Assessment of the efficiency of the routine epidemiological surveillance system for malaria at the Tambacounda Health District, Senegal.

Introduction: as part of the fight against malaria, epidemiological surveillance (ES) is one of the key pillars of the global technical strategy 2016-2030 to combat this disease. However, in the south-east of Senegal, where malaria poses a major public health problem, epidemiological surveillance has until recently been very neglected. To help reduce malaria-related morbidity and mortality in Senegal, an evaluation of the routine malaria ES system was conducted in the Tambacounda Health District in 2021. Methods: we conducted a cross-sectional, descriptive survey of 27 health structures in Tambacounda district from 20th February to 1st March 2022. Results: overall, the routine ES system in the district was acceptable according to its users, with satisfactory tool filling time in 96.3% of the structures in our study, a cumulative completeness of reports at 92% despite a 77% promptness. The data collected at the services delivery points (SDP) level allowed a representativeness of the ES system in 100% of health facilities. The ES system was also rated as simple by 74.1% of SDP managers even though only 55.6% of them were trained. However, the stability of the system was low because 55.6% of SDP had staff to ensure the continuity of ES service despite the availability of management tools (100%) and the telephone network (96.3%). The same was true for the usefulness of the ES because only 25.9% of SDP managers analyzed their produced data. The reported ES and malaria morbidity data were not adequate. On the other hand, the ES system was reactive with a speed of transmission of information at 96.3% and a possibility of rapid diagnosis and management of cases at 100%. Conclusion: the routine malaria ES system at the level of health facilities in Tambacounda District was acceptable, simple, flexible, representative, and responsive. However, an increase in qualified staff at the health posts, capacity strengthening of the ES staff and regular supervision of SDP are needed essentials to make the district's malaria surveillance system more efficient.

Perspectives and challenges in developing and implementing integrated dengue surveillance tools and technology in Thailand: a qualitative study.

BACKGROUND: Dengue remains a persistent public health concern, especially in tropical and sub-tropical countries like Thailand. The development and utilization of quantitative tools and information technology show significant promise for enhancing public health policy decisions in integrated dengue control. However, the effective implementation of these tools faces multifaceted challenges and barriers that are relatively underexplored. METHODS: This qualitative study employed in-depth interviews to gain a better understanding of the experiences and challenges of quantitative tool development and implementation with key stakeholders involved in dengue control in Thailand, using a phenomenological framework. A diverse range of participants, including public health workers and dengue control experts, participated in these interviews. The collected interview data were systematically managed and investigated using thematic analysis to extract meaningful insights. RESULTS: The ability to collect dengue surveillance data and conduct ongoing analyses were contingent upon the availability of individuals possessing essential digital literacy and analytical skills, which were often in short supply. Furthermore, effective space-time early warning and precise data collection were hindered by the absence of user-friendly tools, efficient reporting systems, and complexities in data integration. Additionally, the study underscored the importance of the crucial role of community involvement and collaboration among organizations involved in integrated dengue surveillance, control and quantitative tool development. CONCLUSIONS: This study employed a qualitative approach to gain a deeper understanding of the contextual intricacies surrounding the development and implementation of quantitative tools, which, despite their potential for strengthening public health policy decisions in dengue control, remain relatively unexplored in the Thai context. The findings yield valuable insights and recommendations for the development and utilization of quantitative tools to support dengue control in Thailand. This information also has the potential to support use of such tools to exert impact beyond dengue to a broader spectrum of diseases.

Assessment of Brazil's vesicular syndrome surveillance system: Profile of notifications and performance of the official veterinary service.

Foot-and-mouth disease (FMD) is an ailment that causes serious damage to the productive chain, and its control through vaccination is of utmost importance for its eradication. Brazil initiated the National Foot-and-Mouth Disease Surveillance Program (PNEFA) with the aim of making the country FMD-free by 2026. As part of the program, notifications of vesicular lesions became mandatory for the Official Veterinary Service (OVS), which is responsible for verifying them. Due to its size, border areas with countries that do not have FMD-free status pose a risk to Brazil and require greater attention. This study described the profile of notifications of suspected outbreaks of vesicular syndrome in Brazil and analyzed the performance of the surveillance system. The results showed 7134 registered notifications of suspected vesicular syndrome outbreaks from 2018 to 2022, with 2022 having the highest number (n = 2343 or 32.85 %). The species that generated the most notifications were swine (90.99 %), cattle and buffaloes (7.54 %), goats and sheep (1.44 %), and others (0.03 %). The sources of notification were "Veterinary medicine professionals" (61.82 %), "Owners or employees" (13.66 %), "Third parties" (8.90 %), "OVS" (7.20 %), and "others" (2.66 %). 41.69 % of notifications originated from non-border municipalities, and 58.32 % from border areas. Only the state of Paraná account for 51.73 % of the total notifications. This state also accounted for 66.70 % of the 32.47 % of notifications with a final diagnosis of "absence of clinically compatible signs or susceptible animals", indicating a certain lack of knowledge in the area, leading to unnecessary notifications and system overload. The performance of the OVS was evaluated based on the service response time from notification registration trough Logistic and Negative binomial regressions. A total of 27.83 % of notifications did not meet the Brazilian legally specified time, and the zone related to the state of Parana needs improvements in performance. The presence and peaks of Senecavirus A cases may have influenced an increased number of swine notifications and led to a decrease in OVS response time. The results demonstrate better performance of surveillance in border areas. Given the vast territory of Brazil, it is not expected that 100 % of responses occur within the legal timeframe, however, the performance of the surveillance system proved to be adequate, with 86 % complied to the legislation. The performance indicators could be used as a monitoring tool, along with indicators to demonstrate system overload. Continued education actions are crucial for strengthening PNEFA.

Unexpected arboviruses found in an epidemiological surveillance of acute tropical febrile syndrome in the department of Meta, Eastern Colombia.

BACKGROUND: Nonspecific acute tropical febrile illnesses (NEATFI) are common in the Latin American tropics. Dengue, Chikungunya, Zika, Mayaro, and Usutu, among others, can coexist in the American tropics. This study aimed to surveil the arboviruses that cause| acute febrile syndrome in patients in the Meta department, Colombia. METHODS: Between June 2021 and February 2023, an epidemiological surveillance study was conducted in the Llanos of the Meta department in Eastern Colombia. RESULTS: One hundred patients in the acute phase with typical prodromal symptoms of NEATFI infection who attended the emergency department of the Villavicencio Departmental Hospital were included. ELISA tests were performed for Dengue, Usutu, Chikungunya, and Mayaro. RT-qPCR was performed to detect the arboviruses Usutu, Dengue, Zika, Mayaro, and Oropouche. The seroprevalence for the Chikungunya, Mayaro, and Usutu viruses was 41 % (28/68), 40 % (27/67), and 62 % (47/75), respectively. Seroconversion for Chikungunya was observed in one patient; two seroconverted to Mayaro and one to Usutu. The NS5 gene fragment of the Usutu virus was detected in nine febrile patients. RT-qPCR of the remaining arboviruses was negative. The clinical symptoms of the nine Usutu-positive patients were very similar to those of Dengue, Chikungunya, Zika, and Mayaro infections. CONCLUSIONS: The pervasive detection of unexpected viruses such as Usutu and Mayaro demonstrated the importance of searching for other viruses different from Dengue. Because Usutu infection and Mayaro fever have clinical features like Dengue, a new algorithm should be proposed to improve the accuracy of acute tropical fevers.

Genomics for Arbovirus Surveillance: Considerations for Routine Use in Public Health Laboratories.

The emergence and re-emergence of arthropod-borne viruses is a public health threat. For routine surveillance in public health laboratories, cost-effective and reproducible methods are essential. In this review, we address the technical considerations of high-throughput sequencing methods (HTS) for arbovirus surveillance in national health laboratories, focusing on pre-sequencing, sequencing, and post-sequencing approaches, underlining the importance of robust wet and dry laboratory workflows for reproducible analysis. We aim to provide insights for researchers and clinicians interested in arbovirus, diagnosis, and surveillance by discussing current advances in sequencing methods and bioinformatics pipelines applied to arboviruses.

MARVEL-minimising the emergence and dissemination of HIV-1 drug resistance in Portuguese-speaking African Countries (PALOP): low-cost portable NGS platform for HIV-1 surveillance in Africa.

BACKGROUND: HIV-1 infections remain a global public health concern. Scaled-up antiretroviral treatment (ART) is crucial for reducing morbidity and mortality related to HIV/AIDS. The emergence of drug-resistance mutations (DRMs) compromises viral suppression and contributes to the continued HIV-1 transmission. Several reports indicate a recent increase in acquired (ADR) and transmitted (TDR) drug resistance in Africa, probably linked to the lack of implementation of HIV drug resistance (HIVDR) testing and suboptimal treatment adherence. Herein, we will develop a low-cost protocol using third-generation sequencing (Oxford Nanopore Technology) for HIV-1 surveillance in Portuguese-speaking African Countries - PALOP [Angola (AO), Cape Verde (CV), Mozambique (MZ), and Sao Tome & Principe (STP)]. METHODS: This is a multicentric cross-sectional study that includes around 600 adult patients newly diagnosed with HIV-1 in the PALOP. An epidemiological questionnaire previously validated by our research team will be used to collect sociodemographic and clinical data. Also, whole blood samples will be collected and the plasma samples will be subjected to drug resistance testing using an in-house low-cost NGS protocol. Data analysis will involve bioinformatics, biostatistics and machine learning techniques to generate accurate and up-to-date information about HIV-1 genetic diversity, ADR and TDR. DISCUSSION: The implementation of this low-cost NGS platform for HIV-1 surveillance in the PALOP will allow: (i) to increase DRM surveillance capacity in resource-limited settings; (ii) to understand the pattern and determinants of dissemination of resistant HIV-1 strains; and (iii) to promote the development of technical and scientific skills of African researchers for genomic surveillance of viral pathogens and bioinformatics analysis. These objectives will contribute to reinforcing the capacity to combat HIV infection in Africa by optimizing the selection of ART regimens, improving viral suppression, and reducing ADR or TDR prevalence in PALOPs, with relevant implications for public health.

The effect of spatio-temporal sample imbalance in epidemiologic surveillance using opportunistic samples: An ecological study using real and simulated self-reported COVID-19 symptom data.

Open surveys complementing surveillance programs often yield opportunistically sampled data characterised by spatio-temporal imbalance. We set up our study to understand to what extent spatio-temporal statistical models using such data achieve in describing epidemiological trends. We used self-reported symptomatic COVID-19 data from two Belgian regions, Flanders and the Brussels-Capital Region. These data were collected in a large-scale open survey with spatio-temporally imbalanced participation rates. We compared incidence estimates of both self-reported symptoms and test-confirmed COVID-19 cases obtained through generalised linear mixed models correcting for spatio-temporal correlation. We additionally simulated symptom incidences under different sampling strategies to explore the impact of sample imbalance, sample size and disease incidence, on trend detection. Our study shows that spatio-temporal sample imbalance generally does not lead to bad model performances in spatio-temporal trend estimation and high-risk area detection. Except for low-incidence diseases, collecting large samples will often be more essential than ensuring spatio-temporally sample balance.

[The epidemiological survey as a key instrument for events of Public Health importance]. / La encuesta epidemiológica como instrumento clave frente a eventos de importancia en Salud Pública.

The epidemiological survey is one of the key instruments, both in Public Health alerts or emergencies, and in epidemiological surveillance. Its main objective is to obtain information quickly, systematically, uniformly and easily. It is characterized by being dynamic and flexible, in addition to offering the relevant descriptive information of the epidemiological event studied: person, place and time . Thus, it allows us to quantify the frequency and distribution pattern of the event through measures such as incidence, prevalence or mortality, providing the basic information to propose a starting hypothesis.

La encuesta epidemiológica es uno de los instrumentos clave, tanto en las alertas o emergencias de Salud Pública, como en la vigilancia epidemiológica. Su principal objetivo es obtener información de forma rápida, sistemática, uniforme y sencilla. Se caracteriza por ser dinámica y flexible, además de ofrecer la información descriptiva relevante del evento epidemiológico estudiado: persona, lugar y tiempo . Así, permite cuantificar la frecuencia y el patrón de distribución del evento a través de medidas como la incidencia, la prevalencia o la mortalidad, aportando la información básica para plantear una hipótesis de partida.

Orientaciones para la búsqueda activa de casos de parálisis flácida aguda, sarampión y rubéola / Guidelines for active case finding of acute flaccid paralysis, measles and rubella

La presente publicación describe las orientaciones técnicas e instrumentos de recolección de datos para realizar la búsqueda activa integral de parálisis flácida aguda, sarampión y rubéola a nivel institucional (establecimientos de salud) y comunitario. La implementación conjunta de la búsqueda activa para estas tres enfermedades pretende lograr una sinergia de los recursos humanos y financieros, tomando en cuenta las consideraciones específicas de cada enfermedad. Asimismo, presenta, en los anexos, los diagnósticos diferenciales e instrumentos de recolección de datos para otras enfermedades prevenibles por vacunación como difteria, tétanos, tétanos neonatal y tos ferina, en caso de que el país tenga interés en incluir alguna de estas enfermedades durante la implementación de la búsqueda activa

Standardization of an antimicrobial resistance surveillance network through data management.

Introduction: The rapid spread of COVID-19 worldwide within 2 months demonstrated the vulnerability of the world's population to infectious diseases. In 2015, the Global Antimicrobial Resistance and Use Surveillance System (GLASS) was launched to combat antimicrobial resistance (AMR). However, there has been no comprehensive assessment of the decade-long global battle against AMR based on GLASS data. Methods: South Korea established Kor-GLASS (Korean-GLASS) to proactively monitor data quality and enable international collaborations. A unique feature of Kor-GLASS is the quality control center (QCC), which uses network hubs and ensures standardized, high-quality data through interlaboratory proficiency testing (IPT) and external quality assessment (EQA). In addition, the QCC multifaceted endeavors for integrated data quality management. Results: Since 2020, high-quality AMR data have indicated fluctuating antibiotic resistance rates in South Korea. This trend does not align with the decrease in antibiotic usage seen in humans but coincides with non-human antibiotic sales, indicating a need for greater monitoring of non-human antibiotic resistance. Comprehensive and robust management taking account of the intricate interplay among humans, animals, and the environment is essential. Kor-GLASS has been expanded into a "One Health" multiagency collaborative initiative. Discussion: Although a standardized solution is not suitable for all countries, it must align with the local context and international standards. A centralized top-down management structure such as that of the QCC is essential to ensure continuous data quality coordination. Sustained efforts and surveillance systems are crucial for monitoring and managing AMR and safeguarding human health.

A novel method to select time-varying multivariate time series models for the surveillance of infectious diseases.

BACKGROUND: Describing the transmission dynamics of infectious diseases across different regions is crucial for effective disease surveillance. The multivariate time series (MTS) model has been widely adopted for constructing cross-regional infectious disease transmission networks due to its strengths in interpretability and predictive performance. Nevertheless, the assumption of constant parameters frequently disregards the dynamic shifts in disease transmission rates, thereby compromising the accuracy of early warnings. This study investigated the applicability of time-varying MTS models in multi-regional infectious disease monitoring and explored strategies for model selection. METHODS: This study focused on two prominent time-varying MTS models: the time-varying parameter-stochastic volatility-vector autoregression (TVP-SV-VAR) model and the time-varying VAR model using the generalized additive framework (tvvarGAM), and intended to explore and verify their applicable conditions for the surveillance of infectious diseases. For the first time, this study proposed the time delay coefficient and spatial sparsity indicators for model selection. These indicators quantify the temporal lags and spatial distribution of infectious disease data, respectively. Simulation study adopted from real-world infectious disease surveillance was carried out to compare model performances under various scenarios of spatio-temporal variation as well as random volatility. Meanwhile, we illustrated how the modelling process could help the surveillance of infectious diseases with an application to the influenza-like case in Sichuan Province, China. RESULTS: When the spatio-temporal variation was small (time delay coefficient: 0.1-0.2, spatial sparsity:0.1-0.3), the TVP-SV-VAR model was superior with smaller fitting residuals and standard errors of parameter estimation than those of the tvvarGAM model. In contrast, the tvvarGAM model was preferable when the spatio-temporal variation increased (time delay coefficient: 0.2-0.3, spatial sparsity: 0.6-0.9). CONCLUSION: This study emphasized the importance of considering spatio-temporal variations when selecting appropriate models for infectious disease surveillance. By incorporating our novel indicators-the time delay coefficient and spatial sparsity-into the model selection process, the study could enhance the accuracy and effectiveness of infectious disease monitoring efforts. This approach was not only valuable in the context of this study, but also has broader implications for improving time-varying MTS analyses in various applications.

Utilization of novel molecular multiplex methods for the detection and, epidemiological surveillance of dengue virus serotypes and chikungunya virus in Burkina Faso, West Africa.

BACKGROUND: Dengue virus (DENV) and Chikungunya virus (CHIKV) are major arboviruses that are transmitted to humans by Aedes aegypti (A. aegypti) and Aedes Albopictus (A. Albopictus) mosquitoes. In absence of specific antivirals and vaccine against these two viruses, prompt diagnosis of acute infections and robust surveillance for outbreak identification remain crucial. Therefore, rapid, robust, high-throughput, accessible, and low-cost assays are essential for endemic countries. This study evaluated our recently developed multiplex RT-PCR and RT-qPCR assays to screen for DENV1-4 and CHIKV circulation in Burkina Faso. METHODS AND RESULTS: This study, conducted between June to August 2023, enrolled patients with suspected arbovirus infection presenting at healthcare facilities in three Burkina Faso cities (Bobo-Dioulasso, Houndé, and Ouagadougou). Serum samples were collected and screened for DENV serotypes and CHIKV using our newly multiplex RT-PCR and RT-q PCR techniques recently developed. A total of 408 patients (age median = 33, range from 3 to 84 years) participated in this study. Of these, 13.7% (56/408) had DENV infection; DENV-1 was 32.1% (18/56) and DENV-3 was 67.9% (38/56). DENV-2, DENV-4 and CHIKV were not detected. CONCLUSIONS: This study demonstrates the effectiveness of our molecular methods for DENV detection and serotyping in Burkina Faso. The affordability of our methods makes them valuable for implementing widespread routine clinical diagnostics or arbovirus surveillance in resource-limited settings.

Epidemiological trends in viral meningitis in England: Prospective national surveillance, 2013-2023.

BACKGROUND: In the conjugate vaccine era, viruses are the most common cause of meningitis. Here, we evaluated epidemiological trends in laboratory-confirmed viral meningitis across all age-groups over an 11-year period in England. METHODS: In England, hospital laboratories routinely report laboratory-confirmed infections electronically to the UK Health Security Agency. Records of positive viral detections in cerebrospinal fluid during 2013-2023 were extracted. Incidence rates with confidence intervals were calculated using mid-year resident population estimates. RESULTS: There were 22,114 laboratory-confirmed viral meningitis cases, including 15,299 cases during 2013-19 (pre COVID-19), with a gradual increase in incidence from 3.5/100,00 (95%CI: 3.3-3.6) to 3.9/100,000 (95%CI: 3.6-4.1). During 2020-21 when pandemic restrictions were in place, there were 2061 cases (1.8/100,000; 1.7-1.9), which increased to 4754 (4.2/100,000; 4.0-4.3) during 2022-23 (post pandemic restrictions). Infants aged <3 months accounted for 39.4% (8702/22,048) of all cases, with a stable incidence 2013-19 (504/100,000, 95%CI: 491-517), followed by a significant decline during 2020-21 (204/100,000; 188-221) and then an increase during 2022-23 (780/100,000; 749-812), with enteroviruses being the commonest cause (84.9%, 7387/8702; 424.74/100,000; 95%CI: 415.12-434.51), followed by parechoviruses (9.1%, 792/8702; 45.54/100,000; 95%CI: 42.42-48.82) and herpes simplex virus (4.4%, 380/8702; 21.85/100,000; 95%CI: 19.71-24.16). Pandemic restrictions were associated with significant declines in the incidence of enterovirus (77.7%) and parechoviruses (64% lower), with rebounds after societal restrictions were lifted. CONCLUSIONS: Rates of viral meningitis have returned to pre-pandemic levels since societal restrictions were lifted. The highest incidence of viral meningitis remains in infants aged <3 months and most commonly due to enteroviral infection.

Establishing a surveillance programme for Salmonella Dublin in Austrian dairy herds by comparing herd-level vs. individual animal detection methods.

Due to its increasing occurrence in cattle farms in various countries, leading to significant economic losses in affected livestock, Salmonella enterica subspecies enterica serovar Dublin (S. Dublin) has become a highly investigated pathogen in cattle production. In Austria, there have been occasional human cases of S. Dublin as well as an increase in laboratory-confirmed cases in cattle, indicating the need for a screening programme to determine the current status in Austria. The aims of this study were, firstly, to determine the seroprevalence of S. Dublin in dairy herds through bulk milk screenings in two federal states (Salzburg, Tyrol) of Austria. Secondly, the study aimed to identify the infection status of the herds through individual animal and herd level detection, comparing microbiological, molecular and serological detection methods. The results of the study will allow the development of a sampling strategy for a surveillance programme in Austria. A total of 6973 dairy farms were tested through serological bulk milk screening. The seroprevalence for the federal state of Tyrol was 14.8 % and for Salzburg it was 18.2 %, resulting in an average seroprevalence of 16.5 %. At an individual animal level, 205 (11.3 %) animals tested positive for shedding of S. Dublin in the faeces through microbiological detection, and 268 (17.0 %) animals had positive values (ct value ≤ 38) by qPCR. The association between microbiological and molecular detection was statistically significant (p < 0.001), with a calculated kappa value of 0.65 ± 0.27 (p ≤ 0.001), assuming a substantial level of agreement. In 17 herds, where an individual animal tested positive for shedding of S. Dublin, environmental sampling and testing were carried out. At a herd level 16 (94.1 %) out of the 17 participating herds, tested positive for S. Dublin either microbiologically or by molecular assay in boot swab samples. Bulk milk samples from 14 out of the 17 participating herds were analysed for antibodies to S. Dublin and 12 samples (85.7 %) were positive. In total 111 (18.9 %) out of 587 blood samples tested positive for S. Dublin antibodies, demonstrating a statistically significant correlation (p < 0.001) both with microbiological (κ = 0.32 ± 0.49; p ≤ 0.001) and molecular (κ=0.23 ± 0.06; p ≤ 0.001) findings. It was possible to identify S. Dublin by culture from boot swabs in 14 (82.4 %) out of 17 herds and by molecular assay using qPCR in 15 (88.2 %) out of 17 herds, indicating a suitable sample type for screening on a herd level-basis for acute infections, but not for identifying chronic infections or asymptomatic carriers. Other environmental samples, such as sponge-sticks, are only suitable to a limited extent for the detection of S. Dublin. The results of this study demonstrate a moderate S. Dublin prevalence in dairy herds in the selected Austrian regions, signalling further screening and management programmes for the future.

Development and implementation of a core genome multilocus sequence typing scheme for Yersinia enterocolitica: a tool for surveillance and outbreak detection.

Yersinia enterocolitica (Y. enterocolitica) is the most frequent etiological agent of yersiniosis and has been responsible for several national outbreaks in Norway and elsewhere. A standardized high-resolution method, such as core genome Multilocus Sequence Typing (cgMLST), is needed for pathogen traceability at the national and international levels. In this study, we developed and implemented a cgMLST scheme for Y. enterocolitica. We designed a cgMLST scheme in SeqSphere + using high-quality genomes from different Y. enterocolitica biotype sublineages. The scheme was validated if more than 95% of targets were found across all tested Y. enterocolitica: 563 Norwegian genomes collected between 2012 and 2022 and 327 genomes from public data sets. We applied the scheme to known outbreaks to establish a threshold for identifying major complex types (CTs) based on the number of allelic differences. The final cgMLST scheme included 2,582 genes with a median of 97.9% (interquartile range 97.6%-98.8%) targets found across all tested genomes. Analysis of outbreaks identified all outbreak strains using single linkage clustering at four allelic differences. This threshold identified 311 unique CTs in Norway, of which CT18, CT12, and CT5 were identified as the most frequently associated with outbreaks. The cgMLST scheme showed a very good performance in typing Y. enterocolitica using diverse data sources and was able to identify outbreak clusters. We recommend the implementation of this scheme nationally and internationally to facilitate Y. enterocolitica surveillance and improve outbreak response in national and cross-border outbreaks.

First detection of multiple cases related to CV-A16 strain of B1c clade in Beijing in 2022.

Coxsackievirus A16 (CV-A16) is a significant etiologic agent of hand, foot, and mouth disease (HFMD) and herpangina (HA), with the capacity to progress to severe complications, including encephalitis, aseptic meningitis, acute flaccid paralysis, myocarditis, and other critical conditions. Beijing's epidemiological surveillance system, established in 2008, encompasses 29 hospitals and 16 district disease control centers. From 2019 to 2021, the circulation of CV-A16 was characterized by the co-circulation of B1a and B1b clades. Multiple cases of HFMD linked to clade B1c has not been reported in Beijing until 2022. This study enrolled 400 HFMD and 493 HA cases. Employing real-time RT-PCR, 368 enterovirus-positive cases were identified, with 180 selected for sequencing. CV-A16 was detected in 18.89% (34/180) of the cases, second only to CV-A6, identified in 63.33% (114/180). Full-length VP1 gene sequences were successfully amplified and sequenced in 22 cases, revealing the presence of clades B1a, B1b, and B1c in 14, 3, and 5 cases, respectively. A cluster of five B1c clade cases occurred between June 29 and July 17, 2022, within a 7-km diameter region in Shunyi District. Phylogenetic analysis of five complete VP1 gene sequences and two full-genome sequences revealed close clustering with the 2018 Indian strain (GenBank accession: MH780757.1) within the B1c India branch, with NCBI BLAST results showing over 98% similarity. Comparative sequence analysis identified three unique amino acid variations (P3S, V25A, and I235V). The 2022 Shunyi District HFMD cases represent the first instances of spatiotemporally correlated CV-A16 B1c clade infections in Beijing, underscoring the necessity for heightened surveillance of B1c clade CV-A16 in HFMD and HA in this region.

Global contribution of statistical control charts to epidemiology monitoring: A 23-year analysis with optimized EWMA real-life application on COVID-19.

Control charts help epidemiologists and healthcare professionals monitor disease incidence and prevalence in real time, preventing outbreaks and health emergencies. However, there remains a notable gap in the comprehensive exploration and application of these techniques, particularly in the context of monitoring and managing disease outbreaks. This study analyses and categorizes worldwide control chart applications from 2000 to 2023 in outbreak monitoring in over 20 countries, focusing on corona-virus (COVID-19), and chooses optimal control charts for monitoring US COVID-19 death waves from February 2020 to December 2023. The systematic literature review analyzes available 35 articles, categorizing data by year, variable, country, study type, and chart design. A selected optimal chart is applied to monitor COVID-19 death patterns and waves in the USA. Control chart adoption in epidemiology monitoring increased during the COVID-19 pandemic, with annual patterns showing a rise in 2021 to 2023 (18%, 36%, 41%). Important variables from 2000 to 2019 include influenza counts, Salmonella cases, and infection rates, while COVID-19 studies focus more on cases, infection rates, symptoms, and deaths. Among 22 countries, the USA (29%) is the top applier of control charts. The monitoring of USA COVID-19 deaths reveals 8 waves with varying severity  >  >  >  >  >  >  > . The associated with the JN.1 variant, highlights ongoing challenges. This study emphasizes the significance of control charts in outbreak monitoring for early disease diagnosis and intervention. Control charts help healthcare workers manage epidemics using data-driven methods, improving public health. COVID-19 mortality analysis emphasizes their importance, encouraging worldwide use.