Concept: Infectious diseases
- Proceedings of the National Academy of Sciences of the United States of America
- Published over 2 years ago
The spatiotemporal evolution of human mobility and the related fluctuations of population density are known to be key drivers of the dynamics of infectious disease outbreaks. These factors are particularly relevant in the case of mass gatherings, which may act as hotspots of disease transmission and spread. Understanding these dynamics, however, is usually limited by the lack of accurate data, especially in developing countries. Mobile phone call data provide a new, first-order source of information that allows the tracking of the evolution of mobility fluxes with high resolution in space and time. Here, we analyze a dataset of mobile phone records of ∼150,000 users in Senegal to extract human mobility fluxes and directly incorporate them into a spatially explicit, dynamic epidemiological framework. Our model, which also takes into account other drivers of disease transmission such as rainfall, is applied to the 2005 cholera outbreak in Senegal, which totaled more than 30,000 reported cases. Our findings highlight the major influence that a mass gathering, which took place during the initial phase of the outbreak, had on the course of the epidemic. Such an effect could not be explained by classic, static approaches describing human mobility. Model results also show how concentrated efforts toward disease control in a transmission hotspot could have an important effect on the large-scale progression of an outbreak.
Candida aurisis an emerging multidrug-resistant pathogen that can be difficult to identify using traditional biochemical methods. C. auris is capable of causing invasive fungal infections, particularly among hospitalized patients with significant medical comorbidities. Echinocandins are the empiric drugs of choice for C. auris, although not all isolates are susceptible and resistance may develop on therapy. Nosocomial C. auris outbreaks have been reported in a number of countries and aggressive infection control measures are paramount to stopping transmission.
Treating hospital patient textiles with ionic silver after each washing results in a significant decrease in microbial contamination. Although further study is needed to better understand the role textiles play in hospital-acquired infections and to quantify the influence of silver textile treatment on health care-associated infection risk and patient outcomes, ionic silver treatment of textiles may prove useful in hospital-acquired infection reduction strategies.
How social structures, space, and behaviors shape the spread of infectious diseases using chikungunya as a case study
- Proceedings of the National Academy of Sciences of the United States of America
- Published about 2 years ago
Whether an individual becomes infected in an infectious disease outbreak depends on many interconnected risk factors, which may relate to characteristics of the individual (e.g., age, sex), his or her close relatives (e.g., household members), or the wider community. Studies monitoring individuals in households or schools have helped elucidate the determinants of transmission in small social structures due to advances in statistical modeling; but such an approach has so far largely failed to consider individuals in the wider context they live in. Here, we used an outbreak of chikungunya in a rural community in Bangladesh as a case study to obtain a more comprehensive characterization of risk factors in disease spread. We developed Bayesian data augmentation approaches to account for uncertainty in the source of infection, recall uncertainty, and unobserved infection dates. We found that the probability of chikungunya transmission was 12% [95% credible interval (CI): 8-17%] between household members but dropped to 0.3% for those living 50 m away (95% CI: 0.2-0.5%). Overall, the mean transmission distance was 95 m (95% CI: 77-113 m). Females were 1.5 times more likely to become infected than males (95% CI: 1.2-1.8), which was virtually identical to the relative risk of being at home estimated from an independent human movement study in the country. Reported daily use of antimosquito coils had no detectable impact on transmission. This study shows how the complex interplay between the characteristics of an individual and his or her close and wider environment contributes to the shaping of infectious disease epidemics.
Perceived social support has been hypothesized to protect against the pathogenic effects of stress. How such protection might be conferred, however, is not well understood. Using a sample of 404 healthy adults, we examined the roles of perceived social support and received hugs in buffering against interpersonal stress-induced susceptibility to infectious disease. Perceived support was assessed by questionnaire, and daily interpersonal conflict and receipt of hugs were assessed by telephone interviews on 14 consecutive evenings. Subsequently, participants were exposed to a virus that causes a common cold and were monitored in quarantine to assess infection and illness signs. Perceived support protected against the rise in infection risk associated with increasing frequency of conflict. A similar stress-buffering effect emerged for hugging, which explained 32% of the attenuating effect of support. Among infected participants, greater perceived support and more-frequent hugs each predicted less-severe illness signs. These data suggest that hugging may effectively convey social support.
Generalist microorganisms are the agents of many emerging infectious diseases (EIDs), but their natural life cycles are difficult to predict due to the multiplicity of potential hosts and environmental reservoirs. Among 250 known human EIDs, many have been traced to tropical rain forests and specifically freshwater aquatic systems, which act as an interface between microbe-rich sediments or substrates and terrestrial habitats. Along with the rapid urbanization of developing countries, population encroachment, deforestation, and land-use modifications are expected to increase the risk of EID outbreaks. We show that the freshwater food-web collapse driven by land-use change has a nonlinear effect on the abundance of preferential hosts of a generalist bacterial pathogen, Mycobacterium ulcerans. This leads to an increase of the pathogen within systems at certain levels of environmental disturbance. The complex link between aquatic, terrestrial, and EID processes highlights the potential importance of species community composition and structure and species life history traits in disease risk estimation and mapping. Mechanisms such as the one shown here are also central in predicting how human-induced environmental change, for example, deforestation and changes in land use, may drive emergence.
Infection may modify the behaviour of the host and of its conspecifics in a group, potentially altering social connectivity. Because many infectious diseases are transmitted through social contact, social connectivity changes can impact transmission dynamics. Previous approaches to understanding disease transmission dynamics in wild populations were limited in their ability to disentangle different factors that determine the outcome of disease outbreaks. Here we ask how social connectivity is affected by infection and how this relationship impacts disease transmission dynamics. We experimentally manipulated disease status of wild house mice using an immune challenge and monitored social interactions within this free-living population before and after manipulation using automated tracking. The immune-challenged animals showed reduced connectivity to their social groups, which happened as a function of their own behaviour, rather than through conspecific avoidance. We incorporated these disease-induced changes of social connectivity among individuals into models of disease outbreaks over the empirically-derived networks. The models revealed that changes in host behaviour frequently resulted in the disease being contained to very few animals, as opposed to becoming widespread. Our results highlight the importance of considering the role that behavioural alterations during infection can have on social dynamics when evaluating the potential for disease outbreaks.
Infectious diseases remain one of the most important causes of fever of unexplained origin (FUO). We review the spectrum of infectious diseases in the different clinical situations of patients with FUO, namely in classical FUO, in patients with HIV infection, in health care-associated or nosocomial FUO, and in immunocompromised patients with FUO. The most important question is which clinical features make a specific disease a candidate to cause FUO.
Cholera and many waterborne diseases exhibit multiple characteristic timescales or pathways of infection, which can be modeled as direct and indirect transmission. A major public health issue for waterborne diseases involves understanding the modes of transmission in order to improve control and prevention strategies. An important epidemiological question is: given data for an outbreak, can we determine the role and relative importance of direct vs. environmental/waterborne routes of transmission? We examine whether parameters for a differential equation model of waterborne disease transmission dynamics can be identified, both in the ideal setting of noise-free data (structural identifiability), as well as in the more realistic setting in the presence of noise (practical identifiability). We used a differential algebra approach together with several numerical approaches, with a particular emphasis on identifiability of the transmission rates. To examine these issues in a practical public health context, we apply the model to a recent cholera outbreak in Angola (2006). Our results show that the model parameters-including both water and person-to-person transmission routes-are globally structurally identifiable, although they become unidentifiable when the environmental transmission timescale is fast. Even for water dynamics within the identifiable range, when noisy data are considered, only a combination of the water transmission parameters can practically be estimated. This makes the waterborne transmission parameters difficult to estimate, leading to inaccurate estimates of important epidemiological parameters such as the basic reproduction number (R(0)). However, measurements of pathogen persistence time in environmental water sources or measurements of pathogen concentration in the water can improve model identifiability and allow for more accurate estimation of waterborne transmission pathway parameters as well as R(0). Parameter estimates for the Angola outbreak suggest that both transmission pathways are needed to explain the observed cholera dynamics. These results highlight the importance of incorporating environmental data when examining waterborne disease.
Ventilator-associated pneumonia (VAP) is the most frequent cause of death among the nosocomial infections acquired in the ICU. Routine surveillance endotracheal aspirate (ETA) cultures in patients on mechanical ventilation have been proposed to predict the cause of VAP. Our aim is to review the available experience regarding the role of surveillance ETA cultures in guiding VAP antimicrobial therapy.