Multi-agent modeling of the South Korean avian influenza epidemic

<p>Abstract</p> <p>Background</p> <p>Several highly pathogenic avian influenza (AI) outbreaks have been reported over the past decade. South Korea recently faced AI outbreaks whose economic impact was estimated to be 6.3 billion dollars, equivalent to nearly 50% of the profit generated by the poultry-related industries in 2008. In addition, AI is threatening to cause a human pandemic of potentially devastating proportions. Several studies show that a stochastic simulation model can be used to plan an efficient containment strategy on an emerging influenza. Efficient control of AI outbreaks based on such simulation studies could be an important strategy in minimizing its adverse economic and public health impacts.</p> <p>Methods</p> <p>We constructed a spatio-temporal multi-agent model of chickens and ducks in poultry farms in South Korea. The spatial domain, comprised of 76 (37.5 km × 37.5 km) unit squares, approximated the size and scale of South Korea. In this spatial domain, we introduced 3,039 poultry flocks (corresponding to 2,231 flocks of chickens and 808 flocks of ducks) whose spatial distribution was proportional to the number of birds in each province. The model parameterizes the properties and dynamic behaviors of birds in poultry farms and quarantine plans and included infection probability, incubation period, interactions among birds, and quarantine region.</p> <p>Results</p> <p>We conducted sensitivity analysis for the different parameters in the model. Our study shows that the quarantine plan with well-chosen values of parameters is critical for minimize loss of poultry flocks in an AI outbreak. Specifically, the aggressive culling plan of infected poultry farms over 18.75 km radius range is unlikely to be effective, resulting in higher fractions of unnecessarily culled poultry flocks and the weak culling plan is also unlikely to be effective, resulting in higher fractions of infected poultry flocks.</p> <p>Conclusions</p> <p>Our results show that a prepared response with targeted quarantine protocols would have a high probability of containing the disease. The containment plan with an aggressive culling plan is not necessarily efficient, causing a higher fraction of unnecessarily culled poultry farms. Instead, it is necessary to balance culling with other important factors involved in AI spreading. Better estimations for the containment of AI spreading with this model offer the potential to reduce the loss of poultry and minimize economic impact on the poultry industry.</p

The impact of surgical delay on resectability of colorectal cancer: An international prospective cohort study

AIM: The SARS-CoV-2 pandemic has provided a unique opportunity to explore the impact of surgical delays on cancer resectability. This study aimed to compare resectability for colorectal cancer patients undergoing delayed versus non-delayed surgery. METHODS: This was an international prospective cohort study of consecutive colorectal cancer patients with a decision for curative surgery (January-April 2020). Surgical delay was defined as an operation taking place more than 4 weeks after treatment decision, in a patient who did not receive neoadjuvant therapy. A subgroup analysis explored the effects of delay in elective patients only. The impact of longer delays was explored in a sensitivity analysis. The primary outcome was complete resection, defined as curative resection with an R0 margin. RESULTS: Overall, 5453 patients from 304 hospitals in 47 countries were included, of whom 6.6% (358/5453) did not receive their planned operation. Of the 4304 operated patients without neoadjuvant therapy, 40.5% (1744/4304) were delayed beyond 4 weeks. Delayed patients were more likely to be older, men, more comorbid, have higher body mass index and have rectal cancer and early stage disease. Delayed patients had higher unadjusted rates of complete resection (93.7% vs. 91.9%, P = 0.032) and lower rates of emergency surgery (4.5% vs. 22.5%, P < 0.001). After adjustment, delay was not associated with a lower rate of complete resection (OR 1.18, 95% CI 0.90-1.55, P = 0.224), which was consistent in elective patients only (OR 0.94, 95% CI 0.69-1.27, P = 0.672). Longer delays were not associated with poorer outcomes. CONCLUSION: One in 15 colorectal cancer patients did not receive their planned operation during the first wave of COVID-19. Surgical delay did not appear to compromise resectability, raising the hypothesis that any reduction in long-term survival attributable to delays is likely to be due to micro-metastatic disease

Model for bioremediation of oil contaminated soil system-A simulation study

Pollution has reached levels which demand immediate attention and scientific and technological solutions are required on an urgent basis. We are concerned in this report with bioremediation og organically contaminated soil and groundwater. Specifically, we have in mind the situation obtaining in the oil fields where the oil system is contaminated with crude oil during its extraction process. To achieve managed in situ bioremediation in practice, treated water is recycled with added nutrients into the ground surface so that ozygen and nitrogen are carried with the water to the sub surface regions. Sorption, conective-dispersive flow and chemical and biological transformation are the chief processes involved which have to be modelled. A simulation model that combines a completely mixed macropore flow model with a contaminated aggregates bioremediation model ( Dhawan et al., 1993) was employed by us ( Gogoi et al., 1998) in the development of a treatability protocol for bioremediation of contaminated soil at Borhola oil fields. Assam, India, an unusual feature of this simulation model is that it is governed by coupled partial differential equations (PDEs) and ordinary differential equations (ODEs). PDEs model the diffusion and biodegradation process occuring in the micropores of soil aggregates while the ODEs describe the bioremediation in the macropores, the interstital spaces between soil aggregates; both the PDEs and ODEs are nonlinear. Simulation models are a must in this case since laboratory experiments take periods of the order of months. The model was applied to the case of high initial contaminant concentrations as observed at Borhola oil fields, Assam. Sensitivity of the model to the parameters was seen to be nonlinear in nature. Alternate normalisation schemes are required to place in context some of the results. The model was turneed with the experimental results available from Regionl Research Laboratory (RRL), Jorhst, where field pilot studies of a bioremediation system for Borhola were conducted over a period of one year. Over studies showed that the model is inefficient and that it is impractical to use it for high initial contaminant concentration. Ways of improving the model efficiency as well as comprehensiveness are discussed

Knowledge Creation and Dissemination during 1988-2000

The CSIR Centre for Mathematical Modelling and Computer Simulation is a quintessential knowledge organisation . The main products resulting from its activities in modelling and simulation are in the form of data, information and knowledge . These are archived (publications in journals, books/proceedings, internal reports) and communicated orally (presentation in conferences, symposia, etc.).C-MMACS also takes the lead in organising scientific meetings and workshops in the area of mathematical and numerical modelling .It was felt that a compilation in one document of all the knowledge output and knowledge based activities of C-MMACS will give the reader an account of CMMACS contributions over the entire period of existence till date. The list is meant to be as exhaustive and comprehensive as possible, but still some omissions are inevitable. I thank Stella Margaret A, S Sita and the Knowledge Management Group at CMMACS under Dr T R Krishna Mohan for compiling this document meticulously

Growth of transport sector in India: A modelling exercise

A general methodology is given to describe the growth of the Transport Sector in India on the time scale of decades in terms of appropriate mathematical models. Available data for rail, road and air sectors in independent India are analysed to determine the dominant long-term trends and to calibrate the models. These models are then used to estimate the growth in the next two decades. An important conclusion is that for many variables describing supply, demand, current capacity and system performance, the long-term trend is exponential

The N-terminal region containing the zinc finger domain of tobacco streak virus coat protein is essential for the formation of virus-like particles

Tobacco streak virus (TSV), a member of the genus Ilarvirus (family Bromoviridae), has a tripartite genome and forms quasi-isometric virions. All three viral capsids, encapsidating RNA 1, RNA 2 or RNA 3 and subgenomic RNA 4, are constituted of a single species of coat protein (CP). Formation of virus-like particles (VLPs) could be observed when the TSV CP gene was cloned and the recombinant CP (rCP) was expressed in E. coli. TSV VLPs were found to be stabilized by Zn2+ ions and could be disassembled in the presence of 500 mM CaCl2. Mutational analysis corroborated previous studies that showed that an N-terminal arginine-rich motif was crucial for RNA binding; however, the results presented here demonstrate that the presence of RNA is not a prerequisite for assembly of TSV VLPs. Instead, the N-terminal region containing the zinc finger domain preceding the arginine-rich motif is essential for assembly of these VLPs