Estimating the reproduction number and transmission heterogeneity from the size distribution of clusters of identical pathogen sequences.

Quantifying transmission intensity and heterogeneity is crucial to ascertain the threat posed by infectious diseases and inform the design of interventions. Methods that jointly estimate the reproduction number R and the dispersion parameter k have however mainly remained limited to the analysis of epidemiological clusters or contact tracing data, whose collection often proves difficult. Here, we show that clusters of identical sequences are imprinted by the pathogen offspring distribution, and we derive an analytical formula for the distribution of the size of these clusters. We develop and evaluate an inference framework to jointly estimate the reproduction number and the dispersion parameter from the size distribution of clusters of identical sequences. We then illustrate its application across a range of epidemiological situations. Finally, we develop a hypothesis testing framework relying on clusters of identical sequences to determine whether a given pathogen genetic subpopulation is associated with increased or reduced transmissibility. Our work provides tools to estimate the reproduction number and transmission heterogeneity from pathogen sequences without building a phylogenetic tree, thus making it easily scalable to large pathogen genome datasets.

A causal relationship between educational attainment and risk of infectious diseases: A Mendelian randomisation study.

Background: Previous observational studies have investigated the association between educational attainment and sepsis, pneumonia, and urinary tract infections (UTIs). However, their findings have been susceptible to reverse causality and confounding factors. Furthermore, no study has examined the effect of educational level on the risk of infections of the skin and subcutaneous tissue (SSTIs). Thus, we aimed to evaluate the causal relationships between educational level and the risk of four infectious diseases using Mendelian randomisation (MR) techniques. Methods: We used univariable MR analysis to investigate the causal associations between educational attainment (years of schooling (n = 766 345) and holding college or university degree (n = 334 070)) and four infectious diseases (sepsis (n = 486 484), pneumonia (n = 486 484), UTIs (n = 463 010), and SSTIs (n = 218 792)). We included genetic instrumental variables with a genome-wide significance (P < 5 × 10-8) in the study. We used inverse variance-weighted estimation in the primary analysis and explored the stability of the results using multivariable MR analysis after adjusting for smoking, alcohol consumption, and body mass index. Results: Genetically predicted years of schooling were associated with a reduced risk of sepsis (odds ratio (OR) = 0.763; 95% confidence interval (CI) = 0.668-0.870, P = 5.525 × 10-5), pneumonia (OR = 0.637; 95% CI = 0.577-0.702, P = 1.875 × 10-19), UTIs (OR = 0.995; 95% CI = 0.993-0.997, P = 1.229 × 10-5), and SSTIs (OR = 0.696; 95% CI = 0.605-0.801, P = 4.034 × 10-7). We observed consistent results for the correlation between qualifications and infectious diseases. These findings remained stable in the multivariable MR analyses. Conclusions: Our findings suggest that increased educational attainment may be causally associated with a decreased risk of sepsis, pneumonia, UTIs, and SSTIs.

Construction and application of the core competence course training system for infectious disease specialist nurses.

OBJECTIVES: This study aims to construct and apply a training course system which was scientific and comprehensive to foster the core competence of infectious disease specialist nurses. DESIGN: A two-round Delphi consultation survey was carried out to collect feedback from experts on constructing the training course system of core competence for infectious disease specialist nurses. Besides, a non-randomized controlled experimental study was adopted to check the application effect of the courses. METHODS: This study adopted a series of methods including group discussion, theoretical analysis and Delphi consultation to draft the training course content of core competence of infectious disease specialist nurses. Twenty-one Chinese experts were invited to participate in the Delphi consultation from November 2021 to December 2021. From October 2022 to January 2023, a total of 105 infectious disease specialist nurses from two training bases were selected by the convenience sampling method, of which the nurses in one training base were the control group and the nurses in the other training base were the observation group. The observation group was trained by the constructed core competence training course. Questionnaire evaluation was used to compare the core competence of infectious disease specialist nurses and the training effect. RESULTS: The experts, regarded as the authorities on the subject, were highly motivated in this study. Besides, they reached a consensus on the results. The final training course system of core competence for infectious disease specialist nurses focused on 5 competence modules and was composed of 12 categories of courses with 66 classes and corresponding objectives. The core competence scores of the observation group were significantly higher than those in the control group after training (P < 0.05), which proved the training system can effectively enhance the core competence of infectious disease specialist nurses. CONCLUSIONS: The research methods embodied scientific and precise properties. The course system was comprehensive in content and reliable in results. It could serve as a reference for training infectious disease specialist nurses.

Mathematical modeling and dynamics of immunological exhaustion caused by measles transmissibility interaction with HIV host.

This paper mainly addressed the study of the transmission dynamics of infectious diseases and analysed the effect of two different types of viruses simultaneously that cause immunodeficiency in the host. The two infectious diseases that often spread in the populace are HIV and measles. The interaction between measles and HIV can cause severe illness and even fatal patient cases. The effects of the measles virus on the host with HIV infection are studied using a mathematical model and their dynamics. Analysing the dynamics of infectious diseases in communities requires the use of mathematical models. Decisions about public health policy are influenced by mathematical modeling, which sheds light on the efficacy of various control measures, immunization plans, and interventions. We build a mathematical model for disease spread through vertical and horizontal human population transmission, including six coupled nonlinear differential equations with logistic growth. The fundamental reproduction number is examined, which serves as a cutoff point for determining the degree to which a disease will persist or die. We look at the various disease equilibrium points and investigate the regional stability of the disease-free and endemic equilibrium points in the feasible region of the epidemic model. Concurrently, the global stability of the equilibrium points is investigated using the Lyapunov functional approach. Finally, the Runge-Kutta method is utilised for numerical simulation, and graphic illustrations are used to evaluate the impact of different factors on the spread of the illness. Critical factors that effect the dynamics of disease transmission and greatly affect the rate and range of the disease's spread in the population have been determined through a thorough analysis. These factors are crucial in determining the expansion of the disease.

Memory effects in disease modelling through kernel estimates with oscillatory time history.

We design a linear chain trick algorithm for dynamical systems for which we have oscillatory time histories in the distributed time delay. We make use of this algorithmic framework to analyse memory effects in disease evolution in a population. The modelling is based on a susceptible-infected-recovered SIR-model and on a susceptible-exposed-infected-recovered SEIR-model through a kernel that dampens the activity based on the recent history of infectious individuals. This corresponds to adaptive behavior in the population or through governmental non-pharmaceutical interventions. We use the linear chain trick to show that such a model may be written in a Markovian way, and we analyze the stability of the system. We find that the adaptive behavior gives rise to either a stable equilibrium point or a stable limit cycle for a close to constant number of susceptibles, i.e. locally in time. We also show that the attack rate for this model is lower than it would be without the dampening, although the adaptive behavior disappears as time goes to infinity and the number of infected goes to zero.

A study of the attenuation stage of a global infectious disease.

Introduction: Differences in control measures and response speeds between regions may be responsible for the differences in the number of infections of global infectious diseases. Therefore, this article aims to examine the decay stage of global infectious diseases. We demonstrate our method by considering the first wave of the COVID-19 epidemic in 2020. Methods: We introduce the concept of the attenuation rate into the varying coefficient SEIR model to measure the effect of different cities on epidemic control, and make inferences through the integrated adjusted Kalman filter algorithm. Results: We applied the varying coefficient SEIR model to 136 cities in China where the total number of confirmed cases exceeded 20 after the implementation of control measures and analyzed the relationship between the estimated attenuation rate and local factors. Subsequent analysis and inference results show that the attenuation rate is significantly related to the local annual GDP and the longitude and latitude of a city or a region. We also apply the varying coefficient SEIR model to other regions outside China. We find that the fitting curve of the average daily number of new confirmed cases simulated by the variable coefficient SEIR model is consistent with the real data. Discussion: The results show that the cities with better economic development are able to control the epidemic more effectively to a certain extent. On the other hand, geographical location also affected the effectiveness of regional epidemic control. In addition, through the results of attenuation rate analysis, we conclude that China and South Korea have achieved good results in controlling the epidemic in 2020.

An immuno-epidemiological model with waning immunity after infection or vaccination.

In epidemics, waning immunity is common after infection or vaccination of individuals. Immunity levels are highly heterogeneous and dynamic. This work presents an immuno-epidemiological model that captures the fundamental dynamic features of immunity acquisition and wane after infection or vaccination and analyzes mathematically its dynamical properties. The model consists of a system of first order partial differential equations, involving nonlinear integral terms and different transfer velocities. Structurally, the equation may be interpreted as a Fokker-Planck equation for a piecewise deterministic process. However, unlike the usual models, our equation involves nonlocal effects, representing the infectivity of the whole environment. This, together with the presence of different transfer velocities, makes the proved existence of a solution novel and nontrivial. In addition, the asymptotic behavior of the model is analyzed based on the obtained qualitative properties of the solution. An optimal control problem with objective function including the total number of deaths and costs of vaccination is explored. Numerical results describe the dynamic relationship between contact rates and optimal solutions. The approach can contribute to the understanding of the dynamics of immune responses at population level and may guide public health policies.

Surveillance for Emerging and Reemerging Pathogens Using Pathogen Agnostic Metagenomic Sequencing in the United States: A Critical Role for Federal Government Agencies.

The surveillance and identification of emerging, reemerging, and unknown infectious disease pathogens is essential to national public health preparedness and relies on fluidity, coordination, and interconnectivity between public and private pathogen surveillance systems and networks. Developing a national sentinel surveillance network with existing resources and infrastructure could increase efficiency, accelerate the identification of emerging public health threats, and support coordinated intervention strategies that reduce morbidity and mortality. However, implementing and sustaining programs to detect emerging and reemerging pathogens in humans using advanced molecular methods, such as metagenomic sequencing, requires making large investments in testing equipment and developing networks of clinicians, laboratory scientists, and bioinformaticians. In this study, we sought to gain an understanding of how federal government agencies currently support such pathogen agnostic testing of human specimens in the United States. We conducted a landscape analysis of federal agency websites for publicly accessible information on the availability and type of pathogen agnostic testing and details on flow of clinical specimens and data. The website analysis was supplemented by an expert review of results with representatives from the federal agencies. Operating divisions within the US Department of Health and Human Services and the US Department of Veterans Affairs have developed and sustained extensive clinical and research networks to obtain patient specimens and perform metagenomic sequencing. Metagenomic facilities supported by US agencies were not equally geographically distributed across the United States. Although many entities have work dedicated to metagenomics and/or support emerging infectious disease surveillance specimen collection, there was minimal formal collaboration across agencies.

Interconnecting global threats: climate change, biodiversity loss, and infectious diseases.

The concurrent pressures of rising global temperatures, rates and incidence of species decline, and emergence of infectious diseases represent an unprecedented planetary crisis. Intergovernmental reports have drawn focus to the escalating climate and biodiversity crises and the connections between them, but interactions among all three pressures have been largely overlooked. Non-linearities and dampening and reinforcing interactions among pressures make considering interconnections essential to anticipating planetary challenges. In this Review, we define and exemplify the causal pathways that link the three global pressures of climate change, biodiversity loss, and infectious disease. A literature assessment and case studies show that the mechanisms between certain pairs of pressures are better understood than others and that the full triad of interactions is rarely considered. Although challenges to evaluating these interactions-including a mismatch in scales, data availability, and methods-are substantial, current approaches would benefit from expanding scientific cultures to embrace interdisciplinarity and from integrating animal, human, and environmental perspectives. Considering the full suite of connections would be transformative for planetary health by identifying potential for co-benefits and mutually beneficial scenarios, and highlighting where a narrow focus on solutions to one pressure might aggravate another.

Identification of Early Warning Signals of Infectious Diseases in Hospitals by Integrating Clinical Treatment and Disease Prevention.

The global incidence of infectious diseases has increased in recent years, posing a significant threat to human health. Hospitals typically serve as frontline institutions for detecting infectious diseases. However, accurately identifying warning signals of infectious diseases in a timely manner, especially emerging infectious diseases, can be challenging. Consequently, there is a pressing need to integrate treatment and disease prevention data to conduct comprehensive analyses aimed at preventing and controlling infectious diseases within hospitals. This paper examines the role of medical data in the early identification of infectious diseases, explores early warning technologies for infectious disease recognition, and assesses monitoring and early warning mechanisms for infectious diseases. We propose that hospitals adopt novel multidimensional early warning technologies to mine and analyze medical data from various systems, in compliance with national strategies to integrate clinical treatment and disease prevention. Furthermore, hospitals should establish institution-specific, clinical-based early warning models for infectious diseases to actively monitor early signals and enhance preparedness for infectious disease prevention and control.

Interferon-γ and infectious diseases: Lessons and prospects.

Infectious diseases continue to claim many lives. Prevention of morbidity and mortality from these diseases would benefit not just from new medicines and vaccines but also from a better understanding of what constitutes protective immunity. Among the major immune signals that mobilize host defense against infection is interferon-γ (IFN-γ), a protein secreted by lymphocytes. Forty years ago, IFN-γ was identified as a macrophage-activating factor, and, in recent years, there has been a resurgent interest in IFN-γ biology and its role in human defense. Here we assess the current understanding of IFN-γ, revisit its designation as an "interferon," and weigh its prospects as a therapeutic against globally pervasive microbial pathogens.

Infection Prevention and Control in Correctional Settings.

Correctional facilities house millions of residents in communities throughout the United States. Such congregate settings are critical for national infection prevention and control (IPC) efforts. Carceral settings can be sites where infectious diseases are detected in patient populations who may not otherwise have access to health care services, and as highlighted by the COVID-19 pandemic, where outbreaks of infectious diseases may result in spread to residents, correctional staff, and the community at large. Correctional IPC, while sharing commonalities with IPC in other settings, is unique programmatically and operationally. In this article, we identify common challenges with correctional IPC program implementation and recommend action steps for advancing correctional IPC as a national public health priority.

Medicaid Inmate Exclusion Policy and Infectious Diseases Care for Justice-Involved Populations.

The Medicaid Inmate Exclusion Policy (MIEP) prohibits using federal funds for ambulatory care services and medications (including for infectious diseases) for incarcerated persons. More than one quarter of states, including California and Massachusetts, have asked the federal government for authority to waive the MIEP. To improve health outcomes and continuation of care, those states seek to cover transitional care services provided to persons in the period before release from incarceration. The Massachusetts Sheriffs' Association, Massachusetts Department of Correction, Executive Office of Health and Human Services, and University of Massachusetts Chan Medical School have collaborated to improve infectious disease healthcare service provision before and after release from incarceration. They seek to provide stakeholders working at the intersection of criminal justice and healthcare with tools to advance Medicaid policy and improve treatment and prevention of infectious diseases for persons in jails and prisons by removing MIEP barriers through Section 1115 waivers.

Exploring hospital resilience protective or risk factors: lessons for future disaster response efforts.

Background: Hospital resilience is essential in responding to disasters, but current research focuses mainly on frameworks and models rather than the protection of resilience and analysis of risk factors during public health emergencies. This study aims to examine the development of resilience in Chinese frontline hospitals during the initial COVID-19 outbreak in 2020, providing insights for future disaster response efforts. Objectives: We conducted interviews with 26 hospital staff members who were involved in the initial response to the COVID-19 outbreak in China. We used a semi-structured interview approach and employed purposive sampling and snowball sampling techniques. The interview outline was guided by the 'Action Framework' proposed by the World Health Organization (WHO) for responding to infectious disease emergencies. This framework includes dimensions such as command, surveillance, risk communication, medical response, and public health response. We analyzed the collected data using Colaizzi's seven-step data analysis method and the template analysis method. Results: WHO's 'action framework' effectively highlights the factors that contribute to hospital resilience. While medical response, including the availability of materials and facilities, the use of information technology, and the capacity for infectious disease diagnosis and treatment, remains crucial, other important aspects include awareness and beliefs about infections, treatment experience, interdisciplinary collaboration, and more. Additionally, it is essential to establish an intelligent command system, foster trusting partnerships between teams, improve monitoring capabilities for infectious disease agents, enhance risk communication through information synchronization and transparency, strengthen infection control planning, and improve environmental disinfection capabilities for effective public health emergency response. These contradictions significantly impact the enhancement of hospital resilience in dealing with major infectious disease outbreaks. Conclusion: In responding to sudden major infectious diseases, hospitals play a vital role within the healthcare system. Enhancing hospital resilience involves more than just improving treatment capabilities. It also requires effective command coordination at the hospital level, infection control planning, and the deployment of intelligent equipment. Additionally, planning for effective communication and coordination between hospitals, communities, and the national healthcare system can further enhance hospital resilience.

Assessing the impact of different contact patterns on disease transmission: Taking COVID-19 as a case.

Human-to-human contact plays a leading role in the transmission of infectious diseases, and the contact pattern between individuals has an important influence on the intensity and trend of disease transmission. In this paper, we define regular contacts and random contacts. Then, taking the COVID-19 outbreak in Yangzhou City, China as an example, we consider age heterogeneity, household structure and two contact patterns to establish discrete dynamic models with switching between daytime and nighttime to depict the transmission mechanism of COVID-19 in population. We studied the changes in the reproduction number with different age groups and household sizes at different stages. The effects of the proportion of two contacts patterns on reproduction number were also studied. Furthermore, taking the final size, the peak value of infected individuals in community and the peak value of quarantine infected individuals and nucleic acid test positive individuals as indicators, we evaluate the impact of the number of random contacts, the duration of the free transmission stage and summer vacation on the spread of the disease. The results show that a series of prevention and control measures taken by the Chinese government in response to the epidemic situation are reasonable and effective, and the young and middle-aged adults (aged 18-59) with household size of 6 have the strongest transmission ability. In addition, the results also indicate that increasing the proportion of random contact is beneficial to the control of the infectious disease in the phase with interventions. This work enriches the content of infectious disease modeling and provides theoretical guidance for the prevention and control of follow-up major infectious diseases.

Long-term variations of urban-Rural disparities in infectious disease burden of over 8.44 million children, adolescents, and youth in China from 2013 to 2021: An observational study.

BACKGROUND: An accelerated epidemiological transition, spurred by economic development and urbanization, has led to a rapid transformation of the disease spectrum. However, this transition has resulted in a divergent change in the burden of infectious diseases between urban and rural areas. The objective of our study was to evaluate the long-term urban-rural disparities in infectious diseases among children, adolescents, and youths in China, while also examining the specific diseases driving these disparities. METHODS AND FINDINGS: This observational study examined data on 43 notifiable infectious diseases from 8,442,956 cases from individuals aged 4 to 24 years, with 4,487,043 cases in urban areas and 3,955,913 in rural areas. The data from 2013 to 2021 were obtained from China's Notifiable Infectious Disease Surveillance System. The 43 infectious diseases were categorized into 7 categories: vaccine-preventable, bacterial, gastrointestinal and enterovirus, sexually transmitted and bloodborne, vectorborne, zoonotic, and quarantinable diseases. The calculation of infectious disease incidence was stratified by urban and rural areas. We used the index of incidence rate ratio (IRR), calculated by dividing the urban incidence rate by the rural incidence rate for each disease category, to assess the urban-rural disparity. During the nine-year study period, most notifiable infectious diseases in both urban and rural areas exhibited either a decreased or stable pattern. However, a significant and progressively widening urban-rural disparity in notifiable infectious diseases was observed. Children, adolescents, and youths in urban areas experienced a higher average yearly incidence compared to their rural counterparts, with rates of 439 per 100,000 compared to 211 per 100,000, respectively (IRR: 2.078, 95% CI [2.075, 2.081]; p < 0.001). From 2013 to 2021, this disparity was primarily driven by higher incidences of pertussis (IRR: 1.782, 95% CI [1.705, 1.862]; p < 0.001) and seasonal influenza (IRR: 3.213, 95% CI [3.205, 3.220]; p < 0.001) among vaccine-preventable diseases, tuberculosis (IRR: 1.011, 95% CI [1.006, 1.015]; p < 0.001), and scarlet fever (IRR: 2.942, 95% CI [2.918, 2.966]; p < 0.001) among bacterial diseases, infectious diarrhea (IRR: 1.932, 95% CI [1.924, 1.939]; p < 0.001), and hand, foot, and mouth disease (IRR: 2.501, 95% CI [2.491, 2.510]; p < 0.001) among gastrointestinal and enterovirus diseases, dengue (IRR: 11.952, 95% CI [11.313, 12.628]; p < 0.001) among vectorborne diseases, and 4 sexually transmitted and bloodborne diseases (syphilis: IRR 1.743, 95% CI [1.731, 1.755], p < 0.001; gonorrhea: IRR 2.658, 95% CI [2.635, 2.682], p < 0.001; HIV/AIDS: IRR 2.269, 95% CI [2.239, 2.299], p < 0.001; hepatitis C: IRR 1.540, 95% CI [1.506, 1.575], p < 0.001), but was partially offset by lower incidences of most zoonotic and quarantinable diseases in urban areas (for example, brucellosis among zoonotic: IRR 0.516, 95% CI [0.498, 0.534], p < 0.001; hemorrhagic fever among quarantinable: IRR 0.930, 95% CI [0.881, 0.981], p = 0.008). Additionally, the overall urban-rural disparity was particularly pronounced in the middle (IRR: 1.704, 95% CI [1.699, 1.708]; p < 0.001) and northeastern regions (IRR: 1.713, 95% CI [1.700, 1.726]; p < 0.001) of China. A primary limitation of our study is that the incidence was calculated based on annual average population data without accounting for population mobility. CONCLUSIONS: A significant urban-rural disparity in notifiable infectious diseases among children, adolescents, and youths was evident from our study. The burden in urban areas exceeded that in rural areas by more than 2-fold, and this gap appears to be widening, particularly influenced by tuberculosis, scarlet fever, infectious diarrhea, and typhus. These findings underscore the urgent need for interventions to mitigate infectious diseases and address the growing urban-rural disparity.