, which makes wastewater-based surveillance possible, independent of symptomatic cases and unbiased by any testing strategies and frequencies. We investigated the entire population of the Principality of Liechtenstein with samples from the wastewater treatment plant Bendern (serving all 39,000 inhabitants). Twenty-four-hour composite samples were taken once or twice a week during a period of 6 months from September 2020 to March 2021. Viral RNA was concentrated using the PEG centrifugation method followed by reverse transcription quantitative PCR. The aim of this research was to assess the suitability of COVID-19 fragments to relate the viral wastewater signal to the incidences and assess the impact of the emerging B.1.1.7. variant. The viral load in the wastewater peaked at almost 9 × 108 viral fragments per person equivalent (PE) and day on October 25, and showed a second peak on December 22 reaching a viral load of approximately 2 × 108 PE−1d−1. Individual testing showed a lag of 4 days and a distinct underestimation of cases at the first peak when testing frequency was low. The wastewater signal showed an immediate response on the implementation of non-pharmaceutical interventions. The new virus variant B.1.1.7. was first detected in wastewater on December 23, while it was first observed with individual testing not before January 13, 2021. Further, our data indicate that the emergence of new virus variant may change the wastewater signal, probably due to different shedding patterns, which should be considered in future models.

Sustaining success: a qualitative study of gay and bisexual men’s experiences and perceptions of HIV self-testing in a randomized controlled trial

Background HIV self-testing was proved as an effective tool for increasing testing frequency in gay and bisexual men at high risk of infection. Questions remain about understanding why HIVST encouraged testing and how such success can be translated to programmatic implementation. Methods We conducted a qualitative investigation of how FORTH participants experienced and perceived HIVST. Stratified sampling was used to recruit gay and bisexual men participating in the FORTH HIVST intervention to take part in interviews, focusing on infrequent testers and those who had received inaccurate HIVST results. Results Our analysis identified several prominent themes organized into two overarching domains from the 15 interviews: (i) aspects of HIVST contributing to HIV testing frequency, and (ii) sustaining HIVST into the future. Participants also believed that their use of HIVST in the future would depend on the test kit’s reliability, particularly when compared with highly reliable clinic-based testing. Conclusion HIVST increases the frequency of HIV testing among gay and bisexual men due, in part, to the practical, psychological, and social benefits it offers. To capitalize fully on these benefits, however, strategies to ensure the availability of highly reliable HIVST are required to sustain benefits beyond the confines of a structured research study.

Assessment of the National Test Strategy on the Development of the COVID-19 Pandemic in Denmark

During the COVID-19 pandemic, Denmark has pursued a mass testing strategy culminating in the testing of 12.167 individuals per 100,000 inhabitants per day during the spring of 2021. The strategy included free access to COVID-19 testing, and since 2021, compulsory documentation for negative tests or vaccination has been required for access to workplace, educational institutions, restaurants, and many other places. Testing and subsequent isolation if testing was positive were voluntary. The present study provides an analysis of whether testing frequency in Denmark showed any correlation to hospitalizations throughout the relevant stages of the pandemic. Mass testing was found not to correlate significantly with the number of hospitalizations during the pandemic. Interestingly, during the highest level of testing in spring 2021 the fraction of positive tests increased slightly; thus, the Danish mass testing strategy, at its best, failed to reduce the prevalence of COVID-19. Furthermore, the relationship between positives in antigen testing and in rt-PCR testing indicated that many patients were not tested early in their infection when the risk of transmission was at the highest. In conclusion, the Danish mass testing strategy for COVID-19 does not appear to have a detectable correlation to the number of hospitalizations due to COVID-19.

The stochastic dynamics of early epidemics: probability of establishment, initial growth rate, and infection cluster size at first detection

Emerging epidemics and local infection clusters are initially prone to stochastic effects that can substantially impact the early epidemic trajectory. While numerous studies are devoted to the deterministic regime of an established epidemic, mathematical descriptions of the initial phase of epidemic growth are comparatively rarer. Here, we review existing mathematical results on the size of the epidemic over time, and derive new results to elucidate the early dynamics of an infection cluster started by a single infected individual. We show that the initial growth of epidemics that eventually take off is accelerated by stochasticity. As an application, we compute the distribution of the first detection time of an infected individual in an infection cluster depending on testing effort, and estimate that the SARS-CoV-2 variant of concern Alpha detected in September 2020 first appeared in the UK early August 2020. We also compute a minimal testing frequency to detect clusters before they exceed a given threshold size. These results improve our theoretical understanding of early epidemics and will be useful for the study and control of local infectious disease clusters.