Mapping the Distribution of Anthrax in Mainland China, 2005–2013

BackgroundAnthrax, a global re-emerging zoonotic disease in recent years is enzootic in mainland China. Despite its significance to the public health, spatiotemporal distributions of the disease in human and livestock and its potential driving factors remain poorly understood.Conclusions/SignificanceAnthrax in China was characterized by significant seasonality and spatial clustering. The spatial distribution of human anthrax was largely driven by livestock husbandry, human density, land cover, elevation, topsoil features and climate. Enhanced surveillance and intervention for livestock and human anthrax in the high-risk regions, particularly on the Qinghai-Tibetan Plateau, is the key to the prevention of human infections.     

Serotypes and Clonal Diversity of Streptococcus pneumoniae Causing Invasive Disease in the Era of PCV13 in Catalonia,Spain

The aim of this study was to study the serotypes and clonal diversity of pneumococci causing invasive pneumococcal disease in Catalonia, Spain, in the era of 13-valent pneumococcal conjugate vaccine (PCV13). In our region, this vaccine is only available in the private market and it is estimated a PCV13 vaccine coverage around 55% in children. A total of 1551 pneumococcal invasive isolates received between 2010 and 2013 in the Molecular Microbiology Department at Hospital Sant Joan de Déu, Barcelona, were included. Fifty-two serotypes and 249 clonal types—defined by MLST—were identified. The most common serotypes were serotype 1 (n = 182; 11.7%), 3 (n = 145; 9.3%), 19A (n = 137; 8.8%) and 7F (n = 122; 7.9%). Serotype 14 was the third most frequent serotype in children < 2 years (15 of 159 isolates). PCV7 serotypes maintained their proportion along the period of study, 16.6% in 2010 to 13.4% in 2013, whereas there was a significant proportional decrease in PCV13 serotypes, 65.3% in 2010 to 48.9% in 2013 (p<0.01). This decrease was mainly attributable to serotypes 19A and 7F. Serotype 12F achieved the third position in 2013 (n = 22, 6.4%). The most frequent clonal types found were ST306 (n = 154, 9.9%), ST191 (n = 111, 7.2%), ST989 (n = 85, 5.5%) and ST180 (n = 80, 5.2%). Despite their decrease, PCV13 serotypes continue to be a major cause of disease in Spain. These results emphasize the need for complete PCV13 vaccination.     

Distribution and Diversity of Pathogenic Leptospira Species in Peri-domestic Surface Waters from South Central Chile

BackgroundLeptospirosis is a neglected zoonosis affecting animals and humans caused by infection with Leptospira. The bacteria can survive outside of hosts for long periods of time in soil and water. While identification of Leptospira species from human cases and animal reservoirs are increasingly reported, little is known about the diversity of pathogenic Leptospira species in the environment and how surveillance of the environment might be used for monitoring and controlling disease.ConclusionsThis study reports the presence of pathogenic Leptospira in the peri-domestic environment of households in three community types and the differences in Leptospira diversity at the community level. Systematic environmental surveillance of Leptospira can be used for detecting changes in pathogen diversity and to identify and monitor contaminated areas where an increased risk of human infection exists.     

Approximate parameter inference in systems biology using gradient matching: a comparative evaluation

Background

A challenging problem in current systems biology is that of parameter inference in biological pathways expressed as coupled ordinary differential equations (ODEs). Conventional methods that repeatedly numerically solve the ODEs have large associated computational costs. Aimed at reducing this cost, new concepts using gradient matching have been proposed, which bypass the need for numerical integration. This paper presents a recently established adaptive gradient matching approach, using Gaussian processes (GPs), combined with a parallel tempering scheme, and conducts a comparative evaluation with current state-of-the-art methods used for parameter inference in ODEs. Among these contemporary methods is a technique based on reproducing kernel Hilbert spaces (RKHS). This has previously shown promising results for parameter estimation, but under lax experimental settings. We look at a range of scenarios to test the robustness of this method. We also change the approach of inferring the penalty parameter from AIC to cross validation to improve the stability of the method.

Methods

Methodology for the recently proposed adaptive gradient matching method using GPs, upon which we build our new method, is provided. Details of a competing method using RKHS are also described here.

Results

We conduct a comparative analysis for the methods described in this paper, using two benchmark ODE systems. The analyses are repeated under different experimental settings, to observe the sensitivity of the techniques.

Conclusions

Our study reveals that for known noise variance, our proposed method based on GPs and parallel tempering achieves overall the best performance. When the noise variance is unknown, the RKHS method proves to be more robust.