Preventing infectious disease in dynamic populations under uncertainty

32nd AAAI Conference on Artificial Intelligence, AAAI 2018

Volumn , Issue , 2018, Pages 841-848

  Wilder, Bryan ^a,b   Suen, Sze Chuan ^a,b   Tambe, Milind ^a,b  

^a Department of Computer Science ^*  (United States)

^b UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; PATIENT TREATMENT; POPULATION DYNAMICS; STOCHASTIC SYSTEMS;

CONTACT PATTERN; CRITICAL CHALLENGES; DEMOGRAPHIC GROUPS; DISEASE SPREAD; DYNAMIC POPULATION; INFECTIOUS DISEASE; MULTI-AGENT MODEL; STOCHASTIC SETTINGS;

DISEASES;

EID: 85055725363     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (32)

1. Bach, F. 2015. Submodular functions: from discrete to conti-nous domains. arXiv preprint arXiv:1511.00394.
2. Beheshti, R., and Sukthankar, G. 2014. A normative agent-based model for predicting smoking cessation trends. In Proceedings of the 2014 international conference on Autonomous agents and multi-agent systems, 557-564. International Foundation for Autonomous Agents and Multiagent Systems.
3. Bian, A. A.; Mirzasoleiman, B.; Buhmann, J. M.; and Krause, A. 2017. Guaranteed non-convex optimization: Submodular maximization over continuous domains. In AISTATS.
4. Borgs, C.; Chayes, J.; Ganesh, A.; and Saberi, A. 2010. How to distribute antidote to control epidemics. Random Structures & Algorithms 37(2):204-222.
5. CDC. 2015. Reported STDs in the United States.
6. Chan, C. H.; McCabe, C. J.; and Fisman, D. N. 2011. Core groups, antimicrobial resistance and rebound in gonorrhoea in north america. Sex Transm Infect sextrans-2011.
7. Chen, C.; Tong, H.; Prakash, B. A.; Tsourakakis, C. E.; Eliassi-Rad, T.; Faloutsos, C.; and Chau, D. H. 2016. Node immunization on large graphs: Theory and algorithms. IEEE Transactions on Knowledge and Data Engineering 28(1):113-126.
8. Chung, F.; Horn, P.; and Tsiatas, A. 2009. Distributing antidote using pagerank vectors. Internet Mathematics 6(2):237-254.
9. Dowdy, D. W.; Golub, J. E.; Chaisson, R. E.; and Saraceni, V. 2012. Heterogeneity in tuberculosis transmission and the role of geographic hotspots in propagating epidemics. Proceedings of the National Academy of Sciences 109(24):9557-9562.
10. Drakopoulos, K.; Ozdaglar, A.; and Tsitsiklis, J. N. 2014. An efficient curing policy for epidemics on graphs. IEEE Transactions on Network Science and Engineering 1(2):67-75.
11. Han, S.; Preciado, V. M.; Nowzari, C.; and Pappas, G. J. 2015. Data-driven network resource allocation for controlling spreading processes. IEEE Transactions on Network Science and Engineering 2(4):127-138.
12. Hazan, E., and Luo, H. 2016. Variance-reduced and projection-free stochastic optimization. In International Conference on Machine Learning, 1263-1271.
13. IIPS. 2014. International Institute for Population Sciences. District level household and facility survey. New Delhi, India. http://www.rchiips.org/obtainingdata.html.
14. Jindal, A., and Rao, S. 2017. Agent-based modeling and simulation of mosquito-borne disease transmission. In Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems, 426-435. International Foundation for Autonomous Agents and Multiagent Systems.
15. Lee, B. Y.; Brown, S. T.; Korch, G. W.; Cooley, P. C.; Zimmerman, R. K.; Wheaton, W. D.; Zimmer, S. M.; Grefenstette, J. J.; Bailey, R. R.; Assi, T.-M.; et al. 2010. A computer simulation of vaccine prioritization, allocation, and rationing during the 2009 h1n1 influenza pandemic. Vaccine 28(31):4875-4879.
16. Luke, D. A., and Stamatakis, K. A. 2012. Systems science methods in public health: dynamics, networks, and agents. Annual review of public health 33:357-376.
17. Perez, L., and Dragicevic, S. 2009. An agent-based approach for modeling dynamics of contagious disease spread. International journal of health geographics 8(1):50.
18. Petersen, K. B., and Pedersen, M. S. 2008. The matrix cookbook. Technical University of Denmark 7:15.
19. Picault, S.; Huang, Y.-L.; Sicard, V.; and Ezanno, P. 2017. Enhancing sustainability of complex epidemiological models through a generic multilevel agent-based approach. In International Joint Conference on Artificial Intelligence (IJCAI'2017), 374-380.
20. Prakash, B. A.; Tong, H.; Valler, N.; Faloutsos, M.; and Faloutsos, C. 2010. Virus propagation on time-varying networks: Theory and immunization algorithms. In Joint European Conference on Machine Learning and Knowledge Discovery in Databases, 99-114. Springer.
21. RNTCP. 2010. Training module for medical practitioners. New Delhi, India: Revised National Tuberculosis Control Pro-gramme, Ministry of Health and Family Welfare.
22. RNTCP. 2016. Revised national tuberculosis control pro-gramme annual status report. New Delhi, India: Ministry of Health and Family Welfare. http://tbcindia.nic.in/showfile.php?lid=3180.
23. Saha, S.; Adiga, A.; Prakash, B. A.; and Vullikanti, A. K. S. 2015. Approximation algorithms for reducing the spectral radius to control epidemic spread. In Proceedings of the SIAM International Conference on Data Mining, 568-576. SIAM.
24. Song, C.; Hsu, W.; and Lee, M. L. 2015. Node immunization over infectious period. In Proceedings of the 24th ACM International on Conference on Information and Knowledge Management, 831-840. ACM.
25. Suen, S.; Bendavid, E.; and Goldhaber-Fiebert, J. 2015. Cost-effectiveness of improvements in diagnosis and treatment accessibility for tuberculosis control in india. The International Journal of Tuberculosis and Lung Disease 19(9):1115-1124.
26. Swarup, S.; Eubank, S. G.; and Marathe, M. V. 2014. Computational epidemiology as a challenge domain for multiagent systems. In Proceedings of the 2014 international conference on Autonomous agents and multi-agent systems, 1173-1176. International Foundation for Autonomous Agents and Multiagent Systems.
27. UN. 2015. United Nations Statistics Division Demographic Statistics. http://data.un.org/Data.aspx?d=POP&f=tableCode%3A22.
28. White, P. J.; Ward, H.; Cassell, J. A.; Mercer, C. H.; and Gar-nett, G. P. 2005. Vicious and virtuous circles in the dynamics of infectious disease and the provision of health care: gonorrhea in britain as an example. The Journal of infectious diseases 192(5):824-836.
29. WHO. 2015a. World Health Organization. Life Tables. http://www.who.int/gho/mortality burden disease/life tables/life tables/en/.
30. WHO. 2015b. World Health Organization. Tuberculosis country profiles. http://www.who.int/tb/country/data/profiles/en/.
31. Zhang, Y., and Prakash, B. A. 2014. Scalable vaccine distribution in large graphs given uncertain data. In Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management, 1719-1728. ACM.
32. Zhang, Y.; Adiga, A.; Saha, S.; Vullikanti, A.; and Prakash, B. A. 2016. Near-optimal algorithms for controlling propagation at group scale on networks. IEEE Transactions on Knowledge and Data Engineering 28(12):3339-3352.