Seasonal variations of EPG levels in gastro-intestinal parasitic infection in a southeast asian controlled locale:a statistical analysis

We present a data based statistical study on the effects of seasonal variations in the growth rates of the gastro-intestinal (GI) parasitic infection in livestock. The alluded growth rate is estimated through the variation in the number of eggs per gram (EPG) of faeces in animals. In accordance with earlier studies, our analysis too shows that rainfall is the dominant variable in determining EPG infection rates compared to other macro-parameters like temperature and humidity. Our statistical analysis clearly indicates an oscillatory dependence of EPG levels on rainfall fluctuations. Monsoon recorded the highest infection with a comparative increase of at least 2.5 times compared to the next most infected period (summer). A least square fit of the EPG versus rainfall data indicates an approach towards a super diffusive (i. e. root mean square displacement growing faster than the square root of the elapsed time as obtained for simple diffusion) infection growth pattern regime for low rainfall regimes (technically defined as zeroth level dependence) that gets remarkably augmented for large rainfall zones. Our analysis further indicates that for low fluctuations in temperature (true on the bulk data), EPG level saturates beyond a critical value of the rainfall, a threshold that is expected to indicate the onset of the nonlinear regime. The probability density functions (PDFs) of the EPG data show oscillatory behavior in the large rainfall regime (greater than 500 mm), the frequency of oscillation, once again, being determined by the ambient wetness (rainfall, and humidity). Data recorded over three pilot projects spanning three measures of rainfall and humidity bear testimony to the universality of this statistical argument. © 2013 Chattopadhyay and Bandyopadhyay.

The de-gaying and re-gaying of AIDS:contested homophobias in lesbian and gay awareness training

From the first recognition of AIDS as a disease, it was publicly conceptualized as a 'gay plague'. In response, health education and diversity training sought to counter this association claiming that AIDS is an 'equal opportunity' virus - that it can affect anyone. In this article, we analyse talk about HIV/AIDS within a data corpus of 13 tape-recorded lesbian and gay awareness training sessions. Counter to the way in which interactions are described in the lesbian and gay awareness training literature, we found that it was trainees, rather than trainers, who pursued discussions about HIV/AIDS, and who did so in order to claim the 'de-gaying' of AIDS, which they treated as representing a 'non-prejudiced' position. By contrast, and in response to trainees' insistence on de-gaying AIDS, trainers were 're-gaying' AIDS. Our analysis highlights that in these sessions - designed explicitly to counter homophobic attitudes - apparently 'factual' claims and counter-claims about infection rates and risk groups are underpinned by essentially contested definitions of what constitutes a 'homophobic' attitude. We conclude by pointing to the value of detailed analysis of talk-in-interaction for understanding professional practices, and suggest strategies for improving the pedagogic value of training. Copyright © 2005 SAGE Publications.

Spatio-temporal analyses of West Nile virus transmission in Culex mosquitoes in northern Illinois, USA, 2004

After a severe outbreak of West Nile virus (WNV) in Cook County, Illinois, in 2002, detections of WNV in mosquitoes were frequent across the state in the following years despite small numbers of human cases. We conducted a spatio-temporal analysis of Culex (subgenus Culex) mosquitoes collected in 2004 in three mosquito abatement districts (MAD) in Cook County by calculating monthly estimates of mosquito density, prevalence of infected mosquitoes, and exposure intensity, which in turn is a product of mosquito density and infection rates. Mosquito infections were detected early at three sites in late May and were widely detected throughout the three MADs in the summer with infection rates as high as 13 per 1000 in August. Exposure intensities were higher at sites adjacent to the Des Plaines River, especially in August and September. The aggregated pattern of WNV transmission along the river might be related to the existence of substantial forest preserves and wetlands that might produce ecological conditions favorable for mosquito proliferation and interactions between mosquitoes and birds.

Progmosis:evaluating risky individual behavior during epidemics using mobile network data

The possibility to analyze, quantify and forecast epidemic outbreaks is fundamental when devising effective disease containment strategies. Policy makers are faced with the intricate task of drafting realistically implementable policies that strike a balance between risk management and cost. Two major techniques policy makers have at their disposal are: epidemic modeling and contact tracing. Models are used to forecast the evolution of the epidemic both globally and regionally, while contact tracing is used to reconstruct the chain of people who have been potentially infected, so that they can be tested, isolated and treated immediately. However, both techniques might provide limited information, especially during an already advanced crisis when the need for action is urgent. In this paper we propose an alternative approach that goes beyond epidemic modeling and contact tracing, and leverages behavioral data generated by mobile carrier networks to evaluate contagion risk on a per-user basis. The individual risk represents the loss incurred by not isolating or treating a specific person, both in terms of how likely it is for this person to spread the disease as well as how many secondary infections it will cause. To this aim, we develop a model, named Progmosis, which quantifies this risk based on movement and regional aggregated statistics about infection rates. We develop and release an open-source tool that calculates this risk based on cellular network events. We simulate a realistic epidemic scenarios, based on an Ebola virus outbreak; we find that gradually restricting the mobility of a subset of individuals reduces the number of infected people after 30 days by 24%.