Progress and Challenges in Measles and Rubella Elimination in the WHO European Region.

The elimination of both measles and rubella remains a priority for all 53 Member States of the World Health Organization (WHO) European Region. To provide an update on the epidemiological status of measles and rubella in the Region, we reviewed surveillance data on both diseases for 2023 submitted monthly by national surveillance institutions. We analyzed the cases of measles and rubella for 2023 by age group, case classification, vaccination, hospitalization, and importation status and report on measles-related deaths. In 2023, 60,860 measles cases, including 13 fatal cases, were reported in 41 countries. Most cases (95%; n = 57,584) were reported by six countries: Azerbaijan, Kazakhstan, Kyrgyzstan, Romania, the Russian Federation, and Türkiye. Of the 60,848 cases with data on age, 19,137 (31%) were 1-4 years old and 12,838 (21%) were 5-9 years old. A total of 10,412 (17%) were 20 years and older. The genotypes identified in the Region were largely dominated by D8 variants (n = 1357) and the remainder were B3 variants (n = 221). In 2023, 345 rubella cases were reported by 17 countries, mostly from Poland, Kyrgyzstan, Tajikistan, Türkiye, and Ukraine. A total of 262 cases (76%) were classified as clinically compatible and 79 (23%) were laboratory-confirmed. To achieve the elimination of measles and rubella in the Region, political commitment needs to be revived to enable urgent efforts to increase vaccination coverage, improve surveillance and outbreak preparedness, and respond immediately to outbreaks.

COVID-19 Pandemic and Food Insecurity among Pregnant Women in an Important City of the Amazon Region: A Study of the Years 2021 and 2022.

INTRODUCTION: Food insecurity (FI) experienced during pregnancy represents a relevant public health problem, as it negatively affects maternal and child health. OBJECTIVE: To investigate the prevalence of FI among pregnant women during the COVID-19 pandemic and determine associated factors. METHODS: A cross-sectional study was carried out in the period from 2021 to 2022, with a representative sample of 423 women resulting from a sample calculation based on the average (2912 births) that occurred in the years 2016 to 2020 in the only maternity hospital in the municipality. After analyzing the medical records, interviews were carried out with the postpartum women using a standardized questionnaire and the Brazilian Food Insecurity Scale. Poisson regression with robust variance was used to calculate prevalence ratios and 95% confidence intervals to measure associations. RESULTS: FI was observed in 57.0% of cases and was associated with age under 20 years (PR = 1.52; 95% CI 1.29; 1.79), receipt of government assistance (PR = 1.31; 95% CI 1.10; 1.55), loss of family employment (PR = 1.40; 95% CI 1.20; 1.64), greater number of residents (PR = 1.17; 95% CI 1.00; 1.37), and prenatal care in a public institution (PR = 1.53; 95% CI 1.04; 2.26). CONCLUSION: There was a high prevalence of FI cases, associated with socioeconomic, demographic, and prenatal care characteristics during the COVID-19 pandemic.

Syndromic case definitions for lower respiratory tract infection (LRTI) are less sensitive in older age: an analysis of symptoms among hospitalised adults.

BACKGROUND: Lower Respiratory Tract Infections (LRTI) pose a serious threat to older adults but may be underdiagnosed due to atypical presentations. Here we assess LRTI symptom profiles and syndromic (symptom-based) case ascertainment in older (≥ 65y) as compared to younger adults (< 65y). METHODS: We included adults (≥ 18y) with confirmed LRTI admitted to two acute care Trusts in Bristol, UK from 1st August 2020- 31st July 2022. Logistic regression was used to assess whether age ≥ 65y reduced the probability of meeting syndromic LRTI case definitions, using patients' symptoms at admission. We also calculated relative symptom frequencies (log-odds ratios) and evaluated how symptoms were clustered across different age groups. RESULTS: Of 17,620 clinically confirmed LRTI cases, 8,487 (48.1%) had symptoms meeting the case definition. Compared to those not meeting the definition these cases were younger, had less severe illness and were less likely to have received a SARS-CoV-2 vaccination or to have active SARS-CoV-2 infection. Prevalence of dementia/cognitive impairment and levels of comorbidity were lower in this group. After controlling for sex, dementia and comorbidities, age ≥ 65y significantly reduced the probability of meeting the case definition (aOR = 0.67, 95% CI:0.63-0.71). Cases aged ≥ 65y were less likely to present with fever and LRTI-specific symptoms (e.g., pleurisy, sputum) than younger cases, and those aged ≥ 85y were characterised by lack of cough but frequent confusion and falls. CONCLUSIONS: LRTI symptom profiles changed considerably with age in this hospitalised cohort. Standard screening protocols may fail to detect older and frailer cases of LRTI based on their symptoms.

Molecular and spatial evaluation of small rodents and Didelphimorphis infected with Mycobacterium leprae in the southern Amazon, Brazil.

BACKGROUND: The high levels of recent transmission of leprosy worldwide demonstrate the necessity of epidemiologic surveillance to understand and control its dissemination. Brazil remains the second in number of cases around the world, indicating active transmission of Mycobacterium leprae (M. leprae) in the population. At this moment, there is a consensus that the bacillus is transmitted by inter-human contact, however, different serologic, molecular, and histopathological approaches indicate the existence of non-human transmission sources. METHODS AND RESULTS: The qPCR assay was used to amplify the molecular targets 16S RNAr and RLEP, in samples of liver, spleen, and ear of wild animals belonging to Didelphimorphia and Rodentia orders, in highly endemic areas of Mato Grosso, Brazil. The RLEP repetitive sequence was positive in 202 (89.0%) samples, with 96 (42.3%) of these also being positive for the 16S gene. Regarding the collection sites, it was observed that the animals were found in areas profoundly deforested, close to urban areas. CONCLUSIONS: Our results suggest that wild animals can play an important role in the maintenance of M. leprae in endemic regions with major anthropic action in Brazil. Therefore, integrating human, animal, and environmental health care with the One Health initiative is highly efficient for the development of effective strategies to contain and control leprosy in Brazil.

Assessment of the pathogen genomics landscape highlights disparities and challenges for effective AMR Surveillance and outbreak response in the East African community.

The East African Community (EAC) grapples with many challenges in tackling infectious disease threats and antimicrobial resistance (AMR), underscoring the importance of regional and robust pathogen genomics capacities. However, a significant disparity exists among EAC Partner States in harnessing bacterial pathogen sequencing and data analysis capabilities for effective AMR surveillance and outbreak response. This study assesses the current landscape and challenges associated with pathogen next-generation sequencing (NGS) within EAC, explicitly focusing on World Health Organization (WHO) AMR-priority pathogens. The assessment adopts a comprehensive approach, integrating a questionnaire-based survey amongst National Public Health Laboratories (NPHLs) with an analysis of publicly available metadata on bacterial pathogens isolated in the EAC countries. In addition to the heavy reliance on third-party organizations for bacterial NGS, the findings reveal a significant disparity among EAC member States in leveraging bacterial pathogen sequencing and data analysis. Approximately 97% (n = 4,462) of publicly available high-quality bacterial genome assemblies of samples collected in the EAC were processed and analyzed by external organizations, mainly in Europe and North America. Tanzania led in-country sequencing efforts, followed by Kenya and Uganda. The other EAC countries had no publicly available samples or had all their samples sequenced and analyzed outside the region. Insufficient local NGS sequencing facilities, limited bioinformatics expertise, lack of adequate computing resources, and inadequate data-sharing mechanisms are among the most pressing challenges that hinder the EAC's NPHLs from effectively leveraging pathogen genomics data. These insights emphasized the need to strengthen microbial pathogen sequencing and data analysis capabilities within the EAC to empower these laboratories to conduct pathogen sequencing and data analysis independently. Substantial investments in equipment, technology, and capacity-building initiatives are crucial for supporting regional preparedness against infectious disease outbreaks and mitigating the impact of AMR burden. In addition, collaborative efforts should be developed to narrow the gap, remedy regional imbalances, and harmonize NGS data standards. Supporting regional collaboration, strengthening in-country genomics capabilities, and investing in long-term training programs will ultimately improve pathogen data generation and foster a robust NGS-driven AMR surveillance and outbreak response in the EAC, thereby supporting global health initiatives.

Prevalence and clinical significance of incidental findings in chest and abdominopelvic CT scans of trauma patients; A cross-sectional study.

BACKGROUND: Imaging may inadvertently reveal pathologies unrelated to their performing purpose, known as incidental findings (IF). This study aimed to assess the prevalence, clinical significance, and documentation of IFs in chest and abdominopelvic computed tomography (CT) scans of trauma patients. METHODS: This observational study was conducted at two urban level-1 trauma centers from March 2019 through April 2022. Official radiology reports of trauma patients who underwent chest and/or abdominopelvic CT scans at the emergency department (ED) were explored, and IF were extracted. Predictive factors of the presence of IFs and their documenting were investigated. RESULTS: Out of 656 chest and 658 abdominopelvic CT scans, 167 (25.37%) and 212 (32.31%) scans harbored at least one IF, respectively. Patients with IFs tended to be of higher age and female in both chest (age: 48 [IQR: 35-62] vs. 34 [IQR: 25-42.5]; female: 31.14% vs 14.66%, p < 0.001 for both) and abdominopelvic CT scans (age: 41 [IQR: 30-57.5] vs 33 [IQR: 25-43], female: 26.42% vs. 13.96%, p < 0.001 for both). As for documentation of significant IFs, only 49 of 112 chest IFs (43.8%) and 55 of 176 abdominopelvic IFs (31.3%) were documented. Investigating factors associated with documentation of clinically significant IFs, shorter length of hospital stay (1.5 (IQR: 0-4) vs. 3 (IQR: 2-8), p = 0.003), and discharging by ED physicians (documentation rate: 13.2% vs 42.6%, p < 0.001) were associated with poorer documentation of IFs only in abdominopelvic scans. CONCLUSION: CT imaging in ED trauma patients often reveals incidental findings, especially in older patients. Over 50% of these findings are clinically significant, yet they are frequently ignored and not documented. Physicians need to be more vigilant in recognizing and documenting these incidental findings and informing patients of the need for further evaluation.

Risk Factors of Crimean-Congo Hemorrhagic Fever in Sindh Province, Pakistan.

OBJECTIVES: In Sindh Province, Pakistan, confirmed Crimean Congo hemorrhagic fever (CCHF) increased from zero in 2008 to 16 in 2015-2016. To counter this increase, in 2016, we initiated structured CCHF surveillance to improve estimates of risk factors for CCHF in Sindh and to identify potential interventions. METHODS: Beginning in 2016, all referral hospitals in Sindh reported all CCHF cases to surveillance agents. We used laboratory-confirmed cases from CCHF surveillance from 2016 to 2020 to compute incidence rates and in a case-control study to quantify risk factors for CCHF. RESULTS: For the 5 years, CCHF incidence was 4.2 per million for the Sindh capital, Karachi, (68 cases) and 0.4 per million elsewhere. Each year, the onset of new cases peaked during the 13 days during and after the 3-day Eid al Adha festival, when Muslims sacrificed livestock, accounting for 38% of cases. In Karachi, livestock for Eid were purchased at a seasonal livestock market that concentrated up to 700,000 livestock. CCHF cases were most common (44%) among the general population that had visited livestock markets (odds ratio = 102). CONCLUSIONS: Urban CCHF in Sindh province is associated with the general public's exposure to livestock markets in addition to high-risk occupations.

Incidence of public health surveillance-reported Clostridioides difficile infections in thirteen countries worldwide: A narrative review.

Clostridioides difficile infection (CDI) is an important cause of morbidity and mortality worldwide. Data from public health surveillance systems are important for estimating country-level CDI burden. CDI surveillance can be population-based or hospital-based. Population-based surveillance results in overall estimates of CDI incidence (cases per 100,000 population-per-year), and hospital-based surveillance results in estimates of hospital-based CDI incidence (cases per 10,000 patient-days) or CDI admission rates (cases per 1,000 admissions). We sought to better understand temporal trends in CDI incidence reported in publicly available surveillance data worldwide and describe varying surveillance methods. We identified 13 countries in Europe, North America, and Oceania with publicly available population-based and/or hospital-based CDI surveillance data in online reports and/or dashboards. Additional countries in Europe, in particular, also conduct hospital-based CDI surveillance. Inconsistent CDI case definitions and surveillance approaches between countries limit the interpretability of multi-country comparisons. Nonetheless, publicly available CDI surveillance data enabled us to compare CDI incidence among countries with population-based and/or hospital-based surveillance systems and to describe trends in CDI incidence within countries over time. The highest CDI incidence is in the United States. While there have been recent declines in CDI incidence in all countries, the CDI burden remains high, and the need persists for CDI prevention strategies in communities and healthcare settings.

Epidemiological surveillance and infectious disease outbreaks during mass international summertime sports gatherings: A narrative review.

The XXXIIIrd Paris Summer Olympics followed by the XVIIth Paralympics Games will take place in France, predominantly in and around Paris, from July 26 to September 8, 2024. Public health stakeholders and decision-makers are called upon to set up or strengthen surveillance systems in areas hosting Olympic or Paralympic Games (OPGs) or large-scale international competitions, the objective being to detect and manage outbreaks should they occur during that period. We undertook a narrative review of the literature so as to identify major reported infectious disease outbreaks linked with or during OPGs / international sporting events during warm seasons. Our review found that since 1992, Summer Olympic and Paralympic games and international football competitions have been associated with sporadic cases of infectious diseases, principally respiratory, gastrointestinal/foodborne, but not with any major communicable or other infectious disease outbreak. Communicable disease risks should be assessed for the population taken as a whole, an integrated ecosystem with several population compartments potentially exchanging pathogens among one another. Although the Games afford an opportunity to federate or invent new surveillance systems to fill a gap, surveillance should be based on existing medical and laboratory systems, proven tools reinforced with the necessary human and financial resources. The performance of the public health surveillance system is ultimately predicated on trust on the part of participating clinicians, policymakers and international partners.

Dentistry and Bioterrorism: A Legitimate Threat.

Bioterrorism involves the deliberate release of harmful biological agents, such as bacteria and viruses, aimed at causing mass casualties within a population. Often referred to as "poor man's nuclear weapons," chemical and biological weapons pose a significant threat due to their potential for mass destruction. Detecting and preventing bioterrorist attacks is challenging, making them one of the most feared scenarios. Dentistry plays a crucial role in responding to bioterrorism and other catastrophic events, leveraging its personnel and facilities effectively. This paper explores the signs and symptoms of biological agents used in mass destruction, as well as the oral and dental manifestations of both naturally occurring and bioengineered infectious agents. Furthermore, the article stresses the importance of countermeasures against bioterrorism, including deterrence, prevention, surveillance, medical management, and training. Emphasis is placed on implementing surveillance systems, bolstering medical readiness, and conducting training programs to effectively detect, assess, and respond to bioterrorism threats. Ultimately, the article underscores the critical role of dentists and healthcare professionals in collaborative efforts to mitigate the impacts of bioterrorism through proactive measures.

Electronic Health Record Data for Lyme Disease Surveillance, Massachusetts, USA, 2017-2018.

Lyme disease surveillance based on provider and laboratory reports underestimates incidence. We developed an algorithm for automating surveillance using electronic health record data. We identified potential Lyme disease markers in electronic health record data (laboratory tests, diagnosis codes, prescriptions) from January 2017-December 2018 in 2 large practice groups in Massachusetts, USA. We calculated their sensitivities and positive predictive values (PPV), alone and in combination, relative to medical record review. Sensitivities ranged from 57% (95% CI 47%-69%) for immunoassays to 87% (95% CI 70%-100%) for diagnosis codes. PPVs ranged from 53% (95% CI 43%-61%) for diagnosis codes to 58% (95% CI 50%-66%) for immunoassays. The combination of a diagnosis code and antibiotics within 14 days or a positive Western blot had a sensitivity of 100% (95% CI 86%-100%) and PPV of 82% (95% CI 75%-89%). This algorithm could make Lyme disease surveillance more efficient and consistent.

Strengthening disease surveillance capacity at national level across five countries: a qualitative study.

OBJECTIVES: Disease surveillance is an essential component of public health and a core function of National Public Health Institutes (NPHIs), including to better prepare and respond to infectious diseases outbreaks. Strengthening NPHIs in their efforts to establish and maintain efficient surveillance systems is an opportunity to ensure future outbreak preparedness and response; yet, guidance on how to increase and prioritise capacity building efforts is limited. This study sought to investigate approaches to capacity building and training for disease surveillance at national level and understand the potential role of NPHIs. STUDY DESIGN: Qualitative study. METHODS: This is a qualitative study, based on a literature review and interviews undertaken between June and November 2022. Fifty seven in-depth interviews were conducted in five countries: Côte d'Ivoire, Ecuador, Madagascar, Namibia, and the Kingdom of Saudi Arabia. Participants included a range of professionals from government, NPHIs, academic institutions and the private sector. Interviews were thematically analysed. RESULTS: Selected countries varied in terms of their disease surveillance capacities, as well as in the structure of their surveillance systems and decision-making. Research identified shared priority areas for action at national level, identifying common challenges and opportunities: 1) capacity building, here specifically the need for a training agenda at national level to ensure sustainability and guide donor funded training offers; 2) data tools and technology-to help decision-makers select the best software tool to address countries' identified need; 3) data sharing-the need for clear data sharing standards and norms for national to international data sharing; and 4) genomic sequencing-the need for national genomic surveillance strategies and reporting guidelines. CONCLUSION: Addressing challenges and using opportunities to strengthen disease surveillance at national level is an important step to build capacity in this area and to help prevent future epidemic and pandemics globally. The findings of this study help decision-makers to identify priority areas for capacity building and understand the potential role and significance of NPHIs.

Prevalence of post-traumatic stress disorder and depressive symptoms among civilians residing in armed conflict-affected regions: a systematic review and meta-analysis.

Background: Globally, populations afflicted by armed conflict are known to have high rates of mental health disorders. Aims: This meta-analysis aims to estimate the prevalence of post-traumatic stress disorder (PTSD) and depressive symptoms among civilians residing in armed conflict-affected regions. Methods: This meta-analysis was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. A literature search employing MEDLINE(R), Embase Classic+Embase, APA PsycINFO, Ovid Healthstar, Journal@Ovid Full Text, Cochrane, PTSDpubs and CINAHL was conducted from inception until 19 March 2024 to identify relevant studies. Quality assessment was performed using the Joanna Briggs Institute Critical Appraisal Checklist for Prevalence Studies, and a Comprehensive Meta-Analysis was used to conduct the statistical analysis. Results: The search yielded 38 595 articles, of which 57 were considered eligible for inclusion. The included studies comprised data from 64 596 participants. We estimated a prevalence of 23.70% (95% CI 19.50% to 28.40%) for PTSD symptoms and 25.60% (95% CI 20.70% to 31.10%) for depressive features among war-afflicted civilians. The subgroup analysis based on time since the war and the country's economic status revealed the highest prevalence for both PTSD and depressive symptoms was present during the years of war and in low/middle-income countries. Conclusions: The results of this study provide conclusive evidence of the detrimental impacts of armed conflict on mental health outcomes. Hence, it is crucial to emphasise the significance of both physical and mental health in the aftermath of war and take appropriate humanistic measures to overcome challenges in the management of psychiatric illnesses. PROSPERO registration number: CRD42023416096.

Corrigendum: Implementing a provisional overarching intervention for COVID-19 monitoring and control in the Brazil-Colombia-Peru frontier.

[This corrects the article DOI: 10.3389/fpubh.2023.1330347.].

Demographic characteristics, perinatal smoking patterns, and risk for neonatal health complications among pregnant smokers in the United States who begin using electronic cigarettes during pregnancy: A descriptive study using population-based surveillance data.

INTRODUCTION: Health agencies have called for research evaluating e-cigarette (EC) use in supporting prenatal smoking cessation. This study aimed to describe (a) characteristics of smokers who begin using ECs during pregnancy, (b) how frequently smokers reduce or eliminate pre- and post-natal combustible cigarette (CC) use, and (c) risk for neonatal health complications among smokers who initiate ECs during pregnancy. METHODS: Pregnant women using CCs exclusively pre-pregnancy, who participated in a U.S. surveillance study, were classified by their reported late-pregnancy smoking behavior as CC-exclusive users, EC initiators, or quitters. EC initiators were further subclassified as dual users (used both ECs and CCs) or EC replacers (used ECs exclusively). RESULTS: Of 29,505 pregnant smokers, 1.5% reported using ECs during the last 3 pregnancy months. Among them, 29.7% became EC-exclusive users. EC initiators were disproportionately non-Hispanic White. Relative to quitters, EC initiators had lower income, were less likely to be married, have intended pregnancies, receive first-trimester prenatal care, and participate in a federal assistance program. Compared to CC-exclusive users, EC initiators overall, and dual users specifically, were more likely to reduce pre- and post-natal CC usage relative to pre-pregnancy levels. EC initiators' risk for neonatal health complications fell between quitters and CC-exclusive users, though differences were not statistically significant. CONCLUSIONS: Although EC initiators reduced CC use more than CC-exclusive users, only 29.7% reported complete CC cessation, and there was insufficient evidence of reduction in neonatal health complications relative to CC-exclusive users. Currently, ECs should not be considered a viable gestational smoking cessation strategy. IMPLICATIONS: Health agencies have identified a critical need for research evaluating the use of e-cigarettes in supporting prenatal smoking cessation. Using the US Pregnancy Risk Assessment Monitoring System surveillance study data, we provide real-world evidence that prenatal e-cigarette initiation as a smoking cessation tool is used infrequently among pregnant combustible cigarettes smokers. Most using e-cigarettes in the last three months of pregnancy also used combustible cigarettes.

Data Equity as a Building Block for Health Equity: Improving Surveillance Data for People With Disabilities, With Substance Use Disorder, or Experiencing Homelessness, United States.

OBJECTIVES: People with disabilities, people experiencing homelessness, and people who have substance use disorders face unique health challenges. Gaps in public health surveillance data limit the identification of public health needs of these groups and data-driven action. This study aimed to identify current practices, challenges, and opportunities for collecting and reporting COVID-19 surveillance data for these populations. METHODS: We used a rapid qualitative assessment to explore COVID-19 surveillance capacities. From July through October 2021, we virtually interviewed key informants from the Centers for Disease Control and Prevention, state and local health departments, and health care providers across the United States. We thematically analyzed and contextualized interview notes, peer-reviewed articles, and participant documents using a literature review. RESULTS: We identified themes centered on foundational structural and systems issues that hinder actionable surveillance data for these and other populations that are disproportionately affected by multiple health conditions. Qualitative data analysis of 61 interviews elucidated 4 primary challenges: definitions and policies, resources, data systems, and articulation of the purpose of data collection to these groups. Participants noted the use of multisector partnerships, automated data collection and integration, and data scorecards to circumvent challenges. CONCLUSIONS: This study highlights the need for multisector, systematic improvements in surveillance data collection and reporting to advance health equity. Improvements must be buttressed with adequate investment in data infrastructure and promoted through clear communication of how data are used to protect health.

A regionally tailored epidemiological forecast and monitoring program to guide a healthcare system in the COVID-19 pandemic.

BACKGROUND: During the COVID-19 pandemic, analytics and predictive models built on regional data provided timely, accurate monitoring of epidemiological behavior, informing critical planning and decision-making for health system leaders. At Atrium Health, a large, integrated healthcare system in the southeastern United States, a team of statisticians and physicians created a comprehensive forecast and monitoring program that leveraged an array of statistical methods. METHODS: The program utilized the following methodological approaches: (i) exploratory graphics, including time plots of epidemiological metrics with smoothers; (ii) infection prevalence forecasting using a Bayesian epidemiological model with time-varying infection rate; (iii) doubling and halving times computed using changepoints in local linear trend; (iv) death monitoring using combination forecasting with an ensemble of models; (v) effective reproduction number estimation with a Bayesian approach; (vi) COVID-19 patients hospital census monitored via time series models; and (vii) quantified forecast performance. RESULTS: A consolidated forecast and monitoring report was produced weekly and proved to be an effective, vital source of information and guidance as the healthcare system navigated the inherent uncertainty of the pandemic. Forecasts provided accurate and precise information that informed critical decisions on resource planning, bed capacity and staffing management, and infection prevention strategies. CONCLUSIONS: In this paper, we have presented the framework used in our epidemiological forecast and monitoring program at Atrium Health, as well as provided recommendations for implementation by other healthcare systems and institutions to facilitate use in future pandemics.

Enhancing Public Health Surveillance: Outbreak Detection Algorithms Deployed for Syndromic Surveillance During Arbaeenia Mass Gatherings in Iraq.

BACKGROUND: Large gatherings often involve extended and intimate contact among individuals, creating environments conducive to the spread of infectious diseases. Despite this, there is limited research utilizing outbreak detection algorithms to analyze real syndrome data from such events. This study sought to address this gap by examining the implementation and efficacy of outbreak detection algorithms for syndromic surveillance during mass gatherings in Iraq. METHODS: For the study, 10 data collectors conducted field data collection over 10 days from August 25, 2023, to September 3, 2023. Data were gathered from 10 healthcare clinics situated along Ya Hussein Road, a major route from Najaf to Karbala in Iraq. Various outbreak detection algorithms, such as moving average, cumulative sum, and exponentially weighted moving average, were applied to analyze the reported syndromes. RESULTS: During the 10 days from August 25, 2023, to September 3, 2023, 12202 pilgrims visited 10 health clinics along a route in Iraq. Most pilgrims were between 20 and 59 years old (77.4%, n=9444), with more than half being foreigners (58.1%, n=7092). Among the pilgrims, 40.5% (n=4938) exhibited syndromes, with influenza-like illness (ILI) being the most common (48.8%, n=2411). Other prevalent syndromes included food poisoning (21.2%, n=1048), heatstroke (17.7%, n=875), febrile rash (9.0%, n=446), and gastroenteritis (3.2%, n=158). The cumulative sum (CUSUM) algorithm was more effective than exponentially weighted moving average (EWMA) and moving average (MA) algorithms for detecting small shifts. CONCLUSION: Effective public health surveillance systems are crucial during mass gatherings to swiftly identify and address emerging health risks. Utilizing advanced algorithms and real-time data analysis can empower authorities to improve their readiness and response capacity, thereby ensuring the protection of public health during these gatherings.

MENDS-on-FHIR: leveraging the OMOP common data model and FHIR standards for national chronic disease surveillance.

Objectives: The Multi-State EHR-Based Network for Disease Surveillance (MENDS) is a population-based chronic disease surveillance distributed data network that uses institution-specific extraction-transformation-load (ETL) routines. MENDS-on-FHIR examined using Health Language Seven's Fast Healthcare Interoperability Resources (HL7® FHIR®) and US Core Implementation Guide (US Core IG) compliant resources derived from the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) to create a standards-based ETL pipeline. Materials and Methods: The input data source was a research data warehouse containing clinical and administrative data in OMOP CDM Version 5.3 format. OMOP-to-FHIR transformations, using a unique JavaScript Object Notation (JSON)-to-JSON transformation language called Whistle, created FHIR R4 V4.0.1/US Core IG V4.0.0 conformant resources that were stored in a local FHIR server. A REST-based Bulk FHIR $export request extracted FHIR resources to populate a local MENDS database. Results: Eleven OMOP tables were used to create 10 FHIR/US Core compliant resource types. A total of 1.13 trillion resources were extracted and inserted into the MENDS repository. A very low rate of non-compliant resources was observed. Discussion: OMOP-to-FHIR transformation results passed validation with less than a 1% non-compliance rate. These standards-compliant FHIR resources provided standardized data elements required by the MENDS surveillance use case. The Bulk FHIR application programming interface (API) enabled population-level data exchange using interoperable FHIR resources. The OMOP-to-FHIR transformation pipeline creates a FHIR interface for accessing OMOP data. Conclusion: MENDS-on-FHIR successfully replaced custom ETL with standards-based interoperable FHIR resources using Bulk FHIR. The OMOP-to-FHIR transformations provide an alternative mechanism for sharing OMOP data.

Non-traditional sources for health surveillance: using emergency data for early-detection / O uso de fontes não-tradicionais para a vigilância em saúde: atendimentos de urgência para detecção precoce de eventos

Preparation and response to Public Health emergencies involve efforts in developing systems for early detection, alert and response. Models for dealing with notification delay and diversification of data sources are some of the commonly used strategies for faster information and action. In this paper, we present the strategy implemented in Rio de Janeiro municipality, where data from urgency and emergency visits were acquired and modeled, in order to detect trend shifts and generate alerts. From the ICD-10 field in electronic records, time series representing events of interest were created. A GAM model was fitted for smoothing, slope determination in each point, and alert generation. The results obtained are displayed in a dashboard, monitored daily. From 2023, multiple events of interest were identified through the dashboard, some of which lead to coordinated communication and actions in the territory. We draw attention to the potentials in the use of these type of data on identifying events of interest in a timely manner, approaching the concepts of a modern surveillance.

A preparação e resposta às emergências em Saúde Pública envolve o investimento em sistemas de detecção precoce, alerta e resposta. Modelos de correção de atraso de notificação e a diversificação de fontes de dados utilizadas são algumas abordagens comumente utilizadas para geração de informação e ação mais oportunos. Neste artigo é apresentada a estratégia implementada no município do Rio de Janeiro de utilização de dados de atendimentos de urgência e emergência unida à aplicação de modelos de detecção de tendências para geração automatizada de alertas. A partir de CIDs marcados nos prontuários eletrônicos de atendimentos, monitoram-se séries temporais de eventos de interesse no município. Um modelo GAM é ajustado às séries para suavização, determinação da inclinação e geração dos alertas. Os resultados são exibidos em painel e monitorados diariamente. Desde 2023, múltiplos eventos de interesse foram identificados através do painel e resultaram em comunicação coordenada e ações no território. Os resultados exaltam a potencialidade no uso desses dados na identificação de eventos de interesse em tempo oportuno, alinhando-se a conceitos de uma vigilância moderna.