Disease Surveillance Research Articles

Cardiovascular diseases in Quebec health administrative databases: missing diagnoses and underestimation of the number of cases in a 28-year prospective cohort

Introduction Cardiovascular disease (CVD) surveillance in Quebec and the rest of Canada is carried out using health administrative databases, which in Quebec includes the physician claims database. The presence of billing claims without diagnoses can lead to the number of CVD cases being underestimated. The purpose of this study is to estimate the proportion of CVD diagnoses and CVD cases that may be missing from these databases. Methods The study was conducted using a prospective cohort of 8781 participants living in the Québec City area. Access to health administrative databases was granted for the entire 28-year follow-up period. First, we performed frequency analyses to estimate the proportion of missing CVD diagnoses. Then we used validated algorithms to identify CVD cases and estimate the proportion of CVD cases that were potentially not captured over the 28-year period. Results About one-fifth (22.1%) of the diagnoses in the physician claims database were missing. The proportion of missing CVD cases was estimated at 12.7% for 1991–2018, although this varied with the period covered (1991–1996: 15.5%; 1997–2013: 10.7%; and 2014–2018: 16.3%). Conclusion Approximatively 1 in 10 CVD cases are not identified due to a missing diagnosis. This underestimation of CVD cases is a potential limitation that should be considered when using Quebec health administrative databases to identify CVD cases for surveillance work and epidemiological studies.

Health Care Costs and Utilisation for Diabetes Mellitus among Hospitalised Patients in Ireland: The National Kidney Disease Surveillance System

Health Care Costs and Utilisation for Diabetes Mellitus among Hospitalised Patients in Ireland: The National Kidney Disease Surveillance System

Temporal Characterization of Prion Shedding in Secreta of White-Tailed Deer in Longitudinal Study of Chronic Wasting Disease, United States.

Chronic wasting disease (CWD) affects cervids in North America, Asia, and Scandinavia. CWD is unique in its efficient spread, partially because of contact with infectious prions shed in secreta. To assess temporal profiles of CWD prion shedding, we collected saliva, urine, and feces from white-tailed deer for 66 months after exposure to low oral doses of CWD-positive brain tissue or saliva. We analyzed prion seeding activity by using modified amyloid amplification assays incorporating iron oxide bead extraction, which improved CWD detection and reduced false positives. CWD prions were detected in feces, urine, and saliva as early as 6 months postinfection. More frequent and consistent shedding was observed in deer homozygous for glycine at prion protein gene codon 96 than in deer expressing alternate genotypes. Our findings demonstrate that improved amplification methods can be used to identify early antemortem CWD prion shedding, which might aid in disease surveillance of cervids.

Associations Between Acute COVID-19 Symptom Profiles and Long COVID Prevalence: Population-Based Cross-Sectional Study.

Growing evidence suggests that severe acute COVID-19 illness increases the risk of long COVID (also known as post-COVID-19 condition). However, few studies have examined associations between acute symptoms and long COVID onset. This study aimed to examine associations between acute COVID-19 symptom profiles and long COVID prevalence using a population-based sample. We used a dual mode (phone and web-based) population-based probability survey of adults with polymerase chain reaction-confirmed SARS-CoV-2 between June 2020 and May 2022 in the Michigan Disease Surveillance System to examine (1) how acute COVID-19 symptoms cluster together using latent class analysis, (2) sociodemographic and clinical predictors of symptom clusters using multinomial logistic regression accounting for classification uncertainties, and (3) associations between symptom clusters and long COVID prevalence using modified Poisson regression. In our sample (n=4169), 15.9% (n=693) had long COVID, defined as new or worsening symptoms at least 90 days post SARS-CoV-2 infection. We identified 6 acute COVID-19 symptom clusters resulting from the latent class analysis, with flu-like symptoms (24.7%) and fever (23.6%) being the most prevalent in our sample, followed by nasal congestion (16.4%), multi-symptomatic (14.5%), predominance of fatigue (10.8%), and predominance of shortness of breath (10%) clusters. Long COVID prevalence was highest in the multi-symptomatic (39.7%) and predominance of shortness of breath (22.4%) clusters, followed by the flu-like symptom (15.8%), predominance of fatigue (14.5%), fever (6.4%), and nasal congestion (5.6%) clusters. After adjustment, females (vs males) had greater odds of membership in the multi-symptomatic, flu-like symptom, and predominance of fatigue clusters, while adults who were Hispanic or another race or ethnicity (vs non-Hispanic White) had greater odds of membership in the multi-symptomatic cluster. Compared with the nasal congestion cluster, the multi-symptomatic cluster had the highest prevalence of long COVID (adjusted prevalence ratio [aPR] 6.1, 95% CI 4.3-8.7), followed by the predominance of shortness of breath (aPR 3.7, 95% CI 2.5-5.5), flu-like symptom (aPR 2.8, 95% CI 1.9-4.0), and predominance of fatigue (aPR 2.2, 95% CI 1.5-3.3) clusters. Researchers and clinicians should consider acute COVID-19 symptom profiles when evaluating subsequent risk of long COVID, including potential mechanistic pathways in a research context, and proactively screen high-risk patients during the provision of clinical care.

Love thy neighbour: Feral buffalos show greater space use, resource overlap and encounters during the wet season in the Northern Territory.

Managing feral water buffalo in the Northern Territory is a formidable challenge. As an introduced species, buffalo are associated with a myriad of biosecurity, economic, cultural and environmental issues ranging from overgrazing, decreased water quality, disease vectors to the destruction of cultural assets. Nevertheless, the buffalo are also a harvestable resource that can support economic development of the region. To mitigate some of the biosecurity, economic, cultural and environmental risks they pose and manage buffalo effectively, we need a detailed understanding of their spatial and behavioural ecology. However, several factors make understanding how best to manage the dense populations of wild individuals challenging as buffalo inhabit remote areas with limited infrastructure and accessibility and their large size and often aggressive nature can make them difficult to observe in otherwise inaccessible areas. GPS tracking allows for high-frequency data collection and surveillance of individual buffalo. Here, we investigated how the different seasonal periods of a Northern Territory floodplain area shaped patterns of habitat use for 17 buffalo tracked over 16 months. We found in the dry season, buffalo space use is restricted, and the size of home ranges are significantly smaller than in the wet season. During the wet season, buffalo expand their home range area as well as their social encounter area with other buffalo. These differences in their space use and social patterns suggest that increased disease surveillance may be needed for the wet season when buffalo are more likely to share space and interact. During the dry season, however, buffalo movement is more predictable and restricted, suggesting greater optimisation opportunities for buffalo management. Results from these models can be used by land holders, Traditional Owners and wildlife managers to make evidence-based decisions to improve buffalo management with respect to disease risk, sustainable harvest and damage to environmental and cultural assets.

The Mpox Threat: Challenges and Implications of Clade Ib for Afghanistan's Healthcare Stability.

The global spread of the Mpox virus represents a significant public health challenge, particularly for regions with fragile healthcare systems. Afghanistan, already grappling with severe healthcare deficits, faces the added threat of Mpox, a zoonotic disease caused by the monkeypox virus. The recent emergence of Clade Ib, a new strain associated with rising outbreak cases, exacerbates concerns as Afghanistan's healthcare infrastructure continues to deteriorate due to reduced international aid, healthcare worker shortages, and an ongoing socio-political crisis. This commentary underscores the urgent need for international intervention to avert a potential public health crisis that could devastate Afghanistan's already weakened healthcare system. It calls for immediate support to enhance disease surveillance, improve healthcare infrastructure, and address the pressing challenges of malnutrition and access to medical services.

Medical Data NER and Classification Using Hybridized BERT Model

The extraction of important information from medical texts by Named Entity Recognition (NER) is a key component of advanced medical text processing. Medical practitioners rely heavily on NER's assistance with disease surveillance, clinical resolution building, and substantiation-based treatment. As the foundation of text information processing in the medical field, it guarantees precise location of data required for knowledgeable medical decisions and attentive disease surveillance. Additionally, a core goal in medical Natural Language Processing (NLP) is medical text categorization, which tries to classify short medical texts into distinct groups. Most recent work has concentrated on using pre-trained linguistic processes for text cataloging in medicine. The present work presents a novel clinical neural network architecture (NER) method that was created with a customized Rule Based BiLSTM-BERT (Bidirectional Encoder Representations from Transformers) architecture that incorporates Retrieval Augment Generation. Across several fields, including medicine, deep learning has demonstrated noteworthy advancements. These results show that, when applied to our test dataset, the BiLSTM-BERT-RAG model produced results that were almost human-like. The system proficiently recognized pertinent vocabulary representative of the intended protocol.

Data-driven decision-making in public health: The role of advanced statistical models in epidemiology

This paper critically examines the transformative role of data-driven decision-making in public health, focusing on the integration of advanced statistical models in epidemiology. As the volume and complexity of health data increase, leveraging predictive analytics, machine learning, and real-time data integration has become essential for improving public health outcomes. The study explores how these technologies have shifted public health strategies from reactive to proactive approaches, particularly in areas such as disease surveillance, chronic disease management, and health equity. Through comprehensive analysis, the paper identifies key advancements, such as hybrid models that combine traditional epidemiological frameworks with AI, and the integration of multi-modal data sources that enhance predictive accuracy. The findings emphasize the potential of these models to optimize resource allocation, address health disparities, and provide timely interventions. However, challenges such as data quality, algorithmic bias, and the ethical implications of model transparency are highlighted as critical issues requiring ongoing research. The study concludes that for these models to be effectively adopted, there must be a balance between technological innovation and ethical considerations. Recommendations include the need for interdisciplinary collaboration, improved data governance frameworks, and the development of more inclusive models that are generalizable across diverse populations. This research underscores the necessity of combining robust analytical tools with ethical frameworks to enhance the reliability and equity of public health interventions.

Application of loop-mediated isothermal amplification (LAMP) in plant pathogen detection.

Plant diseases impact the production of all kinds of crops, resulting in significant economic losses worldwide. Timely and accurate detection of plant pathogens is crucial for surveillance and management of plant diseases. In recent years, loop-mediated isothermal amplification (LAMP) has become a popular method for pathogen detection and disease diagnosis due to the advantages of its simple instrument requirement and constant reaction temperature. In this review, we provide an overview of current research on LAMP, including the reaction system, design of primers, selection of target regions, visualization of amplicons, and application of LAMP on the detection of all major groups of plant pathogens. We also discuss plant pathogens for which LAMP is yet to be developed, potential improvements of plant disease diagnosis, and disadvantages that need to be considered.

Usefulness of a Pluralistic Approach in Sentinel Surveillance: Seasonal Influenza Activity Based on Case Counts per Sentinel Site in the National Epidemiological Surveillance of Infectious Diseases Program and Test Counts, Case Counts, and Test Positivity from the National Hospital Organization.

In Japan, based on the National Epidemiological Surveillance of Infectious Diseases (NESID) Program, influenza cases from approximately 5,000 sentinel sites are monitored weekly as part of influenza surveillance (as the number of influenza cases per sentinel site). One limitation is that the number of influenza tests conducted is not reported. However, the National Hospital Organization (NHO), with approximately 140 hospitals, routinely publishes three indicators: the number of influenza tests, the number of influenza-positive cases, and test positivity. We used the NESID and NHO data from April 2011 to June 2022 to assess the usefulness of multiple indicators for monitoring influenza activity. The temporal trends of the NHO and NESID indicator were similar, and the NHO indicator levels correlated well with those of the NESID indicators. However, influenza positivity in the NHO data showed an earlier rise and peak time than that in the NESID indicator. Importantly, during the non-epidemic summer periods and the coronavirus disease 2019 pandemic, a sizable number of influenza tests were still performed at NHO hospitals, with results showing considerably low case counts and test positivity. These data show that a relatively small number of sentinel sites is sufficient to monitor influenza activity nationally and that utilizing multiple indicators can increase our confidence in situational awareness and data interpretations.

Artificial Intelligence in Infectious Disease Clinical Practice: An Overview of Gaps, Opportunities, and Limitations.

The integration of artificial intelligence (AI) in clinical medicine marks a revolutionary shift, enhancing diagnostic accuracy, therapeutic efficacy, and overall healthcare delivery. This review explores the current uses, benefits, limitations, and future applications of AI in infectious diseases, highlighting its specific applications in diagnostics, clinical decision making, and personalized medicine. The transformative potential of AI in infectious diseases is emphasized, addressing gaps in rapid and accurate disease diagnosis, surveillance, outbreak detection and management, and treatment optimization. Despite these advancements, significant limitations and challenges exist, including data privacy concerns, potential biases, and ethical dilemmas. The article underscores the need for stringent regulatory frameworks and inclusive databases to ensure equitable, ethical, and effective AI utilization in the field of clinical and laboratory infectious diseases.

Mpox outbreak: South Asia needs caution not fear

The re-emergence of Mpox (formerly monkeypox) has prompted global concern, including in South Asia where cases have surfaced in Pakistan and India. Mpox is a zoonotic virus, primarily spread through direct contact and respiratory droplets, with the 2022 outbreak notably linked to sexual transmission among men who have sex with men (MSM). In August 2024, the World Health Organization declared Mpox a Public Health Emergency of International Concern (PHEIC), urging heightened vigilance. This commentary emphasizes the importance of strengthening disease surveillance at ports of entry, raising public awareness, and targeting high-risk groups, including MSM and HIV-positive individuals. South Asia must also balance its Mpox response with other healthcare priorities. Regional collaboration through SAARC and leveraging local pharmaceutical capacities can enhance preparedness, minimizing the outbreak's impact.

Risk perceptions and preventive preparedness toward anthrax re-emergence within the lens of one health in Northcentral Nigeria.

Anthrax has re-emerged in domestic ruminants in Nigeria with public health concerns. This study assessed stakeholders' perceptions and preventive preparedness toward further resurgence and spread at the human-animal-environment interface. A questionnaire-based cross-sectional study was conducted in Nigeria. Descriptive and analytical statistical analyses were performed at 95% confidence levels. All the 384 recruited stakeholders responded. The majority (96.2%) of animal health practitioners (AHPs) and 56.7% of pastoralists were aware of the recent anthrax re-emergence in Nigeria (p < 0.001). Noteworthy, 88.5% of the AHPs and 32.2% of pastoralists mentioned that anthrax has an environmental component in its transmission to humans and animals. From the environmental perspective, 87.7% of AHPs and 24.0% of pastoralists significantly perceived that soil and aerosol contamination with anthrax spores are highly plausible explanation routes for its re-emergence. Extreme weather events (high rainfall, flooding, winds, and drought) (p = 0.001); grazing of livestock on pastures grown on contaminated soil (p < 0.001), transboundary movement and trade of animals (p = 0.001); introduction of new animals into the herds without quarantine (p = 0.001); and bioterrorism (p < 0.001) were more likely to influence the re-emergence and spread of anthrax. To tackle gaps in knowledge and risk perceptions, and address the socio-economic and anthropogenic drivers, cooperation and collaborations through the lens of the One Health approach are needed. The partnership will promote an integrated disease surveillance system from planning to implementation for the realization of elimination or reduction of the burden of anthrax and other zoonoses in Nigeria and contribute to achieving food safety, food security, and public and ecosystem health.

Preparation and preliminary application of fluorescent microsphere test strips for feline parvovirus antibodies

This study introduces a novel diagnostic modality for the detection of feline panleukopenia virus (FPV) antibodies in feline serum by using fluorescent microsphere immunochromatographic test strips (FM-ICTS). Leveraging the inherent specificity of antigen-antibody interactions, the FM-ICTS approach demonstrates considerable potential for efficient and accurate FPV antibody detection within a short timeframe. The FM-ICTS method demonstrates strong diagnostic performance, with consistent accuracy and stability over time. PBS buffer dilution enables detection across the range of FPV antibody haemagglutination inhibition (HI) titres in both healthy and immunized or infected cats. A high correlation (R² = 0.9733) between the T/C ratio and FPV antibody titres confirms the method’s effectiveness in quantifying these titres. Clinical validation with 84 samples supports its reliability by matching results with HI assays. Additionally, stability tests show that the test strips maintain performance during storage, with a coefficient of variation (CV) below 12% over three months at 25℃. This innovative FM-ICTS framework emerges as a promising avenue for expedient and dependable disease diagnosis within the realm of veterinary science, offering implications for timely disease management and surveillance.

Urban-rural disparities in mortality due to stroke subtypes in China and its provinces, 2015-2020.

Death burden of stroke is severe in China with over one-third rural residents, but there is still a lack of specific national and high-quality reports on the urban-rural differences in stroke burden, especially for subtypes. We aimed to update the understanding of urban-rural differences in stroke deaths. This is a descriptive observational study. Data from the national mortality surveillance system, which covers 323.8 million with 605 disease surveillance points (DSPs) across all 31 provinces, municipalities, and autonomous regions in China. All deaths from stroke as the underlying cause from 2015 to 2020 according to DSPs. Crude mortality rate and age-standardized mortality rate (ASMR) were estimated through DSPs. Average annual percentage change was used to explain the change in mortality rate. From 2015 to 2020, the majority of deaths from all stroke subtypes occurred in rural areas. There were significant differences between the changes of urban and rural ASMRs. On the whole, the changes in urban areas were evidently better, and the ASMR differences were basically expanding. Stroke ASMR in urban China decreased by 15.5%. The rural ASMR of ischemic stroke (IS) increased by 12.9%. The rural and urban ASMRs of intracerebral hemorrhage decreased by 24.9% and 27.4%, and those of subarachnoid hemorrhage decreased by 29.5% and 40.4%, respectively. The highest ASMRs of all stroke subtypes and the increasing trend of IS ASMR make rural males the focus of stroke management. The death burden of stroke varies greatly between urban and rural China. Rural residents face unique challenges.

Integrating short- and full-length 16S rRNA gene sequencing to elucidate microbiome profiles in Pacific white shrimp (Litopenaeus vannamei) ponds.

Despite their immense economic value as a key aquaculture species, the production of Pacific white shrimp (Litopenaeus vannamei) faces significant challenges from intensive farming practices and disease outbreaks. Routine microbial profiling for disease surveillance could be a promising approach to anticipate and control disease outbreaks. To achieve this, accuracy in microbial profiling in shrimp ponds is crucial for enabling targeted action and prevention. Extensive documentation emphasizes that, beyond biological factors (related to the host, diet, or health status during the rearing period), technical elements, including sequencing techniques significantly influence bacterial community profiling. This study investigated the influence of short- and long-read sequencing of 16S rRNA genes on the microbial profiles in shrimp intestines, water, and sediments. The origin of the samples (intestine or environmental) in shrimp culture ponds primarily drove the observed differences in core microbial species. The ecological niches accounted for 56% of bacterial community variations in culture ponds. Both sequencing approaches showed consistent results in identifying higher-rank taxa and assessing alpha and beta diversity. However, at the species level, full-length 16S rRNA gene sequences provided better resolution than V3-V4 sequences. For routine microbial profiling in shrimp culture ponds, our study suggests that short-read sequences were sufficient for determining overall bacterial community.IMPORTANCEThis interdisciplinary study investigated the influence of sequencing techniques on bacterial communities profiling within Pacific white shrimp (Litopenaeus vannamei) ponds. By integrating aquaculture, microbiology, and environmental science, we revealed the role of ecological niches and factors like salinity and pH on microbiota diversity and composition in shrimp intestines, pond water, and sediment. Additionally, we compared the taxonomic resolution using partial versus full-length 16S rRNA gene sequences, highlighting the value of longer amplicons for precise identification of key taxa. These findings provide novel insights into microbial dynamics underlying environmental effects in shrimp aquaculture. Comprehensive characterization of the pond microbiome could lead to management strategies that promote shrimp health and productivity. Furthermore, the potential of a multi-omics approach for integrating complementary data streams to elucidate environment-microbiome-host interactions was highlighted.

Urban wastewater contains a functional human antibody repertoire of mucosal origin

Wastewater-based surveillance of human disease offers timely insights to public health, helping to mitigate infectious disease outbreaks and decrease downstream morbidity and mortality. These systems rely on nucleic acid amplification tests for monitoring disease trends, while antibody-based seroprevalence surveys gauge community immunity. However, serological surveys are resource-intensive and subject to potentially long lead times and sampling bias. We identified and characterized a human antibody repertoire, predominantly secretory IgA, isolated from a central wastewater treatment plant and building-scale wastewater collection points. These antibodies partition to the solids fraction and retain immunoaffinity for SARS-CoV-2 and Influenza A virus antigens. This stable pool could enable real-time tracking for correlates of vaccination, infection, and immunity, aiding in establishing population-level thresholds for immune protection and assessing the efficacy of future vaccine campaigns.

Understanding the dynamics of nipah virus (NiV) transmission and outbreaks in India from Kerala’s perspective

This comprehensive analysis delves into the series of Nipah virus (NiV) outbreaks across India, with a particular focus on occurrences in Kerala. NiV, which belongs to the Paromyxoviridae family and Henipavirus genus, originated in Malaysia in 1998 and has consistently posed significant global health threats. In India, NiV outbreaks have sporadically emerged since the initial case in West Bengal in 2001, often with alarming mortality rates. The 2018 resurgence in Kerala exhibited an astonishing case fatality rate of 89%, emphasizing the need for tailored diagnostic and management strategies due to substantial variability in the incubation period and clinical manifestations. Understanding the predominant person-to-person transmission underscores the importance of comprehending transmission dynamics. Early detection, facilitated by the Integrated Disease Surveillance Program (IDSP), remains vital, as treatment options are currently confined to supportive care, necessitating the exploration of more effective therapeutics. The sporadic nature of NiV outbreaks, exemplified by the recent Kerala episode, emphasizes the urgency for robust response mechanisms, while collaborative efforts and capacity-building initiatives are essential for effectively managing these occurrences. Continued focus on prompt detection, advanced laboratory testing, accessibility to cutting-edge facilities, and heightened infection control measures remains imperative to mitigate future incidents.

Borealpox Virus: a Comprehensive Review of its Emergence and Global Recommendations

The emergence of the Borealpox virus (BRPV), formerly known as the Alaskapox virus (AKPV), in 2015 poses an intriguing scientific challenge. Despite being first discovered in Alaska, BRPV is a potential global threat, and reports of instances have raised questions about how serious it can be; especially in those with impaired immune systems. The unique characteristics of BRPV have been clarified through genomic characterization, providing insight into its evolutionary lineage and transmission dynamics. A recent death linked to BRPV highlights the difficulties presented by newly developing infectious illnesses, particularly for individuals who are already at risk. The implications of BRPV for public health call for all-encompassing management approaches; such as creating efficient treatments and customized interventions for various clinical presentations. Research and surveillance initiatives are vital for comprehending ecological reservoirs and patterns of transmission. Additionally, biosafety regulations and immunization programs are critical for controlling outbreaks and reducing the worldwide effects of BRPV. Prioritizing vaccination drive approaches, implementing stringent infection control measures, and reinvigorating disease surveillance systems are imperative for preventing BRPV. In addition, enhancing the training of frontline healthcare professionals and implementing the One Health concept are crucial measures that foster robust cooperation and adaptability, while confronting new public health concerns. A comprehensive review of the emergence and consequences of the Borealpox virus is necessary to direct future investigations and global public health campaigns. By utilizing interdisciplinary approaches and promoting global collaboration, we may successfully alleviate the danger presented by BRPV and protect public health across borders.

The Impact of Public Health on Health Regulation

Public health and regulatory frameworks are interdependent, with public health advancements driving the evolution of health regulations, and health regulations reinforcing public health efforts. This review examines the relationship between public health initiatives and regulatory measures, tracing their historical development, particularly in response to diseases and social change. The focus includes the role of epidemiology, disease surveillance, and health promotion in shaping public health policies. Furthermore, it delves into the challenges governments and international organizations face in implementing effective health regulations, particularly in an increasingly globalized world. Finally, it highlights future directions for adaptive regulation, emphasizing the integration of technology and stakeholder engagement to overcome current public health challenges. Keywords: Public Health, Health Regulation, Disease Surveillance, Epidemiology, Health Promotion.