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Background: Antimicrobial resistance, particularly from methicillin-resistant Staphylococcus aureus (MRSA), is a growing global health threat. Alternative therapies derived from medicinal plants are gaining attention for their potential to combat resistant pathogens. This study aimed to evaluate the antibacterial activity of Morus alba (white mulberry) extracts and investigate their action mechanisms using proteomic analysis.

Methods: Leaf and stem samples of M. alba were extracted using both decoction and maceration techniques with water and ethanol as solvents. The antibacterial activity against MRSA was assessed through minimum inhibitory concentration (MIC), minimum bactericidal concentration (MBC), and time-kill assays. Chemical profiling of the most active extract was performed using liquid chromatography-quadrupole time-of-flight tandem mass spectrometry (LC-QTOF-MS/MS). Proteomic analysis was conducted to explore changes in bacterial protein expression after treatment.

Results: The ethanol extract of M. alba stem exhibited the strongest antibacterial activity, with MIC values ranging from 0.3125 to 20 mg/mL and MBC values from 0.6250 to 40 mg/mL. A time-kill assay demonstrated that bacterial counts fell below the detection limit within 4 hours at four times the MIC concentration, based on three independent replicates. LC-QTOF-MS/MS profiling identified betulinic acid as the most abundant compound in the extract. Proteomic analysis revealed significant changes in MRSA protein expression, including upregulation of GlmU, N-acetylneuraminate lyase, and ribonuclease E, and downregulation of ribose-phosphate pyrophosphokinase and SecA. Pathway enrichment analysis suggested that the observed protein expression changes are consistent with enhanced N-acetylneuraminate catabolism and RNA polymerase activity, and suppression of protein export and fatty acid biosynthesis.

Discussion: These findings highlight the strong anti-MRSA potential of M. alba stem extract and provide mechanistic insights into its antibacterial action. The extract disrupts critical metabolic and regulatory pathways in MRSA, supporting its potential development as a novel antimicrobial agent.

Objective: The UK government's response to the COVID-19 pandemic included a 'test, trace and isolate' strategy. Testing services for healthcare workers, care homes and schools accounted for the greatest spend and volume of tests. We reviewed relevant literature to identify common and unique barriers and facilitators to engaging with each of these testing services.

Design: Scoping review.

Search strategy: PubMed, Scopus and the WHO COVID-19 Research Database were searched for evidence published between 1 January 2020 and 7 November 2022. This was supplemented by evidence identified via free-text searches on Google Scholar and provided by the UK Health Security Agency (UKHSA).

Data extraction and synthesis: Data were extracted by a team of reviewers and synthesised thematically under the broad headings of perceptions, experiences, barriers and facilitators to engaging with the COVID-19 testing programme.

Results: This study included 40 sources, including 17 from projects that informed UKHSA's decisions during the pandemic. Eight themes emerged and were used to categorise barriers and facilitators to engaging with the testing services for healthcare workers, care homes and schools: (1) perceived value, (2) trust in the tests and public bodies, (3) importance of infrastructure, (4) impact of media and social networks, (5) physical burden of the test, (6) perceived capability to undertake testing, (7) importance of relevant information and 8) consequences of testing.

Conclusions: Universal barriers and facilitators to engagement with the testing programme related to the core elements of each testing service, such as uncomfortable specimen collection and the influence of media and peers; these could be mitigated or leveraged to increase engagement across settings. However, the individuals involved, perceptions of value and available resources differed across services, leading to unique experiences between settings. Thus, consideration of context is crucial when designing and implementing a testing programme in response to a pandemic.

Introduction: We retrospectively evaluated the impact of COVID-19 testing among residents and staff in social care homes in England.

Methods: We obtained 80 million reported PCR and lateral flow device (LFD) test results, from 14 805 care homes (residents and staff) in England, conducted between October 2020 and March 2022. These testing data were then linked to care home characteristics, test costs and 24 500 COVID-19-related deaths of residents. We decomposed the mechanism of outbreak mitigation into outbreak discovery and outbreak control and used Poisson regressions to investigate how reported testing intensity was associated with the size of outbreak discovered and to uncover its association with outbreak control. We used negative binomial regressions to determine the factors influencing COVID-19-related deaths subsequent to outbreaks. We performed a cost-effectiveness analysis of the impact of testing on preventing COVID-19-related deaths of residents.

Results: Reported testing intensity generally reflected changes in testing policy over time, although there was considerable heterogeneity among care homes. Client type was the strongest determinant of whether COVID-19-related deaths in residents occurred subsequent to testing positive. Higher staff-to-resident ratios were associated with larger outbreak sizes but rapid outbreak control and a decreased risk of COVID-19-related deaths. Assuming our regression estimates represent causal effects, care home testing in England was cost-effective at preventing COVID-19-related deaths among residents during the pandemic and approximately 3.5 times more cost-effective prior to the vaccine rollout.

Conclusions: PCR and LFD testing was likely an impactful intervention for detecting and controlling COVID-19 outbreaks in care homes in England and cost-effective for preventing COVID-19-related deaths among residents. In future pandemics, testing must be prioritised for care homes, especially if severe illness and death particularly affect older people or individuals with characteristics similar to care home residents, and an efficacious vaccine is unavailable.

Background: Parasitic helminths exhibit significant diversity, complicating both morphological and molecular species identification. Moreover, no helminth-specific tool is currently available to aid in species identification of helminths using molecular data. To address this, we developed and validated a straightforward, user-friendly application named Applying Taxonomic Boundaries for Species Identification of Helminths (ABIapp) using R and the Shiny framework. Serving as a preliminary step in species identification, ABIapp is designed to assist in visualizing taxonomic boundaries for nematodes, trematodes, and cestodes. ABIapp employs a database of genetic distance cut-offs determined by the K-means algorithm to establish taxonomic boundaries for ten genetic markers. Validation of ABIapp was performed both in silico and with actual specimens to determine its classification accuracy. The in silico validation involved 591 genetic distances sourced from 117 publications, while the validation with actual specimens utilized ten specimens. ABIapp's accuracy was also compared with other online platforms to ensure its robustness to assist in helminth identification.

Results: ABIapp achieved an overall classification accuracy of 76% for in silico validation and 75% for actual specimens. Additionally, compared to other platforms, the classification accuracy of ABIapp was superior, proving its effectiveness to determine helminth taxonomic boundaries. With its user-friendly interface, minimal data input requirements, and precise classification capabilities, ABIapp offers multiple benefits for helminth researchers and can aid in identification.

Conclusions: Built on a helminth-specific database, ABIapp serves as a pioneering tool for helminth researchers, offering an invaluable resource for determining species boundaries and aiding in species identification of helminths. The availability of ABIapp to the community of helminth researchers may further enhance research in the field of helminthology. To enhance ABIapp's accuracy and utility, the database will be updated annually.

Background: Understanding underlying mechanisms of heterogeneity in test-seeking and reporting behaviour during an infectious disease outbreak can help to protect vulnerable populations and guide equity-driven interventions. The COVID-19 pandemic probably exerted different stresses on individuals in different sociodemographic groups and ensuring fair access to and usage of COVID-19 tests was a crucial element of England's testing programme. We aimed to investigate the relationship between sociodemographic factors and COVID-19 testing behaviours in England during the COVID-19 pandemic.

Methods: We did a population-based study of COVID-19 testing behaviours with mass COVID-19 testing data for England and data from community prevalence surveillance surveys (REACT-1 and ONS-CIS) from Oct 1, 2020, to March 30, 2022. We used mass testing data for lateral flow device (LFD; data for approximately 290 million tests performed and reported) and PCR (data for approximately 107 million tests performed and returned from the laboratory) tests made available for the general public and provided by date and self-reported age and ethnicity at the lower tier local authority (LTLA) level. We also used publicly available data on mean population size estimates for individual LTLAs, and data on ethnic groups, age groups, and deprivation indices for LTLAs. We did not have access to REACT-1 or ONS-CIS prevalence data disaggregated by sex or gender. Using a mechanistic causal model to debias the PCR testing data, we obtained estimates of weekly SARS-CoV-2 prevalence by both self-reported ethnic groups and age groups for LTLAs in England. This approach to debiasing the PCR (or LFD) testing data also estimated a testing bias parameter defined as the odds of testing in infected versus not infected individuals, which would be close to zero if the likelihood of test seeking (or seeking and reporting) was the same regardless of infection status. With confirmatory PCR data, we estimated false positivity rates, sensitivity, specificity, and the rate of decline in detection probability subsequent to reporting a positive LFD for PCR tests by sociodemographic groups. We also estimated the daily incidence, allowing us to calculate the fraction of cases captured by the testing programme.

Findings: From March, 2021 onwards, individuals in the most deprived regions reported approximately half as many LFD tests per capita as individuals in the least deprived areas (median ratio 0·50 [IQR 0·44-0·54]). During the period October, 2020, to June, 2021, PCR testing patterns showed the opposite trend, with individuals in the most deprived areas performing almost double the number of PCR tests per capita than those in the least deprived areas (1·8 [1·7-1·9]). Infection prevalences in Asian or Asian British individuals were considerably higher than those of other ethnic groups during the alpha (B.1.1.7) and omicron (B.1.1.529) BA.1 waves. Our estimates indicate that the England Pillar 2 COVID-19 testing programme detected 26-40% of all cases (including asymptomatic cases) over the study period with no consistent differences by deprivation levels or ethnic groups. Testing biases for PCR were generally higher than those for LFDs, in line with the general policy of symptomatic and asymptomatic use of these tests. Deprivation and age were associated with testing biases on average; however, the uncertainty intervals overlapped across deprivation levels, although the age-specific patterns were more distinct. We also found that ethnic minorities and older individuals were less likely to use confirmatory PCR tests through most of the pandemic and that delays in reporting a positive LFD test were possibly longer in populations self-reporting as "Black; African; Black British or Caribbean".

Interpretation: Differences in testing behaviours across sociodemographic groups might be reflective of the higher costs of self-isolation to vulnerable populations, differences in test accessibility, differences in digital literacy, and differing perceptions about the utility of tests and risks posed by infection. This study shows how mass testing data can be used in conjunction with surveillance surveys to identify gaps in the uptake of public health interventions both at fine-scale levels and across sociodemographic groups. It provides a framework for monitoring local interventions and yields valuable lessons for policy makers in ensuring an equitable response to future pandemics.

Funding: UK Health Security Agency.

Background: Hepatitis C Virus is endemic to many areas of Thailand, whose population structure is tending towards older age groups as birth rate and mortality decrease. With around 790,000 cases in 2019, prevalence is still relatively high, but the World Health Organisation has called for elimination of HCV by 2030.

Methods: An age structured compartmental transmission model was used to explore the effectiveness of screening strategies with respect to WHO elimination goals, as well as the effect of changing population structure on the success or failure of such strategies.

Results: Population structure did not appear to affect the timeline of elimination targets and screening individuals over the age of 30 at a high (50% per year) coverage could bring forward achievement of the incidence elimination target by four years compared to baseline (approximately 6% per year). Achievement of mortality elimination targets was not reached until after the end of the simulation (2040), and intensive screening strategies did not appear to lead to incidence elimination by 2030.

Conclusion: The model suggested that with age-targeted screening programmes incidence elimination could be brought forward by several years. However, WHO elimination goals may not be met by 2030.

Context: Plant peptides garner attention for their potential antimicrobial properties amid the rising concern over antibiotic-resistant bacteria.

Objective: This study investigates the antibacterial potential of crude peptide extracts from 27 Thai plants collected locally.

Materials and methods: Peptide extracts from 34 plant parts, derived from 27 Thai plants, were tested for their antimicrobial efficacy against four highly resistant bacterial strains: Streptococcus aureus MRSA, Pseudomonas aeruginosa, Acinetobacter baumannii, and Escherichia coli. The stability of these peptide extracts was examined at different temperatures, and the synergistic effects of two selected plant peptide extracts were investigated. Additionally, the time-kill kinetics of the individual extracts and their combination were determined against the tested pathogens.

Results: Peptides from Allium sativum L. and Allium oschaninii O. Fedtsch (Amaryllidaceae) were particularly potent, inhibiting bacterial growth with MICs ranging from 1.43 to 86.50 µg/mL. The consistent MICs and MBCs of these extracts across various extraction time points highlight their reliability. Stability tests reveal that these peptides maintain their antimicrobial activity at -20 °C for over a month, emphasizing their durability for future exploration and potential applications in addressing antibiotic resistance. Time-kill assays elucidate the time and concentration-dependent nature of these antimicrobial effects, underscoring their potent initial activity and sustained efficacy over time.

Discussion and conclusions: This study highlights the antimicrobial potential of Allium-derived peptides, endorsing them for combating antibiotic resistance and prompting further investigation into their mechanisms.

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Background: Malaria continues to pose a significant health threat. Rapid identification of malaria infections and the deployment of active surveillance tools are crucial for achieving malaria elimination in regions where malaria is endemic, such as certain areas of Thailand. In this study, an anomaly detection system is introduced as an early warning mechanism for potential malaria outbreaks in countries like Thailand.

Methods: Unsupervised clustering-based, and time series-based anomaly detection algorithms are developed and compared to identify abnormal malaria activity in Thailand. Additionally, a user interface tailored for anomaly detection is designed, enabling the Thai malaria surveillance team to utilize these algorithms and visualize regions exhibiting unusual malaria patterns.

Results: Nine distinct anomaly detection algorithms we developed. Their efficacy in pinpointing verified outbreaks was assessed using malaria case data from Thailand spanning 2012 to 2022. The historical average threshold-based anomaly detection method triggered three times fewer alerts, while correctly identifying the same number of verified outbreaks when compared to the current method used in Thailand. A limitation of this analysis is the small number of verified outbreaks; further consultation with the Division of Vector Borne Disease could help identify more verified outbreaks. The developed dashboard, designed specifically for anomaly detection, allows disease surveillance professionals to easily identify and visualize unusual malaria activity at a provincial level across Thailand.

Conclusion: An enhanced early warning system is proposed to bolster malaria elimination efforts for countries with a similar malaria profile to Thailand. The developed anomaly detection algorithms, after thorough comparison, have been optimized for integration with the current malaria surveillance infrastructure. An anomaly detection dashboard for Thailand is built and supports early detection of abnormal malaria activity. In summary, the proposed early warning system enhances the identification process for provinces at risk of outbreaks and offers easy integration with Thailand's established malaria surveillance framework.

Background: The artemisinins are potent and widely used antimalarial drugs that are eliminated rapidly. A simple concentration-effect pharmacometric model does not explain why dosing more frequently than once daily fails to augment parasite clearance and improve therapeutic responses in vivo. Artemisinins can induce a temporary non-replicative or 'dormant' drug refractory state in Plasmodium falciparum malaria parasites which may explain recrudescences observed in clinical trials despite full drug susceptibility, but whether it explains the dosing-response relationship is uncertain.

Objectives: To propose a revised model of antimalarial pharmacodynamics that incorporates reversible asexual parasite injury and temporary drug refractoriness in order to explain the failure of frequent dosing to augment therapeutic efficacy in falciparum malaria.

Methods: The model was fitted using a Bayesian Markov Chain Monte Carlo approach with the parasite clearance data from 39 patients with uncomplicated falciparum malaria treated with artesunate from western Cambodia and 40 patients from northwestern Thailand reported previously.

Results: The revised model captured the dynamics of parasite clearance data. Its predictions are consistent with observed therapeutic responses.

Conclusions: A within-host pharmacometric model is proposed in which it is hypothesized that some malaria parasites enter a temporary drug refractory state after exposure to artemisinin antimalarials, which is followed by delayed parasite death or reactivation. The model fitted the observed sequential parasite density data from patients with acute P. falciparum malaria, and it supported reduced ring stage activity in artemisinin-resistant infections.

Summary: Thailand faced a dilemma of which groups to prioritise with a limited first tranche of COVID-19 vaccinations in early 2021, at a time when there was low incidence and low mortality in the country. A mathematical modelling analysis was performed to compare the potential short-term impact of allocating the available doses to either the high severity group (over 65-year-olds) or the high transmission group (aged 20-39). At the time of the analysis, there was uncertainty about the precise characteristics of the vaccines available, in terms of their potential impact on transmission and reductions to the severity of infection. As such, a range of vaccine characteristic scenarios, with differing levels of severity and transmission reductions were explored. Using the evidence available at the time regarding severity reduction of infection due to the vaccines, the model suggested that vaccinating high severity group should be the priority if reductions in deaths is the priority. Vaccinating this group was found to have a direct impact on reducing the number of deaths, while the incidence and hospitalisations remained unchanged. However, the model found that vaccinating the high transmission group with a vaccine with sufficiently high protection against infection (more than 70%) could provide enough herd effects to delay the expected epidemic peak, resulting in both case and death reductions in both target groups. The model explored a 12-month time horizon. These analyses helped to inform the vaccination strategy in Thailand throughout 2021 and can inform future modelling studies for policymaking when the characteristics of vaccines are uncertain.