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Despite much progress, image processing remains a significant bottleneck for high-throughput analysis of microscopy data. One popular platform for single-cell time-lapse imaging is the mother machine, which enables long-term tracking of microbial cells under precisely controlled growth conditions. While several mother machine image analysis pipelines have been developed in the past several years, adoption by a non-expert audience remains a challenge. To fill this gap, we implemented our own software, MM3, as a plugin for the multidimensional image viewer napari. napari-MM3 is a complete and modular image analysis pipeline for mother machine data, which takes advantage of the high-level interactivity of napari. Here, we give an overview of napari-MM3 and test it against several well-designed and widely used image analysis pipelines, including BACMMAN and DeLTA. Researchers often analyze mother machine data with custom scripts using varied image analysis methods, but a quantitative comparison of the output of different pipelines has been lacking. To this end, we show that key single-cell physiological parameter correlations and distributions are robust to the choice of analysis method. However, we also find that small changes in thresholding parameters can systematically alter parameters extracted from single-cell imaging experiments. Moreover, we explicitly show that in deep learning-based segmentation, what you put is what you get (WYPIWYG) - that is, pixel-level variation in training data for cell segmentation can propagate to the model output and bias spatial and temporal measurements. Finally, while the primary purpose of this work is to introduce the image analysis software that we have developed over the last decade in our lab, we also provide information for those who want to implement mother machine-based high-throughput imaging and analysis methods in their research.

Host-directed therapy (HDT) is an emerging approach to overcome antimicrobial resistance in pathogenic microorganisms. Specifically, HDT targets host-encoded factors required for pathogen replication and survival without interfering with microbial growth or metabolism, thereby eliminating the risk of resistance development. By applying HDT and a drug repurposing approach, we demonstrate that (R)-DI-87, a clinical-stage anticancer drug and potent inhibitor of mammalian deoxycytidine kinase (dCK), mitigates Staphylococcus aureus abscess formation in organ tissues upon invasive bloodstream infection. Mechanistically, (R)-DI-87 shields phagocytes from staphylococcal death-effector deoxyribonucleosides that target dCK and the mammalian purine salvage pathway-apoptosis axis. In this manner, (R)-DI-87-mediated protection of immune cells amplifies macrophage infiltration into deep-seated abscesses, a phenomenon coupled with enhanced pathogen control, ameliorated immunopathology, and reduced disease severity. Thus, pharmaceutical blockade of dCK represents an advanced anti-infective intervention strategy against which staphylococci cannot develop resistance and may help to fight fatal infectious diseases in hospitalized patients.

Infection, autoimmunity, and cancer are principal human health challenges of the 21st century. Often regarded as distinct ends of the immunological spectrum, recent studies hint at potential overlap between these diseases. For example, inflammation can be pathogenic in infection and autoimmunity. T resident memory (TRM) cells can be beneficial in infection and cancer. However, these findings are limited by size and scope; exact immunological factors shared across diseases remain elusive. Here, we integrate large-scale deeply clinically and biologically phenotyped human cohorts of 526 patients with infection, 162 with lupus, and 11,180 with cancer. We identify an NKG2A+ immune bias as associative with protection against disease severity, mortality, and autoimmune/post-acute chronic disease. We reveal that NKG2A+ CD8+ T cells correlate with reduced inflammation and increased humoral immunity and that they resemble TRM cells. Our results suggest NKG2A+ biases as a cross-disease factor of protection, supporting suggestions of immunological overlap between infection, autoimmunity, and cancer.

It remains poorly understood how SARS-CoV-2 infection influences the physiological host factors important for aerosol transmission. We assessed breathing pattern, exhaled droplets, and infectious virus after infection with Alpha and Delta variants of concern (VOC) in the Syrian hamster. Both VOCs displayed a confined window of detectable airborne virus (24-48 hr), shorter than compared to oropharyngeal swabs. The loss of airborne shedding was linked to airway constriction resulting in a decrease of fine aerosols (1-10 µm) produced, which are suspected to be the major driver of airborne transmission. Male sex was associated with increased viral replication and virus shedding in the air. Next, we compared the transmission efficiency of both variants and found no significant differences. Transmission efficiency varied mostly among donors, 0-100% (including a superspreading event), and aerosol transmission over multiple chain links was representative of natural heterogeneity of exposure dose and downstream viral kinetics. Co-infection with VOCs only occurred when both viruses were shed by the same donor during an increased exposure timeframe (24-48 hr). This highlights that assessment of host and virus factors resulting in a differential exhaled particle profile is critical for understanding airborne transmission.

OBJECTIVES: The study aimed to compare the risk of gastrointestinal infections among patients with and without metabolic dysfunction-associated fatty liver disease (MAFLD). METHODS: This was a population-based, retrospective, observational study using data from the National Inpatient Sample (NIS), the largest all-payer US inpatient care database. SETTING: Hospitalisation of adults aged ≥18 years old admitted in 2020 was identified using the NIS. Patients were stratified by the presence and absence of MAFLD. PARTICIPANTS: 26.4 million adults aged ≥18 years old were included in the study. Patients younger than 18 and those with missing demographic or mortality data were excluded. PRIMARY AND SECONDARY OUTCOMES: Primary outcome was to assess the overall risk of gastrointestinal infections in patients with and without MAFLD. Secondary outcomes were demographics and comorbidities stratified by the presence or absence of gastrointestinal infection, and the risk of specific gastrointestinal pathogens. RESULTS: Of 26.4 million patients admitted in 2020, 755 910 (2.85%) had the presence of MAFLD. There was a higher prevalence of bacterial gastrointestinal infections in patients with MAFLD than those without (1.6% vs 0.9%, p

BK virus (BKV) is a small DNA virus, a member of the polyomavirus family, that causes an opportunistic infection in immunocompromised patients, especially kidney transplant patients. This virus establishes a lifelong infection in most of the population, and once it reactivates in an immunocompromised state, leads to BKV nephropathy. This review seeks to assess the correlation between severe immunosuppression, evident by low CD4 cell counts in HIV-positive patients, and the reactivation of BKV, causing nephropathy. A literature review was conducted, extracting, and analyzing case reports of HIV-positive patients showing correlations between their degree of immunosuppression, as evidenced by their CD4 counts, and the degree of BKV infectivity, confirmed by kidney biopsy. A total of 12 cases of BKV nephropathy in HIV-infected patients were reviewed. A common finding was the presence of profound immunosuppression, with most patients having CD4 counts ≤50 cells/ mm3. A substantial number also had comorbid malignancies, with some undergoing chemotherapy, potentially increasing the risk of BKV reactivation. In addition to the HIV status and malignancies, other risk factors for BKV reactivation included older age, male gender, diabetes mellitus, Caucasian race, and ureteral stent placement. BKV nephropathy in HIV patients with native kidneys is closely correlated with severe immunosuppression. Although therapeutic strategies exist for post-transplant patients, aside from the treatment of HIV with highly active anti-retroviral therapy (HAART), which potentially helps with clearing BKV by increasing CD4 count, there is no definitive treatment for a native kidney BKV nephropathy in patients with AIDS. The complexity of the cases and severity of comorbidities indicate the need for further research to develop therapeutic strategies tailored to this population.

INTRODUCTION: Climate change is a global phenomenon with far-reaching consequences, and its impact on human health is a growing concern. The intricate interplay of various factors makes it challenging to accurately predict and understand the implications of climate change on human well-being. Conventional methodologies have limitations in comprehensively addressing the complexity and nonlinearity inherent in the relationships between climate change and health outcomes. OBJECTIVES: The primary objective of this paper is to develop a robust theoretical framework that can effectively analyze and interpret the intricate web of variables influencing the human health impacts of climate change. By doing so, we aim to overcome the limitations of conventional approaches and provide a more nuanced understanding of the complex relationships involved. Furthermore, we seek to explore practical applications of this theoretical framework to enhance our ability to predict, mitigate, and adapt to the diverse health challenges posed by a changing climate. METHODS: Addressing the challenges outlined in the objectives, this study introduces the Complex Adaptive Systems (CAS) framework, acknowledging its significance in capturing the nuanced dynamics of health effects linked to climate change. The research utilizes a blend of field observations, expert interviews, key informant interviews, and an extensive literature review to shape the development of the CAS framework. RESULTS AND DISCUSSION: The proposed CAS framework categorizes findings into six key sub-systems: ecological services, extreme weather, infectious diseases, food security, disaster risk management, and clinical public health. The study employs agent-based modeling, using causal loop diagrams (CLDs) tailored for each CAS sub-system. A set of identified variables is incorporated into predictive modeling to enhance the understanding of health outcomes within the CAS framework. Through a combination of theoretical development and practical application, this paper aspires to contribute valuable insights to the interdisciplinary field of climate change and health. Integrating agent-based modeling and CLDs enhances the predictive capabilities required for effective health outcome analysis in the context of climate change. CONCLUSION: This paper serves as a valuable resource for policymakers, researchers, and public health professionals by employing a CAS framework to understand and assess the complex network of health impacts associated with climate change. It offers insights into effective strategies for safeguarding human health amidst current and future climate challenges.

Drug resistance remains a major obstacle to malaria control and eradication efforts, necessitating the development of novel therapeutic strategies to treat this disease. Drug combinations based on collateral sensitivity, wherein resistance to one drug causes increased sensitivity to the partner drug, have been proposed as an evolutionary strategy to suppress the emergence of resistance in pathogen populations. In this study, we explore collateral sensitivity between compounds targeting the Plasmodium dihydroorotate dehydrogenase (DHODH). We profiled the cross-resistance and collateral sensitivity phenotypes of several DHODH mutant lines to a diverse panel of DHODH inhibitors. We focus on one compound, TCMDC-125334, which was active against all mutant lines tested, including the DHODH C276Y line, which arose in selections with the clinical candidate DSM265. In six selections with TCMDC-125334, the most common mechanism of resistance to this compound was copy number variation of the dhodh locus, although we did identify one mutation, DHODH I263S, which conferred resistance to TCMDC-125334 but not DSM265. We found that selection of the DHODH C276Y mutant with TCMDC-125334 yielded additional genetic changes in the dhodh locus. These double mutant parasites exhibited decreased sensitivity to TCMDC-125334 and were highly resistant to DSM265. Finally, we tested whether collateral sensitivity could be exploited to suppress the emergence of resistance in the context of combination treatment by exposing wildtype parasites to both DSM265 and TCMDC-125334 simultaneously. This selected for parasites with a DHODH V532A mutation which were cross-resistant to both compounds and were as fit as the wildtype parent in vitro. The emergence of these cross-resistant, evolutionarily fit parasites highlights the mutational flexibility of the DHODH enzyme.

BACKGROUND: The Global Typhoid Genomics Consortium was established to bring together the typhoid research community to aggregate and analyse Salmonella enterica serovar Typhi (Typhi) genomic data to inform public health action. This analysis, which marks 22 years since the publication of the first Typhi genome, represents the largest Typhi genome sequence collection to date (n=13,000). METHODS: This is a meta-analysis of global genotype and antimicrobial resistance (AMR) determinants extracted from previously sequenced genome data and analysed using consistent methods implemented in open analysis platforms GenoTyphi and Pathogenwatch. RESULTS: Compared with previous global snapshots, the data highlight that genotype 4.3.1 (H58) has not spread beyond Asia and Eastern/Southern Africa; in other regions, distinct genotypes dominate and have independently evolved AMR. Data gaps remain in many parts of the world, and we show the potential of travel-associated sequences to provide informal sentinel surveillance for such locations. The data indicate that ciprofloxacin non-susceptibility (>1 resistance determinant) is widespread across geographies and genotypes, with high-level ciprofloxacin resistance (≥3 determinants) reaching 20% prevalence in South Asia. Extensively drug-resistant (XDR) typhoid has become dominant in Pakistan (70% in 2020) but has not yet become established elsewhere. Ceftriaxone resistance has emerged in eight non-XDR genotypes, including a ciprofloxacin-resistant lineage (4.3.1.2.1) in India. Azithromycin resistance mutations were detected at low prevalence in South Asia, including in two common ciprofloxacin-resistant genotypes. CONCLUSIONS: The consortiums aim is to encourage continued data sharing and collaboration to monitor the emergence and global spread of AMR Typhi, and to inform decision-making around the introduction of typhoid conjugate vaccines (TCVs) and other prevention and control strategies. FUNDING: No specific funding was awarded for this meta-analysis. Coordinators were supported by fellowships from the European Union (ZAD received funding from the European Unions Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 845681), the Wellcome Trust (SB, Wellcome Trust Senior Fellowship), and the National Health and Medical Research Council (DJI is supported by an NHMRC Investigator Grant [GNT1195210]).

BackgroundNeuropsychiatric symptoms (NPS) and cognitive impairment are highly prevalent among persons with HIV (PWH). We examined the effect of the most common NPS, depression and anxiety, on cognitive change among PWH and compared these associations to those among persons without HIV (PWoH).MethodsParticipants included 168 PWH and 91 PWoH who completed baseline self-report measures of depression (Beck Depression Inventory-II) and anxiety (Profile of Mood States [POMS] - Tension-anxiety subscale) and completed a comprehensive neurocognitive evaluation at baseline and at 1-year follow-up. Demographically-corrected scores from 15 neurocognitive tests were used to calculate global and domain-specific T-scores. Linear mixed-effects models examined the effect of depression and anxiety and their interaction with HIV-serostatus and time on global T-scores.ResultsThere were significant depression-by-HIV and anxiety-by-HIV interactions on global T-scores such that, among PWH only, greater depressive and anxiety symptoms at baseline related to worse global T-scores across visits. Non-significant interactions with time suggest stability in these relationships across visits. Follow-up analyses examining cognitive domains revealed that both the depression-by-HIV and the anxiety-by-HIV interactions were driven by learning and recall.LimitationsFollow-up was limited to one-year and there were fewer PWoH than PWH, creating a differential in statistical power.ConclusionFindings suggest that anxiety and depression have stronger links to worse cognitive functioning in PWH than PWoH, particularly learning and memory, and that these associations seem to persist for at least one-year.

BACKGROUNDAutoimmune diseases often have strong genetic associations with specific HLA-DR alleles. The synovial lesion in chronic inflammatory forms of arthritis shows marked upregulation of HLA-DR molecules, including in postinfectious Lyme arthritis (LA). However, the identity of HLA-DR-presented peptides, and therefore the reasons for these associations, has frequently remained elusive.METHODSUsing immunopeptidomics to detect HLA-DR-presented peptides from synovial tissue, we identified T cell epitopes from 3 extracellular matrix (ECM) proteins in patients with postinfectious LA, identified potential Borreliella burgdorferi-mimic (Bb-mimic) epitopes, and characterized T and B cell responses to these peptides or proteins.RESULTSOf 24 postinfectious LA patients, 58% had CD4+ T cell responses to at least 1 epitope of 3 ECM proteins, fibronectin-1, laminin B2, and/or collagen Vα1, and 17% of 52 such patients had antibody responses to at least 1 of these proteins. Patients with autoreactive T cell responses had significantly increased frequencies of HLA-DRB1*04 or -DRB1*1501 alleles and more prolonged arthritis. When tetramer reagents were loaded with ECM or corresponding Bb-mimic peptides, binding was only with the autoreactive T cells. A high percentage of ECM-autoreactive CD4+ T cells in synovial fluid were T-bet-expressing Th1 cells, a small percentage were RoRγt-expressing Th17 cells, and a minimal percentage were FoxP3-expressing Tregs.CONCLUSIONAutoreactive, proinflammatory CD4+ T cells and autoantibodies develop to ECM proteins in a subgroup of postinfectious LA patients who have specific HLA-DR alleles. Rather than the traditional molecular mimicry model, we propose that epitope spreading provides the best explanation for this example of infection-induced autoimmunity.FUNDINGSupported by National Institute of Allergy and Infectious Diseases R01-AI101175, R01-AI144365, and F32-AI125764; National Institute of Arthritis and Musculoskeletal and Skin Diseases K01-AR062098 and T32-AR007258; NIH grants P41-GM104603, R24-GM134210, S10-RR020946, S10-OD010724, S10-OD021651, and S10-OD021728; and the G. Harold and Leila Y. Mathers Foundation, the Eshe Fund, and the Lyme Disease and Arthritis Research Fund at Massachusetts General Hospital.

BackgroundThe health status of people with HIV (PWH) influences their health-related quality of life (HRQOL). Modifiable lifestyle factors may improve HRQOL. This study (1) explores the association between modifiable lifestyle factors (physical activity and nutrition) and HRQOL and (2) examines if these lifestyle factors moderate the association health status and HRQOL.MethodsParticipants included 91 community dwelling PWH (age 36-65 years) from the university lab. Participants reported mental and physical HRQOL via the Medical Outcome Study 36-Item Short-Form (SF-36). Physical activity was examined via the International Physical Activity Questionnaire and nutrition (i.e., fruit and vegetable consumption) was assessed with the By-Meal Screener. Health status was ascertained via the Veterans Aging Cohort Study (VACS) Index.ResultsAim 1 analyses indicated that neither physical activity nor nutrition was related to mental HRQOL (p's > .05). However, greater physical activity (β = .33, p  .05).ConclusionPhysical HRQOL is related to self-reported physical activity and nutrition, with nutrition showing a moderating effect on the association between health status and physical HRQOL. Thus, future interventional studies designed to improve physical HRQOL should target both physical activity and nutrition.

Abstract This study aimed to evaluate the blood bacterial microbiota in healthy and febrile cats. High-quality sequencing reads from the 16S rRNA gene variable region V3-V4 were obtained from genomic blood DNA belonging to 145 healthy cats, and 140 febrile cats. Comparisons between the blood microbiota of healthy and febrile cats revealed dominant presence of Actinobacteria, followed by Firmicutes and Proteobacteria, and a lower relative abundance of Bacteroidetes. Upon lower taxonomic levels, the bacterial composition was significantly different between healthy and febrile cats. The families Faecalibacterium and Kineothrix (Firmicutes), and Phyllobacterium (Proteobacteria) experienced increased abundance in febrile samples. Whereas Thioprofundum (Proteobacteria) demonstrated a significant decrease in abundance in febrile. The bacterial composition and beta diversity within febrile cats was different according to the affected body system (Oral/GI, systemic, skin, and respiratory) at both family and genus levels. Sex and age were not significant factors affecting the blood microbiota of febrile cats nor healthy ones. Age was different between young adult and mature adult healthy cats. Alpha diversity was unaffected by any factors. Overall, the findings suggest that age, health status and nature of disease are significant factors affecting blood microbiota diversity and composition in cats, but sex is not.

Japanese Encephalitis (JE) poses a significant public health threat across Asia and the Western Pacific, leading to considerable mortality and morbidity if not promptly diagnosed and treated. This flaviviral infection, transmitted by Culex mosquitoes, primarily affects children but can impact individuals of all ages. Prompt diagnosis relies on detecting Japanese Encephalitis Virus (JEV) IgM antibodies in serum or Cerebrospinal Fluid (CSF), alongside characteristic Magnetic Resonance Imaging (MRI) findings. In this MRI case series, three confirmed cases of JE are presented, showcasing the typical neuroimaging manifestations observed in affected individuals. All cases exhibited bilateral thalamic hyperintensities on T2-weighted and Fluid Attenuated Inversion Recovery (FLAIR) images, a hallmark feature of JE. Additionally, one patient demonstrated involvement of the substantia nigra and bilateral frontal cortex. The clinical implications of present study findings underscore the importance of considering JE as a differential diagnosis in patients presenting with symptoms of encephalitis, especially when MRI reveals bi-thalamic signal alterations. Early recognition and initiation of appropriate treatment, including antiviral agents, are crucial for improving outcomes and reducing mortality. This study contributes to the existing literature by reinforcing the importance of neuroimaging in diagnosing JE and highlighting the distinct MRI patterns associated with the disease. Recognising these characteristic imaging features can aid clinicians in promptly identifying and managing JE cases, thereby mitigating the associated morbidity and mortality.

Background: Infectious diseases impose a significant burden on the global public health and economy, resulting in an estimated 15 million deaths out of 57 million annually worldwide. This study examines the current state of CRISPR-Cas12/Cas13 research, focusing on its applications in infectious disease detection and its evolutionary trajectory. Methods: A bibliometric analysis and systematic review were conducted by retrieving CRISPR-Cas12/Cas13-related articles published between January 1, 2015 to December 31, 2022, from the Web of Science database. The research protocol was registered with International Platform of Registered Systematic Review and Meta-analysis Protocols (INPLASY202380062). Results: Our search identified 1987 articles, of which, 1856 were included in the bibliometric analysis and 445 were used in qualitative analysis. The study reveals a substantial increase in scientific production on CRISPR-Cas12/Cas13, with an annual growth rate of 104.5%. The United States leads in the number of published articles. The systematic review identified 580 different diagnostic assays targeting 170 pathogens, with SARS-CoV-2 dominating with 158 assays. Recombinase polymerase amplification (RPA)/reverse transcription-RPA (RT-RPA) emerged as the predominant amplification method, while lateral flow assay was the most common readout method. Approximately 72% of the diagnostic assays developed are suitable for point-of-care testing. Conclusion: The rapid increase in research on CRISPR-Cas12/Cas13 between 2015 and 2022 suggests promising potential for advancements in infectious disease diagnosis. Given the numerous advantages of CRISPR-Cas technology for disease detection over other methods, and the dedicated efforts of scientists from around the world, it is reasonable to anticipate that CRISPR-Cas technology may emerge as a formidable alternative, offering the possibility of expedited point-of-care testing in the not-too-distant future.

Abstract Measles remains a significant threat to children worldwide despite the availability of effective vaccines. The COVID-19 pandemic exacerbated the situation by leading to the postponement of supplementary measles immunization activities. Along with this postponement, measles surveillance also deteriorated, with the lowest number of submitted specimens in over a decade. In this study, we focus on measles as a challenging case study due to its high vaccination coverage, which leads to smaller outbreaks and potentially weaker signals on Google Trends. Our research aimed to explore the feasibility of using Google Trends for real-time monitoring of infectious disease outbreaks. We evaluated the correlation between Google Trends searches and clinical case data using the Pearson correlation coefficient and Spearman’s rank correlation coefficient across 30 European countries and Japan. The results revealed that Google Trends was most suitable for monitoring acute disease outbreaks at the regional level in high-income countries, even when there are only a few weekly cases. For example, from 2017 to 2019, the Pearson correlation coefficient was 0.86 (p-value< 0.05) at the prefecture level for Okinawa, Japan, versus 0.33 (p-value< 0.05) at the national level for Japan. Furthermore, we found that the Pearson correlation coefficient may be more suitable than Spearman’s rank correlation coefficient for evaluating the correlations between Google Trends search data and clinical case data. This study highlighted the potential of utilizing Google Trends as a valuable tool for timely public health interventions to respond to infectious disease outbreaks, even in the context of diseases with high vaccine coverage.

Abstract Background Monkeypox is an emerging infectious disease with confirmed cases and deaths in several parts of the world. In light of this crisis, this study aims to analyze the global knowledge pattern of monkeypox-related patents and explore current trends and future technical directions in the medical development of monkeypox to inform research and policy. Methods A comprehensive study of 1,791 monkeypox-related patents worldwide was conducted using the Derwent patent database by descriptive statistics, social network method and linear regression analysis. Results Since the 21st century, the number of monkeypox-related patents has increased rapidly, accompanied by increases in collaboration between commercial and academic patentees. Enterprises contributed the most in patent quantity, whereas the initial milestone patent was filed by academia. The core developments of technology related to the monkeypox include biological and chemical medicine. The innovations of vaccines and virus testing lack sufficient patent support in portfolios. Conclusions Monkeypox-related therapeutic innovation is geographically limited with strong international intellectual property right barriers though it has increased rapidly in recent years. The transparent licensing of patent knowledge is driven by the merger and acquisition model, and the venture capital, intellectual property and contract research organization model. Currently, the patent thicket phenomenon in the monkeypox field may slow the progress of efforts to combat monkeypox. Enterprises should pay more attention to the sharing of technical knowledge, make full use of drug repurposing strategies, and promote innovation of monkeypox-related technology in hotspots of antivirals (such as tecovirimat, cidofovir, brincidofovir), vaccines (JYNNEOS, ACAM2000), herbal medicine and gene therapy.

Abstract Background The use of systems engineering tools, including the development and use of care cascades using routinely collected data, process mapping, and continuous quality improvement, is used for frontline healthcare workers to devise systems level change. South Africa experiences high rates of tuberculosis (TB) infection and disease as well as HIV co-infection. The Department of Health has made significant gains in HIV services over the last two decades, reaching their set “90–90-90” targets for HIV. However, TB services, although robust, have lagged in comparison for both disease and infection. The Systems Analysis and Improvement Approach (SAIA) is a five-step implementation science method, drawn from systems engineering, to identify, define, and implement workflow modifications using cascade analysis, process mapping, and repeated quality improvement cycles within healthcare facilities. Methods This stepped-wedge cluster randomized trial will evaluate the effectiveness of SAIA on TB (SAIA-TB) cascade optimization for patients with TB and high-risk contacts across 16 clinics in four local municipalities in the Sarah Baartman district, Eastern Cape, South Africa. We hypothesize that SAIA-TB implementation will lead to a 20% increase in each of: TB screening, TB preventive treatment initiation, and TB disease treatment initiation during the 18-month intervention period. Focus group discussions and key informant interviews with clinic staff will also be conducted to determine drivers of implementation variability across clinics. Discussion This study has the potential to improve TB screening, treatment initiation, and completion for both active disease and preventive measures among individuals with and without HIV in a high burden setting. SAIA-TB provides frontline health care workers with a systems-level view of their care delivery system with the aim of sustainable systems-level improvements. Trial registration Clinicaltrials.gov, NCT06314386. Registered 18 March 2024, https://clinicaltrials.gov/study/NCT06314386 . NCT06314386.

Abstract Background Defining healthcare facility catchment areas is a key step in predicting future healthcare demand in epidemic settings. Forecasts of hospitalisations can be informed by leading indicators measured at the community level. However, this relies on the definition of so-called catchment areas or the geographies whose populations make up the patients admitted to a given hospital, which are often not well-defined. Little work has been done to quantify the impact of hospital catchment area definitions on healthcare demand forecasting. Methods We made forecasts of local-level hospital admissions using a scaled convolution of local cases (as defined by the hospital catchment area) and delay distribution. Hospital catchment area definitions were derived from either simple heuristics (in which people are admitted to their nearest hospital or any nearby hospital) or historical admissions data (all emergency or elective admissions in 2019, or COVID-19 admissions), plus a marginal baseline definition based on the distribution of all hospital admissions. We evaluated predictive performance using each hospital catchment area definition using the weighted interval score and considered how this changed by the length of the predictive horizon, the date on which the forecast was made, and by location. We also considered the change, if any, in the relative performance of each definition in retrospective vs. real-time settings, or at different spatial scales. Results The choice of hospital catchment area definition affected the accuracy of hospital admission forecasts. The definition based on COVID-19 admissions data resulted in the most accurate forecasts at both a 7- and 14-day horizon and was one of the top two best-performing definitions across forecast dates and locations. The “nearby” heuristic also performed well, but less consistently than the COVID-19 data definition. The marginal distribution baseline, which did not include any spatial information, was the lowest-ranked definition. The relative performance of the definitions was larger when using case forecasts compared to future observed cases. All results were consistent across spatial scales of the catchment area definitions. Conclusions Using catchment area definitions derived from context-specific data can improve local-level hospital admission forecasts. Where context-specific data is not available, using catchment areas defined by carefully chosen heuristics is a sufficiently good substitute. There is clear value in understanding what drives local admissions patterns, and further research is needed to understand the impact of different catchment area definitions on forecast performance where case trends are more heterogeneous.

AbstractBackground There has been a notable decrease in antibiotic prescribing in the last thirty years in Sweden. Little is known about factors influencing antibiotic prescribing over several years.Objective To compare primary care physicians who, over time, reduced their antibiotic prescribing for respiratory tract infections with those who remained either high or low prescribers regarding potentially influencing factors.Design and setting A register-based study including all RTI visits in primary care in Region Kronoberg, Sweden 2006–2014. The data were divided into three 3-year periods.Subjects The data comprised all physicians who had diagnosed at least one RTI for each of the three-year periods. The antibiotic prescribing rate adjusted for the patients’ sex and age group was calculated for each physician and period, and based on the change between the first and the third period, the physicians were divided into three prescriber groups: The High Prescribing Group, the Decreasing Prescribing Group, and the Low Prescribing Group.Main outcome measures For the three prescriber groups, we compared factors influencing antibiotic prescribing such as the characteristics of the physicians, their use of point-of-care tests, their choice of diagnoses, and whether the patients returned and received antibiotics.Results The High Prescribing Group ordered more point-of-care tests, registered more potential bacterial diagnoses, prescribed antibiotics at lower C-reactive protein levels, and prescribed antibiotics more often despite negative group A Streptococci test than in the Low Prescribing Group. The Decreasing Prescribing Group was between the High Prescribing Group and the Low Prescribing Group regarding these variables. The lower prescription rate in the Low Prescribing Group did not result in more return visits or new antibiotic prescriptions within 30 days.Conclusion Point-of-care testing and its interpretation differed between the prescriber groups. Focus on interpreting point-of-care test results could be a way forward in antibiotic stewardship.

Objectives: Although studies have revealed that dentists’ mental health was initially affected by the COVID-19 pandemic, there are no reports on how this notion has evolved during the pandemic years. The aim of this study therefore was to compare Thai dentists’ stress prevalence and levels due to the pandemic over a three period of the pandemic, 2020, 2021, and 2022. The associated risk and protective factors were also investigated. Methods: A questionnaire was distributed to Thai dentists via social media, that is, Facebook pages and Line groups, from April 24 through May 5, 2020, June 10 through 30, 2021, and April 10 through July 11, 2022. The Self-Administered Stress Evaluation Form-20 (SASEF-20) was used to evaluate the dentists’ stress levels. Results: Higher stress levels and prevalence were found in 2021 and 2022 compared with 2020. Sex, age, religion, specialty, working status, and cash flow during the pandemic were identified as stress predictors. Conclusion: The extended COVID-19 pandemic resulted in increased mental health deterioration. National and regional bodies overseeing dentists should be aware of vulnerable groups of dentists, such as younger dentists whose financial status might be unstable. Internet-based cognitive behavioural therapy may be a useful tool to reduce stress in this situation.

Background: The COVID-19 pandemic is spreading rapidly around the world, causing countries to impose lockdowns and efforts to develop vaccines on a global scale. However, human-to-animal and animal-to-human transmission cannot be ignored, as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can spread rapidly in farmed and wild animals. This could create a worrying cycle of SARS-CoV-2 spillover from humans to animals and spillback of new strains back into humans, rendering vaccines ineffective. Method: This study provides a key indicator of animals that may be potential susceptible hosts for SARS-CoV-2 and coronavirus infections by analysing the phylogenetic distance between host angiotensin-converting enzyme 2 and the coronavirus spike protein. Crucially, our analysis identifies animals that are at elevated risk from a spillover and spillback incident. Results: One group of animals has been identified as potentially susceptible to SARS-CoV-2 by harbouring a parasitic coronavirus spike protein similar to the SARS-CoV-2 spike protein. These animals may serve as amplification hosts in spillover events from zoonotic reservoirs. This group consists of a mixture of animals infected internally and naturally: minks, dogs, cats, tigers. Additionally, no internal or natural infections have been found in masked palm civet. Conclusion: Tracing interspecies transmission in multi-host environments based solely on in vitro and in vivo examinations of animal susceptibility or serology is a time-consuming task. This approach allows rapid identification of high-risk animals to prioritize research and assessment of the risk of zoonotic disease transmission in the environment. It is a tool to rapidly identify zoonotic species that may cause outbreaks or participate in expansion cycles of coexistence with their hosts. This prevents the spread of coronavirus infections between species, preventing spillover and spillback incidents from occurring.

Typhoid fever, caused by Salmonella Typhi, is a severe bacterial infection prevalent in developing countries, and can result in life-threatening complications if untreated. Nutcracker Syndrome is a rare vascular disorder involving compression of the left renal vein between the aorta and the superior mesenteric artery. It can lead to various symptoms and poses diagnostic and management challenges. We present a case study of a patient diagnosed with typhoid fever in a Unit of Critical Emergency Care. Coincidentally, the evaluation through CT-scan revealed the presence of Nutcracker Syndrome. This report underscores the incidental discovery of Nutcracker Syndrome during the assessment of a patient with typhoid fever in a critical emergency care setting.

Highlights: 1. Comics centered around tuberculosis offer a novel method tailored for specific audiences, specifically children or those of school age, to learn about the disease. 2. The tuberculosis comics feature the etiology, prevention, and treatment of tuberculosis conveyed through their unique design. 3. Comics can be an innovative promotional method to support the preventive campaign against tuberculosis. Abstract As a tropical country, Indonesia continues to grapple with the prevalence of tuberculosis. This study conducted by the Department of Public Health and Preventive Medicine at Universitas Airlangga, Surabaya, Indonesia, presented a novel approach to prevent tuberculosis through measures tailored to the socio-cultural context of the population. Specifically, this study assessed how effective the use of tuberculosis comics is as an educational tool to inform junior high school students about tuberculosis. This research was quasi-experimental, with a one-group pre-test-post-test design. Seventy junior high school students in Dukun District, Gresik, Indonesia participated in this study. Each participant received a questionnaire consisting of ten questions about tuberculosis. Afterward, tuberculosis education was shared through comics. The post-test was carried out using the same questions as the pre-test. The data were analyzed using the R Program for Windows, version 4.1.3 (Auckland University, New Zealand). The analysis revealed a significant difference between the pre-test and post-test results (p < 0.0001). As indicated by the data, comics proved to be an effective method of educating people about infectious diseases, specifically tuberculosis. Here, we introduce an educational tool designed to revitalize the educational method for disseminating knowledge about infectious diseases. Ultimately, comics can increase students' interest in learning about tuberculosis, including its etiology, prevention, and treatment strategies.

Abstract Background Highlighted by the rise of COVID-19, climate change, and conflict, socially vulnerable populations are least resilient to disaster. In infectious disease management, mathematical models are a commonly used tool. Researchers should include social vulnerability in models to strengthen their utility in reflecting real-world dynamics. We conducted a scoping review to evaluate how researchers have incorporated social vulnerability into infectious disease mathematical models. Methods The methodology followed the Joanna Briggs Institute and updated Arksey and O'Malley frameworks, verified by the PRISMA-ScR checklist. PubMed, Clarivate Web of Science, Scopus, EBSCO Africa Wide Information, and Cochrane Library were systematically searched for peer-reviewed published articles. Screening and extracting data were done by two independent researchers. Results Of 4075 results, 89 articles were identified. Two-thirds of articles used a compartmental model (n = 58, 65.2%), with a quarter using agent-based models (n = 24, 27.0%). Overall, routine indicators, namely age and sex, were among the most frequently used measures (n = 42, 12.3%; n = 22, 6.4%, respectively). Only one measure related to culture and social behaviour (0.3%). For compartmental models, researchers commonly constructed distinct models for each level of a social vulnerability measure and included new parameters or influenced standard parameters in model equations (n = 30, 51.7%). For all agent-based models, characteristics were assigned to hosts (n = 24, 100.0%), with most models including age, contact behaviour, and/or sex (n = 18, 75.0%; n = 14, 53.3%; n = 10, 41.7%, respectively). Conclusions Given the importance of equitable and effective infectious disease management, there is potential to further the field. Our findings demonstrate that social vulnerability is not considered holistically. There is a focus on incorporating routine demographic indicators but important cultural and social behaviours that impact health outcomes are excluded. It is crucial to develop models that foreground social vulnerability to not only design more equitable interventions, but also to develop more effective infectious disease control and elimination strategies. Furthermore, this study revealed the lack of transparency around data sources, inconsistent reporting, lack of collaboration with local experts, and limited studies focused on modelling cultural indicators. These challenges are priorities for future research.

Abstract Background Although Zika virus infection is rarely reported now, continuous prevention is needed to achieve sustained eradication. This study aimed to explore the knowledge gaps, risk perception and preventive measures against Zika virus infection (ZIKV) in pregnant women in Malaysia. Methods We conducted in-depth virtual interviews with pregnant women between February and April 2022. The interviews were recorded and transcribed, and data were analyzed by content analysis. Results The majority of the participants demonstrated a commendable level of awareness regarding the signs and symptoms associated with ZIKV infection. They also exhibited a clear understanding of preventive measures, particularly emphasizing the importance of avoiding mosquito bites to minimize the risk of ZIKV transmission. However, a noteworthy gap in knowledge surfaced as a subset of participants remained uninformed about the potential for sexual transmission of ZIKV, which could lead to congenital ZIKV in pregnant women. Even among women who were cognizant of ZIKV and its potential negative health outcomes, associated with the infection, many of them did not perceive themselves to be at risk, mainly because ZIKV infection is infrequently discussed or heard of, leading to a sense of infections’ rarity. While the adoption of preventive measures such as mosquito bite prevention during pregnancy was a common practice, however, prevention of sexually transmitted infections (STIs) including mosquito-borne diseases such as Zika is low. A minority of women express concerns about the sensitivity surrounding discussions and prevention of STIs within the context of marriage. Most of the participants were supportive of the provision of awareness of ZIKV infection in women during pregnancy and the involvement of men, especially in initiatives aimed at preventing transmission through sexual contact. Conclusion This study uncovered gaps in both knowledge and practices pertaining ZIKV infection among pregnant women in the aftermath of the ZIKV pandemic. The insights gleaned from our research are valuable for shaping future interventions geared towards preventing the resurgence or facilitating the sustainable eradication of ZIKV.

Many clinical procedures and biomedical research workflows rely on microscopy, including diagnosis of cancer, genetic disorders, autoimmune diseases, infections, and quantification of cell culture. Despite its widespread use, traditional image acquisition and review by trained microscopists is often lengthy and expensive, limited to large hospitals or laboratories, precluding use in point‐of‐care settings. In contrast, lensless or lensfree holographic microscopy (LHM) is inexpensive and widely deployable because it can achieve performance comparable to expensive and bulky objective‐based benchtop microscopes while relying on components that cost only a few hundred dollars or less. Lab‐on‐a‐chip integration is practical and enables LHM to be combined with single‐cell isolation, sample mixing, and in‐incubator imaging. Additionally, many manual tasks in conventional microscopy are instead computational in LHM, including image focusing, stitching, and classification. Furthermore, LHM offers a field of view hundreds of times greater than that of conventional microscopy without sacrificing resolution. Here, the basic LHM principles are summarized, as well as recent advances in artificial intelligence integration and enhanced resolution. How LHM is applied to the above clinical and biomedical applications is discussed in detail. Finally, emerging clinical applications, high‐impact areas for future research, and some current challenges facing widespread adoption are identified. [ABSTRACT FROM AUTHOR]

High‐precision viral detection at point of need with clinical samples plays a pivotal role in the diagnosis of infectious diseases and the control of a global pandemic. However, the complexity of clinical samples that often contain very low viral concentrations makes it a huge challenge to develop simple diagnostic devices that do not require any sample processing and yet are capable of meeting performance metrics such as very high sensitivity and specificity. Herein we describe a new single‐pot and single‐step electrochemical method that uses real‐time kinetic profiling of the interaction between a high‐affinity aptamer and an antigen on a viral surface. This method generates many data points per sample, which when combined with machine learning, can deliver highly accurate test results in a short testing time. We demonstrate this concept using both SARS‐CoV‐2 and Influenza A viruses as model viruses with specifically engineered high‐affinity aptamers. Utilizing this technique to diagnose COVID‐19 with 37 real human saliva samples results in a sensitivity and specificity of both 100 % (27 true negatives and 10 true positives, with 0 false negative and 0 false positive), which showcases the superb diagnostic precision of this method. [ABSTRACT FROM AUTHOR]

AbstractWe propose a novel micro-level and spatially explicit agent-based modeling framework dubbed TranEpiSim to model the spread of infectious diseases through micromobility systems and a baseline population in an urban area. A case study is conducted on the Chicago City public bikesharing system to demonstrate the ability of the model to isolate the role of transportation as a vector and assess the efficacy of the model. Results show that the emergence of viral disease through micromobility transportation is possible, but the overall impact of the system on the disease dynamics in a worst-case scenario, especially with the current size of the system, is rather small. The proposed model offers a comprehensive approach to estimate the impact of micromobility (and more generally, specific transportation modes) on disease spread by considering infections that occur both at destinations and in/on transportation vehicles and infrastructure. The spatial pattern for the risk of exposure shows a higher risk in the central business district and north of it, where most of the shared bike transportation occurs. Because of its intrinsic features, the proposed framework is uniquely placed to assess the efficacy of interventions and make trade-offs between competing scenarios when dealing with epidemics. [ABSTRACT FROM AUTHOR]

IntroductionMethodsResultsConclusionsPeople living with HIV (PLWH) often experience difficulties in everyday functioning, which can arise in part from deficits in the strategic/executive aspects of prospective memory (PM). Using Suchy’s Contextually Valid Executive Assessment (ConVExA) framework, this study sought to determine whether the contextual factors of busyness and routine moderate the relationship between the strategic/executive aspects of PM and everyday functioning in older PLWH.Participants in this cross-sectional analysis were 145 PLWH aged 50 years and older who had completed the Martin and Park Environmental Demands (MPED) questionnaire of routine and busyness, the performance-based Cambridge Test of Prospective Memory, and self-report measures of activities of daily living (ADLs) and cognitive symptoms in daily life.Multiple regression analyses covarying for relevant comorbidities showed that higher levels of busyness – but not routine – were associated with more frequent cognitive symptoms in daily life. Neither busyness nor routine interacted with PM in association with cognitive symptoms. However, routine and a strategic/executive measure of PM interacted in predicting ADLs; specifically, the association between time-based PM and ADLs was stronger in persons with higher levels of routine in their daily lives. Parallel analyses with less executively-demanding event-based PM were null and small.Overall, findings provided mixed – and unexpected – evidence for the associations between contextual factors (i.e. routine and busyness), everyday functioning, and PM in this sample of older adults with HIV disease. Results and clinical implications are interpreted and discussed in the framework of the ConVExA model. [ABSTRACT FROM AUTHOR]

N, N‐diethyl‐meta‐toluamide (DEET) has been considered the 'gold standard' for insect repellent use since the 1950s and constitutes most insect repellents on the market. However, conflicting data in the scientific literature and confusing information in the media are at the core of debates about the safety of DEET insect repellents for the protection of children against arthropod bites. The few fatal occurrences involving DEET insect repellents and complications of their use in the pediatric population are typically the result of accidental overdoses or misuse of insect repellents that disregard warnings on product labels. With appropriate application, the safety record of DEET insect repellents continues to be excellent with few side effects. The purpose of this review is to provide a summary of the literature on safety outcomes of DEET insect repellent use in children; outline the pediatric recommendations relating to DEET insect repellents; and provide an overview of EPA‐approved and naturally derived alternatives to DEET that possess low toxicity while providing a similar level of protection to synthetic insect repellents. [ABSTRACT FROM AUTHOR]

Serosurveys are a widely used tool to estimate the cumulative incidence—the fraction of a population that has been infected by a given pathogen. These surveys rely on serological assays that measure the level of pathogen-specific antibodies. Because antibody levels are waning, the fraction of previously infected individuals that have seroreverted increases with time past infection. To avoid underestimating the true cumulative incidence, it is therefore essential to correct for waning antibody levels. We present an empirically supported approach for seroreversion correction in cumulative incidence estimation when sequential serosurveys are conducted in the context of a newly emerging infectious disease. The correction is based on the observed dynamics of antibody titers in seropositive cases and validated using several in silico test scenarios. Furthermore, through this approach we revise a previous cumulative incidence estimate relying on the assumption of an exponentially declining probability of seroreversion over time, of severe acute respiratory syndrome coronavirus 2, of 76% in Manaus, Brazil, by October 2020 to 47.6% (95% confidence region: 43.5–53.5). This estimate has implications, for example, for the proximity to herd immunity in Manaus in late 2020. [ABSTRACT FROM AUTHOR]

Objectives We assess how age, the presence of mature adults aged 45+ years, and recent deaths in rural households are associated with coronavirus disease 2019 (COVID-19) preventative actions and the likelihood of getting vaccinated against the virus in Malawi during early stages of the pandemic. Methods We draw upon data from 2,187 rural Malawians who participated in a 2020 COVID-19 Phone Survey. We estimate the log odds of engaging in "low-cost" and "high-cost" COVID-19 preventative actions based on age, gender, household composition, and recent household deaths. Low-cost prevention efforts were washing hands with soap and water frequently, avoiding close contact with people when going out, and avoiding shaking hands. High-cost actions included staying at home and decreasing time spent close to people not living in their household. We also estimate the chances of acquiring the COVID-19 vaccine in early stages of its availability. Results Mature women (45+ years) in general and younger men (<45 years)—living with at least one mature adult in the household—were less likely than others to comply with low-cost actions. Mature men were more likely than younger men (<45 years) to take on high-cost actions. To some extent, individuals who experienced a recent family death were more likely to engage in high-cost COVID-19 preventative actions as well as getting vaccinated. Discussion Gendered age differences in preventing the transmission of COVID-19 offer hints of larger social norms affecting protective efforts. The analyses also inform future COVID-19 public health outreach efforts in Malawi and other rural SSA contexts. [ABSTRACT FROM AUTHOR]

The article summarizes key considerations and opportunities for sexually transmitted infection (STI) programs and policy makers to expand the role of community health workers (CHWs) in addressing STIs, identify optimal Medicaid reimbursement approaches, and coordinate CHWs' role. Topics include potential role of CHWs in the STI field, ways public health departments could promote the role of CHWs in STI programs, and Medicaid support of CHWs.

How infectious diseases shape individual minds and behaviors has been of interest to researchers. We conducted four studies to examine whether the threat perception of the COVID-19 pandemic was positively related to pro-environmentalism. Study 1 (N = 1,508) showed that individuals' threat perception of the pandemic was correlated with their pro-environmental behaviors. Study 2 (N = 241) clarified the causality by manipulating threat perception and found that individuals with high (vs. low) threat perception reported higher pro-environmental willingness. Study 3 (N = 406) revealed that awe for nature mediated this relationship. Study 4 (N = 405) replicated Study 3 more than two years after the outbreak and demonstrated the findings were robust regardless of decreases in infection fear. These findings suggest that the COVID-19 pandemic provides individuals with an opportunity to reconsider the way they treat nature. [ABSTRACT FROM AUTHOR]

In studies of infectious disease prevention, the level of protective efficacy of medicinal products such as vaccines and prophylactic drugs tends to vary over time. Many products require administration of multiple doses at scheduled times, as opposed to one‐off or continual intervention. Accurate information on the trajectory of the level of protective efficacy over time facilitates informed clinical recommendations and implementation strategies, for example, with respect to the timing of administration of the doses. Based on concepts from pharmacokinetic and pharmacodynamic modeling, we propose a non‐linear function for modeling the trajectory after each dose. The cumulative effect of multiple doses of the products is captured by an additive series of the function. The model has the advantages of parsimony and interpretability, while remaining flexible in capturing features of the trajectories. We incorporate this series into the Andersen‐Gill model for analysis of recurrent event time data and compare it with alternative parametric and non‐parametric functions. We use data on clinical malaria disease episodes from a trial of four doses of an anti‐malarial drug combination for chemoprevention to illustrate, and evaluate the performance of the methods using simulation. The proposed method out‐performed the alternatives in the analysis of real data in terms of Akaike and Bayesian Information Criterion. It also accurately captured the features of the protective efficacy trajectory such as the area under curve in simulations. The proposed method has strong potential to enhance the evaluation of disease prevention measures and improve their implementation strategies. [ABSTRACT FROM AUTHOR]

Measles remains a significant threat to children worldwide despite the availability of effective vaccines. The COVID-19 pandemic exacerbated the situation by leading to the postponement of supplementary measles immunization activities. Along with this postponement, measles surveillance also deteriorated, with the lowest number of submitted specimens in over a decade. In this study, we focus on measles as a challenging case study due to its high vaccination coverage, which leads to smaller outbreaks and potentially weaker signals on Google Trends. Our research aimed to explore the feasibility of using Google Trends for real-time monitoring of infectious disease outbreaks. We evaluated the correlation between Google Trends searches and clinical case data using the Pearson correlation coefficient and Spearman’s rank correlation coefficient across 30 European countries and Japan. The results revealed that Google Trends was most suitable for monitoring acute disease outbreaks at the regional level in high-income countries, even when there are only a few weekly cases. For example, from 2017 to 2019, the Pearson correlation coefficient was 0.86 (p-value< 0.05) at the prefecture level for Okinawa, Japan, versus 0.33 (p-value< 0.05) at the national level for Japan. Furthermore, we found that the Pearson correlation coefficient may be more suitable than Spearman’s rank correlation coefficient for evaluating the correlations between Google Trends search data and clinical case data. This study highlighted the potential of utilizing Google Trends as a valuable tool for timely public health interventions to respond to infectious disease outbreaks, even in the context of diseases with high vaccine coverage. [ABSTRACT FROM AUTHOR]

Background: Defining healthcare facility catchment areas is a key step in predicting future healthcare demand in epidemic settings. Forecasts of hospitalisations can be informed by leading indicators measured at the community level. However, this relies on the definition of so-called catchment areas or the geographies whose populations make up the patients admitted to a given hospital, which are often not well-defined. Little work has been done to quantify the impact of hospital catchment area definitions on healthcare demand forecasting. Methods: We made forecasts of local-level hospital admissions using a scaled convolution of local cases (as defined by the hospital catchment area) and delay distribution. Hospital catchment area definitions were derived from either simple heuristics (in which people are admitted to their nearest hospital or any nearby hospital) or historical admissions data (all emergency or elective admissions in 2019, or COVID-19 admissions), plus a marginal baseline definition based on the distribution of all hospital admissions. We evaluated predictive performance using each hospital catchment area definition using the weighted interval score and considered how this changed by the length of the predictive horizon, the date on which the forecast was made, and by location. We also considered the change, if any, in the relative performance of each definition in retrospective vs. real-time settings, or at different spatial scales. Results: The choice of hospital catchment area definition affected the accuracy of hospital admission forecasts. The definition based on COVID-19 admissions data resulted in the most accurate forecasts at both a 7- and 14-day horizon and was one of the top two best-performing definitions across forecast dates and locations. The "nearby" heuristic also performed well, but less consistently than the COVID-19 data definition. The marginal distribution baseline, which did not include any spatial information, was the lowest-ranked definition. The relative performance of the definitions was larger when using case forecasts compared to future observed cases. All results were consistent across spatial scales of the catchment area definitions. Conclusions: Using catchment area definitions derived from context-specific data can improve local-level hospital admission forecasts. Where context-specific data is not available, using catchment areas defined by carefully chosen heuristics is a sufficiently good substitute. There is clear value in understanding what drives local admissions patterns, and further research is needed to understand the impact of different catchment area definitions on forecast performance where case trends are more heterogeneous. [ABSTRACT FROM AUTHOR]

Background: Monkeypox is an emerging infectious disease with confirmed cases and deaths in several parts of the world. In light of this crisis, this study aims to analyze the global knowledge pattern of monkeypox-related patents and explore current trends and future technical directions in the medical development of monkeypox to inform research and policy. Methods: A comprehensive study of 1,791 monkeypox-related patents worldwide was conducted using the Derwent patent database by descriptive statistics, social network method and linear regression analysis. Results: Since the 21st century, the number of monkeypox-related patents has increased rapidly, accompanied by increases in collaboration between commercial and academic patentees. Enterprises contributed the most in patent quantity, whereas the initial milestone patent was filed by academia. The core developments of technology related to the monkeypox include biological and chemical medicine. The innovations of vaccines and virus testing lack sufficient patent support in portfolios. Conclusions: Monkeypox-related therapeutic innovation is geographically limited with strong international intellectual property right barriers though it has increased rapidly in recent years. The transparent licensing of patent knowledge is driven by the merger and acquisition model, and the venture capital, intellectual property and contract research organization model. Currently, the patent thicket phenomenon in the monkeypox field may slow the progress of efforts to combat monkeypox. Enterprises should pay more attention to the sharing of technical knowledge, make full use of drug repurposing strategies, and promote innovation of monkeypox-related technology in hotspots of antivirals (such as tecovirimat, cidofovir, brincidofovir), vaccines (JYNNEOS, ACAM2000), herbal medicine and gene therapy. [ABSTRACT FROM AUTHOR]

AbstractBackgroundObjectiveDesign and settingSubjectsMain outcome measuresResultsConclusion\nKEY POINTSThere has been a notable decrease in antibiotic prescribing in the last thirty years in Sweden. Little is known about factors influencing antibiotic prescribing over several years.To compare primary care physicians who, over time, reduced their antibiotic prescribing for respiratory tract infections with those who remained either high or low prescribers regarding potentially influencing factors.A register-based study including all RTI visits in primary care in Region Kronoberg, Sweden 2006–2014. The data were divided into three 3-year periods.The data comprised all physicians who had diagnosed at least one RTI for each of the three-year periods. The antibiotic prescribing rate adjusted for the patients’ sex and age group was calculated for each physician and period, and based on the change between the first and the third period, the physicians were divided into three prescriber groups: The High Prescribing Group, the Decreasing Prescribing Group, and the Low Prescribing Group.For the three prescriber groups, we compared factors influencing antibiotic prescribing such as the characteristics of the physicians, their use of point-of-care tests, their choice of diagnoses, and whether the patients returned and received antibiotics.The High Prescribing Group ordered more point-of-care tests, registered more potential bacterial diagnoses, prescribed antibiotics at lower C-reactive protein levels, and prescribed antibiotics more often despite negative group A Streptococci test than in the Low Prescribing Group. The Decreasing Prescribing Group was between the High Prescribing Group and the Low Prescribing Group regarding these variables. The lower prescription rate in the Low Prescribing Group did not result in more return visits or new antibiotic prescriptions within 30 days.Point-of-care testing and its interpretation differed between the prescriber groups. Focus on interpreting point-of-care test results could be a way forward in antibiotic stewardship.High prescribers used antibiotics at lower CRP levels and were more likely to identify a potential bacterial diagnosis.Many physicians reduced their antibiotic prescribing during the study period. Nine out of ten low prescribers remained low prescribers.Seeing a low-prescribing physician did not lead to more return visits or antibiotic changes.High prescribers used antibiotics at lower CRP levels and were more likely to identify a potential bacterial diagnosis.Many physicians reduced their antibiotic prescribing during the study period. Nine out of ten low prescribers remained low prescribers.Seeing a low-prescribing physician did not lead to more return visits or antibiotic changes. [ABSTRACT FROM AUTHOR]

Cutaneous leishmaniasis (CL), a parasitic infection caused by Leishmania protozoa and transmitted by sandfly bites, can be classified into Old World and New World subtypes. We report a case of a 2‐year‐old female who developed complex CL after travel to Panama. Ultimately, successful treatment required two rounds of liposomal amphotericin B. We report this case for its challenging clinical course and management. [ABSTRACT FROM AUTHOR]

Clinical severity scores facilitate comparisons to understand risk factors for severe illness. For the 2022 multinational monkeypox clade IIb virus outbreak, we developed a 7-item Mpox Severity Scoring System (MPOX-SSS) with initial variables refined by data availability and parameter correlation. Application of MPOX-SSS to the first 200 patients diagnosed with mpox revealed higher scores in those treated with tecovirimat, presenting >3 days after symptom onset, and with CD4 counts <200 cells/mm3. For individuals evaluated repeatedly, serial scores were concordant with clinical observations. The pilot MPOX-SSS demonstrated good discrimination, distinguished change over time, and identified higher scores in expected groups. [ABSTRACT FROM AUTHOR]

As infectious diseases have a severe impact on the individual survival and competitive ability of host species in grassland communities, competition between relevant species may have different consequences, potentially influencing the species composition of grassland communities and the functioning of grassland ecosystems. Understanding the impact of infectious diseases on competition is thus crucial for the health management of grassland ecosystems. How do infectious diseases affect the competitive coexistence of grassland plant species? In this study, by drawing on Tilman's multispecies competition model and incorporating the spread characteristics of grassland plant diseases, we built three spatial competition models of two grass species subject to infectious diseases, and we analyzed the invasion conditions of infectious diseases and how they impact the population dynamics and competitive consequences of the species. Our model revealed the following: (1) Diseases with high transmission rates and low virulence are more likely to invade populations, while the presence of non-host species is detrimental to disease invasion. (2) Disease promotes the coexistence of competing species, breaking down the original competition–compromise trade-off mechanism for species coexistence and greatly expanding the range of parameters within which the two species can coexist. (3) Pathogen infections indirectly weaken the suppression of inferior species by dominant species, which is similar to the cascade effect seen in trophic interactions. Our findings highlight the importance of disease in species coexistence and grassland biodiversity maintenance. [ABSTRACT FROM AUTHOR]

Background Malaria continues to pose a significant burden in endemic countries, many of which lack access to molecular surveillance. Insights from malaria cases in travellers returning to non-endemic areas can provide valuable data to inform endemic country programmes. To evaluate the potential for novel global insights into malaria, we examined epidemiological and molecular data from imported malaria cases to Australia. Methods We analysed malaria cases reported in Australia from 2012 to 2022 using National Notifiable Disease Surveillance System data. Molecular data on imported malaria cases were obtained from literature searches. Results Between 2012 and 2022, 3204 malaria cases were reported in Australia. Most cases (69%) were male and 44% occurred in young adults aged 20–39 years. Incidence rates initially declined between 2012 and 2015, then increased until 2019. During 2012–2019, the incidence in travellers ranged from 1.34 to 7.71 per 100 000 trips. Cases were primarily acquired in Sub-Saharan Africa (n  = 1433; 45%), Oceania (n  = 569; 18%) and Southern and Central Asia (n  = 367; 12%). The most common countries of acquisition were Papua New Guinea (n  = 474) and India (n  = 277). Plasmodium falciparum accounted for 58% (1871/3204) of cases and was predominantly acquired in Sub-Saharan Africa, and Plasmodium vivax accounted for 32% (1016/3204), predominantly from Oceania and Asia. Molecular studies of imported malaria cases to Australia identified genetic mutations and deletions associated with drug resistance and false-negative rapid diagnostic test results, and led to the establishment of reference genomes for P. vivax and Plasmodium malariae. Conclusions Our analysis highlights the continuing burden of imported malaria into Australia. Molecular studies have offered valuable insights into drug resistance and diagnostic limitations, and established reference genomes. Integrating molecular data into national surveillance systems could provide important infectious disease intelligence to optimize treatment guidelines for returning travellers and support endemic country surveillance programmes. [ABSTRACT FROM AUTHOR]

Background In settings with large case detection gaps, active case-finding (ACF) may play a critical role in the uberculosis (TB) response. However, ACF is resource intensive, and its effectiveness depends on whether people detected with TB through ACF might otherwise spontaneously resolve or be diagnosed through routine care. We analysed the potential effectiveness of ACF for TB relative to the counterfactual scenario of routine care alone. Methods We constructed a Markov simulation model of TB natural history, diagnosis, symptoms, ACF and treatment, using a hypothetical reference setting using data from South East Asian countries. We calibrated the model to empirical data using Bayesian methods, and simulated potential 5-year outcomes with an 'aspirational' ACF intervention (reflecting maximum possible effectiveness) compared with the standard-of-care outcomes. Results Under the standard of care, 51% (95% credible interval, CrI: 31%, 75%) of people with prevalent TB at baseline were estimated to be diagnosed and linked to care over 5 years. With aspirational ACF, this increased to 88% (95% CrI: 84%, 94%). Most of this difference represented people who were diagnosed and treated through ACF but experienced spontaneous resolution under standard-of-care. Aspirational ACF was projected to reduce the average duration of TB disease by 12 months (95% CrI: 6%, 18%) and TB-associated disability-adjusted life-years by 71% (95% CrI: 67%, 76%). Conclusion These data illustrate the importance of considering outcomes in a counterfactual standard of care scenario, as well as trade-offs between overdiagnosis and averted morbidity through earlier diagnosis—not just for TB, but for any disease in which population-based screening is recommended. [ABSTRACT FROM AUTHOR]

Infectious diseases, caused by pathogenic microorganisms such as bacteria, viruses, parasites, or fungi, are crucial for efficient disease management, reducing morbidity and mortality rates and controlling disease spread. Traditional laboratory‐based diagnostic methods face challenges such as high costs, time consumption, and a lack of trained personnel in resource‐poor settings. Diagnostic biosensors have gained momentum as a potential solution, offering advantages such as low cost, high sensitivity, ease of use, and portability. Nanobiosensors are a promising tool for detecting and diagnosing infectious diseases such as coronavirus disease, human immunodeficiency virus, and hepatitis. These sensors use nanostructured carbon nanotubes, graphene, and nanoparticles to detect specific biomarkers or pathogens. They operate through mechanisms like the lateral flow test platform, where a sample containing the biomarker or pathogen is applied to a test strip. If present, the sample binds to specific recognition probes on the strip, indicating a positive result. This binding event is visualized through a colored line. This review discusses the importance, benefits, and potential of nanobiosensors in detecting infectious diseases. [ABSTRACT FROM AUTHOR]