The Role of Nursing Homes in the Spread of Antimicrobial Resistance Over the Healthcare Network.

OBJECTIVE Recerntly, the role of the healthcare network, defined as a set of hospitals linked by patient transfers, has been increasingly considered in the control of antimicrobial resistance. Here, we investigate the potential impact of nursing homes on the spread of antimicrobial-resistant pathogens across the healthcare network and its importance for control strategies. METHODS Based on patient transfer data, we designed a network model representing the Dutch healthcare system of hospitals and nursing homes. We simulated the spread of an antimicrobial-resistant pathogen across the healthcare network, and we modeled transmission within institutions using a stochastic susceptible-infected-susceptible (SIS) epidemic model. Transmission between institutions followed transfers. We identified the contribution of nursing homes to the dispersal of the pathogen by comparing simulations of the network with and without nursing homes. RESULTS Our results strongly suggest that nursing homes in the Netherlands have the potential to drive and sustain epidemics across the healthcare network. Even when the daily probability of transmission in nursing homes is much lower than in hospitals, transmission of resistance can be more effective because of the much longer length of stay of patients in nursing homes. CONCLUSIONS If an antimicrobial-resistant pathogen emerges that spreads easily within nursing homes, control efforts aimed at hospitals may no longer be effective in preventing nationwide outbreaks. It is important to consider nursing homes in planning regional and national infection control and in implementing surveillance systems that monitor the spread of antimicrobial resistance. Infect Control Hosp Epidemiol 2016;37:761-767.

Driving factors of influenza transmission in the Netherlands.

Influenza epidemics in temperate regions show a characteristic seasonal pattern with peak incidence occurring in winter. Previous research has shown that low absolute humidity and school holidays can both affect influenza transmission. During an epidemic, transmission is strongly influenced by the depletion of susceptibles (i.e., increase in the number of those immune). To assess how much variability in influenza transmission intensity is due to each of these driving factors, we used a long time series of the number of weekly visits to general practitioners for influenzalike illness in the Netherlands from 1970-2011 and transformed this into a time series of weekly influenza reproduction numbers, which are a measure of transmission intensity. We used statistical regression techniques to quantify how the reproduction numbers were affected by each driving factor. We found a clear ranking of importance of driving factors in explaining the variation in transmission intensity. Most of the variation (30%) was explained by the depletion of susceptibles during the season, 27% was explained by between-season effects, and 3% was explained by absolute humidity. School holidays at the Christmas period did not have a statistically significant effect on influenza transmission. Although the influence of absolute humidity was small, its seasonal fluctuations may determine when sustained influenza transmission is possible and may thus drive influenza seasonality.

A model-based assessment of oseltamivir prophylaxis strategies to prevent influenza in nursing homes.

Prophylaxis with neuraminidase inhibitors is important for controlling seasonal influenza outbreaks in long-term care settings. We used a stochastic individual-based model that simulates influenza virus transmission in a long-term care nursing home department to study the protection offered to patients by different strategies of prophylaxis with oseltamivir and determined the effect of emerging resistance. Without resistance, postexposure and continuous prophylaxis reduced the patient infection attack rate from 0.19 to 0.13 (relative risk [RR] 0.67) and 0.05 (RR 0.23), respectively. Postexposure prophylaxis prevented more infections per dose (118 and 323 daily doses needed to prevent 1 infection, respectively) and required fewer doses per season than continuous prophylaxis. If resistance to oseltamivir was increased, both prophylaxis strategies became less efficacious and efficient, but postexposure prophylaxis posed a lower selection pressure for resistant virus strains. Extension of prophylaxis to healthcare workers offered little additional protection to patients.

The effects of influenza vaccination of health care workers in nursing homes: insights from a mathematical model.

BACKGROUND: Annual influenza vaccination of institutional health care workers (HCWs) is advised in most Western countries, but adherence to this recommendation is generally low. Although protective effects of this intervention for nursing home patients have been demonstrated in some clinical trials, the exact relationship between increased vaccine uptake among HCWs and protection of patients remains unknown owing to variations between study designs, settings, intensity of influenza seasons, and failure to control all effect modifiers. Therefore, we use a mathematical model to estimate the effects of HCW vaccination in different scenarios and to identify a herd immunity threshold in a nursing home department. METHODS AND FINDINGS: We use a stochastic individual-based model with discrete time intervals to simulate influenza virus transmission in a 30-bed long-term care nursing home department. We simulate different levels of HCW vaccine uptake and study the effect on influenza virus attack rates among patients for different institutional and seasonal scenarios. Our model reveals a robust linear relationship between the number of HCWs vaccinated and the expected number of influenza virus infections among patients. In a realistic scenario, approximately 60% of influenza virus infections among patients can be prevented when the HCW vaccination rate increases from 0 to 1. A threshold for herd immunity is not detected. Due to stochastic variations, the differences in patient attack rates between departments are high and large outbreaks can occur for every level of HCW vaccine uptake. CONCLUSIONS: The absence of herd immunity in nursing homes implies that vaccination of every additional HCW protects an additional fraction of patients. Because of large stochastic variations, results of small-sized clinical trials on the effects of HCW vaccination should be interpreted with great care. Moreover, the large variations in attack rates should be taken into account when designing future studies.

When three is not a crowd: a Crossregulation model of the dynamics and repertoire selection of regulatory CD4+ T cells.

Regulatory CD4(+) T cells, enriched in the CD25 pool of healthy individuals, mediate natural tolerance and prevent autoimmune diseases. Despite their fundamental and potential clinical significance, regulatory T (T(R)) cells have not yet been incorporated in a coherent theory of the immune system. This article reviews experimental evidence and theoretical arguments supporting a model of T(R) cell dynamics, uncovering some of its most relevant biological implications. According to this model, the persistence and expansion of T(R) cell populations depend strictly on specific interactions they make with antigen-presenting cells (APCs) and conventional effector T (T(E)) cells. This three-partner crossregulation imposes that T(R) cells feed on the specific autoimmune activities they suppress, with implications ranging from their interactions with other cells to their repertoire selection in the periphery and in the thymus, and to the relationship between these cells and the innate immune system. These implications stem from the basic prediction that the peripheral dynamics sort the CD4(+) T-cell repertoire into two subsets: a less diverse set of small clones of autoreactive effector and regulatory cells that regulate each other's growth, and a more diverse set of barely autoreactive T(E) cell clones, whose expansion is limited only by APC availability. It is argued that such partitioning of the repertoire sets the ground for self-non-self discrimination.

The effects of age, thymectomy, and HIV Infection on alpha and beta TCR excision circles in naive T cells.

Due to homeostasis total naive T cell numbers remain fairly constant over life despite a gradual involution of the thymus. The contribution of the thymus to maintaining naive T cell pools is typically measured with TCR excision circles (TRECs) that are formed in thymocytes. The mechanisms underlying thymic involution are poorly understood. Some data suggest that thymocytes undergo fewer divisions in old (small) than young (large) thymi, and other data suggest that the number of TRECs per thymocyte is independent of age. If thymic involution were associated with a decreased number of divisions of the thymocytes, this would markedly complicate the interpretation of TREC data. To study this we develop a mathematical model in which the division rate of thymocytes decreases with increasing age. We describe the dilution of TRECs formed during the arrangement of both chains of the TCR by division of thymocytes, recent thymic emigrants, and mature naive T cells. The model behavior is complicated as TREC contents in naive T cells can increase with age due to decreased dilution in the thymus. Because our model is consistent with current data on the effects of age and thymectomy on TRECs in peripheral T cells, we conclude that aging may well affect thymocyte division, which markedly complicates the interpretation of TREC data. It is possible, but more difficult, to let the model be consistent with the rapid changes in alpha and beta TRECs observed shortly after HIV infection.