Infectious Diseases Community Research Articles

Biopolitics at the Nexus of Chronic and Infectious Diseases.

Non-communicable (chronic) and communicable (infectious) diseases constitute the leading causes of death worldwide. They appear to impact populations in developed and developing nations differently with changing trends in the landscape of human conditions. Greater understanding of changing disease burdens should influence the planning of health programmes, the implementation of related interventions, and policymaking efforts on a national and global scale. However, the knowledge of disease burdens does not reflect how states and global health organizations prioritize their efforts in addressing them. This work aims to address the discrepancy in public health priority setting by improving our understanding of how the two disease categories impact the human condition. It reviews two case studies, COVID-19 and type 2 diabetes, as representative cases of an infectious and a chronic disease, respectively, to answer the following question. How does biopolitics, as the governance of human bodies, at the nexus of infectious and chronic disease, impact national and global public health priorities? This work contextualizes and reframes the relationship towards disease categories by focusing on three primary themes: risk, current public health interventions, and funding priorities for each case study analysed. It argues that the politics over life at the nexus of chronic and infectious diseases, best conceived as future-oriented economic optimization, directs the efforts of prioritization in healthcare based on risk and responsibility-based relationship between multiple stakeholders.

Natural language processing to evaluate texting conversations between patients and healthcare providers during COVID-19 Home-Based Care in Rwanda at scale.

Community isolation of patients with communicable infectious diseases limits spread of pathogens but our understanding of isolated patients' needs and challenges is incomplete. Rwanda deployed a digital health service nationally to assist public health clinicians to remotely monitor and support SARS-CoV-2 cases via their mobile phones using daily interactive short message service (SMS) check-ins. We aimed to assess the texting patterns and communicated topics to better understand patient experiences. We extracted data on all COVID-19 cases and exposed contacts who were enrolled in the WelTel text messaging program between March 18, 2020, and March 31, 2022, and linked demographic and clinical data from the national COVID-19 registry. A sample of the text conversation corpus was English-translated and labeled with topics of interest defined by medical experts. Multiple natural language processing (NLP) topic classification models were trained and compared using F1 scores. Best performing models were applied to classify unlabeled conversations. Total 33,081 isolated patients (mean age 33·9, range 0-100), 44% female, including 30,398 cases and 2,683 contacts) were registered in WelTel. Registered patients generated 12,119 interactive text conversations in Kinyarwanda (n = 8,183, 67%), English (n = 3,069, 25%) and other languages. Sufficiently trained large language models (LLMs) were unavailable for Kinyarwanda. Traditional machine learning (ML) models outperformed fine-tuned transformer architecture language models on the native untranslated language corpus, however, the reverse was observed of models trained on English-only data. The most frequently identified topics discussed included symptoms (69%), diagnostics (38%), social issues (19%), prevention (18%), healthcare logistics (16%), and treatment (8·5%). Education, advice, and triage on these topics were provided to patients. Interactive text messaging can be used to remotely support isolated patients in pandemics at scale. NLP can help evaluate the medical and social factors that affect isolated patients which could ultimately inform precision public health responses to future pandemics.

Regional Factors Affecting Liver Cancer Mortality Using GWR

Objectives: This study aimed to identify the regional factors affecting liver cancer mortality using geographically weighted regression (GWR). Methods: Data from 2017 to 2019 were utilized, including health examination statistics and regional medical utilization statistics from the National Health Insurance Corporation, regional infectious disease statistics and community health surveys from the Korea Centers for Disease Control and Prevention, mortality statistics and population census data from Statistics Korea. Spatial data were obtained from the Statistical Geographic Information Service, covering 229 cities, counties, and districts. Statistical analysis was performed using R version 4.3.2, with significant variables identified through ordinary least squares (OLS) analysis, followed by GWR to assess model improvement. Results: The OLS analysis identified percent of population aged 40+, incidence of hepatitis C, high-risk drinking rate, and national health insurance premium as significant factors. Moran’s Index showed a positive spatial autocorrelation (0.373, <i>p</i><0.001). GWR analysis increased the adjusted R² from 48% to 61% and reduced the AIC from 1,062.21 to 1,038.59, indicating an improvement in the model’s explanatory power and fit. In Jeollanam-do and Jeju-do, the explanatory power was high, and the percent of population aged 40+ had a strong influence in Gangwon-do. The incidence of hepatitis C had a strong influence in the southern coastal regions, the high-risk drinking rate was notably significant in the Yeongnam region, and the national health insurance premium had a strong influence in Busan. Conclusions: As significant factors vary by region, it is considered important to establish health care policies and projects that take into account the characteristics of each region, and through this, we can expect to reduce liver cancer mortality in the region and improve community health levels.

Toward a lightweight model for pulmonary tuberculosis classification

As in every developing country, Madagascar is still fighting against the tuberculosis (TB), the second leading cause of death from a communicable infectious disease. Its incidence remains high, exacerbated by limited medical infrastructure and unequal distribution of health resources. Several researches were conducted to automatically diagnosis disease to greatly lowering the total expenses. Deep learning approaches demonstrated its high effectiveness in the domain using chest x-ray images (CXR) that are the most cost-effective and widely utilized imaging technology to classify TB. Some preprocessing was necessary for getting better features from the images. Using a more lightweight model inspired by SSD Lite X, this work achieves the highest accuracy (training, validation and testing), recall, F1-Score and specificity of 100% each, making this model the most effective one in the state-of-the-art. It could be deployed in a low-resource environments, enabling automated diagnosis in every region of Madagascar and other developing countries

"Like and Subscribe": A Compendium of Infectious Diseases Audio Podcasts.

In little more than 15 years, the podcast has gone from being virtually unknown to becoming a multibillion-dollar industry. There are an estimated half-billion podcast listeners worldwide. Podcasts are available for various interests, from entertainment to news, politics, sports, hobbies, and education. Podcasting in medicine has similar origins, beginning with journals and academic/educational institutions wishing to share information on new clinical trials or publications, as well as by those who wanted to promote the free and open access model of online education. The COVID-19 outbreak led to a renaissance in the availability of infectious diseases-oriented audio podcasts, due to the need for regular information about SARS-CoV-2 and the pandemic-related preference for virtual learning. However, many in the infectious diseases community have not yet been introduced to available infectious diseases podcast resources. In this article, we highlight 38 of the most popular infectious diseases-oriented audio podcasts.

Single Monoclonal Antibodies Should Not Be Used for COVID-19 Therapy: A Call for Antiviral Stewardship.

The COVID-19 pandemic witnessed the greatest deployment of monoclonal antibody (mAb) therapies for an infectious disease, but all were defeated by SARS-CoV-2 evolution. As new mAbs are developed, the infectious disease community needs stewardship practices to reduce emergence of resistance.

The Role Of Posyandu Cadres In Empowering Communities With Infectious Diseases In Petir District

<em><span>Indonesia ranks third out of eight countries contributing 2/3 of TB (tuberculosis) cases in the world. DHF is a disease that spreads not from one human to another, but from the Aedes Aegypti mosquito. The role of cadres in empowering the infectious disease community is urgently needed as an intermediary for sources of information from medical personnel. Cadres are not only as Posyandu or Posbindu services but cadres can also help medical personnel to turn residents into healthy communities. The purpose of this study was to find out whether Posyandu Cadres and health workers in had carried out their duties to make the community a healthy society or not, and whether they had been optimal in dealing with infectious diseases and also how the cadres worked in handling infectious diseases. The method used in this study is a qualitative method, namely by interviewing one of the cadres in the village of Rt.06 Petir and also the second method, namely by observation. The cadres have worked according to their capacity and have done well, and maybe in the future it will be even better. The results of this research have implications for policy development and implementation of dengue fever eradication programs. Apart from that, finding cadres who have carried out their duties in accordance with their capacity and standard procedures can improve cooperative relations with other related cadres and institutions.</span></em>

Health and Nutrition Promotion Programs in Papua New Guinea: A Scoping Review.

There is a rising prevalence of non-communicable diseases (NCDs) in Papua New Guinea (PNG), adding to the disease burden from communicable infectious diseases and thus increasing the burden on the healthcare system in a low-resource setting. The aim of this review was to identify health and nutrition promotion programs conducted in PNG and the enablers and barriers to these programs. Four electronic databases and grey literature were searched. Two reviewers completed screening and data extraction. This review included 23 papers evaluating 22 health and nutrition promotion programs, which focused on the Ottawa Charter action areas of developing personal skills (12 programs), reorienting health services (12 programs) and strengthening community action (6 programs). Nineteen programs targeted communicable diseases; two addressed NCDs, and one addressed health services. Enablers of health promotion programs in PNG included community involvement, cultural appropriateness, strong leadership, and the use of mobile health technologies for the decentralisation of health services. Barriers included limited resources and funding and a lack of central leadership to drive ongoing implementation. There is an urgent need for health and nutrition promotion programs targeting NCDs and their modifiable risk factors, as well as longitudinal study designs for the evaluation of long-term impact and program sustainability.

Beyond Infection: Mortality and End-of-Life Care Associated with Infectious Disease Consultation in an Academic Health System.

Infectious diseases (ID) physicians are increasingly faced with the challenge of caring for patients with terminal illnesses or incurable infections. This was a retrospective cohort of all patients with an ID consult within an academic health system 1/1/2014 - 12/31/2023, including community, general, and transplant ID consult services. There were 60,820 inpatient ID consults (17,235 community, 29,999 general, and 13,586 transplant) involving 37,848 unique patients. The number of consults increased by 94% and the rate rose from 5.0 to 9.9 consults per 100 inpatients (p<0.001). In total, 7.5% of patients receiving an ID consult died during admission, and 1,006 (2.6%) of patients were discharged to hospice. In-hospital mortality was 5.2% for community ID, 7.8% for general ID, and 10.7% for transplant ID patients (p<0.001). Six-month mortality was 9% for all non-obstetric admissions, , vs. 19% for community ID, 20.9% for general ID, and 22.3% for transplant ID.In total 2,866 (7.6%) of all patients receiving ID consultation also received palliative care consultation during the same hospitalization. The index ID consult preceded any palliative consult in the majority (69.5%) of cases. 16.3% of patients had a do-not-resuscitate order during the index hospitalization. 12.2% of all patients with a do-not-resuscitate order had this placed on the same day as the ID consult. Patients receiving ID consultation were increasingly complex and more likely to die soon after consultation. These results provide a framework for ID clinicians to consider their role in end-of-life care.

Overcoming Challenges for Non-US International Medical Graduates in Pediatric Infectious Diseases.

International medical graduates (IMGs) in pediatric infectious diseases face unique and complex challenges related to their immigration status. This Perspective provides a review of challenges impacting non-US IMG trainees and early-career faculty, and how the infectious diseases community can respond.

Healthcare Sustainability to Address Climate Change: Call for Action to the Infectious Diseases Community.

The U.S. healthcare system's contribution to greenhouse gas emissions and climate change is disproportionately high and harms the public. Several medical specialties are now reassessing how they can mitigate healthcare's harmful environmental impact. Healthcare sustainability is broadly defined as measures to decrease greenhouse gas emissions, waste, and other pollutants generated during the healthcare delivery process. Prior efforts and programs by infectious diseases (ID) professionals, such as antimicrobial stewardship and infection prevention and control can form a framework for ID professionals to help apply this expertise to healthcare environmental sustainability more broadly. This call to action proposes strategies for ID societies and professionals to incorporate climate change education for trainees, increase research and funding opportunities in healthcare sustainability, and calls for action by ID societies to champion system changes to decrease greenhouse gas emissions.

Wastewater-based proteomics: A proof-of-concept for advancing early warning system for infectious diseases and immune response monitoring

In this proof-of-concept study, a new mass spectrometry-based framework was introduced for concurrent tracking of infectious disease prevalence and community responses. The study focused on the detection of SARS-CoV-2 as the test pathogen and C-reactive protein (CRP) as the representative acute phase response protein. Through mass spectrometry (MS), the research provided preliminary insights into the prevalence of the virus and community acute immune responses, suggesting its strong potential as an early warning system. The high specificity and sensitivity of MS, combined with wastewater-based epidemiology's ability to provide a population-level perspective on virus prevalence, make it a valuable tool for public health surveillance. The study's findings demonstrate the utility of targeted proteomics technology in detecting specific protein biomarkers associated with SARS-CoV-2 infection and inflammation in complex wastewater samples. This approach has advantages over traditional RNA-based methods, including the ability to simultaneously detect acute-phase response proteins such as CRP. The study lays the foundation for future research towards refining analytical techniques to extract more precise data from complex matrices. SynopsisWBE proteomics holds a strong potential in wastewater surveillance for pathogens and disease outcomes

Seasonal syndromic surveillance by sentinel system of ILI, ARI, SARI and pneumonia in Romania – season 2023/2024

Syndromic surveillance was initially developed for early detection compared to traditional methods of an epidemiological event with an impact on public health, but as it was applied by more countries it was observed that it can provide information on the size, dynamics of the spread with an emphasis on the potential for national, regional and global evolution, the severity and the most affected population groups, but also to the development of a quick, specific response. Globalization, which involves the intensification of the movement of people (including sick or incubating infectious diseases), live animals, or products of animal origin in and from any part of the planet, but also climate change and pollution, amplifies the danger of the spread of communicable infectious diseases from areas so-called “specific” diseases in new areas, unknown to populations and healthcare systems. In this context, the One Health initiative needs efficient surveillance methods to help promote the health of people, animals, the environment, and ultimately the planet Earth. Recently, there have been substantial changes in the surveillance and control of infectious diseases with an impact on public health aimed at assessing the risks of the emergence of infectious agents with epidemic and pandemic potential by identifying and analyzing favorable factors related to the infectious agent (virulence, variability, transmissibility, etc.), the host organism (immunity, physiological factors, vaccination status, associated chronic diseases, nutritional status, living conditions, etc.), demographic factors (birth rate, mortality, population agglomerations), climatic factors and insect populations vectors, rodents and wild animals (including birds) and last but not least domestic animal populations (including birds). Among these methods, syndromic surveillance stands out, which in addition has the quality of using automatic data acquisition and generating statistical alerts, monitors disease indicators in real-time or near real-time to detect disease outbreaks earlier than would be possible with conventional methods traditional public health. In this context, we will present the Romanian experience regarding the syndromic surveillance of ILI, ARI and SARI in Romania through the national sentinel system season 2023/2024.

Crises in Antimicrobial Stewardship: Misuse of Clarithromycin for Helicobacter pylori Therapy.

Helicobacter pylori is a class I carcinogen that infects more than 100 million individuals in the United States. Antimicrobial therapy for H. pylori has typically been prescribed empirically rather than based on susceptibility testing. Until recently, therapeutic recommendations have generally ignored the principles of antibiotic stewardship. A combination of a proton pump inhibitor (PPI), amoxicillin, and clarithromycin (triple therapy) remains popular despite increasing clarithromycin resistance and poor cure rates. Concomitant therapy (a PPI, amoxicillin, clarithromycin, and metronidazole) is recommended and widely used despite all patients receiving at least one unneeded antibiotic. In 2020, the Food and Drug Administration approved vonoprazan, amoxicillin, and clarithromycin triple therapy, which administers unneeded clarithromycin to >90% of patients (i.e., ~6 tons of unneeded clarithromycin/million treatments). In the late 1980s, the infectious disease community functionally transferred responsibility for the management of H. pylori to gastroenterology, which has managed the infection as another common gastrointestinal disease such as constipation. In 2022, both traditional and noninvasive molecular-based susceptibility testing for H. pylori became available in the United States. In order to reduce and prevent antibiotic misuse, the infectious disease community should reclaim responsibility for the management of this important infectious disease.

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.

A Genetic-Algorithm-Based Dynamic Transmission of Data for Communicable Disease in IoMT Environment

Recent advancements in the field of the Internet of medical things (IoMT) have enabled the real-time monitoring and treatment of patients with communicable infectious diseases while minimizing human intervention. However, IoMT devices face challenges such as unbalanced energy consumption, memory constraints, computation power, and low latency, which can deter the efficient transfer of patient monitoring data. Thus, there is an urgent need to establish an energy-efficient infrastructure for IoMT devices to remotely monitor and collect data on communicable diseases. For this, a genetic algorithm (GA) based dynamic transmission of data for communicable diseases in the IoMT environment is proposed in this paper. The energy utilization of the IoMT is enhanced by considering the GA evolutionary processing based on the dynamic sensor range. The proposed work incorporates a periphery of the fixed area for deploying the IoMT devices to settle the energy hole problem. Multiple sinks and direct information collection concepts are also introduced which further improve the performance and reduce the movement of data packets. The proposed protocols not only optimize energy usage but also provide a robust approach for massive data collection and communication.

Hematopoietic stem cell transplantation: an Italian monocentric experience on the health assessment and eligibility of adult-related donors.

Indications for HSCT are increasing worldwide, paralleled by a growing demand for donors of therapeutic cells. Herein, we report our real-world experience of adult HPC donor assessment during a 5-year study period (2018-2023): we have retrospectively revised data of 455 potential related stem cell donors, consecutively evaluated at our center. Donor medical history was assessed by a questionnaire and an interview with a trained physician experienced in donation procedures to evaluate donor fitness and medical history. Pre-existing health disorders were fully investigated. Behavioral risk factors for communicable infectious diseases were also routinely explored. Overall, 351 donors were finally assessed as eligible for HPC donation, and 233 underwent stem cell collection, 158 through apheresis from mobilized peripheral blood, and 75 through bone marrow harvest. Among them, 27 donors were selected despite the presence of pre-existing health conditions, which would be potential exclusion criteria for unrelated donors: 16 suffered from well-controlled cardiovascular diseases (CVD) and 11 from allergic diathesis. Most of the selected donors with pre-existing disorders were candidates for apheresis HPC collection (21, 77.8%), while only six (22.2%) underwent BM harvest. We then analyzed the data relative to the corresponding 233 allogeneic HSCT to explore if the presence of pre-existing diseases in the donors could show any association with transplant characteristics. Transplants from CVD and allergy donors showed no significant disparities in comparison with those from healthy donors. A significant difference emerged regarding the disease severity, with a higher proportion of patients with high/very high disease risk index (DRI) among those receiving grafts from CVD donors (68.7% in transplants from CVD donors versus 36.0% in transplants from healthy donors, p=0.005). Multivariate analysis confirmed that high/very high DRI patients had an increased probability of receiving donations from CVD donors (OR, 4.89; 95%CI, 1.15-20.86; p=0.031). Among donors with well-controlled pre-existing conditions, no adverse events were recorded during stem cell collection or at follow-up. Our results suggest that in patients at high risk for relapse requiring a prompt allogeneic transplant, a familiar donor might be accepted for HPC apheresis donation on less strict criteria than unrelated donors, without risk for both donor and patient.

High-Density Communities and Infectious Disease Vulnerability: A Built Environment Perspective for Sustainable Health Development

High-density communities have proliferated globally during rapid urbanization. They are characterized by a high population density and limited per capita public spaces, making them susceptible to infectious disease risks. The impact of infectious diseases in these communities, as evident during the COVID-19 pandemic, underscores their vulnerabilities. Yet, research on disease prevention in high-density areas remains limited. This study aims to investigate the relationship between the built environment and the transmission of infectious diseases in high-density urban communities, with a particular focus on the lessons learned during the COVID-19 pandemic. Utilizing Shenzhen city as a case study, this study collected data on the built environment and epidemic trends and involved a generalized linear regression analysis, aiming to understand the key built environment factors that affect epidemic spread in high-density areas. The results from the study revealed that high-density communities experience higher rates of infectious disease transmission compared to their medium- to low-density counterparts. The significant factors identified include land use mixture and walkability, with land use mixture showing the most substantial impact on infection rates. Through a combination of qualitative analysis and empirical research, we constructed a conceptual framework linking containment measures, non-pharmaceutical interventions, and the built environment. The findings emphasize the significance to focus on the health development of high-density communities and offer valuable insights for tailored urban planning and built environment design. These insights are crucial for promoting the healthy and sustainable transformation of existing high-density communities.

The Influence of Cultural Factors, Social Norms, and Social Support on the Spread of Infectious Diseases in Communities in Indonesia

This research investigates the influence of cultural factors, social norms, and social support on the spread of infectious diseases in communities in Indonesia through a quantitative analysis. The structural equation model (SEM) employed in this study examines the complex interplay between these sociocultural elements and their impact on the transmission of infectious diseases. Results indicate significant positive associations between cultural factors and the spread of infectious diseases, social norms and disease transmission, and unexpectedly, social support and disease spread. These findings challenge conventional assumptions, emphasizing the need for nuanced and culturally sensitive public health interventions. The study contributes valuable insights to the understanding of infectious disease dynamics within diverse communities and informs targeted strategies for effective mitigation.

Clinical and Demographic Patterns of Pulmonary Tuberculosis in Patients with Diabetes Mellitus: Impact of Diabetes Mellitus on Patient

Background: Tuberculosis (TB) is a communicable infectious disease and one of the leading causes of death. Until the coronavirus pandemic, tuberculosis was the leading cause of death from a single infectious agent, more than HIV/AIDS. Due to urbanization and rapid social and economic development, there is a rapidly increasing diabetes mellitus (DM) epidemic and India has the second largest number of DM patients in the world. There are around 74.2 million DM cases and 40.1 million people with impaired glucose tolerance. Tuberculosis is more common in low- and middle-income countries. The increasing trend of the two diseases poses a major challenge for the tuberculosis control program.&#x0D; Methods: The main goal of this research was to investigate clinical and demographic patterns of pulmonary tuberculosis in patients with DM. It is a prospective, observational, in-hospital study. We studied 165 PTB patients associated with DM who were at least scanty/1+ positive on smear or had Mycobacterium TB sputum CBNAAT detected.&#x0D; Results: Of the 165 patients, 127 PTB-DM patients were male and 38 were female. The most common symptom was cough, which occurred in 164 (99.4%) patients. Fever was the second most common symptom in 152 (92.1%) patients and anorexia was the third most common symptom, occurring in 119 (72.1%) patients.&#x0D; Conclusion: The majority of patients were from IPD 88 (54%), suggesting that PTB–DM cases have a more severe and complicated presentation. Male patients are affected more frequently than female patients. People in the age group 31–60 years often suffer from PTB–DM. Cough, fever, and anorexia are the most common symptoms, while chest pain and breathlessness are more common in the older age group. The history of PTB in DM patients is also of concern as the present study shows that there is a possible association with relapse or reactivation of PTB as well as drug resistance of PTB.