Ticks in the wrong boxes: assessing error in blanket-drag studies due to occasional sampling

BACKGROUND The risk posed by ticks as vectors of disease is typically assessed by blanket-drag sampling of host-seeking individuals. Comparisons of peak abundance between plots - either in order to establish their relative risk or to identify environmental correlates - are often carried out by sampling on one or two occasions during the period of assumed peak tick activity. METHODS This paper simulates this practice by 're-sampling' from model datasets derived from an empirical field study. Re-sample dates for each plot are guided by either the previous year's peak at the plot, or the previous year's peak at a similar, nearby plot. Results from single, double and three-weekly sampling regimes are compared. RESULTS Sampling on single dates within a two-month window of assumed peak activity has the potential to introduce profound errors; sampling on two dates (double sampling) offers greater precision, but three-weekly sampling is the least biased. CONCLUSIONS The common practice of sampling for the abundance of host-seeking ticks on single dates in each plot-year should be strenuously avoided; it is recommended that field acarologists employ regular sampling throughout the year at intervals no greater than three weeks, for a variety of epidemiological studies

Early Prediction of Movie Box Office Success based on Wikipedia Activity Big Data

Use of socially generated "big data" to access information about collective states of the minds in human societies has become a new paradigm in the emerging field of computational social science. A natural application of this would be the prediction of the society's reaction to a new product in the sense of popularity and adoption rate. However, bridging the gap between "real time monitoring" and "early predicting" remains a big challenge. Here we report on an endeavor to build a minimalistic predictive model for the financial success of movies based on collective activity data of online users. We show that the popularity of a movie can be predicted much before its release by measuring and analyzing the activity level of editors and viewers of the corresponding entry to the movie in Wikipedia, the well-known online encyclopedia.Comment: 13 pages, Including Supporting Information, 7 Figures, Download the dataset from: http://wwm.phy.bme.hu/SupplementaryDataS1.zi

Twitter-based analysis of the dynamics of collective attention to political parties

Large-scale data from social media have a significant potential to describe complex phenomena in real world and to anticipate collective behaviors such as information spreading and social trends. One specific case of study is represented by the collective attention to the action of political parties. Not surprisingly, researchers and stakeholders tried to correlate parties' presence on social media with their performances in elections. Despite the many efforts, results are still inconclusive since this kind of data is often very noisy and significant signals could be covered by (largely unknown) statistical fluctuations. In this paper we consider the number of tweets (tweet volume) of a party as a proxy of collective attention to the party, identify the dynamics of the volume, and show that this quantity has some information on the elections outcome. We find that the distribution of the tweet volume for each party follows a log-normal distribution with a positive autocorrelation of the volume over short terms, which indicates the volume has large fluctuations of the log-normal distribution yet with a short-term tendency. Furthermore, by measuring the ratio of two consecutive daily tweet volumes, we find that the evolution of the daily volume of a party can be described by means of a geometric Brownian motion (i.e., the logarithm of the volume moves randomly with a trend). Finally, we determine the optimal period of averaging tweet volume for reducing fluctuations and extracting short-term tendencies. We conclude that the tweet volume is a good indicator of parties' success in the elections when considered over an optimal time window. Our study identifies the statistical nature of collective attention to political issues and sheds light on how to model the dynamics of collective attention in social media.Comment: 16 pages, 7 figures, 3 tables. Published in PLoS ON

Evaluation and Validation of a Real-Time PCR Assay for Detection and Quantitation of Human Adenovirus 14 from Clinical Samples

In 2007, the Centers for Disease Control and Prevention (CDC) reported that Human adenovirus type 14 (HAdV-14) infected 106 military personnel and was responsible for the death of one U.S. soldier at Lackland Air Force Base in Texas. Identification of the responsible adenovirus, which had not previously been seen in North America and for which rapid diagnostic tools were unavailable, required retrospective analysis at reference laboratories. Initial quarantine measures were also reliant on relatively slow traditional PCR analysis at other locations. To address this problem, we developed a real-time PCR assay that detects a 225 base pair sequence in the HAdV-14a hexon gene. Fifty-one oropharyngeal swab specimens from the Naval Health Research Center, San Diego, CA and Advanced Diagnostic Laboratory, Lackland AFB, TX were used to validate the new assay. The described assay detected eight of eight and 19 of 19 confirmed HAdV-14a clinical isolates in two separate cohorts from respiratory disease outbreaks. The real-time PCR assay had a wide dynamic range, detecting from 102 to 107 copies of genomic DNA per reaction. The assay did not cross-react with other adenoviruses, influenza, respiratory syncytial virus, or common respiratory tract bacteria. The described assay is easy to use, sensitive and specific for HAdV-14a in clinical throat swab specimens, and very rapid since turnaround time is less than four hours to obtain an answer

Evidence of the Importance of Host Habitat Use in Predicting the Dilution Effect of Wild Boar for Deer Exposure to Anaplasma spp

Foci of tick-borne pathogens occur at fine spatial scales, and depend upon a complex arrangement of factors involving climate, host abundance and landscape composition. It has been proposed that the presence of hosts that support tick feeding but not pathogen multiplication may dilute the transmission of the pathogen. However, models need to consider the spatial component to adequately explain how hosts, ticks and pathogens are distributed into the landscape

Using Web Search Query Data to Monitor Dengue Epidemics: A New Model for Neglected Tropical Disease Surveillance

A variety of obstacles, including bureaucracy and lack of resources, delay detection and reporting of dengue and exist in many countries where the disease is a major public health threat. Surveillance efforts have turned to modern data sources such as Internet usage data. People often seek health-related information online and it has been found that the frequency of, for example, influenza-related web searches as a whole rises as the number of people sick with influenza rises. Tools have been developed to help track influenza epidemics by finding patterns in certain web search activity. However, few have evaluated whether this approach would also be effective for other diseases, especially those that affect many people, that have severe consequences, or for which there is no vaccine. In this study, we found that aggregated, anonymized Google search query data were also capable of tracking dengue activity in Bolivia, Brazil, India, Indonesia and Singapore. Whereas traditional dengue data from official sources are often not available until after a long delay, web search query data is available for analysis within a day. Therefore, because it could potentially provide earlier warnings, these data represent a valuable complement to traditional dengue surveillance

Monitoring Influenza Activity in the United States: A Comparison of Traditional Surveillance Systems with Google Flu Trends

Google Flu Trends was developed to estimate US influenza-like illness (ILI) rates from internet searches; however ILI does not necessarily correlate with actual influenza virus infections.Influenza activity data from 2003-04 through 2007-08 were obtained from three US surveillance systems: Google Flu Trends, CDC Outpatient ILI Surveillance Network (CDC ILI Surveillance), and US Influenza Virologic Surveillance System (CDC Virus Surveillance). Pearson's correlation coefficients with 95% confidence intervals (95% CI) were calculated to compare surveillance data. An analysis was performed to investigate outlier observations and determine the extent to which they affected the correlations between surveillance data. Pearson's correlation coefficient describing Google Flu Trends and CDC Virus Surveillance over the study period was 0.72 (95% CI: 0.64, 0.79). The correlation between CDC ILI Surveillance and CDC Virus Surveillance over the same period was 0.85 (95% CI: 0.81, 0.89). Most of the outlier observations in both comparisons were from the 2003-04 influenza season. Exclusion of the outlier observations did not substantially improve the correlation between Google Flu Trends and CDC Virus Surveillance (0.82; 95% CI: 0.76, 0.87) or CDC ILI Surveillance and CDC Virus Surveillance (0.86; 95%CI: 0.82, 0.90).This analysis demonstrates that while Google Flu Trends is highly correlated with rates of ILI, it has a lower correlation with surveillance for laboratory-confirmed influenza. Most of the outlier observations occurred during the 2003-04 influenza season that was characterized by early and intense influenza activity, which potentially altered health care seeking behavior, physician testing practices, and internet search behavior

An early rise in body temperature is related to unfavorable outcome after stroke: Data from the PAIS study

Subfebrile temperature or fever is present in about a third of patients on the first day after stroke onset and is associated with poor outcome. However, the temporal profile of this association is not well established. We aimed to assess the relationship between body temperature on admission as well as the change in body temperature from admission to 24 h thereafter and functional outcome and death. We analyzed data of 1,332 patients admitted within 12 h of stroke onset. The relation between body temperature on admission or the change in body temperature from admission to 24 h thereafter (adjusted for body temperature on admission) on the one hand and unfavorable outcome (death, or a modified Rankin Scale score >2) at 3 months on the other were expressed as odds ratio per 1.0°C increase in body temperature. Adjustments for potential confounders were made with a multiple logistic regression model. No relation was found between admission body temperature and poor outcome (aOR 1.06; 95% CI 0.85-1.32) and death (aOR 1.23; 95% CI 0.95-1.60). In contrast, increased body temperature in the first 24 h after stroke onset was associated with poor outcome (aOR 1.30; 95% CI 1.05-1.63) and death (aOR 1.51; 95% CI 1.15-1.98). An early rise in body temperature rather than high body temperature on admission is a risk factor for unfavorable outcome in patients with acute stroke

Diverse tick-borne microorganisms identified in free-living ungulates in Slovakia

Background: Free-living ungulates are hosts of ixodid ticks and reservoirs of tick-borne microorganisms in central Europe and many regions around the world. Tissue samples and engorged ticks were obtained from roe deer, red deer, fallow deer, mouflon, and wild boar hunted in deciduous forests of south-western Slovakia. DNA isolated from these samples was screened for the presence of tick-borne microorganisms by PCR-based methods. Results: Ticks were found to infest all examined ungulate species. The principal infesting tick was Ixodes ricinus, identified on 90.4% of wildlife, and included all developmental stages. Larvae and nymphs of Haemaphysalis concinna were feeding on 9.6% of wildlife. Two specimens of Dermacentor reticulatus were also identified. Ungulates were positive for A. phagocytophilum and Theileria spp. Anaplasma phagocytophilum was found to infect 96.1% of cervids, 88.9% of mouflon, and 28.2% of wild boar, whereas Theileria spp. was detected only in cervids (94.6%). Importantly, a high rate of cervids (89%) showed mixed infections with both these microorganisms. In addition to A. phagocytophilum and Theileria spp., Rickettsia helvetica, R. monacensis, unidentified Rickettsia sp., Coxiella burnetii, "Candidatus Neoehrlichia mikurensis", Borrelia burgdorferi (s.l.) and Babesia venatorum were identified in engorged I. ricinus. Furthermore, A. phagocytophilum, Babesia spp. and Theileria spp. were detected in engorged H. concinna. Analysis of 16S rRNA and groEL gene sequences revealed the presence of five and two A. phagocytophilum variants, respectively, among which sequences identified in wild boar showed identity to the sequence of the causative agent of human granulocytic anaplasmosis (HGA). Phylogenetic analysis of Theileria 18S rRNA gene sequences amplified from cervids and engorged I. ricinus ticks segregated jointly with sequences of T. capreoli isolates into a moderately supported monophyletic clade. Conclusions: The findings indicate that free-living ungulates are reservoirs for A. phagocytophilum and Theileria spp. and engorged ixodid ticks attached to ungulates are good sentinels for the presence of agents of public and veterinary concern. Further analyses of the A. phagocytophilum genetic variants and Theileria species and their associations with vector ticks and free-living ungulates are required.Fil: Kazimírová, Mária. Slovak Academy of Sciences. Institute of Zoology; EslovaquiaFil: Hamšíková, Zuzana. Slovak Academy of Sciences. Institute of Zoology; EslovaquiaFil: Spitalská, Eva. Slovak Academy of Sciences. Institute of Virology. Biomedical Research Center,; EslovaquiaFil: Minichová, Lenka. Slovak Academy of Sciences. Institute of Virology. Biomedical Research Center,; EslovaquiaFil: Mahríková, Lenka. Slovak Academy of Sciences. Institute of Zoology; EslovaquiaFil: Caban, Radoslav. Široká ; EslovaquiaFil: Sprong, Hein. National Institute for Public Health and Environment.Laboratory for Zoonoses and Environmental Microbiology; Países BajosFil: Fonville, Manoj. National Institute for Public Health and Environment.Laboratory for Zoonoses and Environmental Microbiology; Países BajosFil: Schnittger, Leonhard. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Patobiología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Kocianová, Elena. Slovak Academy of Sciences. Institute of Virology. Biomedical Research Center,; Eslovaqui

Multiple Routes of Pesticide Exposure for Honey Bees Living Near Agricultural Fields

Populations of honey bees and other pollinators have declined worldwide in recent years. A variety of stressors have been implicated as potential causes, including agricultural pesticides. Neonicotinoid insecticides, which are widely used and highly toxic to honey bees, have been found in previous analyses of honey bee pollen and comb material. However, the routes of exposure have remained largely undefined. We used LC/MS-MS to analyze samples of honey bees, pollen stored in the hive and several potential exposure routes associated with plantings of neonicotinoid treated maize. Our results demonstrate that bees are exposed to these compounds and several other agricultural pesticides in several ways throughout the foraging period. During spring, extremely high levels of clothianidin and thiamethoxam were found in planter exhaust material produced during the planting of treated maize seed. We also found neonicotinoids in the soil of each field we sampled, including unplanted fields. Plants visited by foraging bees (dandelions) growing near these fields were found to contain neonicotinoids as well. This indicates deposition of neonicotinoids on the flowers, uptake by the root system, or both. Dead bees collected near hive entrances during the spring sampling period were found to contain clothianidin as well, although whether exposure was oral (consuming pollen) or by contact (soil/planter dust) is unclear. We also detected the insecticide clothianidin in pollen collected by bees and stored in the hive. When maize plants in our field reached anthesis, maize pollen from treated seed was found to contain clothianidin and other pesticides; and honey bees in our study readily collected maize pollen. These findings clarify some of the mechanisms by which honey bees may be exposed to agricultural pesticides throughout the growing season. These results have implications for a wide range of large-scale annual cropping systems that utilize neonicotinoid seed treatments