Principais motivos de descarte de córneas para transplante na Paraíba: por que o anti-HBc merece atenção?* / Main reasons for discarding corneas for transplant in Paraíba: why does anti-HBc deserve attention?*

RESUMO Objetivo: Identificar o perfil dos doadores de tecidos oculares humanos na área de atuação do Banco de Olhos da Paraíba, destacando o impacto da sorologia positiva para hepatite B no descarte dos tecidos para transplante. Métodos: O estudo é transversal e utilizou dados do Banco de Olhos da Paraíba entre janeiro de 2013 e dezembro de 2022. Dados sobre procedência, idade, sexo, causa do óbito, tempo entre óbito e enucleação, resultados sorológicos e motivo de descarte das córneas dos doadores foram coletados. Resultados: O maior motivo de descarte foi por sorologia positiva (56,5%), sendo positivadas as sorologias positivas para hepatite B e HBsAg em 11,1% e 4,75% dos pacientes, respectivamente. Conclusão: A sorologia positiva para hepatite B como um critério de descarte absoluto é responsável por grande parcela de descartes, apesar da pouca informação sobre suas repercussões e representação de infectividade nos receptores do transplante.

ABSTRACT Objective: To identify the profile of human ocular tissue donors in the area covered by the Eye Bank of Paraíba (PB), highlighting the impact of positive serology for hepatitis B (anti-HBc) in the disposal of tissues for transplantation. Methods: This is a cross-sectional that uses data from the Eye Bank of Paraíba (PB) between January 2013 and December 2022. Data on origin, age, sex, cause of death, time between death and enucleation, serological results, and reason for discarded donor corneas were collected. Results: The main reason for discarding was due to positive serology (56.5%), with positive anti-HBc and HBsAg serology in 11.1% and 4.75% of patients, respectively. Conclusion: Anti-HBc positive serology as an absolute disposal criterion is responsible for great part of disposals, despite little information about its repercussions and representation of infectivity in transplant recipients.

The burden and dynamics of hospital-acquired SARS-CoV-2 in England.

Hospital-based transmission had a dominant role in Middle East respiratory syndrome coronavirus (MERS-CoV) and severe acute respiratory syndrome coronavirus (SARS-CoV) epidemics1,2, but large-scale studies of its role in the SARS-CoV-2 pandemic are lacking. Such transmission risks spreading the virus to the most vulnerable individuals and can have wider-scale impacts through hospital-community interactions. Using data from acute hospitals in England, we quantify within-hospital transmission, evaluate likely pathways of spread and factors associated with heightened transmission risk, and explore the wider dynamical consequences. We estimate that between June 2020 and March 2021 between 95,000 and 167,000 inpatients acquired SARS-CoV-2 in hospitals (1% to 2% of all hospital admissions in this period). Analysis of time series data provided evidence that patients who themselves acquired SARS-CoV-2 infection in hospital were the main sources of transmission to other patients. Increased transmission to inpatients was associated with hospitals having fewer single rooms and lower heated volume per bed. Moreover, we show that reducing hospital transmission could substantially enhance the efficiency of punctuated lockdown measures in suppressing community transmission. These findings reveal the previously unrecognized scale of hospital transmission, have direct implications for targeting of hospital control measures and highlight the need to design hospitals better equipped to limit the transmission of future high-consequence pathogens.

Human Fecal Carriage of Streptococcus agalactiae Sequence Type 283, Thailand.

Streptococcus agalactiae (group B Streptococcus) sequence type 283 bacteremia, found almost exclusively in Southeast Asia, is associated with consuming raw freshwater fish, but some patients deny consumption. We detected fecal carriage in 5/184 (2.7%) persons in northeast Thailand. Human carriers might contribute to transmission or be the original source of this sequence type.

A shift from travel-associated cases to autochthonous transmission with Berlin as epicentre of the monkeypox outbreak in Germany, May to June 2022.

By 22 June 2022, 521 cases of monkeypox were notified in Germany. The median age was 38 years (IQR: 32-44); all cases were men. In Berlin, where 69% of all cases occurred, almost all were men who have sex with men. Monkeypox virus likely circulated unrecognised in Berlin before early May. Since mid-May, we observed a shift from travel-associated infections to mainly autochthonous transmission that predominantly took place in Berlin, often in association with visits to clubs and parties.

IDNetwork: A deep illness-death network based on multi-state event history process for disease prognostication.

Multi-state models can capture the different patterns of disease evolution. In particular, the illness-death model is used to follow disease progression from a healthy state to an intermediate state of the disease and to a death-related final state. We aim to use those models in order to adapt treatment decisions according to the evolution of the disease. In state-of-the art methods, the risks of transition between the states are modeled via (semi-) Markov processes and transition-specific Cox proportional hazard (P.H.) models. The Cox P.H. model assumes that each variable makes a linear contribution to the model, but the relationship between covariates and risks can be more complex in clinical situations. To address this challenge, we propose a neural network architecture called illness-death network (IDNetwork) that relaxes the linear Cox P.H. assumption within an illness-death process. IDNetwork employs a multi-task architecture and uses a set of fully connected subnetworks in order to learn the probabilities of transition. Through simulations, we explore different configurations of the architecture and demonstrate the added value of our model. IDNetwork significantly improves the predictive performance compared to state-of-the-art methods on a simulated data set, on two clinical trials for patients with colon cancer and on a real-world data set in breast cancer.

Professional practice for COVID-19 risk reduction among health care workers: A cross-sectional study with matched case-control comparison.

BACKGROUND: Health care workers (HCWs) are particularly exposed to COVID-19 and therefore it is important to study preventive measures in this population. AIM: To investigate socio-demographic factors and professional practice associated with the risk of COVID-19 among HCWs in health establishments in Normandy, France. METHODS: A cross-sectional and 3 case-control studies using bootstrap methods were conducted in order to explore the possible risk factors that lead to SARS-CoV2 transmission within HCWs. Case-control studies focused on risk factors associated with (a) care of COVID-19 patients, (b) care of non COVID-19 patients and (c) contacts between colleagues. PARTICIPANTS: 2,058 respondents, respectively 1,363 (66.2%) and 695 (33.8%) in medical and medico-social establishments, including HCW with and without contact with patients. RESULTS: 301 participants (14.6%) reported having been infected by SARS-CoV2. When caring for COVID-19 patients, HCWs who declared wearing respirators, either for all patient care (ORa 0.39; 95% CI: 0.29-0.51) or only when exposed to aerosol-generating procedures (ORa 0.56; 95% CI: 0.43-0.70), had a lower risk of infection compared with HCWs who declared wearing mainly surgical masks. During care of non COVID-19 patients, wearing mainly a respirator was associated with a higher risk of infection (ORa 1.84; 95% CI: 1.06-3.37). An increased risk was also found for HCWs who changed uniform in workplace changing rooms (ORa 1.93; 95% CI: 1.63-2.29). CONCLUSION: Correct use of PPE adapted to the situation and risk level is essential in protecting HCWs against infection.

3D modelling and simulation of the dispersion of droplets and drops carrying the SARS-CoV-2 virus in a railway transport coach.

Computational fluid dynamics (CFD) modelling and 3D simulations of the air flow and dispersion of droplets or drops in semi-confined ventilated spaces have found topical applications with the unfortunate development of the Covid-19 pandemic. As an illustration of this scenario, we have considered the specific situation of a railroad coach containing a seated passenger infected with the SARS-CoV-2 virus (and not wearing a face mask) who, by breathing and coughing, releases droplets and drops that contain the virus and that present aerodynamic diameters between 1 and 1000 µm. The air flow is generated by the ventilation in the rail coach. While essentially 3D, the flow is directed from the bottom to the top of the carriage and comprises large to small eddies visualised by means of streamlines. The space and time distribution of the droplets and drops is computed using both an Eulerian model and a Lagrangian model. The results of the two modelling approaches are fully consistent and clearly illustrate the different behaviours of the drops, which fall down close to the infected passenger, and the droplets, which are carried along with the air flow and invade a large portion of the rail coach. This outcome is physically sound and demonstrates the relevance of CFD for simulating the transport and dispersion of droplets and drops with any diameter in enclosed ventilated spaces. As coughing produces drops and breathing produces droplets, both modes of transmission of the SARS-CoV-2 virus in human secretions have been accounted for in our 3D numerical study. Beyond the specific, practical application of the rail coach, this study offers a much broader scope by demonstrating the feasibility and usefulness of 3D numerical simulations based on CFD. As a matter of fact, the same computational approach that has been implemented in our study can be applied to a huge variety of ventilated indoor environments such as restaurants, performance halls, classrooms and open-plan offices in order to evaluate if their occupation could be critical with respect to the transmission of the SARS-CoV-2 virus or to other airborne respiratory infectious agents, thereby enabling relevant recommendations to be made.

Detecting Selection in the HIV-1 Genome during Sexual Transmission Events.

Little is known about whether and how variation in the HIV-1 genome affects its transmissibility. Assessing which genomic features of HIV-1 are under positive or negative selection during transmission is challenging, because very few virus particles are typically transmitted, and random genetic drift can dilute genetic signals in the recipient virus population. We analyzed 30 transmitter-recipient pairs from the Zurich Primary HIV Infection Study and the Swiss HIV Cohort Study using near full-length HIV-1 genomes. We developed a new statistical test to detect selection during transmission, called Selection Test in Transmission (SeTesT), based on comparing the transmitter and recipient virus population and accounting for the transmission bottleneck. We performed extensive simulations and found that sensitivity of detecting selection during transmission is limited by the strong population bottleneck of few transmitted virions. When pooling individual test results across patients, we found two candidate HIV-1 genomic features for affecting transmission, namely amino acid positions 3 and 18 of Vpu, which were significant before but not after correction for multiple testing. In summary, SeTesT provides a general framework for detecting selection based on genomic sequencing data of transmitted viruses. Our study shows that a higher number of transmitter-recipient pairs is required to improve sensitivity of detecting selection.

Neonatal Outcomes of Pregnant Women With Confirmed Coronavirus Disease 2019: One-Year Experience of a Tertiary Care Center.

The coronavirus disease 2019 (COVID-19) pandemic became an important public health problem affecting all age groups. The aim of this study was to evaluate clinical and laboratory findings of newborns born to mothers with COVID-19. Thirty pregnant women with COVID-19 were admitted to Turgut Ozal University Hospital for delivery. Fourteen pregnant women had at least one symptom associated with COVID-19. Positive polymerase chain reaction (PCR) results were seen in only 3 (9.7%) of 31 newborns. A statistically significant difference was observed between PCR-positive and PCR-negative newborns in terms of any adverse pregnancy outcomes. Neonatal lymphocyte count and partial arterial oxygen pressure were significantly lower in the PCR-positive group. Results were also compared according to the interval from the maternal diagnosis time to delivery. Hemoglobin and hematocrit levels in newborns born to mothers diagnosed more than 7 days before delivery were significantly lower. Neonates born to mothers with COVID-19 had mild clinical symptoms and favorable outcomes.

Dos males o menor: representações de universitários sobre o uso das máscaras para prevenção da Covid-19 / The lesser evil: university students representations on the use of masks for Covid-19 prevention / El mal menor: representaciones de universitarios sobre el uso de máscaras para la prevención del Covid-19

Objetivo: conhecer as representações sociais de universitários brasileiros sobre o uso de máscaras para o controle da COVID-19. Método: estudo qualitativo, tipo survey, ancorado na Teoria das Representações Sociais. Participaram 283 universitários brasileiros, selecionados por conveniência. Os dados foram coletados por meio de formulário digital. Para análise, utilizou-se a Análise Temática. Resultados: elaborou-se um tema nomeado "A máscara para prevenção: materialização do medo de contágio", e três subtemas, intitulados respectivamente "A construção de um novo hábito: o mal necessário das máscaras"; "O macrossocial na modificação do eu" e "O uso da máscara no dia-a-dia: a individualização do social". Conclusão: observou-se a compreensão do uso de máscaras como um recurso para prevenção de uma condição ameaçadora à vida. Atitudes favoráveis parecem se organizar em contraposição ao medo causado pelo vírus e suas consequências.

Objective: to know the social representations of brazilian university students about the use of masks to control COVID-19. Method: qualitative survey, based on the Theory of Social Representations. 283 brazilian university students were selected by convenience. Data were collected through digital form. For analysis, the Thematic Analysis was used. Results: a theme named "The mask for prevention: materialization of the fear of contagion" was elaborated, and three sub-themes, respectively titled "The construction of a new habit: the necessary evil of masks"; "The macrosocial in the modification of the self" and "The use of the mask in everyday life: the individualization of the social". Conclusion: the understanding of the use of masks as a resource for preventing a life-threatening condition was observed. These favorable attitudes seem to be organized in contrast to the fear caused by virus and their consequences.

Objetivo: conocer las representaciones sociales de estudiantes universitarios brasileños sobre el uso de máscaras para el control de COVID-19. Método: estudio cualitativo, basado en la Teoría de las Representaciones Sociales. Participaron 283 universitarios brasileños, seleccionados por conveniencia. Los datos fueron recolectados a través de un formulario digital. Para el análisis se utilizó el Análisis Temático. Resultados: se elaboró un tema denominado "La mascarilla para la prevención: materialización del miedo al contagio" y tres subtemas, respectivamente titulados "La construcción de un nuevo hábito: el mal necesario de las máscaras"; "Lo macrosocial en la modificación del yo" y "El uso de la mascarilla en la vida cotidiana: la individualización de lo social". Conclusión: se observó la comprensión del uso de máscaras como recurso para la prevención de una condición potencialmente mortal. Estas actitudes favorables parecen organizarse en contraste con el miedo provocado por el virus y sus consecuencias.

Predicting regional COVID-19 hospital admissions in Sweden using mobility data.

The transmission of COVID-19 is dependent on social mixing, the basic rate of which varies with sociodemographic, cultural, and geographic factors. Alterations in social mixing and subsequent changes in transmission dynamics eventually affect hospital admissions. We employ these observations to model and predict regional hospital admissions in Sweden during the COVID-19 pandemic. We use an SEIR-model for each region in Sweden in which the social mixing is assumed to depend on mobility data from public transport utilisation and locations for mobile phone usage. The results show that the model could capture the timing of the first and beginning of the second wave of the pandemic 3 weeks in advance without any additional assumptions about seasonality. Further, we show that for two major regions of Sweden, models with public transport data outperform models using mobile phone usage. We conclude that a model based on routinely collected mobility data makes it possible to predict future hospital admissions for COVID-19 3 weeks in advance.

Modelling COVID-19 transmission in a hemodialysis centre using simulation generated contacts matrices.

The COVID-19 pandemic has been particularly threatening to patients with end-stage kidney disease (ESKD) on intermittent hemodialysis and their care providers. Hemodialysis patients who receive life-sustaining medical therapy in healthcare settings, face unique challenges as they need to be at a dialysis unit three or more times a week, where they are confined to specific settings and tended to by dialysis nurses and staff with physical interaction and in close proximity. Despite the importance and critical situation of the dialysis units, modelling studies of the SARS-CoV-2 spread in these settings are very limited. In this paper, we have used a combination of discrete event and agent-based simulation models, to study the operations of a typical large dialysis unit and generate contact matrices to examine outbreak scenarios. We present the details of the contact matrix generation process and demonstrate how the simulation calculates a micro-scale contact matrix comprising the number and duration of contacts at a micro-scale time step. We have used the contacts matrix in an agent-based model to predict disease transmission under different scenarios. The results show that micro-simulation can be used to estimate contact matrices, which can be used effectively for disease modelling in dialysis and similar settings.

COVID-19 Seropositive Rates between the Waves, Israel.

BACKGROUND: Israel has experienced three waves of coronavirus disease-2019 (COVID-19) infection since late February 2020, with lockdown and other measures employed to contain infection rates. In cooperation with the Israel Ministry of Health, serological testing was conducted by all four health maintenance organizations (HMO) in order to estimate national infection rates and the proportion of previously undetected disease. OBJECTIVES: To estimate the proportion of the population that was seropositive, identify factors associated with seropositive outcome, and approximate the proportion of residents that were asymptomatic. METHODS: Seroconversion rates (IgG) were measured in a representative sample of over 17,000 members of Maccabi Healthcare Services. Direct standardization was used to estimate the seropositive rates for COVID-19 infection for members of the HMO. Rates were adjusted for sensitivity and specificity of the testing products used. In addition to blood sampling, respondents were asked to complete a digital survey regarding potential exposures and symptoms experienced. RESULTS: It was estimated that 1.9% of the adult HMO population was seropositive 4 months after the first infected person was identified in the country. Seroconversion was associated with travel abroad and exposure to infected individuals. Loss of smell and taste, fever, cough, and fatigue are associated with infection. Of those found to be seropositive for COVID-19, 160 (59%) had a prior negative polymerase chain reaction (PCR) or no PCR test at all. CONCLUSIONS: Adult seropositive rates of infection were low relative to other countries. The findings suggest that early initiatives to limit infection entry and spread were effective.

Optimal Allocation of Vaccine and Antiviral Drugs for Influenza Containment over Delayed Multiscale Epidemic Model considering Time-Dependent Transmission Rate.

In this study, two types of epidemiological models called "within host" and "between hosts" have been studied. The within-host model represents the innate immune response, and the between-hosts model signifies the SEIR (susceptible, exposed, infected, and recovered) epidemic model. The major contribution of this paper is to break the chain of infectious disease transmission by reducing the number of susceptible and infected people via transferring them to the recovered people group with vaccination and antiviral treatment, respectively. Both transfers are considered with time delay. In the first step, optimal control theory is applied to calculate the optimal final time to control the disease within a host's body with a cost function. To this end, the vaccination that represents the effort that converts healthy cells into resistant-to-infection cells in the susceptible individual's body is used as the first control input to vaccinate the susceptible individual against the disease. Moreover, the next control input (antiviral treatment) is applied to eradicate the concentrations of the virus and convert healthy cells into resistant-to-infection cells simultaneously in the infected person's body to treat the infected individual. The calculated optimal time in the first step is considered as the delay of vaccination and antiviral treatment in the SEIR dynamic model. Using Pontryagin's maximum principle in the second step, an optimal control strategy is also applied to an SEIR mathematical model with a nonlinear transmission rate and time delay, which is computed as optimal time in the first step. Numerical results are consistent with the analytical ones and corroborate our theoretical results.

Surveillance for Colonization, Transmission, and Infection With Methicillin-Susceptible Staphylococcus aureus in a Neonatal Intensive Care Unit.

Importance: Staphylococcus aureus is one of the leading causes of infections in neonatal intensive care units (NICUs). Most studies in this patient group focus on methicillin-resistant S aureus or the outbreak setting, whereas data for methicillin-susceptible S aureus are limited. Objectives: To identify risk factors for S aureus colonization and infections in hospitalized newborns and to investigate S aureus transmission and its dynamics in a nonoutbreak setting. Design, Setting, and Participants: This monocentric cohort study in a tertiary NICU in Heidelberg, Germany, enrolled all hospitalized neonates (n = 590) with at least 1 nasal screening swab positive for S aureus. Data were collected from January 1, 2018, to December 31, 2019. Exposures: Weekly screening for S aureus colonization was performed for all newborns until discharge. Main Outcomes and Measures: The primary end point was any S aureus infection until hospital discharge. Transmission of S aureus and performance of routine typing to detect transmissions were defined as the secondary outcomes of the study. Results: In total, 590 newborns were enrolled (276 [46.8%] female and 314 [53.2%] male; 220 [37.3%] with birthweight <1500 g; 477 [80.8%] preterm; 449 [76.1%] singletons; 419 [71.5%] delivered via cesarean section). The median length of stay was 26 (range, 10-62) days. Overall, 135 infants (22.9%) were colonized by S aureus at some time during their hospital stay. The median time to first detection was 17 (interquartile range, 11-37) days. The overall incidence of S aureus infection was 1.7% (10 of 590). Low birth weight (<1500 g [odds ratio, 9.3; 95% CI, 5.9-14.6; P < .001]) and longer hospital stay (odds ratio, 2.3; 95% CI, 1.9-2.7; P < .001) were associated with colonization. Nasal carriage was significantly associated with S aureus infection (odds ratio, 8.2; 95% CI, 2.1-32.3; P = .002). A total of 123 of 135 colonization isolates were sequenced. All recoverable infection isolates (4 of 7) of newborns with colonization were genetically identical to the colonizing isolate. Whole-genome sequencing indicated 23 potential transmission clusters. Conclusions and Relevance: The findings of this cohort study suggest that nasal colonization is a relevant risk factor for S aureus infection in a nonoutbreak NICU setting. In colonized newborns, infection and colonization isolates were genetically identical, suggesting that eradication of colonization may be a useful measure to prevent infection. Further investigations are necessary to validate and assess the generalizability of our findings.

Emergence of universality in the transmission dynamics of COVID-19.

The complexities involved in modelling the transmission dynamics of COVID-19 has been a roadblock in achieving predictability in the spread and containment of the disease. In addition to understanding the modes of transmission, the effectiveness of the mitigation methods also needs to be built into any effective model for making such predictions. We show that such complexities can be circumvented by appealing to scaling principles which lead to the emergence of universality in the transmission dynamics of the disease. The ensuing data collapse renders the transmission dynamics largely independent of geopolitical variations, the effectiveness of various mitigation strategies, population demographics, etc. We propose a simple two-parameter model-the Blue Sky model-and show that one class of transmission dynamics can be explained by a solution that lives at the edge of a blue sky bifurcation. In addition, the data collapse leads to an enhanced degree of predictability in the disease spread for several geographical scales which can also be realized in a model-independent manner as we show using a deep neural network. The methodology adopted in this work can potentially be applied to the transmission of other infectious diseases and new universality classes may be found. The predictability in transmission dynamics and the simplicity of our methodology can help in building policies for exit strategies and mitigation methods during a pandemic.