Why Us?
With life-threatening zoonotic diseases and rising costs of nosocomial infections, it is evident that hospitals and healthcare authorities urgently need a tool that can accurately evaluate their current infection control programs for cost efficiency and effectiveness in surveillance, intervention and adherence during endemic and epidemic outbreaks. ROSS Scientific products and services provide:
- A means to assess the hospital's infection control program by sampling from a customized simulation of the hospital's operations. Assuming that the simulation approximates but underestimates reality, detection of infection cases from the simulation would then provide bounds for the actual nosocomial infection rate.
- A means to predict the appropriate sample size and sample frequency through simulation so as to avoid having to incur costly case findings on the entire patient population.
> WHO Confirmed Human Cases of H5N1
ROSS Scientific achieves this through state-of-the-art simulation technology that is multi-time scalable, spatially explicit, data-driven and user configurable for modeling disease spread within environments that have high heterogeneity in susceptibilities.
ROSS Scientific has successfully developed an agent-based, spatially explicit epidemiological simulation of the spread of influenza for the Communicable Disease Centre of Tan Tock Seng Hospital in Singapore given high heterogeneity in social interactions and individual susceptibilities. A field survey was first conducted to obtain the activity patterns of individuals. The data facilitated the modeling of social behaviours constrained by roles and physical locations so as to achieve a highly precise simulation of the ward's activity.
> Screen capture of PathoSIM Professional simulation output
Our results validated the long-standing belief that within the ward, flu is typically transmitted through staff and less directly between patients, thereby emphasizing the importance of staff-oriented prophylaxis. The model predicted that outbreak size (and attack rate) will increase exponentially with increasing disease infectiousness beyond a certain threshold but eventually tapers due to a target-limited finite population.
The latter constraint also gave rise to a peak in epidemic duration (at the threshold level of infectiousness) that decreased to a steady value for increasing infectiousness. Finally, the results showed that the rate of increase in distinct cumulated contacts will be highest within the first 24 hours and would give the highest yield for contact tracing among patients that had prolonged periods of non-isolation.
