Browsing by Author "Vullikanti, Anil"
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- Discovery of under immunized spatial clusters using network scan statisticsCadena, Jose; Falcone, David; Marathe, Achla; Vullikanti, Anil (2019-02-04)Background Clusters of under-vaccinated children are emerging in a number of states in the United States due to rising rates of vaccine hesitancy and refusal. As the measles outbreaks in California and other states in 2015 and in Minnesota in 2017 showed, such clusters can pose a significant public health risk. Prior methods have used publicly-available school immunization data for analysis (except for a few, which use private healthcare patient records). School immunization data has limited demographic information—as a result, such analyses are not able to provide demographic characteristics of significant clusters. Further, the resolution of the clusters identified by prior methods is limited since they are typically restricted to disks or well-rounded shapes. Methods We use realistic population models for Minnesota (MN) and Washington (WA) state, which provide a model of activities for all individuals in the population. We combine this with school level immunization data for these two states, to estimate vaccine coverage at the level of census block groups. A scan statistic method defined on networks is used for finding significant clusters of under-immunized block groups, without any restrictions on shape. Further we provide the demographic characteristics of these clusters. Results We find 2 significant under-vaccinated clusters in MN and 3 in WA. These are very irregular in shape, in contrast to the circular disks reported in prior work, which rely on the SatScan approach. Some of the clusters found by our method are not contained in those computed using SatScan, a state-of-the-art software tool used in similar studies in other states. Conclusions The emergence of under-immunized clusters is a growing concern for public health agencies because they can act as reservoirs of infection and increase the risk of infection into the wider population. Higher resolution clusters computed using our network based approach and population models provide new insights on the structure and characteristics of such clusters and enable targeted interventions.
- Disparities in spread and control of influenza in slums of Delhi: findings from an agent-based modelling studyAdiga, Abhijin; Chu, Shuyu; Kuhlman, Christopher J.; Lewis, Bryan L.; Marathe, Achla; Nordberg, Eric K.; Swarup, Samarth; Vullikanti, Anil; Wilson, Mandy L. (BMJ Publishing Group, 2017-11-03)Objectives: This research studies the role of slums in the spread and control of infectious diseases in the National Capital Territory of India, Delhi, using detailed social contact networks of its residents. Methods: We use an agent-based model to study the spread of influenza in Delhi through person-to-person contact. Two different networks are used: one in which slum and non-slum regions are treated the same, and the other in which 298 slum zones are identified. In the second network, slum-specific demographics and activities are assigned to the individuals whose homes reside inside these zones. The main effects of integrating slums are that the network has more home-related contacts due to larger family sizes and more outside contacts due to more daily activities outside home. Various vaccination and social distancing interventions are applied to control the spread of influenza. Results: Simulation-based results show that when slum attributes are ignored, the effectiveness of vaccination can be overestimated by 30%–55%, in terms of reducing the peak number of infections and the size of the epidemic, and in delaying the time to peak infection. The slum population sustains greater infection rates under all intervention scenarios in the network that treats slums differently. Vaccination strategy performs better than social distancing strategies in slums. Conclusions: Unique characteristics of slums play a significant role in the spread of infectious diseases. Modelling slums and estimating their impact on epidemics will help policy makers and regulators more accurately prioritise allocation of scarce medical resources and implement public health policies.
- Effect of modelling slum populations on influenza spread in DelhiChen, Jiangzhuo; Chu, Shuyu; Chungbaek, Youngyun; Khan, Maleq; Kuhlman, Christopher J.; Marathe, Achla; Mortveit, Henning; Vullikanti, Anil; Xie, Dawen (BMJ, 2016-01-01)
- Forecasting Social Unrest Using Activity CascadesCadena, Jose; Korkmaz, Gizem; Kuhlman, Christopher J.; Marathe, Achla; Ramakrishnan, Naren; Vullikanti, Anil (PLOS, 2015-06-19)Social unrest is endemic in many societies, and recent news has drawn attention to happenings in Latin America, the Middle East, and Eastern Europe. Civilian populations mobilize, sometimes spontaneously and sometimes in an organized manner, to raise awareness of key issues or to demand changes in governing or other organizational structures. It is of key interest to social scientists and policy makers to forecast civil unrest using indicators observed on media such as Twitter, news, and blogs. We present an event forecasting model using a notion of activity cascades in Twitter (proposed by Gonzalez-Bailon et al., 2011) to predict the occurrence of protests in three countries of Latin America: Brazil, Mexico, and Venezuela. The basic assumption is that the emergence of a suitably detected activity cascade is a precursor or a surrogate to a real protest event that will happen “on the ground.” Our model supports the theoretical characterization of large cascades using spectral properties and uses properties of detected cascades to forecast events. Experimental results on many datasets, including the recent June 2013 protests in Brazil, demonstrate the effectiveness of our approach.
- Modeling targeted layered containment of an influenza pandemic in the United StatesHalloran, Elizabeth M.; Ferguson, Neil M.; Eubank, Stephen; Longini, Ira M. Jr.; Cummings, Derek A. T.; Lewis, Bryan L.; Xu, Shufu; Fraser, Christophe; Vullikanti, Anil; Germann, Timothy C.; Wagener, Diane; Beckman, Richard J.; Kadau, Kai; Barrett, Christopher L.; Macken, Catherine A.; Burke, Donald S.; Cooley, Philip (NAS, 2008-03-25)Planning a response to an outbreak of a pandemic strain of influenza is a high public health priority. Three research groups using different individual-based, stochastic simulation models have examined the consequences of intervention strategies chosen in consultation with U.S. public health workers. The first goal is to simulate the effectiveness of a set of potentially feasible intervention strategies. Combinations called targeted layered containment (TLC) of influenza antiviral treatment and prophylaxis and nonpharmaceutical interventions of quarantine, isolation, school closure, community social distancing, and workplace social distancing are considered. The second goal is to examine the robustness of the results to model assumptions. The comparisons focus on a pandemic outbreak in a population similar to that of Chicago, with 8.6 million people. The simulations suggest that at the expected transmissibility of a pandemic strain, timely implementation of a combination of targeted household antiviral prophylaxis, and social distancing measures could substantially lower the illness attack rate before a highly efficacious vaccine could become available. Timely initiation of measures and school closure play important roles. Because of the current lack of data on which to base such models, further field research is recommended to learn more about the sources of transmission and the effectiveness of social distancing measures in reducing influenza transmission.
- Sustainable provision of food and water using an interdisciplinary, system-of-systems frameworkBosch, Darrell J.; Clark, Susan F.; Cobourn, Kelly M.; Easton, Zachary M.; Godrej, Adil N.; Hession, W. Cully; Hester, Erich T.; Hull, Robert Bruce IV; Little, John C.; Marathe, Achla; McGinnis, Sean; O'Rourke, Megan E.; Schmale, David G. III; Schoenholtz, Stephen H.; Shortridge, Julie; Swecker, Terry; Thomason, Wade E.; Vullikanti, Anil; White, Robin R. (Virginia Tech, 2017-05-15)Although sustainability is an essential concept to ensuring the future of humanity and integrity of the resources and ecosystems on which we depend, identification of a comprehensive approach to assess and enhance sustainability is another grand challenge. Fortuitously, in a groundbreaking re-conceptualization of the problem, we identified the collective limitations of the current suite of approaches used to assess sustainability and instead proposed a computational, system-of-systems framework that is causal, modular, tiered, and scalable. Our approach incorporates a comprehensive definition of sustainability as well as new educational structures to systematically and computationally connect across the disciplines. It also aspires to address the political, economic, and decision-making challenges that limit the applicability of science and technical solutions to wicked problems...