Notifiable Diseases Research Articles

The epidemiological trends of 40 national notifiable infectious diseases in China: An analysis of national surveillance data from 2013 to 2022

The epidemiological trends of 40 national notifiable infectious diseases in China: An analysis of national surveillance data from 2013 to 2022

Campylobacter fetus subspecies specific PCR assays inferred from comparative genomic analysis for accurate subspecies identification

Bovine Genital Campylobacteriosis (BGC) is caused by Campylobacter fetus subsp. venerealis and is a notifiable disease to the WOAH (World Organisation for Animal Health). For an effective BGC control program, the reliable differentiation of Campylobacter fetus subsp. venerealis (Cfv) from the closely related Campylobacter fetus subsp. fetus (Cff) is required. However, the available molecular C. fetus subspecies identification assays lack sensitivity and specificity to differentiate C. fetus isolates based on their phenotypic or genotypic differences. Furthermore, the current biochemical subspecies identification is not fully congruent with the genomic differentiation of C. fetus strains.In this study, the genome sequences of 41C. fetus strains with well identified subspecies, were analyzed with the large-scale BLAST score ratio (LS-BSR) pipeline to identify Cff and Cfv specific sequences. With this analysis, the asd gene encoding an aspartate-semialdehyde dehydrogenase was identified, which contained a 6-bp Cff-specific sequence, and this 6-bp sequence was absent in the asd gene of Cfv strains. This sequence was used for the development of PCR assays to differentiate Cff and Cfv strains. The C. fetus subspecies identification of the developed asd PCR assays was in full congruence with the genomic classification of strains and are recommended for molecular identification of C. fetus subspecies in BGC control programs.The asd PCR can be assessed on sequenced genomes using a web interface containing the Cfvcatch tool, which includes placement of the tested genome in a phylogenetic tree with reference C. fetus genomes to distinguish the two subspecies and to detect antimicrobial resistance genes.

Syphilis and pregnancy.

•Although congenital syphilis has a known etiological agent, accessible diagnosis and low-cost, effective treatment with low fetal toxicity, it continues to challenge obstetric and antenatal care services. •The increasing rates of syphilis in the general population have direct repercussions on the increase in cases of congenital syphilis, a situation of objective interest for public health. •Although transforming the recording of syphilis and congenital syphilis into notifiable diseases improved the records and has made it possible to measure the occurrence of these diseases and create solutions, no effects on reducing their frequency have been reached yet. •The failure to control syphilis/congenital syphilis is multifactorial, and associates variables that range from the deficiency in teaching about these diseases in schools and in the training system of the various health professional segments, as well as the lack of rigid policies for quality control from antenatal care until the clinical follow-up of children exposed to Treponema pallidum during pregnancy. •To date, benzathine penicillin is the only antimicrobial accepted as effective by the main health authorities on the planet for the treatment of syphilis in pregnant women. •The fear of anaphylaxis in response to the treatment of syphilis with benzathine penicillin is an important factor hindering the prompt and correct treatment of pregnant women with syphilis, even though health authorities have made efforts to face the problem with solid arguments, still insufficient to resolve the question. •Although specific protocols are published, the failure to control the treatment of syphilis in pregnant women is still observed with high frequency, indicating and reinforcing a failure in the quality control of these care principles. The National Specialized Commission on Infectious Diseases of the Brazilian Federation of Gynecology and Obstetrics Associations (Febrasgo) endorses this document. Content production is based on scientific evidence on the proposed topic and the results presented contribute to clinical practice.

Early warning and predicting of COVID-19 using zero-inflated negative binomial regression model and negative binomial regression model

BackgroundIt is difficult to detect the outbreak of emergency infectious disease based on the exiting surveillance system. Here we investigate the utility of the Baidu Search Index, an indicator of how large of a keyword is in Baidu’s search volume, in the early warning and predicting the epidemic trend of COVID-19.MethodsThe daily number of cases and the Baidu Search Index of 8 keywords (weighted by population) from December 1, 2019 to March 15, 2020 were collected and analyzed with times series and Spearman correlation with different time lag. To predict the daily number of COVID-19 cases using the Baidu Search Index, Zero-inflated negative binomial regression was used in phase 1 and negative binomial regression model was used in phase 2 and phase 3 based on the characteristic of independent variable.ResultsThe Baidu Search Index of all keywords in Wuhan was significantly higher than Hubei (excluded Wuhan) and China (excluded Hubei). Before the causative pathogen was identified, the search volume of “Influenza” and “Pneumonia” in Wuhan increased with the number of new onset cases, their correlation coefficient was 0.69 and 0.59, respectively. After the pathogen was public but before COVID-19 was classified as a notifiable disease, the search volume of “SARS”, “Pneumonia”, “Coronavirus” in all study areas increased with the number of new onset cases with the correlation coefficient was 0.69 ~ 0.89, while “Influenza” changed to negative correlated (rs: -0.56 ~ -0.64). After COVID-19 was closely monitored, the Baidu Search Index of “COVID-19”, “Pneumonia”, “Coronavirus”, “SARS” and “Mask” could predict the epidemic trend with 15 days, 5 days and 6 days lead time, respectively in Wuhan, Hubei (excluded Wuhan) and China (excluded Hubei). The predicted number of cases would increase 1.84 and 4.81 folds, respectively than the actual number of cases in Wuhan and Hubei (excluded Wuhan) from 21 January to 9 February.ConclusionThe Baidu Search Index could be used in the early warning and predicting the epidemic trend of COVID-19, but the search keywords changed in different period. Considering the time lag from onset to diagnosis, especially in the areas with medical resources shortage, internet search data can be a highly effective supplement of the existing surveillance system.

Mapping dengue in Brazil: an epidemiological, geospatial and climate correlation

Brazil has been suffering for many years from an extensive dengue epidemic. The objective of this study was to map dengue cases in Brazil between 2007 and 2022, correlating their epidemiology, geospatial distribution, and relationship to climatic and social data. An epidemiological survey was conducted based on data available in the Notifiable Diseases Information System, calculating incidence rates (IR), mortality rates (MR), case fatality rates (CFR), and the distribution of epidemiological characteristics, allowing the geolocation of cases and the creation of maps for each year and Brazilian states. Finally, the ecological determinants were correlated with IR and MR. We observed that IR and MR remained high throughout the analyzed period, with a slight decrease in IR in 2017 and 2018. Cases occurring in female individuals were higher, however, with a similar percentage of deaths. A decrease in the average mortality was observed, during the evaluation period, in children and adolescents; however, an increase in the average mortality among elderly was correlated with the presence of comorbidities. The states located in the Midwest region were the most affected, followed by the states in the Northern region. In addition, we observed a significant, but weak, correlation between ecological determinants (maximum temperature and humidity) and IR, GDP per capita and HDI (Human Development Index) with MR. Due to the hyperendemic scenario, it is necessary to take efficient control and constant epidemiological surveillance.

ANÁLISE TEMPORAL DA INCIDÊNCIA DE CASOS NOTIFICADOS DA DOENÇA DE CHAGAS NO BRASIL, NO PERÍODO DE 2010-2019

Chagas disease is caused by Trypanosoma cruzi and remains an important public health concern in Brazil, despite control measures adopted over the last few decades. The objective of this study is to carry out a temporal analysis of the incidence of reported cases of Chagas Disease in Brazil from 2010 to 2019, identifying trends and possible associated factors. Secondary data from the Notifiable Diseases Information System (SINAN) were used to calculate incidence rates by region and year. The statistical analysis included linear regression models to evaluate the temporal variation of notifications. The results indicate an overall reduction in notifications in the country during the period analyzed, with significant regional variations. The North region showed an increase in notifications, suggesting the need for greater surveillance and control strategies. In contrast, the Southeast and South regions maintained a stable downward trend, as a result of continued vector control measures. It is concluded that, although cases of Chagas disease are declining in much of Brazil, the disease still represents a public health challenge in some regions, especially in areas where oral transmission and vector synanthropy are on the rise.

Spatiotemporal relationship between agriculture, livestock, deforestation, and visceral leishmaniasis in Brazilian legal Amazon

Visceral leishmaniasis (VL) is an urgent public health concern in Brazil. We evaluated the spatiotemporal distribution of VL to better understand the effects of economic activities related to agriculture, livestock, and deforestation on its incidence in the Brazilian Legal Amazon (BLA). The data on newly confirmed cases of VL in Brazilian municipalities from 2007 to 2020 were extracted from the Brazilian Notifiable Diseases Information System (SINAN) and analyzed. The data on agricultural production (planted area in hectares) and livestock (total number of cattle) were obtained from the Brazilian Institute of Geography and Statistics (IBGE), whereas deforestation data (in hectares) were obtained from the Amazon Deforestation Estimation Project (PRODES). SatScan and the local indicators of spatial association (LISA) were used to identify the spatial and temporal patterns of VL and its relationships with economic and environmental variables. The cumulative incidence rate was found to be 4.5 cases per 100,000 inhabitants. Based on the LISA results, areas with a high incidence of VL and deforestation were identified in the states of Roraima, Pará, and Maranhão. Strengthening deforestation monitoring programs and environmental enforcement actions can help implement public policies to control illegal deforestation and mitigate the socio-environmental vulnerability in the BLA. Therefore, areas identified in this study should be prioritized for controlling VL.

Burden changes in notifiable infectious diseases in Taiwan during the COVID-19 pandemic.

This study aimed to assess the impact of the COVID-19 pandemic on the disease burden of Taiwan's notifiable infectious diseases (NIDs). We compared disease burdens between the pandemic and pre-pandemic year of 2020 (with non-pharmaceutical interventions (NPIs)) and 2010 (without NPIs), respectively, to understand the overall pandemic impact on NIDs in Taiwan. Forty-three national NIDs were analyzed using the Statistics of Communicable Diseases and Surveillance Report by estimating the premature death and disability via different transmission categories, sex, and age groups. The study evaluated the impact of diseases by assessing the years lost due to death (YLLs), the duration of living with disability (YLDs), and the overall disability-adjusted life years (DALYs) by measuring both the severity of the illness and its duration. Taiwan recorded 1,577 (2010) and 1,260 (2020) DALYs per million population and lost 43 NIDs, decreasing 317 DALYs per million population. Tuberculosis, HIV/AIDS and acute hepatitis B/D were the leading causes of DALYs, accounting for 89% (2010) and 77% (2020). Overall, this study provided the first insight of changes in disease burdens in NIDs between pre- and post-COVID-19 based on a nationwide viewpoint for further preventive measures and interventions to be focused on specific diseases by associated health administrations and policies.

Molecular epidemiology of SARS-CoV-2 genome sentinel surveillance in commercial COVID-19 testing sites targeting asymptomatic individuals during Japan’s seventh epidemic wave

Eight peaks of coronavirus disease 2019 (COVID-19) outbreak occurred in Japan, each associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern. The National Epidemiological Surveillance of Infectious Diseases (NESID) analyzed viral genome sequences from symptomatic patients and submitted the results to GISAID. Meanwhile, commercial testing services occasionally sequence samples from asymptomatic individuals. We compared a total of 1248 SARS-CoV-2 full-genome sequences obtained from the SB Coronavirus Inspection Center Corp. (SBCVIC) during Japan’s seventh wave, which was dominated by Omicron variants, with 1764 sequences obtained in Japan from GISAID during the same period using chronological phylogenies and molecular transmission networks. The number of SBCVIC sequences was consistent with the number of cases reported by NESID. The SBCVIC detected a shift in the PANGO lineage from BA.2 to BA.5 earlier than that of GISAID. BA.2 lineages from the SBCVIC were distributed at different locations in the transmission network dominated by GISAID entries, whereas BA.5 lineages from SBCVIC and GISAID often formed distinct subclusters. Test-based sentinel surveillance of asymptomatic individuals may be a more manageable approach compared to notifiable disease surveillance; however, it may not necessarily capture all infection populations throughout Japan.

Comparison of Three Influenza Surveillance Data Sources for Timely Detection of Epidemic Onset - Chengdu City, Sichuan Province and Beijing Municipality, China, 2017-2023.

The syndromic surveillance system, exemplified by the influenza-like illness (ILI) surveillance system, has long been crucial in providing early warnings of influenza epidemics. The analysis revealed that employing reported influenza case data from the nationwide Notifiable Infectious Diseases Reporting Information System (NIDRIS) enhanced the early detection of influenza epidemics, particularly within the context of multiple respiratory pathogens circulating concurrently. The NIDRIS, characterized by its extensive coverage, obligatory reporting, high specificity, and real-time data transmission, offers a valuable tool for the effective early detection of influenza epidemics. Utilizing this system could enhance preparedness and responses to such health crises, potentially mitigating their impact on public health.

The Potential of Eight Plasma Proteins as Biomarkers in Redefining Leptospirosis Diagnosis.

Leptospirosis, a notifiable endemic disease in Malaysia, has higher mortality rates than regional dengue fever. Diverse clinical symptoms and limited diagnostic methods complicate leptospirosis diagnosis. The demand for accurate biomarker-based diagnostics is increasing. This study investigated the plasma proteome of leptospirosis patients with leptospiraemia and seroconversion compared with dengue patients and healthy subjects using isobaric tags for relative and absolute quantitation (iTRAQ)-mass spectrometry (MS). The iTRAQ analysis identified a total of 450 proteins, which were refined to a list of 290 proteins through a series of exclusion criteria. Differential expression in the plasma proteome of leptospirosis patients compared to the control groups identified 11 proteins, which are apolipoprotein A-II (APOA2), C-reactive protein (CRP), fermitin family homolog 3 (FERMT3), leucine-rich alpha-2-glycoprotein 1 (LRG1), lipopolysaccharide-binding protein (LBP), myosin-9 (MYH9), platelet basic protein (PPBP), platelet factor 4 (PF4), profilin-1 (PFN1), serum amyloid A-1 protein (SAA1), and thrombospondin-1 (THBS1). Following a study on a verification cohort, a panel of eight plasma protein biomarkers was identified for potential leptospirosis diagnosis: CRP, LRG1, LBP, MYH9, PPBP, PF4, SAA1, and THBS1. In conclusion, a panel of eight protein biomarkers offers a promising approach for leptospirosis diagnosis, addressing the limitations of the "one disease, one biomarker" concept.

PANORAMA EPIDEMIOLÓGICO DA TUBERCULOSE EM CRIANÇAS E ADOLESCENTES NO BRASIL: ANÁLISE DE CASOS NOTIFICADOS ENTRE 2003 E 2023.

Tuberculosis (TB) remains a significant public health issue in Brazil, particularly among children and adolescents. This study aims to conduct a retrospective analysis of the epidemiological profile of TB cases reported in the population aged 0 to 19 years between 2003 and 2023, focusing on diagnosis and follow-up. It is a descriptive and analytical study with a quantitative approach, utilizing data extracted from the Notifiable Diseases Information System (SINAN) and the Brazilian Institute of Geography and Statistics (IBGE). A total of 163,262 TB cases were analyzed, of which 55.1% were female and 44.8% were male. The majority of cases were concentrated in the 15 to 19 age group, and the distribution by race/color showed a predominance of mixed-race individuals. A general decline in the number of cases was observed over the years, with a significant reduction between 2020 and 2021. However, the incidence of TB in children under 1 year of age increased gradually. Regarding diagnosis, only 51.87% of cases were confirmed by laboratory tests, with low rates of sputum culture and bacilloscopy. Cure and treatment adherence rates remained stable until 2021 but dropped dramatically in 2023. The study concludes that there are significant challenges in the early diagnosis and management of TB in this population, suggesting the need for more effective public policies to improve health outcomes and reduce TB-related mortality among children and adolescents.

Evolving pathogen trends and spatial–temporal dynamics of hand, foot, and mouth disease in Fengxian District, Shanghai (2009–2022)

Hand, foot, and mouth disease (HFMD) is a prevalent acute infectious disease caused by enteroviruses, presenting substantial public health challenges in Shanghai, especially among children. The dynamic nature of HFMD’s etiology necessitates an ongoing evaluation of its epidemiological and virological trends to inform effective control strategies. This study aims to investigate the epidemiological patterns and viral evolution of HFMD in Fengxian District, Shanghai, China, with a focus on shifts in predominant viral strains over a 14-year period. We conducted a retrospective analysis of HFMD cases reported to the National Notifiable Disease Reporting System in Fengxian District from January 1, 2009 to December 31, 2022. Epidemiological trends, strain prevalence, and demographic impacts were assessed. A total of 27,272 HFMD cases were documented during the study period, with incidence showing pronounced seasonal fluctuations—peaking in spring and summer and a lesser peak in autumn. The disease incidence demonstrated significant positive correlations with several meteorological variables: daily average temperature (r = 0.30, P < 0.05), relative humidity (r = 0.20, P < 0.05), wind speed (r = 0.17, P < 0.05), and precipitation (r = 0.17, P < 0.05). Geographically, Nanqiao Town, Fengcheng Town, and Xidu Subdistrict reported the highest incidence rates. The demographic analysis revealed a male-to-female ratio of 1.60:1, predominantly affecting children aged 1–3 years. Prior to 2017, Enterovirus 71 (EV71) and Coxsackievirus A16 (CoxA16) were the primary detected strains; post-2017, Coxsackievirus A6 (CoxA6) emerged as the dominant strain. Statistical analysis confirmed significant year-to-year variations in virus detection rates, with decreasing trends for EV71 and other enteroviruses and an increasing trend for CoxA6. The findings indicate a distinct seasonal incidence of HFMD in Fengxian District. This study underscores the need for targeted public health education, enhanced surveillance, and proactive measures in childcare facilities to mitigate disease spread during peak seasons. Moreover, the evolving viral landscape warrants accelerated efforts in vaccine development against new strains to reduce HFMD incidence.

Clinical effects of non-pharmaceutical interventions for COVID-19 on other nationally notifiable infectious diseases in South Korea.

This study aimed to assess the impact of non-pharmaceutical interventions (NPIs) implemented during the COVID-19 pandemic on nationally notifiable infectious diseases (NNIDs) in South Korea. Long-term data on seven NNIDs from 2018 to 2021 were analyzed to identify trends and change points using a change point detection technique. The timings of the NPI implementations were compared to the identified change points to determine their association. Varicella, mumps, and scarlet fever showed a significant decrease in incidence following the implementation of NPIs during the COVID-19 pandemic. These diseases, which are primarily transmitted through respiratory droplets, demonstrated a clear response to NPIs. However, carbapenem-resistant Enterobacterales (CRE) showed an increasing trend unrelated to the timing of NPI implementation, suggesting the complex nature of controlling healthcare-associated infections. Hepatitis A, hepatitis C, and scrub typhus did not show significant changes associated with NPIs, likely due to their non-respiratory route of transmission. NPIs effectively controlled NNIDs, particularly those transmitted through respiratory infections. However, the impact varied depending on the disease. Understanding the effectiveness and limitations of NPIs is crucial for developing comprehensive public health strategies during infectious disease outbreaks.

Predictor effect of the Rapid Survey (LIRAa) and priority areas for Dengue surveillance in Maranhão, Brazil

Dengue fever is a serious public health problem in Brazil. However, there are still mechanisms involved in the dynamics of the disease that need to be better elucidated, especially in Maranhão. In this sense, the objective was to evaluate the predictive effect of LIRAa in relation to the incidence of dengue fever in Maranhão in 2022, and to identify priority municipalities for interventions through geospatial analysis. This is a scholastic study, carried out with data obtained from the Zoonosis Surveillance Units - UVZ of the municipalities, in the Notifiable Diseases Information System (SINAN). A simple linear regression with post-hoc analyses and the Local Moran Index (LISA) were performed. A positive effect of LIRAa on the incidence of dengue fever was observed (R2 = 0.0352; p = 0.0062). LISA indicated ten high-risk municipalities and six in a transition situation to high risk of dengue fever in the state. LIRAa has proven to be an efficient entomoepidemiological surveillance tool and the identification of priority areas for surveillance can help health authorities in developing specific strategies to contain future epidemics.

The power of interactive maps for communicating spatio-temporal data to health professionals.

While more and more health-related data is being produced and published every day, few of it is being prepared in a way that would be beneficial for daily use outside the scientific realm. Interactive visualizations that can slice and condense enormous amounts of multi-dimensional data into easy-to-digest portions are a promising tool that has been under-utilized for health-related topics. Here we present two case studies for how interactive maps can be utilized to make raw health data accessible to different target audiences: i) the European Notifiable Diseases Interactive Geovisualization (ENDIG) which aims to communicate the implementation status of disease surveillance systems across the European Union to public health experts and decision makers, and ii) the Zoonotic Infection Risk in Twente-Achterhoek Map (ZIRTA map), which aims to communicate information about zoonotic diseases and their regional occurrence to general practitioners and other healthcare providers tasked with diagnosing infectious diseases on a daily basis. With these two examples, we demonstrate that relatively straight-forward interactive visualization approaches that are already widely used elsewhere can be of benefit for the realm of public health.

The Australian Biosecurity Genomic Database: a new resource for high-throughput sequencing analysis based on the National Notifiable Disease List of Terrestrial Animals.

The Australian Biosecurity Genomic Database (ABGD) is a curated collection of reference viral genome sequences based on the Australian National Notifiable Disease List of Terrestrial Animals. It was created to facilitate the screening of high-throughput sequencing (HTS) data for the potential presence of viruses associated with notifiable disease. The database includes a single verified sequence (the exemplar species sequence, where relevant) for each of the 60 virus species across 21 viral families that are associated with or cause these notifiable diseases, as recognized by the World Organisation for Animal Health. The open-source ABGD on GitHub provides usage guidance documents and is intended to support building a culture in Australian HTS communities that promotes the use of quality-assured, standardized, and verified databases for Australia's national biosecurity interests. Future expansion of the database will include the addition of more strains or subtypes for highly variable viruses, viruses causing diseases of aquatic animals, and genomes of other types of pathogens associated with notifiable diseases, such as bacteria. Database URL: https://github.com/ausbiopathgenDB/AustralianBiosecurityGenomicDatabase.

Optimization of the control strategy and research priorities to combat the resurgence of visceral leishmaniasis in China

Leishmaniasis is a zoonotic parasitic disease caused by Leishmania infection and transmitted by sandflies. There are three main forms of leishmaniasis, including cutaneous leishmaniasis, visceral leishmaniasis and mucocutaneous leishmaniasis. China is mainly endemic for visceral leishmaniasis, which is a class C notifiable infectious disease in the country. Following concerted efforts, the transmission of visceral leishmaniasis had been controlled in most endemic foci of China by the end of 1958, with a few cases reported in western China. Due to global climate changes and population mobility, resurgence of visceral leishmaniasis has recently occurred in historical endemic areas of central and western China, which is characterized by gradual expansion of endemic areas and remarkable rebounding epidemics. Hereby, we summarize the national and global epidemiology and control strategy of visceral leishmaniasis, propose 8 key research areas and 12 key research topics for visceral leishmaniasis control, and recommend the establishment of the joint prevention and control mechanism of "human-animals-vectors" and the working mechanism of animal prevention for human diseases based on the One Health approach, so as to combat the resurgence of visceral leishmaniasis in China.

Harmonizing Norwegian registries onto OMOP common data model: Mapping challenges and opportunities for pregnancy and COVID-19 research

ObjectiveNorwegian health registries covering entire population are used for administration, research, and emergency preparedness. We harmonized these data onto the Observational Medical Outcomes Partnership common data model (OMOP CDM) and enrich real-world data in OMOP format with COVID-19 related data. MethodsData from six registries (2018–2021) covering birth registrations, selected primary and secondary care events, vaccinations, and communicable disease notifications were mapped onto the OMOP CDM v5.3. An Extract-Transform-Load (ETL) pipeline was developed on simulated data using data characterization documents and scanning tools. We ran dashboard quality checks, cohort generations, investigated differences between source and mapped data, and refined the ETL accordingly. ResultsWe mapped 1.5 billion rows of data of 5,673,845 individuals. Among these, there were 804,277 pregnancies, 483,585 mothers together with 792,477 children, and 472,948 fathers. We identified 382,516 positive tests for COVID-19 in 380,794 patients. These figures are consistent with results from source data. In addition to 11 million source codes mapped automatically, we mapped 237 non-standard codes to standard concepts and introduced 38 custom concepts to accommodate pregnancy-related terminologies that were not supported by OMOP CDM vocabularies. A total of 3,700/3,705 (99.8%) checks passed. The 5 failed checks could be explained by the nature of the data and only represent a small number of records. Discussion and conclusionNorwegian registry data were successfully harmonized onto OMOP CDM with high level of concordance and provides valuable source for federated COVID-19 related research. Our mapping experience is highly valuable for data partners with Nordic health registries.

Focus, vigilance, resilience: towards stronger infectious disease surveillance, threat detection and response in the EU/EEA.

This perspective summarises and explains the long-term surveillance framework 2021-2027 for infectious diseases in the European Union/European Economic Area (EU/EEA) published in April 2023. It shows how shortcomings in the areas of public health focus, vigilance and resilience will be addressed through specific strategies in the coming years and how these strategies will lead to stronger surveillance systems for early detection and monitoring of public health threats as well as informing their effective prevention and control. A sharper public health focus is expected from a more targeted list of notifiable diseases, strictly public-health-objective-driven surveillance standards, and consequently, leaner surveillance systems. Vigilance should improve through mandatory event reporting, more automated epidemic intelligence processing and increased use of genomic surveillance. Finally, EU/EEA surveillance systems should become more resilient by modernising the underlying information technology infrastructure, expanding the influenza sentinel surveillance system to other respiratory viruses for better pandemic preparedness, and increasingly exploiting potentially more robust alternative data sources, such as electronic health records and wastewater surveillance. Continued close collaboration across EU/EEA countries will be key to ensuring the full implementation of this surveillance framework and more effective disease prevention and control.