Modelers' Perception of Mathematical Modeling in Epidemiology: A Web-Based Survey

International audienceBackground: Mathematical modeling in epidemiology (MME) is being used increasingly. However, there are many uncertainties in terms of definitions, uses and quality features of MME. Methodology/Principal Findings: To delineate the current status of these models, a 10-item questionnaire on MME was devised. Proposed via an anonymous internet-based survey, the questionnaire was completed by 189 scientists who had published in the domain of MME. A small minority (18%) of respondents claimed to have in mind a concise definition of MME. Some techniques were identified by the researchers as characterizing MME (e.g. Markov models), while others–at the same level of sophistication in terms of mathematics–were not (e.g. Cox regression). The researchers' opinions were also contrasted about the potential applications of MME, perceived as higly relevant for providing insight into complex mechanisms and less relevant for identifying causal factors. The quality criteria were those of good science and were not related to the size and the nature of the public health problems addressed. Conclusions/Significance: This study shows that perceptions on the nature, uses and quality criteria of MME are contrasted, even among the very community of published authors in this domain. Nevertheless, MME is an emerging discipline in epidemiology and this study underlines that it is associated with specific areas of application and methods. The development of this discipline is likely to deserve a framework providing recommendations and guidance at various steps of the studies, from design to report

Chryseobacterium indologenes infection in a newborn: a case report

<p>Abstract</p> <p>Introduction</p> <p><it>Chryseobacterium indologenes </it>is an uncommon human pathogen. Most infections have been detected in hospitalized patients with severe underlying diseases who had indwelling devices implanted. Infection caused by <it>C. indologenes </it>in a newborn has not been previously reported.</p> <p>Case presentation</p> <p>We present a case of ventilator-associated pneumonia caused by <it>C. indologenes </it>in a full-term Caucasian newborn baby boy with congenital heart disease who was successfully treated with piperacillin-tazobactam.</p> <p>Conclusion</p> <p><it>C. indologenes </it>should be considered as a potential pathogen in newborns in the presence of invasive equipment or treatment with long-term broad-spectrum antibiotics. Appropriate choice of effective antimicrobial agents for treatment is difficult because of the unpredictability and breadth of antimicrobial resistance of these organisms, which often involves resistance to many of the antibiotics chosen empirically for serious Gram-negative infections.</p

Erratic Flu Vaccination Emerges from Short-Sighted Behavior in Contact Networks

The effectiveness of seasonal influenza vaccination programs depends on individual-level compliance. Perceptions about risks associated with infection and vaccination can strongly influence vaccination decisions and thus the ultimate course of an epidemic. Here we investigate the interplay between contact patterns, influenza-related behavior, and disease dynamics by incorporating game theory into network models. When individuals make decisions based on past epidemics, we find that individuals with many contacts vaccinate, whereas individuals with few contacts do not. However, the threshold number of contacts above which to vaccinate is highly dependent on the overall network structure of the population and has the potential to oscillate more wildly than has been observed empirically. When we increase the number of prior seasons that individuals recall when making vaccination decisions, behavior and thus disease dynamics become less variable. For some networks, we also find that higher flu transmission rates may, counterintuitively, lead to lower (vaccine-mediated) disease prevalence. Our work demonstrates that rich and complex dynamics can result from the interaction between infectious diseases, human contact patterns, and behavior

Agrobacterium tumefaciens-Induced Bacteraemia Does Not Lead to Reporter Gene Expression in Mouse Organs

Agrobacterium tumefaciens is the main plant biotechnology gene transfer tool with host range which can be extended to non-plant eukaryotic organisms under laboratory conditions. Known medical cases of Agrobacterium species isolation from bloodstream infections necessitate the assessment of biosafety-related risks of A. tumefaciens encounters with mammalian organisms. Here, we studied the survival of A. tumefaciens in bloodstream of mice injected with bacterial cultures. Bacterial titers of 108 CFU were detected in the blood of the injected animals up to two weeks after intravenous injection. Agrobacteria carrying Cauliflower mosaic virus (CaMV) 35S promoter-based constructs and isolated from the injected mice retained their capacity to promote green fluorescent protein (GFP) synthesis in Nicotiana benthamiana leaves. To examine whether or not the injected agrobacteria are able to express in mouse organs, we used an intron-containing GFP (GFPi) reporter driven either by a cytomegalovirus (CMV) promoter or by a CaMV 35S promoter. Western and northern blot analyses as well as RT-PCR analysis of liver, spleen and lung of mice injected with A. tumefaciens detected neither GFP protein nor its transcripts. Thus, bacteraemia induced in mice by A. tumefaciens does not lead to detectible levels of genetic transformation of mouse organs

Chryseobacterium indologenes non-catheter-related bacteremia in a patient with a solid tumor

A case of non-catheter-related bacteremia caused by Chryseobacterium indologenes in a nonneutropenic man with a solid tumor is described. The patient was successfully treated with piperacillin-tazobactam

The non-linear health consequences of living in larger cities

Urbanization promotes economy, mobility, access, and availability of resources, but on the other hand, generates higher levels of pollution, violence, crime, and mental distress. The health consequences of the agglomeration of people living close together are not fully understood. Particularly, it remains unclear how variations in the population size across cities impact the health of the population. We analyze the deviations from linearity of the scaling of several health-related quantities, such as the incidence and mortality of diseases, external causes of death, wellbeing, and health care availability, in respect to the population size of cities in Brazil, Sweden, and the USA. We find that deaths by non-communicable diseases tend to be relatively less common in larger cities, whereas the per capita incidence of infectious diseases is relatively larger for increasing population size. Healthier lifestyle and availability of medical support are disproportionally higher in larger cities. The results are connected with the optimization of human and physical resources and with the non-linear effects of social networks in larger populations. An urban advantage in terms of health is not evident, and using rates as indicators to compare cities with different population sizes may be insufficien