Dynamic vapor microextraction of ignitable liquid from casework containers.

Dynamic vapor microextraction (DVME) is a headspace concentration method that can be used to collect ignitable liquid (IL) from fire debris onto chilled adsorbent capillaries. Unlike passive headspace concentration onto activated carbon strips (ACSs) that must be eluted with a toxic solvent (carbon disulfide), DVME employs a relatively benign solvent (acetone) to recover the adsorbed IL residue, and each headspace collection is monitored for breakthrough. Here, for the first time, we extend DVME to casework containers while exploring a realistic range of oven temperatures and collection volumes. We investigated metal cans sealed with friction lids (container 1), metal cans sealed within polymer bags (container 2), and glass jars sealed with two-piece lids (container 3). Without additional containment, container 1 was found to leak so excessively that flow through the capillary was unreliable. Therefore, for containers 2 and 3 only, we determined the total number of target compounds collected from 50% weathered gasoline for oven temperatures from 54 °C to 96 °C and collection volumes from 47 standard cubic centimeters (scc) to 90 scc. Only high-volatility species with retention times (tR)< n-decane on a non-polar column were recovered from polymer bags, whereas headspace concentration from glass jars led to the recovery of target compounds across the entire volatility range. DVME at 90 °C from 2-mL containers showed that the presence of polymer bag material leads to IL vapor losses, particularly for low-volatility species with tR> n-decane. DVME was strongly influenced by the casework container, whereas oven temperature and collection volume had a minor influence for the IL samples explored here.

PREDICTIVE MODELING OF CHOLERA OUTBREAKS IN BANGLADESH.

Despite seasonal cholera outbreaks in Bangladesh, little is known about the relationship between environmental conditions and cholera cases. We seek to develop a predictive model for cholera outbreaks in Bangladesh based on environmental predictors. To do this, we estimate the contribution of environmental variables, such as water depth and water temperature, to cholera outbreaks in the context of a disease transmission model. We implement a method which simultaneously accounts for disease dynamics and environmental variables in a Susceptible-Infected-Recovered-Susceptible (SIRS) model. The entire system is treated as a continuous-time hidden Markov model, where the hidden Markov states are the numbers of people who are susceptible, infected, or recovered at each time point, and the observed states are the numbers of cholera cases reported. We use a Bayesian framework to fit this hidden SIRS model, implementing particle Markov chain Monte Carlo methods to sample from the posterior distribution of the environmental and transmission parameters given the observed data. We test this method using both simulation and data from Mathbaria, Bangladesh. Parameter estimates are used to make short-term predictions that capture the formation and decline of epidemic peaks. We demonstrate that our model can successfully predict an increase in the number of infected individuals in the population weeks before the observed number of cholera cases increases, which could allow for early notification of an epidemic and timely allocation of resources.

Household Transmission of Vibrio cholerae in Bangladesh.

BACKGROUND: Vibrio cholerae infections cluster in households. This study's objective was to quantify the relative contribution of direct, within-household exposure (for example, via contamination of household food, water, or surfaces) to endemic cholera transmission. Quantifying the relative contribution of direct exposure is important for planning effective prevention and control measures. METHODOLOGY/PRINCIPAL FINDINGS: Symptom histories and multiple blood and fecal specimens were prospectively collected from household members of hospital-ascertained cholera cases in Bangladesh from 2001-2006. We estimated the probabilities of cholera transmission through 1) direct exposure within the household and 2) contact with community-based sources of infection. The natural history of cholera infection and covariate effects on transmission were considered. Significant direct transmission (p-value<0.0001) occurred among 1414 members of 364 households. Fecal shedding of O1 El Tor Ogawa was associated with a 4.9% (95% confidence interval: 0.9%-22.8%) risk of infection among household contacts through direct exposure during an 11-day infectious period (mean length). The estimated 11-day risk of O1 El Tor Ogawa infection through exposure to community-based sources was 2.5% (0.8%-8.0%). The corresponding estimated risks for O1 El Tor Inaba and O139 infection were 3.7% (0.7%-16.6%) and 8.2% (2.1%-27.1%) through direct exposure, and 3.4% (1.7%-6.7%) and 2.0% (0.5%-7.3%) through community-based exposure. Children under 5 years-old were at elevated risk of infection. Limitations of the study may have led to an underestimation of the true risk of cholera infection. For instance, available covariate data may have incompletely characterized levels of pre-existing immunity to cholera infection. Transmission via direct exposure occurring outside of the household was not considered. CONCLUSIONS: Direct exposure contributes substantially to endemic transmission of symptomatic cholera in an urban setting. We provide the first estimate of the transmissibility of endemic cholera within prospectively-followed members of households. The role of direct transmission must be considered when planning cholera control activities.