Assessment of the integrated disease surveillance and response system implementation in health zones at risk for viral hemorrhagic fever outbreaks in North Kivu, Democratic Republic of the Congo, following a major Ebola outbreak, 2021.

BACKGROUND: The Democratic Republic of the Congo (DRC) experienced its largest Ebola Virus Disease Outbreak in 2018-2020. As a result of the outbreak, significant funding and international support were provided to Eastern DRC to improve disease surveillance. The Integrated Disease Surveillance and Response (IDSR) strategy has been used in the DRC as a framework to strengthen public health surveillance, and full implementation could be critical as the DRC continues to face threats of various epidemic-prone diseases. In 2021, the DRC initiated an IDSR assessment in North Kivu province to assess the capabilities of the public health system to detect and respond to new public health threats. METHODS: The study utilized a mixed-methods design consisting of quantitative and qualitative methods. Quantitative assessment of the performance in IDSR core functions was conducted at multiple levels of the tiered health system through a standardized questionnaire and analysis of health data. Qualitative data were also collected through observations, focus groups and open-ended questions. Data were collected at the North Kivu provincial public health office, five health zones, 66 healthcare facilities, and from community health workers in 15 health areas. RESULTS: Thirty-six percent of health facilities had no case definition documents and 53% had no blank case reporting forms, limiting identification and reporting. Data completeness and timeliness among health facilities were 53% and 75% overall but varied widely by health zone. While these indicators seemingly improved at the health zone level at 100% and 97% respectively, the health facility data feeding into the reporting structure were inconsistent. The use of electronic Integrated Disease Surveillance and Response is not widely implemented. Rapid response teams were generally available, but functionality was low with lack of guidance documents and long response times. CONCLUSION: Support is needed at the lower levels of the public health system and to address specific zones with low performance. Limitations in materials, resources for communication and transportation, and workforce training continue to be challenges. This assessment highlights the need to move from outbreak-focused support and funding to building systems that can improve the long-term functionality of the routine disease surveillance system.

Detection of SARS-CoV-2 RNA in wastewater from an enclosed college campus serves as an early warning surveillance system.

SARS-CoV-2, the causative agent of Covid-19, is shed from infected persons in respiratory droplets, feces, and urine. Using quantitative PCR (qPCR), our group hypothesized that we could detect SARS-CoV-2 in wastewater samples collected on a university campus prior to the detection of the virus in individuals on campus. Wastewater samples were collected 3 times a week from 5 locations on the main campus of the University of North Carolina Wilmington (UNCW) from July 24, 2020 to December 21, 2020. Post-collection, total RNA was extracted and SARS-CoV-2 RNA in the samples was detected by qPCR. SARS-CoV-2 signal was detected on campus beginning on August 19 as classes began and the signal increased in both intensity and breadth as the Fall semester progressed. A comparison of two RNA extraction methods from wastewater showed that SARS-CoV-2 was detected more frequently on filter samples versus the direct extracts. Aligning our wastewater data with the reported SARS-CoV-2 cases on the campus Covid-19 dashboard showed the virus signal was routinely detected in the wastewater prior to clusters of individual cases being reported. These data support the testing of wastewater for the presence of SARS-CoV-2 and may be used as part of a surveillance program for detecting the virus in a community prior to an outbreak occurring and could ultimately be incorporated with other SARS-CoV-2 metrics to better inform public health enabling a quick response to contain or mitigating spread of the virus.

Effectiveness of Public Health Digital Surveillance Systems for Infectious Disease Prevention and Control at Mass Gatherings: Systematic Review.

BACKGROUND: Mass gatherings (MGs; eg, religious, sporting, musical, sociocultural, and other occasions that draw large crowds) pose public health challenges and concerns related to global health. A leading global concern regarding MGs is the possible importation and exportation of infectious diseases as they spread from the attendees to the general population, resulting in epidemic outbreaks. Governments and health authorities use technological interventions to support public health surveillance and prevent and control infectious diseases. OBJECTIVE: This study aims to review the evidence on the effectiveness of public health digital surveillance systems for infectious disease prevention and control at MG events. METHODS: A systematic literature search was conducted in January 2022 using the Ovid MEDLINE, Embase, CINAHL, and Scopus databases to examine relevant articles published in English up to January 2022. Interventional studies describing or evaluating the effectiveness of public health digital surveillance systems for infectious disease prevention and control at MGs were included in the analysis. Owing to the lack of appraisal tools for interventional studies describing and evaluating public health digital surveillance systems at MGs, a critical appraisal tool was developed and used to assess the quality of the included studies. RESULTS: In total, 8 articles were included in the review, and 3 types of MGs were identified: religious (the Hajj and Prayagraj Kumbh), sporting (the Olympic and Paralympic Games, the Federation International Football Association World Cup, and the Micronesian Games), and cultural (the Festival of Pacific Arts) events. In total, 88% (7/8) of the studies described surveillance systems implemented at MG events, and 12% (1/8) of the studies described and evaluated an enhanced surveillance system that was implemented for an event. In total, 4 studies reported the implementation of a surveillance system: 2 (50%) described the enhancement of the system that was implemented for an event, 1 (25%) reported a pilot implementation of a surveillance system, and 1 (25%) reported an evaluation of an enhanced system. The types of systems investigated were 2 syndromic, 1 participatory, 1 syndromic and event-based, 1 indicator- and event-based, and 1 event-based surveillance system. In total, 62% (5/8) of the studies reported timeliness as an outcome generated after implementing or enhancing the system without measuring its effectiveness. Only 12% (1/8) of the studies followed the Centers for Disease Control and Prevention guidelines for evaluating public health surveillance systems and the outcomes of enhanced systems based on the systems' attributes to measure their effectiveness. CONCLUSIONS: On the basis of the review of the literature and the analysis of the included studies, there is limited evidence of the effectiveness of public health digital surveillance systems for infectious disease prevention and control at MGs because of the absence of evaluation studies.

States' Methods for Capturing and Reporting Local Responses to Suspected Nonfatal Drug Overdoses.

This study examines the available data used to surveil state-level drug overdoses and characterizes them based on their timeliness, drug involvement, and specification of nonfatal outcomes.

Surveillance of communicable diseases using social media: A systematic review.

BACKGROUND: Communicable diseases pose a severe threat to public health and economic growth. The traditional methods that are used for public health surveillance, however, involve many drawbacks, such as being labor intensive to operate and resulting in a lag between data collection and reporting. To effectively address the limitations of these traditional methods and to mitigate the adverse effects of these diseases, a proactive and real-time public health surveillance system is needed. Previous studies have indicated the usefulness of performing text mining on social media. OBJECTIVE: To conduct a systematic review of the literature that used textual content published to social media for the purpose of the surveillance and prediction of communicable diseases. METHODOLOGY: Broad search queries were formulated and performed in four databases. Both journal articles and conference materials were included. The quality of the studies, operationalized as reliability and validity, was assessed. This qualitative systematic review was guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. RESULTS: Twenty-three publications were included in this systematic review. All studies reported positive results for using textual social media content to surveille communicable diseases. Most studies used Twitter as a source for these data. Influenza was studied most frequently, while other communicable diseases received far less attention. Journal articles had a higher quality (reliability and validity) than conference papers. However, studies often failed to provide important information about procedures and implementation. CONCLUSION: Text mining of health-related content published on social media can serve as a novel and powerful tool for the automated, real-time, and remote monitoring of public health and for the surveillance and prediction of communicable diseases in particular. This tool can address limitations related to traditional surveillance methods, and it has the potential to supplement traditional methods for public health surveillance.

Innovations in Public Health Surveillance for Emerging Infections.

Public health surveillance is defined as the ongoing, systematic collection, analysis, and interpretation of health data and is closely integrated with the timely dissemination of information that the public needs to know and upon which the public should act. Public health surveillance is central to modern public health practice by contributing data and information usually through a national notifiable disease reporting system (NNDRS). Although early identification and prediction of future disease trends may be technically feasible, more work is needed to improve accuracy so that policy makers can use these predictions to guide prevention and control efforts. In this article, we review the advantages and limitations of the current NNDRS in most countries, discuss some lessons learned about prevention and control from the first wave of COVID-19, and describe some technological innovations in public health surveillance, including geographic information systems (GIS), spatial modeling, artificial intelligence, information technology, data science, and the digital twin method. We conclude that the technology-driven innovative public health surveillance systems are expected to further improve the timeliness, completeness, and accuracy of case reporting during outbreaks and also enhance feedback and transparency, whereby all stakeholders should receive actionable information on control and be able to limit disease risk earlier than ever before.

Análise espacial de casos prováveis de dengue no município de São Luís, Maranhão, Brasil / Spatial analysis of probable dengue cases in the municipality of São Luís, Maranhão, Brazil / Análisis espacial de los casos probables de dengue en el municipio de São Luís, Maranhão, Brasil

INTRODUÇÃO: A dengue é considerada uma das principais arboviroses mundiais, caracterizada no Brasil pelo aumento de casos graves e óbitos. OBJETIVO: realizar análise espacial dos casos prováveis de dengue em São Luís - MA. MÉTODOS: Estudo ecológico de base populacional dos casos prováveis de dengue, notificados no Sistema de Informação de Agravos de Notificação (SINAN) em 2015 e 2016, ocorridos no município de São Luís ­ MA. Foram georreferenciados 4.681 casos prováveis de dengue por setores censitários, calculadas as taxas de incidência e ajustadas através do estimador bayesiano empírico local. Foi utilizado o estimador de densidade de Kernel e Moran Global e Local para a análise espacial. RESULTADOS: Evidenciou-se através do estimador de densidade de Kernel, áreas quentes (alta-densidade) nos setores censitários da região noroeste do município. As taxas de incidência foram ajustadas pela aplicação do método bayesiano empírico local, identificando-se maior quantidade de setores com média e alta incidência. A partir do índice de Moran global foi evidenciada autocorrelação espacial positiva estatisticamente significativa para as taxas de incidência de dengue (I=0,69; p<0,001) e para as taxas de incidência ajustadas pelo método bayesiano (I=0,80; p<0,001). De acordo com o índice de Moran local, identificou-se clusters de setores de alta incidência de dengue em áreas com alta densidade populacional na região nordeste e noroeste do município. CONCLUSÃO: A pesquisa demonstrou que os estimadores bayesianos ajudaram a minimizar os problemas de subnotificação e da influência do tamanho populacional nos setores censitários.

INTRODUCTION: Dengue is considered one of the main arboviruses in the world, characterized in Brazil by the increase in severe cases and deaths. OBJECTIVE: to perform spatial analysis of probable dengue cases in São Luís - MA. METHODS: Population-based ecological study of probable dengue cases, reported in the Notifiable Diseases Information System (SINAN) in 2015 and 2016, which took place in the city of São Luís - MA. 4,681 probable dengue cases were georeferenced by census sectors, incidence rates were calculated and adjusted using the local empirical Bayesian estimator. The Kernel and Moran Global and Local density estimator was used for spatial analysis. RESULTS: Hot areas (high-density) in the census sectors of the northwest region of the municipality were evidenced through the Kernel density estimator. Incidence rates were adjusted by applying the local empirical Bayesian method, identifying a greater number of sectors with medium and high incidence. From the global Moran index, statistically significant positive spatial autocorrelation was evidenced for the dengue incidence rates (I = 0.69; p <0.001) and for the incidence rates adjusted by the Bayesian method (I = 0.80; p <0.001). According to the local Moran index, clusters of sectors with a high incidence of dengue were identified in areas with high population density in the northeast and northwest regions of the municipality. CONCLUSION: The research demonstrated that Bayesian estimators helped to minimize the problems of underreporting and the influence of population size on census tracts.

INTRODUCCIÓN: El dengue es considerado una de las principales arbovirosis a nivel mundial, caracterizada en Brasil por el aumento de casos graves y muertes. OBJETIVO: Realizar un análisis espacial de los casos probables de dengue en São Luís - MA. MÉTODOS: Estudio ecológico de base poblacional de los casos probables de dengue, notificados en el Sistema de Informação de Agravos de Notificação (SINAN) en 2015 y 2016, ocurridos en el municipio de São Luís - MA. Se georreferenciaron 4.681 casos probables de dengue por sectores censales, se calcularon las tasas de incidencia y se ajustaron mediante el estimador empírico bayesiano local. Para el análisis espacial se utilizó el estimador de densidad Kernel y Moran global y local. RESULTADOS: Se evidenció a través del estimador de densidad Kernel, áreas calientes (de alta densidad) en los sectores censales de la región noroeste del municipio. Las tasas de incidencia se ajustaron mediante la aplicación del método bayesiano empírico local, identificándose una mayor cantidad de setores con incidencia media y alta. A partir del índice global de Moran se evidenció una autocorrelación espacial positiva estadísticamente significativa para las tasas de incidencia de dengue (I=0,69; p<0,001) y para las tasas de incidencia ajustadas por el método bayesiano (I=0,80; p<0,001). Según el índice local de Moran, se identificaron clusters de sectores de alta incidencia de dengue en áreas con alta densidad de población en las regiones noreste y noroeste del municipio. CONCLUSIÓN: La investigación demostró que los estimadores bayesianos ayudaron a minimizar los problemas de infradeclaración y la influencia del tamaño de la población en los sectores censales.

The COVID-19 Dashboard for Real-time Tracking of the Pandemic: The Lasker-Bloomberg Public Service Award.

In this Viewpoint, Lauren Gardner, winner of the 2022 Lasker-Bloomberg Public Service Award for creating the COVID-19 Dashboard, discusses the development of the Dashboard and the factors that contributed to its success.

Establishing event-based surveillance system in Nigeria: a complementary information generating platform for improved public health performance, 2016.

Introduction: event-based surveillance (EBS) is a surveillance method involving systematic and prompt data collection on incidents of public health importance, and complements the current indicator-based surveillance system and the Integrated Disease Surveillance and Response System (IDSR). It also promotes a rapid assessment and response to public health emergencies in Nigeria, although there is a lack of information regarding the status of EBS among Public Health Stakeholders in Nigeria; hence our study aimed to assess the awareness, availability, and utility of EBS among Nigerian public health stakeholders. Methods: we conducted a cross-sectional study to assess the awareness, availability, functionality, and utilization of EBS in the 36 States in Nigeria, plus the Federal Capital Territory (FCT). We interviewed 53 stakeholders in disease surveillance and response using a self-administered, semi-structured questionnaire to obtain responses on the awareness of the event-based surveillance system, availability, and functionality. We also assessed the common structures used to report health-related events and the availability of minimum requirements for an event-based surveillance system. We performed descriptive statistics for the data obtained. Results: the majority of respondents were males and 37.7% were disease surveillance and notification officers (DSNOs). Awareness of EBS was poor with about half, 49% of the respondents reported hearing of EBS, but only 17% described it correctly. The overall level of availability of the EBS reporting structure was inadequate, 28.2% and poorly utilised in the States. Conclusion: the awareness, availability, and utilization of event-based surveillance systems are low in Nigeria. The government should improve the feasibility and utility of EBS in the States to enhance early disease detection and response.

Overlapping Delta and Omicron Outbreaks During the COVID-19 Pandemic: Dynamic Panel Data Estimates.

BACKGROUND: The Omicron variant of SARS-CoV-2 is more transmissible than prior variants of concern (VOCs). It has caused the largest outbreaks in the pandemic, with increases in mortality and hospitalizations. Early data on the spread of Omicron were captured in countries with relatively low case counts, so it was unclear how the arrival of Omicron would impact the trajectory of the pandemic in countries already experiencing high levels of community transmission of Delta. OBJECTIVE: The objective of this study is to quantify and explain the impact of Omicron on pandemic trajectories and how they differ between countries that were or were not in a Delta outbreak at the time Omicron occurred. METHODS: We used SARS-CoV-2 surveillance and genetic sequence data to classify countries into 2 groups: those that were in a Delta outbreak (defined by at least 10 novel daily transmissions per 100,000 population) when Omicron was first sequenced in the country and those that were not. We used trend analysis, survival curves, and dynamic panel regression models to compare outbreaks in the 2 groups over the period from November 1, 2021, to February 11, 2022. We summarized the outbreaks in terms of their peak rate of SARS-CoV-2 infections and the duration of time the outbreaks took to reach the peak rate. RESULTS: Countries that were already in an outbreak with predominantly Delta lineages when Omicron arrived took longer to reach their peak rate and saw greater than a twofold increase (2.04) in the average apex of the Omicron outbreak compared to countries that were not yet in an outbreak. CONCLUSIONS: These results suggest that high community transmission of Delta at the time of the first detection of Omicron was not protective, but rather preluded larger outbreaks in those countries. Outbreak status may reflect a generally susceptible population, due to overlapping factors, including climate, policy, and individual behavior. In the absence of strong mitigation measures, arrival of a new, more transmissible variant in these countries is therefore more likely to lead to larger outbreaks. Alternately, countries with enhanced surveillance programs and incentives may be more likely to both exist in an outbreak status and detect more cases during an outbreak, resulting in a spurious relationship. Either way, these data argue against herd immunity mitigating future outbreaks with variants that have undergone significant antigenic shifts.

Syndromic Surveillance Systems for Mass Gatherings: A Scoping Review.

Syndromic surveillance involves the near-real-time collection of data from a potential multitude of sources to detect outbreaks of disease or adverse health events earlier than traditional forms of public health surveillance. The purpose of the present study is to elucidate the role of syndromic surveillance during mass gathering scenarios. In the present review, the use of syndromic surveillance for mass gathering scenarios is described, including characteristics such as methodologies of data collection and analysis, degree of preparation and collaboration, and the degree to which prior surveillance infrastructure is utilized. Nineteen publications were included for data extraction. The most common data source for the included syndromic surveillance systems was emergency departments, with first aid stations and event-based clinics also present. Data were often collected using custom reporting forms. While syndromic surveillance can potentially serve as a method of informing public health policy regarding specific mass gatherings based on the profile of syndromes ascertained, the present review does not indicate that this form of surveillance is a reliable method of detecting potentially critical public health events during mass gathering scenarios.

Intervención sanitaria con candidatos vacunales, como estrategia temporal de enfrentamiento a la COVID-19, Cuba, 2021 / Health intervention with vaccine candidates as a temporary strategy to confront COVID-19, Cuba, 2021

Introducción: El Sistema de Vigilancia en Salud, informó en diciembre de 2019, sobre casos con neumonía en la ciudad de Wuhan, en China. La nueva enfermedad, ocasionada por el SARS-CoV-2, se nombró COVID-19. El 11 de marzo del 2020 se diagnosticaron en Cuba los tres primeros casos importados. La introducción paulatina de diferentes variantes virales ocasionó varios brotes. Se hizo necesario buscar alternativas que permitieran lograr el control epidemiológico. Objetivo: Desarrollar una intervención sanitaria efectiva con candidatos vacunales dirigida a revertir la situación epidemiológica ocasionada por la epidemia de la COVID-19 en Cuba en el periodo de enero a agosto de 2021. Métodos: Se realizó un estudio cualitativo de investigación-acción en tres etapas, con la aplicación de grupos de discusión que aportaron información para la organización del proceso y la toma de decisiones. Además, se apoyó en el estudio descriptivo longitudinal para el análisis de datos epidemiológicos a partir de las series cronológicas, que permitió valorar la efectividad de la intervención. El periodo de estudio abarcó desde enero a agosto del 2021. Resultados: El estudio situacional de salud evidenció el nivel de complejidad de la situación epidemiológica y el contexto social y económico prevaleciente. A partir de sus resultados se diseñó e implementó el proyecto de intervención, con las condiciones de factibilidad requeridas. La implementación de la intervención arrojó resultados favorables logrando vacunar al 99,16 por ciento de la población prevista, con la consiguiente reducción en la incidencia de casos al alcanzar coberturas de vacuna del 63,2 por ciento, el 36 por ciento y el 50,9 por ciento en las provincias de La Habana, Matanzas y Santiago de Cuba, respectivamente. Conclusiones: La intervención sanitaria, de carácter temporal, efectuada con los candidatos vacunales Soberana 02 y Abdala, pautó un modo de actuación que se extendió más allá de la propia intervención, al aportar soluciones culturales, gerenciales, metodológicas, educativas, de capacitación en buenas prácticas, intersectorialidad, participación social y manejo del liderazgo, que representan productos extendidos a los servicios de salud(AU)

Introduction: The Health Surveillance System reported in December 2019 cases with pneumonia in the city of Wuhan, China. The new disease, caused by SARS-CoV-2, was named COVID-19. On March 11, 2020, the first three imported cases were diagnosed in Cuba. The gradual introduction of different viral variants caused several outbreaks. It became necessary to look for alternatives that would allow epidemiological control to be achieved. Objective: Develop an effective health intervention with vaccine candidates aimed at reversing the epidemiological situation caused by the COVID-19 epidemic in Cuba during the period from January to August 2021. Methods: A qualitative action research study was carried out in three stages, with the application of debate groups that provided information for the organization of the process and decision making. In addition, it was based on the longitudinal descriptive study for the analysis of epidemiological data from the time series, which allowed to assess the effectiveness of the intervention. The study period spanned from January to August 2021. Results: The situational health study showed the level of complexity of the epidemiological situation and the prevailing social and economic context. Based on its results, the intervention project was designed and implemented, with the required feasibility conditions. The implementation of the intervention yielded favorable results, managing to vaccinate 99.16percent of the planned population, with the consequent reduction in the incidence of cases by reaching vaccine coverage of 63.2percent, 36percentnd 50.9percent in the provinces of Havana, Matanzas and Santiago de Cuba, respectively. Conclusions: The health intervention, of a temporary nature, carried out with the vaccine candidates Soberana 02 and Abdala outlined a mode of action that extended beyond the intervention itself, by providing cultural, managerial, methodological, educational solutions, training in good practices, intersectorality, social participation and leadership management, which represent products extended to health services(AU)

Acidentes e plantas hospedeiras associadas a lagartas urticantes / Accidents and host plants associated with urticant caterpillars / Accidentes y plantas hospedadoras asociadas a orugasurticantes

Introdução: Ambientes urbanos como áreas verdes, praças, parques e escolas estão se tornando cada vez mais propícios ao aparecimento de animais peçonhentos, dentre eles as lagartas urticantes. Acidentes com algumas lagartas urticantes podem ser graves, podendo leva ao óbito, como no caso do gênero Lonomia.Objetivo:descrever o perfil epidemiológico dos acidentes envolvendo lagartas urticantes no município de Chapecó, Santa Catarina e identificar espécies vegetais hospedeiras destas lagartas.Metodologia:Foram coletados os dados epidemiológicos dos acidentes com lagartas urticantes registrados no período entre 2016 e 2017. Os dados foram obtidos junto ao Sistema de Informação de Agravos de Notificação.Foram analisadas as variáveis sexo, idade, parte do corpo acometida, os meses que houve as notificações, a ocupação dos indivíduos que tiveram contato com a lagarta, local em que residem, escolaridade e a espécie da lagarta envolvida. Ainda, foram identificados os espécimes coletados pelo setor de Vigilância em Saúde Ambiental, bem como foram identificadas as plantas hospedeira sem que foram encontrados.Resultados:Foram registrados 377 acidentes envolvendo majoritariamente o sexo feminino e a faixa etária entre 20 a 49 anos.As partes do corpo mais acometidas foram o pé (17,0%), mão (12,9%) e cabeça (11,4%). Foram identificadas seis espécies de plantas associadas à ocorrência de lagartas urticantes Conclusões:O estudo contribui com informações epidemiológicas sobre os acidentes causados por lepidópteros em um município de grande porte. Ressalta-se, a importância de ampliar as pesquisas em relação às plantas hospedeiras e a divulgação dos resultados visando a prevenção de acidentes (AU).

Introduction:Urban environments such as green areas, squares, parks and schools are becoming more and more favorableto the appearance of venomous animals, including urticatingcaterpillars. Accidents with some stinging caterpillars can be serious and can lead to death, as in the case of the genus Lonomia. Objective:to describe the epidemiological profile of accidents involving stinging caterpillars in the municipality of Chapecó, Santa Catarina and to identify host plant species of these caterpillars. Methodology:Epidemiological data on stinging caterpillar accidents recorded in the period between 2016 and 2017were collected. The data were obtained from the Sistema de Informação de Agravos de Notificação. The variables sex, age, body part affected, the months of the notifications, the occupation of the individuals who had contact with the caterpillar, the place where they live, education and the species of the caterpillar involved were analyzed. Still, the specimens collected by the Environmental Health Surveillance sector were identified, as well as the host plants in which they were found. Results:There were 377 accidents involving mostly females and the age group between 20 and 49 years. The parts of the body most affected were the foot (17.0%), hand (12.9%) and head (11.4%). Six species of plants were identified associated with the occurrence of stinging caterpillars.Conclusions:The study contributes with epidemiological information on accidents caused by Lepidoptera in a large municipality. The importance of expanding research in relation to host plants and the dissemination of results aimed at preventing accidents are emphasized (AU).

Introducción: Los entornos urbanos como áreas verdes, plazas, parques y escuelas son cada vez más propicios para la aparición de animales venenosos, incluidas las orugas urticantes. Los accidentes con algunas orugas pueden ser graves y provocar la muerte, como en el caso del género Lonomia.Objetivo: describir el perfil epidemiológico de los accidentes por orugasurticantes en el municipio de Chapecó, Santa Catarina e identificar especies de plantas hospedadoras de estas orugas.Metodología: Se recolectaron datos epidemiológicos sobre accidentes de orugas urticantes registrados en el período entre 2016 y 2017. Los datos se obtuvieron del Sistema de Informação de Agravos de Notificação(SINAN). Se analizaron las variables sexo, edad, parte del cuerpo afectada, los meses delas notificaciones, la ocupación de los individuos que tuvieron contacto con lasorugas, el lugar donde viven, educación y la especie de oruga involucrada. Aún así, se identificaron los especímenes recolectados por el sector de Vigilancia de Salud Ambiental, así como las plantas hospedantes en las que se encontraron.Resultados: Se produjeron 377 accidentes que afectaron en su mayoría a mujeres y al grupo de edad entre 20 y 49 años. Las partes del cuerpo más afectadas fueron el pie (17,0%), mano (12,9%) y cabeza (11,4%).Se identificaron seis especies de plantas asociadas con la ocurrencia de orugas urticantes.Conclusiones: El estudio presentainformación epidemiológica sobre accidentes causados por lepidópteros en un municipio de gran tamaño. Se destacala importancia de ampliar la investigación en relación con las plantas hospedantes y la difusión de resultados orientados a la prevención delosaccidentes (AU).

Surveillance of COVID-19 Vaccination in Nursing Homes, United States, December 2020-July 2021.

Monitoring COVID-19 vaccination coverage among nursing home residents and staff is important to ensure high coverage rates and guide patient-safety policies. With the termination of the federal Pharmacy Partnership for Long-Term Care Program, another source of facility-based vaccination data is needed. We compared numbers of COVID-19 vaccinations administered to nursing home residents and staff reported by pharmacies participating in the temporary federal Pharmacy Partnership for Long-Term Care Program with the numbers of COVID-19 vaccinations reported by nursing homes participating in new COVID-19 vaccination modules of the Centers for Disease Control and Prevention's National Healthcare Safety Network (NHSN). Pearson correlation coefficients comparing the number vaccinated between the 2 approaches were 0.89, 0.96, and 0.97 for residents and 0.74, 0.90, and 0.90 for staff, in the weeks ending January 3, 10, and 17, 2021, respectively. Based on subsequent NHSN reporting, vaccination coverage with ≥1 vaccine dose reached 73.7% for residents and 47.6% for staff the week ending January 31 and increased incrementally through July 2021. Continued monitoring of COVID-19 vaccination coverage is important as new nursing home residents are admitted, new staff are hired, and additional doses of vaccine are recommended.

The Partial Least Squares Spline Model for Public Health Surveillance Data.

Factor discovery of public health surveillance data is a crucial problem and extremely challenging from a scientific viewpoint with enormous applications in research studies. In this study, the main focus is to introduce the improved survival regression technique in the presence of multicollinearity, and hence, the partial least squares spline modeling approach is proposed. The proposed method is compared with the benchmark partial least squares Cox regression model in terms of accuracy based on the Akaike information criterion. Further, the optimal model is practiced on a real data set of infant mortality obtained from the Pakistan Demographic and Health Survey. This model is implemented to assess the significant risk factors of infant mortality. The recommended features contain key information about infant survival and could be useful in public health surveillance-related research.

A distribution-free control charting technique based on change-point analysis for detection of epidemics.

Worldwide, the detection of epidemics has been recognized as a continuing problem of crucial importance to public health surveillance. Various approaches for detecting and quantifying epidemics of infectious diseases in the recent literature are directly influenced by methods of Statistical Process Control (SPC). However, implementing SPC quality tools directly to the general health care monitoring problem, in a similar manner as in industrial quality control, is not feasible since many assumptions such as stationarity, known asymptotic distribution etc. are not met. Toward this end, in this paper, some of the open statistical research issues involved in this field are discussed, and a distribution-free control charting technique based on change-point analysis is applied and evaluated for detection of epidemics. The main tool in this methodology is the detection of unusual trends, in the sense that the beginning of an unusual trend marks a switch from a control state to an epidemic state. The in-control and out-of-control performance of the adapted control scheme from SPC is thoroughly investigated using Monte Carlo simulations, and the applied scheme is found to outperform its parametric and nonparametric competitors in many cases. Moreover, the empirical comparative study provides evidence that the adapted change-point detection scheme has several appealing properties compared to the current practice for detection of epidemics.

Genomic Surveillance for SARS-CoV-2 Variants: Predominance of the Delta (B.1.617.2) and Omicron (B.1.1.529) Variants - United States, June 2021-January 2022.

Genomic surveillance is a critical tool for tracking emerging variants of SARS-CoV-2 (the virus that causes COVID-19), which can exhibit characteristics that potentially affect public health and clinical interventions, including increased transmissibility, illness severity, and capacity for immune escape. During June 2021-January 2022, CDC expanded genomic surveillance data sources to incorporate sequence data from public repositories to produce weighted estimates of variant proportions at the jurisdiction level and refined analytic methods to enhance the timeliness and accuracy of national and regional variant proportion estimates. These changes also allowed for more comprehensive variant proportion estimation at the jurisdictional level (i.e., U.S. state, district, territory, and freely associated state). The data in this report are a summary of findings of recent proportions of circulating variants that are updated weekly on CDC's COVID Data Tracker website to enable timely public health action.† The SARS-CoV-2 Delta (B.1.617.2 and AY sublineages) variant rose from 1% to >50% of viral lineages circulating nationally during 8 weeks, from May 1-June 26, 2021. Delta-associated infections remained predominant until being rapidly overtaken by infections associated with the Omicron (B.1.1.529 and BA sublineages) variant in December 2021, when Omicron increased from 1% to >50% of circulating viral lineages during a 2-week period. As of the week ending January 22, 2022, Omicron was estimated to account for 99.2% (95% CI = 99.0%-99.5%) of SARS-CoV-2 infections nationwide, and Delta for 0.7% (95% CI = 0.5%-1.0%). The dynamic landscape of SARS-CoV-2 variants in 2021, including Delta- and Omicron-driven resurgences of SARS-CoV-2 transmission across the United States, underscores the importance of robust genomic surveillance efforts to inform public health planning and practice.