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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.

INTRODUCTION: Procalcitonin (PCT) is a useful biomarker in the initial evaluation of febrile infants for serious bacterial infections (SBIs). However, PCT is not always available locally and must at times be frozen and shipped to a reference laboratory for research studies. We sought to compare PCT measured locally versus centrally at a reference laboratory during a research study. MATERIALS AND METHODS: This was a secondary analysis of a multicenter study of febrile infants ≤60 days evaluated for SBIs from June 2016 to April 2019. A PCT cutoff value of 0.5 ng/mL was used to stratify infants at low-versus high-risk of SBIs. Statistical analyses consisted of Spearmans correlation, Bland-Altman difference plotting, Passing-Bablok regression, Deming regression, and Fishers exact testing at the 0.5 ng/mL threshold. RESULTS: 241 febrile infants had PCT levels measured both locally and at the reference laboratory. PCT levels measured locally on 5 different platforms and from the frozen research samples demonstrated strong Spearmans correlation (ρ = 0.83) and had similar mean PCT values with an average relative difference of 0.02%. Eleven infants with SBIs had PCT values

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.

The management of patients affected by moderate-to-severe psoriasis may be challenging, in particular in patients with serious infectious diseases [tuberculosis (TB), hepatitis B and C, HIV, COVID-19]. Indeed, these infections should be ruled out before starting and during systemic treatment for psoriasis. Currently, four conventional systemic drugs (methotrexate, dimethyl fumarate, acitretin, cyclosporine), four classes of biologics (anti-tumour necrosis factor alpha, anti-interleukin (IL)12/23, anti-IL-17s, and anti-IL-23], and two oral small molecules (apremilast, deucravacitinib) have been licensed for the treatment of moderate-to-severe psoriasis. Each of these drugs is characterized by a unique safety profile which should be considered before starting therapy. Indeed, some comorbidities or risk factors may limit their use. In this context, the aim of this manuscript was to evaluate the management of patients affected by moderate-to-severe psoriasis with serious infectious diseases. [ABSTRACT FROM AUTHOR]

Coxiella burnetii is a bacterial pathogen capable of causing serious disease in humans and abortions in goats. Infected goats can shed C. burnetii through urine, feces, and parturient byproducts, which can lead to infections in humans when the bacteria are inhaled. Goats are important C. burnetii reservoirs as evidenced by goat-related outbreaks across the world. To better understand the current landscape of C. burnetii infection in the domestic goat population, 4,121 vaginal swabs from 388 operations across the United States were analyzed for the presence of C. burnetii by IS1111 PCR as part of the United States Department of Agriculture, Animal Plant Health Inspection Service, Veterinary Services' National Animal Health Monitoring System Goats 2019 Study. In total, 1.5% (61/4121) of swabs representing 10.3% (40/388) (weighted estimate of 7.8, 95% CI 4.4-13.5) of operations were positive for C. burnetii DNA. The quantity of C. burnetii on positive swabs was low with an average Ct of 37.9. Factors associated with greater odds of testing positive included suspected Q fever in the herd in the previous 3 years, the presence of wild deer or elk on the operation, and the utilization of hormones for estrus synchronization. Factors associated with reduced odds of testing positive include the presence of kittens and treatment of herds with high tannin concentrate plants, diatomaceous earth, and tetrahydropyrimidines. In vitro analysis demonstrated an inhibitory effect of the tetrahydropyrimidine, pyrantel pamoate, on the growth of C. burnetii in axenic media as low as 1 pg per mL. The final multivariable logistic regression modeling identified the presence of wild predators on the operation or adjacent property (OR = 9.0, 95% CI 1.3-61.6, p value = 0.0248) as a risk factor for C. burnetii infection. [ABSTRACT FROM AUTHOR]

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]

There is a rich literature highlighting that pathogens are generally better adapted to infect local than novel hosts, and a separate seemingly contradictory literature indicating that novel pathogens pose the greatest threat to biodiversity and public health. Here, using Batrachochytrium dendrobatidis, the fungus associated with worldwide amphibian declines, we test the hypothesis that there is enough variance in "novel" (quantified by geographic and phylogenetic distance) host‐pathogen outcomes to pose substantial risk of pathogen introductions despite local adaptation being common. Our continental‐scale common garden experiment and global‐scale meta‐analysis demonstrate that local amphibian‐fungal interactions result in higher pathogen prevalence, pathogen growth, and host mortality, but novel interactions led to variable consequences with especially virulent host‐pathogen combinations still occurring. Thus, while most pathogen introductions are benign, enough variance exists in novel host‐pathogen outcomes that moving organisms around the planet greatly increases the chance of pathogen introductions causing profound harm. [ABSTRACT FROM AUTHOR]

Parrot bornavirus (PaBV) is an infectious disease linked with proventricular dilatation disease (PDD) with severe digestive and neurological symptoms affecting psittacine birds. Despite its detection in 2008, PaBV prevalence in Taiwan remains unexplored. Taiwan is one of the leading psittacine bird breeders; hence, understanding the distribution of PaBV aids preventive measures in controlling spread, early disease recognition, epidemiology, and transmission dynamics. Here, we aimed to detect the prevalence rate of PaBV and assess its genetic variation in Taiwan. Among 124 psittacine birds tested, fifty-seven were PaBV-positive, a prevalence rate of 45.97%. Most of the PaBV infections were adult psittacine birds, with five birds surviving the infection, resulting in a low survival rate (8.77%). A year of parrot bornavirus surveillance presented a seasonal pattern, with peak PaBV infection rates occurring in the spring season (68%) and the least in the summer season (25%), indicating the occurrence of PaBV infections linked to seasonal factors. Histopathology reveals severe meningoencephalitis in the cerebellum and dilated cardiomyopathy of the heart in psittacine birds who suffered from PDD. Three brain samples underwent X/P gene sequencing, revealing PaBV-2 and PaBV-4 viral genotypes through phylogenetic analyses. This underscores the necessity for ongoing PaBV surveillance and further investigation into its pathophysiology and transmission routes. [ABSTRACT FROM AUTHOR]

Frog virus 3 (FV3) in the genus Ranavirus of the family Iridoviridae causes mass mortality in both anurans and urodeles worldwide; however, the phylogenetic origin of FV3-like ranaviruses is not well established. In Asia, three FV3-like ranaviruses have been reported in farmed populations of amphibians and reptiles. Here, we report the first case of endemic FV3-like ranavirus infections in the Korean clawed salamander Onychodactylus koreanus, caught in wild mountain streams in the Republic of Korea (ROK), through whole-genome sequencing and phylogenetic analysis. Two isolated FV3-like ranaviruses (Onychodactylus koreanus ranavirus, OKRV1 and 2) showed high similarity with the Rana grylio virus (RGV, 91.5%) and Rana nigromaculata ranavirus (RNRV, 92.2%) but relatively low similarity with the soft-shelled turtle iridovirus (STIV, 84.2%) in open reading frame (ORF) comparisons. OKRV1 and 2 formed a monophyletic clade with previously known Asian FV3-like ranaviruses, a sister group of the New World FV3-like ranavirus clade. Our results suggest that OKRV1 and 2 are FV3-like ranaviruses endemic to the ROK, and RGV and RNRV might also be endemic strains in China, unlike previous speculation. Our data have great implications for the study of the phylogeny and spreading routes of FV3-like ranaviruses and suggest the need for additional detection and analysis of FV3-like ranaviruses in wild populations in Asian countries. [ABSTRACT FROM AUTHOR]

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. [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]

This study aims to screen for IgG antibodies against Toxoplasma gondii (T. gondii) in the sera of 155 newly diagnosed Human Immunodeficiency Virus (HIV) positive patients under surveillance in Greek Infectious Disease Units. Additionally, risk factors based on patient demographics were examined, and a comparative evaluation of commercially available serological methods was conducted. Three methods were employed to detect IgG antibodies against T. gondii: Enzyme-Linked Immunosorbent Assay (ELISA), Indirect Immunofluorescence Antibody Test (IFAT), and Western Blot (WB), which was used as a reference here. Forty-nine sera samples were true-positive for IgG antibodies against T. gondii, resulting in a 31.61% positivity rate, and the immunoassay test statistical reliability analysis resulted in higher IFAT accuracy (90.97%) compared to ELISA (76.26%). Furthermore, statistical analysis of demographic and immunological data included in the study placed female and foreign/non-Greek individuals at 2.24 (p = 0.0009) and 2.34 (p = 0.0006) times higher risk of positive T. gondii IgG testing compared to their male and Greek counterparts, respectively. Our findings on positivity rates and comparative serology underscore the importance of early and suitable screening measures for newly diagnosed HIV+ patients to mitigate the life-threatening outcomes that may arise from a potential subsequent T. gondii activation. [ABSTRACT FROM AUTHOR]

The long-term sequelae of SARS-CoV-2 infection are still under research, since extensive studies showed plenty of systemic effects of the viral infection, extending even after the acute phase of the infection. This study evaluated kidney function tests six months after SARS-CoV-2 infection in patients clinically diagnosed with Post-COVID Syndrome, hypothesizing persistent renal dysfunction evidenced by altered kidney function tests compared to baseline levels. Continuous eGFR decrease <30 at six months post-infection was considered the main study outcome. Conducted at the "Victor Babes" Hospital, this retrospective observational study involved adults with laboratory-confirmed SARS-CoV-2 infection and clinically-diagnosed Post-COVID Syndrome, excluding those with prior chronic kidney disease or significant renal impairment. Kidney function tests, including serum creatinine, blood urea nitrogen (BUN), estimated glomerular filtration rate (eGFR), alongside markers of kidney damage such as proteinuria and hematuria, were analyzed. Among 206 participants, significant differences were observed between the control (n = 114) and the Post-COVID group (n = 92). The Post-COVID group exhibited higher serum creatinine (109.7 μmol/L vs. 84.5 μmol/L, p < 0.001), lower eGFR (65.3mL/min/1.73 m2 vs. 91.2 mL/min/1.73 m2, p < 0.001), and elevated BUN levels (23.7 mg/dL vs. 15.2 mg/dL, p < 0.001) compared to the control group. Regression analysis highlighted significant predictors of continuous eGFR decrease <30 at six months post-infection. The development of acute kidney injury (AKI) during the initial COVID-19 illness emerged as a strong predictor of reduced eGFR (β = 3.47, p < 0.001). Additional factors, including a creatinine increase (23 μmol/L above the normal range) and an elevated Albumin to Creatinine Ratio (ACR) (>11 mg/g above the normal range), were significantly associated with eGFR reduction. Patients with Post-COVID Syndrome demonstrate significant renal impairment six months post-SARS-CoV-2 infection. The study's findings stress the need for ongoing monitoring and intervention strategies for renal health in affected individuals, underscoring the persistent impact of COVID-19 on renal function. [ABSTRACT FROM AUTHOR]

Introduction: Increased demands on infectious diseases (ID) pharmacists and providers may result in targeted antimicrobial stewardship (AMS) interventions. Internal medicine (IM) pharmacists frequently intervene on antimicrobials for their patients during general clinical care, although little is known regarding their overall impact on AMS. Objective: Characterize AMS interventions made by IM pharmacists to identify areas of AMS that can be expanded to patients not covered by ID teams. Methods: This was a prospective, dual‐center, cross‐sectional study where IM pharmacists, and their trainees were recruited to document routinely made AMS interventions that happened during daily patient care activities. These interventions were classified based on infection source, stewardship intervention type, whether recommendations were accepted or rejected by providers, and any barriers incurred during the implementation of interventions. Results: Four IM pharmacists documented 386 interventions from February 2021 through May 2021. Physicians accepted pharmacist interventions 95.6% of the time. The most common interventions were for respiratory (n = 87, 22.5%), genitourinary (n = 80, 20.7%), and skin and skin structure infections (n = 65, 16.8%). The antimicrobials that IM pharmacists most frequently intervened on were vancomycin (n = 89, 23.1%) and ceftriaxone (n = 68, 17.6%). The most common interventions that were made were dose adjustment (n = 105, 27.2%), shortened duration of therapy (n = 86, 22.3%), and intravenous (IV) to oral (PO) conversions (n = 38, 9.8%). Of the 17 interventions not accepted, the most common barrier to implementation was physician concerns (n = 11, 52.4%), which were primarily associated with IV to PO recommendations (n = 7, 63.6%). Conclusion: IM pharmacists participate in AMS for their patients and intervene frequently to adjust dosing for antimicrobials, shorten duration of therapy, and facilitate IV to PO conversions. IM pharmacists could serve as AMS extenders where additional AMS coverage is needed. [ABSTRACT FROM AUTHOR]

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Background: Detection and containment of hospital outbreaks currently depend on variable and personnel-intensive surveillance methods. Whether automated statistical surveillance for outbreaks of health care-associated pathogens allows earlier containment efforts that would reduce the size of outbreaks is unknown. Methods: We conducted a cluster-randomized trial in 82 community hospitals within a larger health care system. All hospitals followed an outbreak response protocol when outbreaks were detected by their infection prevention programs. Half of the hospitals additionally used statistical surveillance of microbiology data, which alerted infection prevention programs to outbreaks. Statistical surveillance was also applied to microbiology data from control hospitals without alerting their infection prevention programs. The primary outcome was the number of additional cases occurring after outbreak detection. Analyses assessed differences between the intervention period (July 2019 to January 2022) versus baseline period (February 2017 to January 2019) between randomized groups. A post hoc analysis separately assessed pre-coronavirus disease 2019 (Covid-19) and Covid-19 pandemic intervention periods. Results: Real-time alerts did not significantly reduce the number of additional outbreak cases (intervention period versus baseline: statistical surveillance relative rate [RR]=1.41, control RR=1.81; difference-in-differences, 0.78; 95% confidence interval [CI], 0.40 to 1.52; P=0.46). Comparing only the prepandemic intervention with baseline periods, the statistical outbreak surveillance group was associated with a 64.1% reduction in additional cases (statistical surveillance RR=0.78, control RR=2.19; difference-in-differences, 0.36; 95% CI, 0.13 to 0.99). There was no similarly observed association between the pandemic versus baseline periods (statistical surveillance RR=1.56, control RR=1.66; difference-in-differences, 0.94; 95% CI, 0.46 to 1.92). Conclusions: Automated detection of hospital outbreaks using statistical surveillance did not reduce overall outbreak size in the context of an ongoing pandemic. (Funded by the Centers for Disease Control and Prevention; ClinicalTrials.gov number, NCT04053075. Support for HCA Healthcare's participation in the study was provided in kind by HCA.) [ABSTRACT FROM AUTHOR]

Accurate diagnostics are critical in public health to ensure successful disease tracking, prevention, and control. Many of the same characteristics are desirable for diagnostic procedures in both medicine and public health: for example, low cost, high speed, low invasiveness, ease of use and interpretation, day-to-day consistency, and high accuracy. This review lays out five principles that are salient when the goal of diagnosis is to improve the overall health of a population rather than that of a particular patient, and it applies them in two important use cases: pandemic infectious disease and antimicrobial resistance. [ABSTRACT FROM AUTHOR]

Acute mastoiditis is a serious condition that carries with it a high rate of morbidity and mortality. This review highlights the pearls and pitfalls of mastoiditis, including the presentation, diagnosis, and management in the emergency department (ED) based on current evidence. Acute mastoiditis most commonly affects pediatric patients and is a suppurative infection of the mastoid air cells. It is often associated with otitis media, and common bacteria include Streptococcus and Staphylococcus. History and examination may reveal tympanic membrane erythema, pinna protrusion, postauricular erythema, mastoid tenderness with palpation, external canal swelling, otorrhea, fever, and malaise. The disease should be suspected in those who fail treatment for otitis media and those who demonstrate the aforementioned abnormalities on examination and systemic symptoms. Laboratory analysis may reveal evidence of systemic inflammation, but a normal white blood cell count and other inflammatory markers should not be used to exclude the diagnosis. Computed tomography (CT) of the temporal bones with intravenous contrast is the recommended imaging modality if the clinician is unsure of the diagnosis. CT may also demonstrate complications. Treatment includes antibiotics such as ampicillin-sulbactam or ceftriaxone as well as otolaryngology consultation. Complications may include subperiosteal and intracranial abscess, deep neck abscess, facial nerve palsy, meningitis/encephalitis, venous sinus thrombosis, and seizures. An understanding of acute mastoiditis can assist emergency clinicians in diagnosing and managing this potentially deadly disease. [ABSTRACT FROM AUTHOR]

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. 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). 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. 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 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]

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 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]