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Confirming bacterial infection at an early stage and distinguishing between sterile inflammation and bacterial infection is still highly needed for efficient treatment. Here, in situ highly sensitive magnetic resonance imaging (MRI) bacterial infection in vivo based on a peptide-modified magnetic resonance tuning (MRET) probe (MPD-1) that responds to matrix metallopeptidase 2 (MMP-2) highly expressed in bacteria-infected microenvironments is achieved. MPD-1 is an assembly of magnetic nanoparticle (MNP) bearing with gadolinium ion (Gd 3+ ) modified MMP-2-cleavable self-assembled peptide (P 1 ) and bacteria-targeting peptide (P), and it shows T 2 -weighted signal due to the assemble of MNP and MRET ON phenomenon between MNP assembly and Gd 3+ . Once MPD-1 accumulates at the bacterially infected site, P 1 included in MPD-1 is cleaved explicitly by MMP-2, which triggers the T 2 contrast agent of MPD-1 to disassemble into the monomer of MNP, leading the recovery of T 1 -weighted signal. Simultaneously, Gd 3+ detaches from MNP, further enhancing the T 1 -weighted signal due to MRET OFF. The sensitive MRI of Staphylococcus aureus (low to 10 4 CFU) at the myositis site and accurate differentiation between sterile inflammation and bacterial infection based on the proposed MPD-1 probe suggests that this novel probe would be a promising candidate for efficiently detecting bacterial infection in vivo., (© 2023 Wiley-VCH GmbH.)

Protective behaviors such as mask wearing and physical distancing are critical to slow the spread of COVID-19, even in the context of vaccine scale-up. Understanding the variation in self-reported COVID-19 protective behaviors is critical to developing public health messaging. The purpose of the study is to provide nationally representative estimates of five self-reported COVID-19 protective behaviors and correlates of such behaviors. In this cross-sectional survey study of US adults, surveys were administered via internet and telephone. Adults were surveyed from April 30-May 4, 2020, a time of peaking COVID-19 incidence within the US. Participants were recruited from the probability-based AmeriSpeak® national panel. Brief surveys were completed by 994 adults, with 73.0% of respondents reported mask wearing, 82.7% reported physical distancing, 75.1% reported crowd avoidance, 89.8% reported increased hand-washing, and 7.7% reported having prior COVID-19 testing. Multivariate analysis (p critical value .05) indicates that women were more likely to report protective behaviors than men, as were those over age 60. Respondents who self-identified as having low incomes, histories of criminal justice involvement, and Republican Party affiliation, were less likely to report four protective behaviors, though Republicans and individuals with criminal justice histories were more likely to report having received COVID-19 testing. The majority of Americans engaged in COVID-19 protective behaviors, with low-income Americans, those with histories of criminal justice involvement, and self-identified Republicans less likely to engage in these preventive behaviors. Culturally competent public health messaging and interventions might focus on these latter groups to prevent future infections. These findings will remain highly relevant even with vaccines widely available, given the complementarities between vaccines and protective behaviors, as well as the many challenges in delivering vaccines., Competing Interests: The authors have declared that no competing interests exist.

Background: A joint infectious disease-podiatry clinic (JIDPC) in which an infectious diseases physician and a podiatrist see patients with diabetic foot infections together once a week was initiated in January 2017. This study was designed to investigate if the JIDPC can improve patient adherence and reduce recurrent infections., Methods: A retrospective analysis of patients with diabetic foot infection admitted to Wheeling Hospital from March 2013 to December 2018 was performed. Initially, the patients were followed by infectious diseases and podiatry in their clinics separately (preintervention group). Beginning January 2017, they were followed together at the JIDPC (postintervention group). Recurrent infection, mortality, and loss to follow-up were compared using logistic regression models., Results: Surgeries were performed in 52.5% of preintervention group participants (n = 99) and 81.9% of postintervention group participants (n = 55; P < .001). The preintervention group was more likely to be lost to follow-up (30.3% vs 9.1%; odds ratio [OR], 4.35 [confidence interval (CI), 1.58-11.99]), but the association was attenuated with further adjustment for surgery (OR 3.35 [CI, 1.17-9.62]). The risk of infection recurrence in 6 months was significantly higher in the preintervention group (36.1% vs 20.8%; OR, 2.16 [CI, 0.99-4.71]), but with further adjustment for surgery, this was not significant (P = .067; OR, 2.17 [CI, 0.95-4.94]). Mortality and 90-day readmission were not significantly different., Conclusions: Implementation of JIDPCs may decrease the incidence of recurrent infections among patients with diabetic foot infections., (Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.)

The Korean government's strategy to combat coronavirus disease 2019 (COVID-19) has focused on non-pharmaceutical interventions, such as social distancing and wearing masks, along with testing, tracing, and treatment; overall, its performance has been relatively good compared to that of many other countries heavily affected by COVID-19. However, little attention has been paid to health equity in measures to control the COVID-19 pandemic. The study aimed to examine the unequal impacts of COVID-19 across socioeconomic groups and to suggest potential solutions to tackle these inequalities. The pathways linking social determinants and health could be entry points to tackle the unequal consequences of this public health emergency. It is crucial for infectious disease policy to consider social determinants of health including poor housing, precarious working conditions, disrupted healthcare services, and suspension of social services. Moreover, the high levels of uncertainty and complexity inherent in this public health emergency, as well as the health and socioeconomic inequalities caused by the pandemic, underscore the need for good governance other than top-down measures by the government. We emphasize that a people-centered perspective is a key approach during the pandemic era. Mutual trust between the state and civil society, strong accountability of the government, and civic participation are essential components of cooperative disaster governance.

In the test-negative design, routine testing at health-care facilities is leveraged to estimate the effectiveness of an intervention such as a vaccine. The odds of vaccination for individuals who test positive for a target pathogen is compared with the odds of vaccination for individuals who test negative for that pathogen, adjusting for key confounders. The design is rapidly growing in popularity, but many open questions remain about its properties. In this paper, we examine temporal confounding by generalizing derivations to allow for time-varying vaccine status, including out-of-season controls, and open populations. We confirm that calendar time is an important confounder when vaccine status varies during the study. We demonstrate that, where time is not a confounder, including out-of-season controls can improve precision. We generalize these results to open populations. We use our theoretical findings to interpret 3 recent papers utilizing the test-negative design. Through careful examination of the theoretical properties of this study design, we provide key insights that can directly inform the implementation and analysis of future test-negative studies., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Hospital palliative care is an essential part of the COVID-19 response, but relevant data are lacking. The recent literature underscores the need to implement protocols for symptom control and the training of non-specialists by palliative care teams., Aim: The aim of the study was to describe a palliative care unit's consultation and assistance intervention at the request of an Infectious Diseases Unit during the COVID-19 pandemic, determining what changes needed to be made in delivering palliative care., Design: This is a single holistic case study design using data triangulation, for example, audio recordings of team meetings and field notes., Setting/participants: This study was conducted in the Palliative Care Unit of the AUSL-IRCCS hospital of Reggio Emilia, which has no designated beds, consulting with the Infectious Diseases Unit of the same hospital., Results: A total of 9 physicians and 22 nurses of the Infectious Diseases Unit and two physicians of the Palliative Care Unit participated in the study.Our Palliative Care Unit developed a feasible 18-day multicomponent consultation intervention. Three macro themes were identified: (1) new answers to new needs, (2) symptom relief and decision-making process, and (3) educational and training issues., Conclusion: From the perspective of palliative care, some changes in usual care needed to be made. These included breaking bad news, patients' use of communication devices, the limited time available for the delivery of care, managing death necessarily only inside the hospital, and relationships with families.

Mucormycosis are life-threatening fungal infections especially affecting immunocompromised or diabetic patients. Despite treatment, mortality remains high (from 32 to 70% according to organ involvement). This review provides an update on mucormycosis management. The latest recommendations strongly recommend as first-line therapy the use of liposomal amphotericin B (≥5mg/kg) combined with surgery whenever possible. Isavuconazole and intravenous or delayed-release tablet forms of posaconazole have remained second-line. Many molecules are currently in development to fight against invasive fungal diseases but few have demonstrated efficacy against Mucorales. Despite in vitro efficacy, combinations of treatment have failed to demonstrate superiority versus monotherapy. Adjuvant therapies are particularly complex to evaluate without prospective randomized controlled studies, which are complex to perform due to low incidence rate and high mortality of mucormycosis. Perspectives are nonetheless encouraging. New approaches assessing relationships between host, fungi, and antifungal drugs, and new routes of administration such as aerosols could improve mucormycosis treatment., (Copyright © 2020 Elsevier Masson SAS. All rights reserved.)

The modeling of the spreading of communicable diseases has experienced significant advances in the last two decades or so. This has been possible due to the proliferation of data and the development of new methods to gather, mine and analyze it. A key role has also been played by the latest advances in new disciplines like network science. Nonetheless, current models still lack a faithful representation of all possible heterogeneities and features that can be extracted from data. Here, we bridge a current gap in the mathematical modeling of infectious diseases and develop a framework that allows to account simultaneously for both the connectivity of individuals and the age-structure of the population. We compare different scenarios, namely, i) the homogeneous mixing setting, ii) one in which only the social mixing is taken into account, iii) a setting that considers the connectivity of individuals alone, and finally, iv) a multilayer representation in which both the social mixing and the number of contacts are included in the model. We analytically show that the thresholds obtained for these four scenarios are different. In addition, we conduct extensive numerical simulations and conclude that heterogeneities in the contact network are important for a proper determination of the epidemic threshold, whereas the age-structure plays a bigger role beyond the onset of the outbreak. Altogether, when it comes to evaluate interventions such as vaccination, both sources of individual heterogeneity are important and should be concurrently considered. Our results also provide an indication of the errors incurred in situations in which one cannot access all needed information in terms of connectivity and age of the population., Competing Interests: The authors have declared that no competing interests exist.

Transmission of infectious diseases between immobile hosts (e.g., plants, farms) is strongly dependent on the spatial distribution of hosts and the distance-dependent probability of transmission. As the interplay between these factors is poorly understood, we use spatial process and transmission modelling to investigate how epidemic size is shaped by host clustering and spatial range of transmission. We find that for a given degree of clustering and individual-level infectivity, the probability that an epidemic occurs after an introduction is generally higher if transmission is predominantly local. However, local transmission also impedes transfer of the infection to new clusters. A consequence is that the total number of infections is maximal if the range of transmission is intermediate. In highly clustered populations, the infection dynamics is strongly determined by the probability of transmission between clusters of hosts, whereby local clusters act as multiplier of infection. We show that in such populations, a metapopulation model sometimes provides a good approximation of the total epidemic size, using probabilities of local extinction, the final size of infections in local clusters, and probabilities of cluster-to-cluster transmission. As a real-world example we analyse the case of avian influenza transmission between poultry farms in the Netherlands., Competing Interests: The authors have declared that no competing interests exist.

Antibiotic prescription in chronic kidney disease patients poses a twofold problem. The appropriate use of antibacterial agents is essential to ensure efficacy and to prevent the emergence of resistance, and dosages should be adapted to the renal function to prevent adverse effects. SiteGPR is a French website for health professionals to help with prescriptions to chronic kidney disease patients. A working group of infectious disease specialists and nephrology pharmacists reviewed the indications, dosing regimens, administration modalities, and dose adjustments of antibiotics marketed in France for patients with renal failure. Data available on the SiteGPR website and detailed in the present article aims to provide an evidence-based update of infectious disease recommendations to health professionals managing patients with chronic kidney disease., (Copyright © 2019 Elsevier Masson SAS. All rights reserved.)

Objectives: Difficult-to-treat invasive fungal infections require infectious diseases expert consultation to improve treatment outcome and increase survival rates., Methods: The European Confederation of Medical Mycology (ECMM) intends to provide expert help free of charge by a newly founded ECMM Expert Consultation Service for medical centres around the globe seeking advice when there is no fungal infection consultant available. The expert consult will provide recommendations and broad expertise on difficult-to-treat invasive fungal infections (eg azole-resistant Aspergillus species, Candida auris, mucormycosis) to improve diagnostic and therapeutic management and outcome., Results: The initiative plans global outreach through video conferencing between ECMM Excellence Centers and treating physicians. FungiScope ® registries will be used to structure case information and to evaluate the impact of the collegial advice system at regular intervals. Advice will follow recent guidelines, and EQUAL Scores will be used to measure guideline adherence., Conclusions: Infectious diseases expert consultation should be an integral component of care for patients with difficult-to-treat invasive fungal infections. The ECMM Expert Consult will attend to this matter on a global scale., (© 2020 The Authors. Mycoses published by Blackwell Verlag GmbH.)

The article discusses possible prevention and prophylaxis of infectious diseases affecting the course of pregnancy with respect to the mother, fetus and newborn. Also mentioned are diseases for which there is no vaccination. The options for prevention targeted at the periods before and during pregnancy and after delivery are explained. Finally, practical procedures related to vaccination and diagnosis of infectious diseases in women of childbearing age are presented.

The role of physicians in the U.S. Armed Forces is diverse, encompassing a wide array of skills and responsibilities to provide superior healthcare to their patients and to advance military medicine. In addition to healthcare delivery and medical education, military physicians are engaged in public health, operational medicine, and cutting-edge medical research. Thus, clinical research is a crucial component of Graduate Medical Education (GME) and supports critical thinking (knowledge, skills, and abilities) and the development of leadership skills among U.S. military physicians. The Infectious Disease Clinical Research Program (IDCRP) education mission was established in 2005 with the overall goal of supporting the development and training of the next generation of clinical researchers in infectious diseases and related public health disciplines in the Armed Forces using several strategies, including didactic learning, mentored research, and research engagement. Through involvement in the IDCRP, infectious disease fellows, residents (e.g., surgical, internal medicine, and pediatrics), and Master of Public Health (MPH) students have continued their education and gained valuable skills related to clinical research. Trainees either conduct research with IDCRP mentors or participate in IDCRP-led practicum experiences, with research projects ranging from epidemiologic studies to microbiological assessments. Consistent with the needs of the Military Health System (MHS), and in accordance with Accreditation Council for Graduate Medical Education goals, the IDCRP provides opportunities for medical and graduate students, residents, and infectious disease fellows to conduct mentored research within the MHS, as well as gain important leadership skills in the conduct of clinical research. Overall, IDCRP continues to further infectious disease research through the support and education of the next generation of active-duty infectious disease researchers in the MHS., (© Association of Military Surgeons of the United States 2019. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Introduction: There are many unique aspects to the practice of military Infectious Diseases (ID). San Antonio Uniformed Services Health Consortium Infectious Disease (ID) Fellowship is a combined Army and Air Force active duty program. Program leadership thought ID military unique curriculum (MUC) was well integrated into the program. We sought to verify this assumption to guide the decision to formalize the ID MUC. This study describes our strategy for the refinement and implementation of ID specific MUC, assesses the fellow and faculty response to these changes, and provides an example for other programs to follow., Methods: We identified important ID areas through lessons learned from personal military experience, data from the ID Army Knowledge Online e-mail consult service, input from military ID physicians, and the Army and Air Force ID consultants to the Surgeons General. The consultants provided feedback on perceived gaps, appropriateness, and strategy. Due to restrictions in available curricular time, we devised a three-pronged strategy for revision: adapt current curricular practices to include MUC content, develop new learning activities targeted at the key content area, and sustain existing, effective MUC experiences.Learners were assessed by multiple choice question correct answer rate, performance during the simulation exercise, and burn rotation evaluation. Data on correct answer rate were analyzed according to level of training by using Mann-Whitney U test. Program assessment was conducted through anonymous feedback at midyear and end of year program evaluations., Results: Twelve military unique ID content areas were identified. Diseases of pandemic potential and blood borne pathogen management were added after consultant input. Five experiences were adapted to include military content: core and noon conference series, simulation exercises, multiple choice quizzes, and infection control essay questions. A burn intensive care unit (ICU) rotation, Transport Isolation System exercise, and tour of trainee health facilities were the new learning activities introduced. The formal tropical medicine course, infection prevention in the deployed environment course, research opportunities and participation in trainee health outbreak investigations were sustained activities. Ten fellows participated in the military-unique spaced-education multiple-choice question series. Twenty-seven questions were attempted 814 times. 50.37% of questions were answered correctly the first time, increasing to 100% correct by the end of the activity. No difference was seen in the initial correct answer rate between the four senior fellows (median 55% [IQR 49.75, 63.25]) and the six first-year fellows (median 44% [IQR 39.25, 53]) (p = 0.114). Six fellows participated in the simulated deployment scenario. No failure of material synthesis was noted during the simulation exercise and all of the fellows satisfied the stated objectives. One fellow successfully completed the piloted burn ICU rotation. Fellows and faculty reported high satisfaction with the new curriculum., Conclusions: Military GME programs are required by congress to address the unique aspects of military medicine. Senior fellow knowledge using the spaced interval multiple-choice quizzes did not differ from junior fellow rate, supporting our concern that the ID MUC needed to be enhanced. Enhancement of the MUC experience can be accomplished with minimal increases to curricular and faculty time., (Published by Oxford University Press on behalf of the Association of Military Surgeons of the United States 2019.)

Objectives: Hepatitis B is a viral infection primarily affecting people from culturally diverse communities in Australia. While vaccination prevents infection, there is increasing mortality resulting from liver damage associated with chronic infection. Deficits in the national policy and clinical response to hepatitis B result in a low diagnosis rate, inadequate testing and diagnosis processes, and poor access to hepatitis B treatment services. While research identifies inadequate hepatitis B knowledge among people with the virus and primary health care workers, this project sought to identify how specialist clinicians in Australia negotiate cultural diversity, and provide often complex clinical information to people with hepatitis B. Design: A vignette was developed and presented to thirteen viral hepatitis specialist clinicians prior to an electronically recorded interview. Recruitment continued until saturation of themes was reached. Data were thematically coded into themes outlined in the interview schedule. Ethical approval for the research was provided by the La Trobe University Human Research Ethics Committee. Results: Key messages provided to patients with hepatitis B by clinical specialists were identified. These messages were not consistently provided to all patients with hepatitis B, but were determined on perceptions of patient knowledge, age and highest educational level. While the vignette stated that English was not an issue for the patient, most specialists identified the need for an interpreter. Combating stigma related to hepatitis B was seen as important by the specialists and this was done through normalising the virus. Having an awareness of different cultural understandings about hepatitis B specifically, and health and well-being generally, was noted as a communication strategy. Conclusion: Key core competencies need to be developed to deliver educational messages to people with hepatitis B within clinical encounters. The provision of adequate resources to specialist clinics will assist in addressing gaps in the clinical response to hepatitis B.

Only a profound understanding of the structure and function of cells-either as single units or in the context of tissues and whole organisms-will allow a comprehension of what happens in pathological conditions and provides the means to fight disease. The Cell Biology and Infection (BCI for Biologie Cellulaire et Infection) department was created in 2002 at the Institut Pasteur in Paris to develop a research program under the umbrella of cell biology, infection biology, and microbiology. Its visionary ambition was to shape a common framework for cellular microbiology, and to interface the latter with hard sciences like physics and mathematics and cutting-edge technology. This concept, ahead of time, has given high visibility to the field of cellular microbiology and quantitative cell biology, and it has allowed the successful execution of highly interdisciplinary research programs linking a molecular understanding of cellular events with disease. Now, the BCI department embraces additional pathologies, namely cancer and neurodegenerative diseases. Here, we will portray how the integrative research approach of BCI has led to major scientific breakthroughs during the last 10 years, and where we see scientific opportunities for the near future.

In this paper, we analyze the effect of environment noise on the transmission dynamics of a stochastic hepatitis B virus (HBV) infection model with intervention strategies. By using the Markov semigroups theory, we define the stochastic basic reproduction number and find it can be used to govern disease extinction or persistence. When it is less than one, under a mild extra condition, the stochastic system has a disease-free equilibrium and the disease is predicted to die out with probability one. When it is greater than one, under mild extra conditions, the model admits a stationary distribution which means the persistence of the disease. Thus, we observe that larger intensity of noise (resulting in a smaller stochastic basic reproduction number) can suppress the emergence of hepatitis B outbreak. Numerical simulations are also carried out to investigate the influence of information intervention strategies that may change individual behavior and protect the susceptible from infection. Our analysis shows that the environmental noise can greatly a ect the long-term behavior of the system, highlighting the importance of the role of intervention strategies in the control of hepatitis B.

Preventing the infectious disease from breakout and maintaining public health have always been placed at the first place when making public healthy policy. When the epidemic trend of infectious disease arises, compulsory treatment is an efficient pattern to control the rapid spreading. A sliding mode is carried out to evaluate the effect of compulsory treatment in the infectious disease controlling. When the number of infected persons reach a certain level I c, the policy of compulsory treatment will be carried out at rate f . We analyze the influence of the compulsory treatment rate f and threshold value I c to commence the control. Finally we investigate the theorems and the existence of the optimality combination.

In this paper, we investigate a delayed HIV-1 infection model with immune response. Though a logistic growth is incorporated in the growth of the target cells, our focus is on the effect of delays on the infection dynamics. We first study the existence of steady states, which depends on the basic reproduction number R ₀. When R ₀≤1, there is only the infection-free steady state, which is globally asymptotically stable if R ₀ < 1when=""r₀="" > 1, besides the unstable infection-free steady state, there is a unique infected steady state. We then study the local stability of the infected steady state and local Hopf bifurcation at it. The theoretical analysis indicates that the dynamics scenario is complicated. For example, there can be three sequences of critical values, stability switches and double Hopf bifurcation can occur. Some of the theoretical results are also illustrated with numerical simulations.

Background: Outpatient parenteral antimicrobial therapy (OPAT) can be managed by specialists in infectious diseases (ID) or by other physicians. Better management of OPAT can reduce the likelihood of readmission or emergency department (ED) use. The relative success of ID specialists and other physicians in managing OPAT has received little study., Methods: We analyzed a national database of insurance claims for privately insured individuals under age 65, locating inpatient acute-care stays in 2013 and 2014 that were followed by OPAT. Through propensity scoring, patients who received outpatient ID intervention (ID-led OPAT) were matched 1-to-1 with those who did not (Other OPAT). We estimated regression models of hospital and ED admissions and of total healthcare payments over the first 30 days after discharge., Results: The final analytic sample of 8200 observations was well balanced on clinical and demographic characteristics. Soft-tissue infection and osteomyelitis were the most common infections in the index event, each affecting more than 40% of individuals. Relative to those with Other OPAT, people with ID-led OPAT had lower odds of an ED admission (odds ratio [OR] 0.449, 95% confidence interval [CI] 0.311-0.645) or hospitalization (OR 0.661, 95% CI 0.557-0.791) over 30 days, and they accumulated $1488 less in total healthcare payments (95% CI -2 688.56--266.58)., Conclusions: Among privately insured individuals below age 65, ID consultations during OPAT are associated with large and significant reductions in the rates of ED admission and hospital admission in the 30 days after index events, as well as lower total healthcare spending., (© The Author(s) 2018. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.)

In this paper, based on the data of the incidence of schistosomiasis in China from January 2011 to May 2018 we establish SARIMA model and NARX model. These two models are used to predict the incidence of schistosomiasis in China from June 2018 to September 2018. By comparing the mean square error and the mean absolute error of two sets of predicted values, the results show that the NARX model is better and it has an e ective forecasting precision to incidence of schistosomiasis. Then according to the results, a mixed model called NARX-SARIMA model is used to predict the incidence future trends and make a comparison with the two model. The mixed model has a better application based on its good fitting capability.

Background: Influenza-like Illness (ILI) is a medical diagnosis of possible influenza or another respiratory illness with a common set of symptoms. The deaths of four schoolchildren, during a pandemic influenza outbreak in December 2017 in Ghana, raised doubts about the ILI surveillance system's performance. We evaluated the ILI surveillance system in the Greater Accra region, Ghana, to assess the system's attributes and its performance on set objectives., Methods: CDC guidelines were used to evaluate the data of the ILI surveillance system between 2013 and 2017. We interviewed the surveillance personnel on the system's description and operation. Additionally, routinely entered ILI data from the National Influenza Center provided by the six sentinel sites in Accra was extracted. We sampled and reviewed 120 ILI case-investigation forms from these sites. Surveillance activities were examined on system's performance indicators, each being scored on a scale of 1 to 3 (poorest to best performance)., Results: All population and age groups were under ILI surveillance over the period evaluated. Overall, 2948 suspected case-patients, including 392 (13.3%) children under-five were reported, with 219 being positive for influenza virus (Predictive value positive = 7.4%). The predominant influenza subtype was H3N2, recorded in 90 (41.1%) of positive case-patients. The system only met two out of its four objectives. None of the six sentinel sites consistently met their annual 260 suspected case-detection quota. Samples reached the laboratory on average 48 hours after collection and results were disseminated within 7 days. Of 120 case-investigation forms sampled, 91 (76.3%) were completely filled in., Conclusions: The ILI surveillance system in the Greater Accra region is only partially meeting its objectives. While it is found to be sensitive, representative and timely, the data quality was sub-optimal. We recommend the determination of thresholds for alert and outbreak detection and ensuring that sentinel sites meet their weekly case-detection targets., Competing Interests: The authors have declared that no competing interests exist.

The estimation of parameters in biomathematical models is useful to characterize quantitatively the dynamics of biological processes. In this paper, we consider some systems of ordinary differential equations (ODEs) modelling the viral dynamics in a cell culture. These models incorporate the loss of viral particles due to the absorption into target cells. We estimated the parameters of models by least-squares minimization between numerical solution of the system and experimental data of cell cultures. We derived a first integral or conserved quantity, and we proved the use of experimental data in order to test the conservation law. The systems have nonhyperbolic equilibrium points, and the conditions for their stability are obtained by using a Lyapunov function. We complemented these theoretical results with some numerical simulations.

In this paper, we formulate a new age-structured malaria model, which incorporates the age of prevention period of susceptible people, the age of latent period of human and the age of latent period of female Anopheles mosquitoes. We show that there exists a compact global attractor and obtain a sufficient condition for uniform persistence of the solution semiflow. We obtain the basic reproduction number R₀ and show that R₀ completely determines the global dynamics of the model, that is, if R₀ < 1, the disease-free equilibrium is globally asymptotically stable, if R₀ > 1, there exists a unique endemic equilibrium that attracts all solutions for which malaria transmission occurs. Finally, we perform some numerical simulations to illustrate our theoretical results and give a brief discussion.

In this paper, we studied an SVIR epidemic model with nonlocal dispersal and delay, and we find that the existence of traveling wave is determined by the basic reproduction number ℜ₀ and minimal wave speed c * . By applying Schauder's fixed point theorem and Lyapunov functional, the existence and boundary asymptotic behaviour of traveling wave solutions is investigated for ℜ₀>1 and c>c * . The existence of traveling waves is obtained for ℜ₀>1 and c=c * by employing a limiting argument. We also show that the nonexistence of traveling wave solutions by Laplace transform. Our results imply that (i) the diffusion and infection ability of infected individuals can accelerate the wave speed; (ii) the latent period and successful rate of vaccination can slow down the wave speed.

Time-varying individual host susceptibility to a disease due to waning and boosting of immunity is known to induce rich long-term behavior of the disease transmission dynamics. Simultaneously, the impact of the time-varying heterogeneity of host susceptibility on the short-term behavior of epidemics is not well-studied despite the availability of a large amount of epidemiological data on short-term epidemics. This paper proposes a parsimonious mathematical model describing the short-term transmission dynamics by taking into account waning and enhancing susceptibility following the infection. In addition to the common classification in the standard SIR model, i.e., "no epidemic" as R₀≤1 or normal epidemic as R₀>1, the proposed model also shows the "delayed epidemic" class when an epidemic takes off after the negative slope of the epidemic curve at the initial phase of the epidemic. The condition for each of the three classes is derived based on the obtained explicit solution for the proposed model.

Cholera is an acute intestinal illness caused by infection with the bacterium Vibrio cholerae. The dynamics of the disease transmission are governed by human-human, environment-human, and within-human sub-dynamics. A multi-scale model is presented to incorporate all three of these dynamical components. The model is divided into three subsystems where the dynamics are analyzed according to their respective time scales. For each subsystem, we conduct a careful equilibrium analysis, with a focus on the disease threshold characterized by the basic reproduction number. Finally, the three subsystems are combined to discuss the dynamical properties of the full system.

Sanitation and awareness programs play a fundamental role and are much effective public health interventions to control the spread of infectious diseases. In this paper, a nonlinear mathematical model for the control of infectious diseases, such as typhoid fever is proposed and analyzed by considering budget required for sanitation and awareness programs as a dynamic variable. It is assumed that the budget allocation regarding the protection against the disease to warn people and for sanitation increases logistically and its per-capita growth rate increases with the increase in number of infected individuals. In the model formulation, it is assumed that the susceptible individuals contract infection through the direct contact with infected individuals as well as indirectly through bacteria shed in the environment. It is further assumed that a fraction of budget is used to warn people via propagating awareness whereas the remaining part is used for sanitation to reduce the density of bacteria. The condition when budget should spend on sanitation/awareness to reduce the number of infected individuals is obtained. Model analysis reveals that the sanitation and awareness programs have capability to reduce the epidemic threshold and thus control the spread of infection. However, delay in providing funds destabilizes the system and may cause stability switches through Hopf-bifurcation. Numerical simulations are also carried out to support analytical findings.

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Zika fever is an acute infectious disease caused by the Zika virus (ZIKV), an RNA virus belonging to the genus Flavivirus. ZIKV can be transmitted by bites from Aedes aegypti and Aedes albopictus species, sexual activity, blood transfusion and from mother to fetus during pregnancy and delivery. A total of 50 territories and countries in the Americas had reported ZIKV infections. For those with symptoms, the presentation is similar to dengue fever with body aches, joint pain, fatigue, malaise, fever and conjunctivitis lasting up to seven days. A maculopapular rash may also occur and is usually pruritic. Neurological complications are well documented and include Guillain-Barré Syndrome (GBS) and congenital ZIKV syndrome, and less frequently acute myelitis and meningoencephalitis. ZIKV infection usually causes a mild illness and most patients are managed conservatively. Currently, no antiviral therapy is available. The most appropriate therapy for ZIKV-associated GBS is yet unclear, however intravenous immunoglobulins have been used, as in conventional GBS. ZIKV infection can be prevented through the use of mosquito repellents, protection with long-sleeved clothing and trousers, and the use of clothes impregnated with permethrin. This review describes the current concepts regarding the epidemiology, diagnosis, clinical manifestations and neurological complications of ZIKV infection., (Copyright © 2018. Published by Elsevier Inc.)

Background: Recent epidemics have entailed global discussions on revamping epidemic control and prevention approaches. A general consensus is that all sources of data should be embraced to improve epidemic preparedness. As a disease transmission is inherently governed by individual-level responses, pathogen dynamics within infected hosts posit high potentials to inform population-level phenomena. We propose a multiscale approach showing that individual dynamics were able to reproduce population-level observations., Methods: Using experimental data, we formulated mathematical models of pathogen infection dynamics from which we simulated mechanistically its transmission parameters. The models were then embedded in our implementation of an age-specific contact network that allows to express individual differences relevant to the transmission processes. This approach is illustrated with an example of Ebola virus (EBOV)., Results: The results showed that a within-host infection model can reproduce EBOV's transmission parameters obtained from population data. At the same time, population age-structure, contact distribution and patterns can be expressed using network generating algorithm. This framework opens a vast opportunity to investigate individual roles of factors involved in the epidemic processes. Estimating EBOV's reproduction number revealed a heterogeneous pattern among age-groups, prompting cautions on estimates unadjusted for contact pattern. Assessments of mass vaccination strategies showed that vaccination conducted in a time window from five months before to one week after the start of an epidemic appeared to strongly reduce epidemic size. Noticeably, compared to a non-intervention scenario, a low critical vaccination coverage of 33% cannot ensure epidemic extinction but could reduce the number of cases by ten to hundred times as well as lessen the case-fatality rate., Conclusions: Experimental data on the within-host infection have been able to capture upfront key transmission parameters of a pathogen; the applications of this approach will give us more time to prepare for potential epidemics. The population of interest in epidemic assessments could be modelled with an age-specific contact network without exhaustive amount of data. Further assessments and adaptations for different pathogens and scenarios to explore multilevel aspects in infectious diseases epidemics are underway.

Introduction: Accurate and timely prediction for endemic infectious diseases is vital for public health agencies to plan and carry out any control methods at an early stage of disease outbreaks. Climatic variables has been identified as important predictors in models for infectious disease forecasts. Various approaches have been proposed in the literature to produce accurate and timely predictions and potentially improve public health response., Methods: We assessed how the machine learning LASSO method may be useful in providing useful forecasts for different pathogens in countries with different climates. Separate LASSO models were constructed for different disease/country/forecast window with different model complexity by including different sets of predictors to assess the importance of different predictors under various conditions., Results: There was a more apparent cyclicity for both climatic variables and incidence in regions further away from the equator. For most diseases, predictions made beyond 4 weeks ahead were increasingly discrepant from the actual scenario. Prediction models were more accurate in capturing the outbreak but less sensitive to predict the outbreak size. In different situations, climatic variables have different levels of importance in prediction accuracy., Conclusions: For LASSO models used for prediction, including different sets of predictors has varying effect in different situations. Short term predictions generally perform better than longer term predictions, suggesting public health agencies may need the capacity to respond at short-notice to early warnings., (Copyright © 2018 Elsevier Inc. All rights reserved.)

The aim of this study was to develop an audit tool with a built-in database using Research Electronic Data Capture (REDCap®) as part of an antimicrobial stewardship program at a regional hospital in the Central Denmark Region, and to analyse the need, if any, to involve more than one expert in the evaluation of cases of antimicrobial treatment, and the level of agreement among the experts. Patients treated with systemic antimicrobials in the period from 1 September 2015 to 31 August 2016 were included, in total 722 cases. Data were collected retrospectively and entered manually. The audit was based on seven flow charts regarding: (1) initiation of antimicrobial treatment (2) infection (3) prescription and administration of antimicrobials (4) discontinuation of antimicrobials (5) reassessment within 48 h after the first prescription of antimicrobials (6) microbiological sampling in the period between suspicion of infection and the first administration of antimicrobials (7) microbiological results. The audit was based on automatic calculations drawing on the entered data and on expert assessments. Initially, two experts completed the audit, and in the cases in which they disagreed, a third expert was consulted. In 31.9% of the cases, the two experts agreed on all elements of the audit. In 66.2%, the two experts reached agreement by discussing the cases. Finally, 1.9% of the cases were completed in cooperation with a third expert. The experts assessed 3406 flow charts of which they agreed on 75.8%. We succeeded in creating an audit tool with a built-in database that facilitates independent expert evaluation using REDCap. We found a large inter-observer difference that needs to be considered when constructing a project based on expert judgements. Our two experts agreed on most of the flow charts after discussion, whereas the third expert's intervention did not have any influence on the overall assessment., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Background: Tuberculosis (TB) is the leading cause of infectious disease deaths worldwide and is the leading cause of death among people with HIV. The World Health Organization (WHO) has called for collaboration between public and private healthcare providers to maximize integration of TB/HIV services and minimize costs. We systematically reviewed published models of public-private sector diagnostic and referral services for TB/HIV co-infected patients., Methods: We searched PubMed, the Cochrane Central Register of Controlled Trials, Google Scholar, Science Direct, CINAHL and Web of Science. We included studies that discussed programs that linked private and public providers for TB/HIV concurrent diagnostic and referral services and used Review Manager (Version 5.3, 2015) for meta-analysis., Results: We found 1,218 unduplicated potentially relevant articles and abstracts; three met our eligibility criteria. All three described public-private TB/HIV diagnostic/referral services with varying degrees of integration. In Kenya private practitioners were able to test for both TB and HIV and offer state-subsidized TB medication, but they could not provide state-subsidized antiretroviral therapy (ART) to co-infected patients. In India private practitioners not contractually engaged with the public sector offered TB/HIV services inconsistently and on a subjective basis. Those partnered with the state, however, could test for both TB and HIV and offer state-subsidized medications. In Nigeria some private providers had access to both state-subsidized medications and diagnostic tests; others required patients to pay out-of-pocket for testing and/or treatment. In a meta-analysis of the two quantitative reports, TB patients who sought care in the public sector were almost twice as likely to have been tested for HIV than TB patients who sought care in the private sector (risk ratio [RR] 1.98, 95% confidence interval [CI] 1.88-2.08). However, HIV-infected TB patients who sought care in the public sector were marginally less likely to initiate ART than TB patients who sought care from private providers (RR 0.89, 95% CI 0.78-1.03)., Conclusion: These three studies are examples of public-private TB/HIV service delivery and can potentially serve as models for integrated TB/HIV care systems. Successful public-private diagnostic and treatment services can both improve outcomes and decrease costs for patients co-infected with HIV and TB.

The intuitive response to an invading pathogen is to start disease management as rapidly as possible, since this would be expected to minimise the future impacts of disease. However, since more spread data become available as an outbreak unfolds, processes underpinning pathogen transmission can almost always be characterised more precisely later in epidemics. This allows the future progression of any outbreak to be forecast more accurately, and so enables control interventions to be targeted more precisely. There is also the chance that the outbreak might die out without any intervention whatsoever, making prophylactic control unnecessary. Optimal decision-making involves continuously balancing these potential benefits of waiting against the possible costs of further spread. We introduce a generic, extensible data-driven algorithm based on parameter estimation and outbreak simulation for making decisions in real-time concerning when and how to control an invading pathogen. The Control Smart Algorithm (CSA) resolves the trade-off between the competing advantages of controlling as soon as possible and controlling later when more information has become available. We show-using a generic mathematical model representing the transmission of a pathogen of agricultural animals or plants through a population of farms or fields-how the CSA allows the timing and level of deployment of vaccination or chemical control to be optimised. In particular, the algorithm outperforms simpler strategies such as intervening when the outbreak size reaches a pre-specified threshold, or controlling when the outbreak has persisted for a threshold length of time. This remains the case even if the simpler methods are fully optimised in advance. Our work highlights the potential benefits of giving careful consideration to the question of when to start disease management during emerging outbreaks, and provides a concrete framework to allow policy-makers to make this decision.

We present a method, known in control theory, to give set-membership estimates for the states of a population in which an infectious disease is spreading. An estimation is reasonable due to the fact that the parameters of the equations describing the dynamics of the disease are not known with certainty. We discuss the properties of the resulting estimations. These include the possibility to determine best- or worst-case-scenarios and identify under which circumstances they occur, as well as a method to calculate confidence intervals for disease trajectories under sparse data. We give numerical examples of the technique using data from the 2014 outbreak of the Ebola virus in Africa. We conclude that the method presented here can be used to extract additional information from epidemiological data.

Tuberculosis (TB) is returning to be a worldwide global public health threat. It is estimated that 9.6 million cases occurred in 2014, of which just two-thirds notified to public health authorities. The "missing cases" constitute a severe challenge for TB transmission control. TB is a severe disease in India, while, worldwide, the WHO estimates that one third of the entire world population is infected. Nowadays, incidence estimation relies increasingly more on notifications of new cases from routine surveillance. There is an urgent need for better estimates of the load of TB, in high-burden settings. We developed a simple model of TB transmission dynamics, using a dynamical system model, consisting of six classes of individuals. It contains the current medical epidemiologists' understanding of the spread of the Mycobacterium tuberculosis in humans, which is substantiated by field observations at the district level in India. The model incorporates the treatment options provided by the public and private sectors in India. Mathematically, an interesting feature of the system is that it exhibits a backward, or subcritical, bifurcation. One of the results of the investigation shows that the discrepancy between the diagnosis rates of the public and private sector does not seem to be the cause of the endemicity of the disease, and, unfortunately, even if they reached 100% of correct diagnosis, this would not be enough to achieve disease eradication. Several other approaches have been attempted on the basis of this model to indicate possible strategies that may lead to disease eradication, but the rather sad conclusion is that they unfortunately do not appear viable in practice.

This paper is dedicated to the application of two types of SEIR models to the influenza outbreak peak prediction in Russian cities. The first one is a continuous SEIR model described by a system of ordinary differential equations. The second one is a discrete model formulated as a set of difference equations, which was used in the Baroyan-Rvachev modeling framework for the influenza outbreak prediction in the Soviet Union. The outbreak peak day and height predictions were performed by calibrating both models to varied-size samples of long-term data on ARI incidence in Moscow, Saint Petersburg, and Novosibirsk. The accuracy of the modeling predictions on incomplete data was compared with a number of other peak forecasting methods tested on the same dataset. The drawbacks of the described prediction approach and possible ways to overcome them are discussed.

For an intervention against the spread of communicable diseases, the idealized situation is when individuals fully comply with the intervention and the exposure to the infectious agent is comparable across all individuals. Some level of non-compliance is likely where the intervention is widely implemented. The focus is on a more accurate view of its effects population-wide. A frailty model is applied. Qualitative analysis, in mathematical terms, reveals how large variability in compliance renders the intervention less effective. This finding sharpens our vague, intuitive and empirical notions. An effective reproduction number in the presence of frailty is defined and is shown to be invariant with respect to the time-scale of disease progression. This makes the results in this paper valid for a wide spectrum of acute and chronic infectious diseases. Quantitative analysis by comparing numerical results shows that they are also robust with respect to assumptions on disease progression structure and distributions, such as with or without the latent period and the assumed distributions of latent and infectious periods.

The recent measles outbreaks in US and Germany emphasize the importance of sustaining and increasing vaccination rates. In Slovakia, despite mandatory vaccination scheme, decrease in the vaccination rates against measles has been observed in recent years. Different kinds of intervention at the state level, like a law making vaccination a requirement for school entry or education and advertising seem to be the only strategies to improve vaccination coverage. This study aims to analyze the economic effectiveness of intervention in Slovakia. Using real options techniques we determine the level of vaccination rate at which it is optimal to perform intervention. We represent immunization rate of newborns as a stochastic process and intervention as a one-period jump of this process. Sensitivity analysis shows the importance of early intervention in the population with high initial average vaccination coverage. Furthermore, our numerical results demonstrate that the less certain we are about the future development of the immunization rate of newborns, the more valuable is the option to intervene.

Funds from various global organizations, such as, The Global Fund, The World Bank, etc. are not directly distributed to the targeted risk groups. Especially in the so-called third-world-countries, the major part of the fund in HIV prevention programs comes from these global funding organizations. The allocations of these funds usually pass through several levels of decision making bodies that have their own specific parameters to control and specific objectives to achieve. However, these decisions are made mostly in a heuristic manner and this may lead to a non-optimal allocation of the scarce resources. In this paper, a hierarchical mathematical optimization model is proposed to solve such a problem. Combining existing epidemiological models with the kind of interventions being on practice, a 3-level hierarchical decision making model in optimally allocating such resources has been developed and analyzed. When the impact of antiretroviral therapy (ART) is included in the model, it has been shown that the objective function of the lower level decision making structure is a non-convex minimization problem in the allocation variables even if all the production functions for the intervention programs are assumed to be linear.

Pathologists have been, are and will be always implicated in the diagnosis of infectious and tropical diseases. The resurgence of opportunistic infections due to the development of immunosuppressive drugs, the increase of migratory involvements draining tropical infections and the last epidemics spotlight the importance of pathologists in the field of infectious diseases. However, cancer is nowadays the first preoccupation of pathologists, which is constantly subject to evaluate diagnostic and prognostic markers and factors predictive to targeted therapy response or immunotherapy. As tumor pathology, infectious diseases require more sophisticated and rapidly changing complementary techniques, appraisals and perhaps a national network of diagnosis. The infectious pathology club committee carries out here a census of methods used in the diagnosis of infectious diseases in France in 2015 and particularly the different techniques used by laboratories to perform infectious diseases diagnosis. This will lay down the foundation of a future national organization of the infectious pathology in providing efficient services (diagnostic support, complementary tools) for the community of French pathologists in this specific domain of competence., (Copyright © 2017 Elsevier Masson SAS. All rights reserved.)

Household contacts of pulmonary tuberculosis (TB) patients are at increased risk of TB infection and disease. However, their risk in relation to the intensity of exposure remains unknown.We studied smear-positive TB cases and their household contacts in Vitória, Brazil. We collected clinical, demographic and radiographic information from TB cases, and obtained tuberculin skin test (TST) and QuantiFERON-TB Gold (QFT) results from household contacts. We measured intensity of exposure using a proximity score and sleep location in relation to the TB index case and defined infection by TST ≥10 mm or QFT ≥0.35 UI·mL -1 We ascertained secondary TB cases by reviewing local and nationwide case registries.We included 160 TB index cases and 894 household contacts. 464 (65%) had TB infection and 23 (2.6%) developed TB disease. Risk of TB infection and disease increased with more intense exposures. In an adjusted analysis, the proximity score was associated with TB disease (OR 1.61, 95% CI 1.25-2.08; p<0.000); however, its diagnostic performance was only moderate.Intensity of exposure increased risk of TB infection and disease among household contacts; however, its diagnostic performance was still suboptimal. A biomarker to target preventive therapy is urgently needed in this at-risk population., Competing Interests: Conflict of interest: Disclosures can be found alongside this article at erj.ersjournals.com, (Copyright ©ERS 2018.)

Latent tuberculosis infection (LTBI) screening is an important intervention for tuberculosis (TB) elimination in low-incidence countries and is, therefore, a key component of England's TB control strategy. This study describes outcomes from a LTBI screening programme in a high-incidence area to inform national LTBI screening in England and other low-incidence countries.We conducted a retrospective cohort study of LTBI screening among eligible migrants (from high-incidence countries and entered the UK within the last 5 years), who were identified at primary-care clinics in Newham, London between August 2014 and August 2015. Multivariable logistic regression was used to identify factors associated with LTBI testing uptake, interferon-γ release assay (IGRA) positivity and treatment uptake.40% of individuals offered LTBI screening received an IGRA test. The majority of individuals tested were 16-35 years old, male and born in India, Bangladesh or Pakistan. Country of birth, smoking status and co-morbidities were associated with LTBI testing uptake. IGRA positivity was 32% among those tested and was significantly associated with country of birth, age, sex and co-morbidities.This study identifies factors associated with screening uptake, IGRA positivity and treatment uptake, and improves understanding of groups that should be supported to increase acceptability of LTBI testing and treatment in the community., Competing Interests: Conflict of interest: None declared., (Copyright ©ERS 2018.)