PHSkb: A knowledgebase to support notifiable disease surveillance

During 1994-1997, approximately 70% and 60% of the cases of conditions reported to the National Notifiable Diseases Surveillance System included persons of known race and ethnicity, respectively. A major goal of the Healthy People 2020 initiative is to eliminate health disparities. To describe trends in the completeness of race and ethnicity in case reports of the National Notifiable Diseases Surveillance System during 2006-2010. The National Notifiable Diseases Surveillance System is a public health surveillance system that aggregates case reports of infectious diseases and conditions that are designated nationally notifiable and are collected by US states and territories. The Centers for Disease Control and Prevention (Atlanta, Georgia) maintains this surveillance system in collaboration with the Council of State and Territorial Epidemiologists. We used Cochran-Armitage Trend Test (SAS, version 9.2) to test the hypothesis that the percentage of case reports with the completeness of race and ethnicity data increased or decreased linearly during 2006-2010. Completeness of race and ethnicity variables. The 32 conditions reviewed included 1 030 804 case records. Seventy percent of records included a known value for race, and 49% of records included ethnicity during 2006-2010. During 2006-2010, race was known in 70% or more of records in 24 of 32 conditions and in 23 of 51 jurisdictions. During 2006-2010, the systemwide reporting of race remained at the same level of completeness (70%) but the reporting of ethnicity increased slightly from 48% in 2006 to 53% in 2010. In comparison with race, the proportions of records coded to ethnicity were less among all conditions. Significant change has occurred in the completeness of reporting of ethnicity but not race during 2006-2010. However, the reporting of ethnicity still lags substantially behind the reporting of race. Jurisdictions that identify conditions with lower rates of completeness of race and ethnicity can assess the net benefits of efforts to improve the completeness of race and ethnicity data.

Data from 3 US public health surveillance systems indicate that an estimated 67 400 people acquired hepatitis C virus infections in 2022, 2.2 million adults had hepatitis C during January 2017-March 2020, and 12 717 people died in 2022 from hepatitis C-related causes, despite the availability of curative treatment since 2013. The 3 surveillance systems that provided these data-the National Notifiable Diseases Surveillance System, the National Health and Nutrition Examination Survey, and the National Vital Statistics System-were selected to monitor progress toward elimination of hepatitis C as a public health threat in the United States by 2030. However, some limitations of these surveillance systems compel the use of additional data sources with more timely information for the general population and for populations with higher incidence, prevalence, or mortality of hepatitis C, such as those experiencing homelessness, incarceration, or injection drug use. Commercial laboratories, health systems, and programs serving these populations could provide such data. This topical review of hepatitis C surveillance describes the history, long-term trends, and recent investments in public health surveillance for hepatitis C. Strengthening and modernizing the hepatitis C surveillance workforce and systems, improving data system interoperability, linking complementary data sources, and leveraging multiple data systems can aid in the measurement of public health efforts to meet hepatitis C elimination goals.

BackgroundReducing TB surveillance incurs significant costs, as effective control and societal impact minimization rely on robust, ongoing surveillance systems that integrate and analyze comprehensive data for prompt action. Our study supports integrating artificial intelligence (LSI) into TB and other notifiable disease monitoring frameworks to improve trackingFigure 1Binary Matrix of 125 Terms: Presence vs. Absence of Root Keywords Retrieved from the Patient ElectronicRecord for the LSI Automatic Retrieval System.Binary Matrix of 125 Terms: Presence vs. Absence of Root Keywords Retrieved from the Patient Electronic Record for the LSI Automatic Retrieval System.MethodsIn 2024, we developed a novel application within Datamart A.R.G.U.S.—Assistant for Recovery and Guarding of Urgent and Epidemiological Sentinels—a cloud-based platform hosted on AWS and developed by our team. This application integrates with hospital systems (MV) and laboratory systems (MATRIX and GAL) to enhance the surveillance of healthcare-associated infections (HAI) and notifiable diseases. Data from both hospital and outpatient care are encoded into a binary matrix of 125 terms (root keywords) extracted from patient electronic records. This matrix is then processed using Singular Value Decomposition (SVD) within an LSI-based information retrieval system (Fig. 1). In our model, each patient is represented as a point in a 125-dimensional hyperdimensional space. When projected into three-dimensional space, this framework allows for effective clustering and classification of notifiable Diseases (Fig. 2), specifically TB (Fig. 3).Figure 2:3D Visualization of High-Dimensional Data: Comparing Mandatory Notifiable Diseases versus Non-Notifiable Diseases. Both patient types are well separated in the space, enabling automatic clustering and classification.3D Visualization of High-Dimensional Data: Comparing Mandatory Notifiable Diseases versus Non-Notifiable Diseases. Both patient types are well separated in the space, enabling automatic clustering and classification.ResultsThe LSI-based matrix was constructed using data from January 2023 to February 2024, encompassing a sample of 17,895 cases (lines) across 125 presence versus absence terms, with each case classified as either a notifiable or non-notifiable disease. The 125-dimensional matrix was reduced to 28 factors using SVD. The sensitivity and specificity of the Euclidean distance were better than those of cosine similarity when automatically identifying TB cases in 1,970 independent queries (Fig. 4).Figure 3:3D Visualization of High-Dimensional Data: Comparing Tuberculosis versus Other Mandatory Notifiable Diseases versus Non-Notifiable Diseases. The three types of patients are well separated in the space, enabling automatic clustering and classification.3D Visualization of High-Dimensional Data: Comparing Tuberculosis versus Other Mandatory Notifiable Diseases versus Non-Notifiable Diseases. The three types of patients are well separated in the space, enabling automatic clustering and classification.ConclusionArtificial Intelligence (LSI), significantly enhances the surveillance of TB and other notifiable diseases by enabling real-time, automated case identification up to one day prior (D-1). This advancement allows surveillance personnel to complete their tasks more efficiently, thereby preventing outbreaks and reducing the risk of unforeseen fatalities.Figure 4:Performance Comparison of Cosine vs. Euclidean Distance Metrics in Automatically Identifying TB Cases Using LSI: Euclidean Distance Demonstrates Superior Accuracy and Has Been Integrated into Datamart A.R.G.U.S. for Real-Time Identification of TB and Other Notifiable Diseases as of the Previous Workday (D-1).Performance Comparison of Cosine vs. Euclidean Distance Metrics in Automatically Identifying TB Cases Using LSI: Euclidean Distance Demonstrates Superior Accuracy and Has Been Integrated into Datamart A.R.G.U.S. for Real-Time Identification of TB and Other Notifiable Diseases as of the Previous Workday (D-1).DisclosuresAll Authors: No reported disclosures

Sociodemographic and geographical inequalities in notifiable infectious diseases in Australia: a retrospective analysis of 21 years of national disease surveillance data

In 2010, 65 diseases and conditions were nationally notifiable in Australia. States and territories reported a total of 209,079 notifications of communicable diseases to the National Notifiable Diseases Surveillance System, a decrease of 12% on the number of notifications in 2009. This decrease was largely due to a reduction of influenza compared with the influenza A(H1N1) pandemic 2009. In 2010, the most frequently notified diseases were sexually transmissible infections (86,620 notifications, 41.4% of total notifications), vaccine preventable diseases (61,964 notifications, 29.6% of total notifications), and gastrointestinal diseases (31,548 notifications, 15.1% of total notifications). There were 18,302 notifications of bloodborne diseases; 8,244 notifications of vectorborne diseases; 1,866 notifications of other bacterial infections; 532 notifications of zoonoses and 3 notifications of quarantinable diseases.

ObjectiveSentinel physician surveillance in the communities has played an important role in detecting early aberrations in epidemics. The traditional approach is to ask primary care physicians to actively report some diseases such as influenza-like illness (ILI), and hand, foot, and mouth disease (HFMD) to health authorities on a weekly basis. However, this is labor-intensive and time-consuming work. In this study, we try to set up an automatic sentinel surveillance system to detect 23 syndromic groups in the communites.IntroductionIn December 2009, Taiwan’s CDC stopped its sentinel physician surveillance system. Currently, infectious disease surveillance systems in Taiwan rely on not only the national notifiable disease surveillance system but also real-time outbreak and disease surveillance (RODS) from emergency rooms, and the outpatient and hospitalization surveillance system from National Health Insurance data. However, the timeliness of data exchange and the number of monitored syndromic groups are limited. The spatial resolution of monitoring units is also too coarse, at the city level. Those systems can capture the epidemic situation at the nationwide level, but have difficulty reflecting the real epidemic situation in communities in a timely manner. Based on past epidemic experience, daily and small area surveillance can detect early aberrations. In addition, emerging infectious diseases do not have typical symptoms at the early stage of an epidemic. Traditional disease-based reporting systems cannot capture this kind of signal. Therefore, we have set up a clinic-based surveillance system to monitor 23 kinds of syndromic groups. Through longitudinal surveillance and sensitive statistical models, the system can automatically remind medical practitioners of the epidemic situation of different syndromic groups, and will help them remain vigilant to susceptible patients. Local health departments can take action based on aberrations to prevent an epidemic from getting worse and to reduce the severity of the infected cases.MethodsWe collected data on 23 syndromic groups from participating clinics in Taipei City (in northern Taiwan) and Kaohsiung City (in southern Taiwan). The definitions of 21 of those syndromic groups with ICD-10 diagnoses were adopted from the International Society for Disease Surveillance (https://www.surveillancerepository.org/icd-10-cm-master-mapping-reference-table). The definitions of the other two syndromic groups, including dengue-like illness and enterovirus-like illness, were suggested by infectious disease and emergency medicine specialists.An enhanced sentinel surveillance system named “Sentinel plus” was designed for sentinel clinics and community hospitals. The system was designed with an interactive interface and statistical models for aberration detection. The data will be computed for different combinations of syndromic groups, age groups and gender groups. Every day, each participating clinic will automatically upload the data to the provider of the health information system (HIS) and then the data will be transferred to the research team.This study was approved by the committee of the Institutional Review Board (IRB) at Academia Sinica (AS-IRB02-106262, and AS-IRB02-107139). The databases we used were all stripped of identifying information and thus informed consent of participants was not required.ResultsThis system started to recruit the clinics in May 2018. As of August 2018, there are 89 clinics in Kaohsiung City and 33 clinics and seven community hospitals in Taipei City participating in Sentinel plus. The recruiting process is still ongoing. On average, the monitored volumes of outpatient visits in Kaohsiung City and Taipei City are 5,000 and 14,000 per day.Each clinic is provided one list informing them of the relative importance of syndromic groups, the age distribution of each syndromic group and a time-series chart of outpatient rates at their own clinic. In addition, they can also view the village-level risk map, with different alert colors. In this way, medical practitioners can know what’s going on, not only in their own clinics and communities but also in the surrounding communities.The Department of Health (Figure 1) can know the current increasing and decreasing trends of 23 syndromic groups by red and blue color, respectively. The spatial resolution has four levels including city, township, village and clinic. The map and bar chart represent the difference in outpatient rate between yesterday and the average for the past week. The line chart represents the daily outpatient rates for one selected syndromic group in the past seven days. The age distribution of each syndromic group and age-specific outpatient rates in different syndromic groups can be examined.ConclusionsSentinel plus is still at the early stage of development. The timeliness and the accuracy of the system will be evaluated by comparing with some syndromic groups in emergency rooms and the national notifiable disease surveillance system. The system is designed to assist with surveillance of not only infectious diseases but also some chronic diseases such as asthma. Integrating with external environmental data, Sentinel plus can alert public health workers to implement better intervention for the right population.

Little information is available in the United States regarding the incidence and distribution of diseases caused by critical microbiologic agents with the potential for use in acts of terrorism. We describe disease-specific, demographic, geographic, and seasonal distribution of selected bioterrorism-related conditions (anthrax, botulism, brucellosis, cholera, plague, tularemia, and viral encephalitides) reported to the National Notifiable Diseases Surveillance System in 1992–1999. Tularemia and brucellosis were the most frequently reported diseases. Anthrax, plague, western equine encephalitis, and eastern equine encephalitis were rare. Higher incidence rates for cholera and plague were noted in the western United States and for tularemia in the central United States. Overall, the incidence of conditions caused by these critical agents in the United States is low. Individual case reports should be considered sentinel events. For potential bioterrorism-related conditions that are endemic and have low incidence, the use of nontraditional surveillance methods and complementary data sources may enhance our ability to rapidly detect changes in disease incidence.

The Centers for Disease Control and Prevention (CDC) is in the process of integrating the existing dual mechanisms for reporting cases of malaria diagnosed in the United States into a single electronic reporting mechanism. Before adoption of this new system, an evaluation of the existing systems for state-level reporting of malaria data to the CDC was conducted. CDC guidelines for evaluating surveillance systems were used to assess the attributes of the National Malaria Surveillance System (NMSS), the current National Notifiable Diseases Surveillance System (NNDSS), and the projected fully integrated NNDSS. We analyzed data collected from NMSS and NNDSS from 2001 to 2005 using the Chandra-Sekar-Deming method to estimate completeness of reporting. The projected fully integrated system was assessed likely to perform better than either of the existing systems on all attributes except stability. The overall completeness of reporting was estimated to be 80.3 percent for NNDSS and 74.7 percent for NMSS. Both existing systems have reasonably high ascertainment of cases. A fully integrated system with malaria-specific data fields would improve upon existing systems if it proved to be stable.

The best way to prevent malaria is to take chemoprophylaxis medication during travel to a country where malaria is endemic. Adherence to recommended malaria prevention strategies among U.S. travelers would reduce the numbers of imported cases; reasons for nonadherence include prematurely stopping after leaving the area where malaria was endemic, forgetting to take the medication, and experiencing a side effect. Travelers might not understand the risk that malaria poses to them; thus, health care providers should incorporate risk education to motivate travelers to be adherent to chemoprophylaxis. Malaria infections can be fatal if not diagnosed and treated promptly with antimalarial medications appropriate for the patient's age, medical history, the likely country of malaria acquisition, and previous use of antimalarial chemoprophylaxis. Antimalarial use for chemoprophylaxis and treatment should be informed by the most recent guidelines, which are frequently updated. In 2018, two formulations of tafenoquine (i.e., Arakoda and Krintafel) were approved by the Food and Drug Administration (FDA) for use in the United States. Arakoda was approved for use by adults for chemoprophylaxis; the regimen requires a predeparture loading dose, taking the medication weekly during travel, and a short course posttravel. The Arakoda chemoprophylaxis regimen is shorter than alternative regimens, which could possibly improve adherence. This medication also might prevent relapses. Krintafel was approved for radical cure of P. vivax infections in those aged >16 years and should be co-administered with chloroquine (https://www.cdc.gov/malaria/new_info/2020/tafenoquine_2020.html). In April 2019, intravenous artesunate became the first-line medication for treatment of severe malaria in the United States. Artesunate was recently FDA approved but is not yet commercially available. The drug can be obtained from CDC under an investigational new drug protocol. Detailed recommendations for preventing malaria are available to the general public at the CDC website (https://www.cdc.gov/malaria/travelers/drugs.html). Health care providers should consult the CDC Guidelines for Treatment of Malaria in the United States and contact the CDC's Malaria Hotline for case management advice when needed. Malaria treatment recommendations are available online (https://www.cdc.gov/malaria/diagnosis_treatment) and from the Malaria Hotline (770-488-7788 or toll-free 855-856-4713). Persons submitting malaria case reports (care providers, laboratories, and state and local public health officials) should provide complete information because incomplete reporting compromises case investigations and efforts to prevent infections and examine trends in malaria cases. Molecular surveillance of antimalarial drug resistance markers (https://www.cdc.gov/malaria/features/ars.html) enables CDC to track, guide treatment, and manage drug resistance in malaria parasites both domestically and internationally. More samples are needed to improve the completeness of antimalarial drug resistance analysis; therefore, CDC requests that blood specimens be submitted for any case of malaria diagnosed in the United States.

Heterogeneity and Interoperability in Local Public Health Information Systems.

Public health surveillance (PHS) is an essential public health activity, which entails collecting data on diseases and disease-related states in a timely manner to aid in international health regulations and in local health planning. Opinions differ sharply on whether it is a research or non-research activity. In recent years, most low- and middle-income countries (LMICs) have been establishing their own PHS systems, with or without support from external donors, to comply with the stipulations of international health regulations. With the expansion of the scope and role of PHS in ensuring the health security of countries, it is important to understand the ethical principles of PHS and the specific ethical issues involved in it, as well as the need for ethical oversight of PHS. This paper deals with these aspects of PHS, and highlights the need for specific ethical guidance and oversight mechanisms in LMICs that are setting up their own PHS systems.

Invasive meningococcal disease (IMD) is a notifiable disease in Australia, and both probable and laboratory-confirmed cases of IMD are reported to the National Notifiable Diseases Surveillance System (NNDSS). In 2020, there were 90 notifications of IMD, the lowest number documented since records began in the NNDSS in 1991. Of these, 97% (87/90) were laboratory-confirmed cases, with 70% (61/87) confirmed by bacterial culture and 30% (26/87) by nucleic acid amplification testing. The serogroup was determined for 85/87 laboratory-confirmed cases of IMD: serogroup B (MenB) accounted for 64% of infections (54/85); MenW for 19% (16/85); MenY for 16% (14/85); and MenC 1.2% (1/85). Fine typing was available on 60/85 (71%) of cases with serogroup determined; of the typed MenW, all were PorA antigen type P1.5,2 and sequence type 11, the hypervirulent strain reported in recent outbreaks in Australia and overseas. The primary peaks of IMD notifications in Australia in 2020 were observed in infants less than 1 year (16/87, 18%) and in adults aged 45-64 years (14/87, 16%). MenB infections predominated in those aged less than 5 years and 15-19 years; MenW and MenY infections predominated in those aged 45 years or more. All 61 IMD isolates were tested for antimicrobial susceptibility: none were penicillin resistant; however, 56/61 (92%) had decreased susceptibility to penicillin. All isolates were susceptible to ceftriaxone, ciprofloxacin and rifampicin.

The purpose of this study was to identify ideas for an enhanced dissemination of the US National Notifiable Diseases Surveillance System (NNDSS) provisional data. The author conducted a search of all US State Health Department websites looking for on-line data display tables and tools for either reportable or notifiable diseases. In addition, the scope of the search of websites was expanded to include notifiable diseases of several countries, organizations and institutions. As a result of this study the author proposes enhancement of the current US notifiable disease data display from a static format to a more interactive dashboard design.

IntroductionTracking the spread of invasive meningococcal disease (IMD) in the United States is important for identifying risk factors and devising public health strategies to prevent infection.MethodsThe epidemiology of IMD in the United States before, during, and after the COVID-19 pandemic (2016–2024) was assessed using surveillance data from the National Notifiable Diseases Surveillance System (NNDSS) and the Enhanced Meningococcal Disease Surveillance program (EMDS).ResultsIMD case numbers declined during the pandemic (2020–2021) to 208 in 2021 but rebounded to 312 in 2022 and have continued to increase through 2024 (provisionally 477 cases). In 2022, serogroup C was the predominant serogroup (107 cases), followed by serogroup B (61 cases). Except during the pandemic, IMD cases were higher among those attending versus not attending college. During and after the pandemic, groups with the highest IMD incidence were those <1 year of age (range, 0.38–0.56 cases per 100,000 persons) and within the Black population (range, 0.09–0.19 cases per 100,000 persons). The percentage of IMD cases occurring after the pandemic in men who have sex with men and those with HIV increased substantially from during the pandemic. The percentage of IMD cases that occurred among people experiencing homelessness (PEH) was relatively high, ranging from 2.4–6.3%.ConclusionThe data indicate a rebound in IMD after the COVID-19 pandemic, highlighting the importance of strengthening surveillance and vaccination among high-risk populations.

Zoonotic diseases pose significant public health threats worldwide, highlighting the need for effective surveillance strategies. The One Health approach, which recognizes the interconnection between human, animal, and environmental health, has gained traction as a comprehensive framework for addressing zoonotic disease surveillance. This review explores integrative strategies for zoonotic disease surveillance in the United States, focusing on the implementation of One Health principles. The review examines the collaborative efforts between human and animal health sectors, environmental agencies, and other relevant stakeholders in implementing One Health surveillance strategies. It highlights the importance of data sharing, communication, and coordination among these sectors to enhance early detection, rapid response, and effective control of zoonotic diseases. Key findings include the establishment of cross-sectoral surveillance systems, such as the National Notifiable Diseases Surveillance System (NNDSS) and the National Animal Health Monitoring System (NAHMS), which facilitate the collection and analysis of zoonotic disease data. These systems enable the identification of emerging zoonotic threats and the implementation of targeted interventions to mitigate risks. The review also discusses the role of technology, such as geographic information systems (GIS) and molecular epidemiology, in enhancing zoonotic disease surveillance. These tools enable the visualization of disease patterns and the tracking of disease transmission pathways, aiding in the development of effective control strategies. Challenges in implementing One Health surveillance strategies include limited resources, fragmented data systems, and regulatory barriers. Addressing these challenges requires increased investment in infrastructure, capacity building, and policy development to support integrated surveillance approaches. Overall, this review highlights the importance of One Health implementation in zoonotic disease surveillance and underscores the need for continued collaboration and innovation to enhance the effectiveness of surveillance efforts in the United States.