Real-time decision-making during emergency disease outbreaks

PLoS Computational Biology

Volumn 14, Issue 7, 2018, Pages

  Probert, William J M ^a,b,j   Jewell, Chris P ^c   Werkman, Marleen ^d   Fonnesbeck, Christopher J ^e   Goto, Yoshitaka ^f   Runge, Michael C ^g   Sekiguchi, Satoshi ^f   Shea, Katriona ^h,i   Keeling, Matt J ^a,b   Ferrari, Matthew J ^h,i   Tildesley, Michael J ^a,b  

^a UNIVERSITY OF WARWICK   (United Kingdom)

^b UNIVERSITY OF WARWICK   (United Kingdom)

^c LANCASTER UNIVERSITY   (United Kingdom)

^d IMPERIAL COLLEGE LONDON   (United Kingdom)

^e VANDERBILT UNIVERSITY MEDICAL CENTER   (United States)

^f UNIVERSITY OF MIYAZAKI   (Japan)

^g PATUXENT WILDLIFE RESEARCH CENTER   (United States)

^h PENNSYLVANIA STATE UNIVERSITY   (United States)

ⁱ PENNSYLVANIA STATE UNIVERSITY   (United States)

^j UNIVERSITY OF OXFORD   (United Kingdom)

more..

Author keywords

[No Author keywords available]

Indexed keywords

DECISION MAKING; DIGITAL STORAGE; DISEASE CONTROL; ESTIMATION; UNCERTAINTY ANALYSIS;

CONTROL STRATEGIES; DISEASE OUTBREAKS; INFECTIOUS DISEASE OUTBREAKS; OUTBREAK MODELS; POLICY MAKERS; REAL TIME DECISION-MAKING; REAL-TIME DECISION MAKING; SIMULATION MODEL; TRANSMISSION PARAMETERS; UNCERTAINTY;

FORECASTING;

FOOT AND MOUTH DISEASE VACCINE; VIRUS VACCINE;

ANIMAL CULLING; ARTICLE; DISEASE TRANSMISSION; EMERGENCY MEDICINE; EPIDEMIC; FOOT AND MOUTH DISEASE; HEALTH CARE POLICY; HUMAN; INFECTION CONTROL; INFORMATION PROCESSING; JAPAN; MARKOV CHAIN; MATHEMATICAL MODEL; MEDICAL DECISION MAKING; MONTE CARLO METHOD; NONHUMAN; PREDICTION; SIMULATION; UNITED KINGDOM; ANIMAL; BOVINE; CATTLE DISEASE; DOMESTIC ANIMAL; FOOT AND MOUTH DISEASE VIRUS; IMMUNOLOGY; ORGANIZATION; PIG; SHEEP; SHEEP DISEASE; SWINE DISEASE; THEORETICAL MODEL; TIME FACTOR; TRANSMISSION;

ANIMALS; ANIMALS, DOMESTIC; CATTLE; CATTLE DISEASES; DECISION MAKING, ORGANIZATIONAL; DISEASE OUTBREAKS; FOOT-AND-MOUTH DISEASE; FOOT-AND-MOUTH DISEASE VIRUS; HEALTH POLICY; HUMANS; JAPAN; MODELS, THEORETICAL; SHEEP; SHEEP DISEASES; SWINE; SWINE DISEASES; TIME FACTORS; UNITED KINGDOM; VIRAL VACCINES;

EID: 85050992207     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.1006202     Document Type: Article

References (30)

1. Keeling MJ, Woolhouse MEJ, Shaw DJ, Matthews L, Chase-Topping M, Haydon DT, Cornell SJ, et al. Dynamics of the 2001 UK foot and mouth epidemic: Stochastic dispersal in a heterogeneous landscape. Science. 2001; 294, 813–817. doi: 10.1126/science.1065973 pmid: 11679661
2. Ferguson NM, Donnelly CA, Anderson RM, The foot-and-mouth epidemic in Great Britain: Pattern of spread and impact of interventions. Science. 2001; 292, 1155–1160. doi: 10.1126/science.1061020 pmid: 11303090
3. Kao RR, The impact of local heterogeneity on alternative control strategies for foot-and-mouth disease. Proc. R. Soc. B. 2003; 270, 2557–2564. doi: 10.1098/rspb.2003.2546 pmid: 14728777
4. Tildesley MJ, Savill NJ, Shaw DJ, Deardon R, Brooks SP, Woolhouse SEJ, et al. Optimal reactive vaccination strategies for a foot-and-mouth outbreak in the UK. Nature. 2006; 440, 83–86. doi: 10.1038/nature04324 pmid: 16511494
5. Stevenson MA, Sanson RL, Stern MW, O’Leary BD, Sujau M, Moles-Benfell N, et al. InterSpread Plus: a spatial and stochastic simulation model of disease in animal populations. Prev. Vet. Med. 2013; 109, 10–24doi: 10.1016/j.prevetmed.2012.08.015 pmid: 22995473
6. Bradhurst RA, Roche SE, East IJ, Kwan P, Garner MG, A hybrid modelling approach to simulating foot-and-mouth disease outbreaks in Australian livestock. Front. Environ. Sci. 2015; 3, 17.
7. Ong JBS, Chen MI-C, Cook AR, Lee HC, Lee VJ, et al. Real-Time Epidemic Monitoring and Forecasting of H1N1-2009 Using Influenza-Like Illness from General Practice and Family Doctor Clinics in Singapore. PLoS ONE. 2010; 5(4): e10036. doi: 10.1371/journal.pone.0010036 pmid: 20418945
8. Shaman J, Karspeck A, Forecasting seasonal outbreaks of influenza. PNAS. 2012; 109, 20425–20430. doi: 10.1073/pnas.1208772109 pmid: 23184969
9. Reis J, Shaman J, Retrospective Parameter Estimation and Forecast of Respiratory Syncytial Virus in the United States. PLoS Comput. Biol. 2016; 12(10): e1005133. doi: 10.1371/journal.pcbi.1005133 pmid: 27716828
10. Zimmer C, Yaesoubi R, Cohen T, A Likelihood Approach for Real-Time Calibration of Stochastic Compartmental Epidemic Models. PLoS Comput. Biol. 2017; 13(1): e1005257. doi: 10.1371/journal.pcbi.1005257 pmid: 28095403
11. Jewell CP, Keeling MJ, Roberts GO, Predicting undetected infections during the 2007 foot-and-mouth disease outbreak. J. R. Soc. Interface. 2009a; 6, 1145–1151.
12. Jewell CP, Kypraios T, Neal P, Roberts GO, Bayesian analysis for emerging infectious diseases. Bayesian Anal. 2009b; 4, 465–496.
13. Anderson I, Foot and Mouth Disease 2001: Lessons to be Learned Inquiry Report. London: The Stationery Office; 2002.
14. Muroga N, Hayama Y, Yamamoto T, Kurogi A, Tsuda T, Tsuitsui T, The 2010 foot-and-mouth disease epidemic in Japan. J. Vet. Med. Sci. 2012; 74, 399–404. pmid: 22075710
15. Geospatial Information Authority of Japan (GSI) Municipalities of Japan. 2014. Available from http://www.gsi.go.jp/common/000136162.pdf. Cited: 19 June 2016.
16. Hayama Y, Kimura Y, Yamamoto T, Kobayashi S, Tsutsui T, Potential risk associated with animal culling and disposal during the foot-and-mouth disease epidemic in Japan in 2010. Res. Vet. Sci. 2015; 102, 228–230. doi: 10.1016/j.rvsc.2015.08.017 pmid: 26412549
17. Nishiura H, Omori R, An Epidemiological Analysis of the Foot-and-Mouth Disease Epidemic in Miyazaki, Japan, 2010. Trans. Bound. Emer. Dis. 2010; 57, 396–403.
18. Li S-L, Bjørnstad ON, Ferrari MJ, Mummah R, Runge MC, Fonnesbeck CJ, et al. Essential information: uncertainty and optimal control of Ebola outbreaks. PNAS. 2017; doi: 10.1073/pnas.1617482114 pmid: 28507121
19. Department for Environment, Food & Rural Affairs and Animal Health and Veterinary Laboratories Agency (DEFRA). Contingency Plan for Exotic Notifiable Diseases of Animals. 2014; Available from https://www.gov.uk/government/publications/contingency-plan-for-exotic-notifiable-diseases-of-animals. Cited: 15 December 2015.
20. Animal and Plant Health Inspection Service (APHIS) Foot-and-Mouth Disease Response Plan: The Red Book. Washington, D.C: United States Department of Agriculture Animal and Plant Health Inspection Service Veterinary Services; 2014.
21. WHO expert committee on smallpox WHO Tech. Rep. Ser. No. 283; 1964.
22. Langwig KE, Voyles J, Wilber WQ, Frick WF, Murray KA, Bolker BM, et al. Context-dependent conservation responses to emerging wildlife diseases. Front. Ecol. Environ. 2015; 13, 195–202.
23. Mariner JC, House JA, Mebus CA, Sollod AE, Chibeu D, Jones BA, et al. Rinderpest eradication: appropriate technology and social innovations. Science. 2012; 337, 1309–1312. doi: 10.1126/science.1223805 pmid: 22984063
24. Shea K, Tildesley MJ, Runge MC, Fonnesbeck CJ, Ferrari MJ, Adaptive management and the value of information: learning via intervention in epidemiology. PLoS Biol. 2014; 12, e1001970. doi: 10.1371/journal.pbio.1001970 pmid: 25333371
25. Dimitrov NB, Goll S, Hupert N, Pourbohloul B, Meyers LA, Optimizing Tactics for Use of the U.S. Antiviral Strategic National Stockpile for Pandemic Influenza. PLoS ONE. 2011; 6 (1), e16094. doi: 10.1371/journal.pone.0016094 pmid: 21283514
26. Tildesley MJ, Deardon R, Savill NJ, Bessell PR, Brooks SP, Woolhouse MEJ, et al. Accuracy of models for the 2001 foot-and-mouth epidemic. Proc. R. Soc. B. 2008; 275, 1459–1468. doi: 10.1098/rspb.2008.0006 pmid: 18364313
27. European Union (EU) Council Directive 2003/85/EC of 29 September 2003 on Community measures for the control of foot-and-mouth disease repealing Directive 85/511/EEC and Decisions 89/531/EEC and 91/665/EEC and amending Directive 92/46/EEC. Official Journal of the European Union. L 306, Volume 46, 22 November 2003, Brussels, 1–87. Available from http://extwprlegs1.fao.org/docs/pdf/eur40556.pdf. Cited: 11 June 2018.
28. Japanese Ministry of Agriculture, Forestry and Fisheries (MAFF) Act on Domestic Animal Infectious Diseases Control. 2016. Available from http://www.maff.go.jp/e/japan_food/fsafe_aphealth/index.html. Cited 11 June 2018.
29. Probert WJM, Jewell CP, Werkman M, Fonnesbeck CJ, Goto Y, Runge MC, et al. Data from: Real-time decision-making during emergency disease outbreaks. Dryad Digital Repository. 2018; https://doi.org/10.5061/dryad.gr656gk
30. Haario H, Saksman E, Tamminen J, An adaptive Metropolis algorithm. Bernoulli. 2001; 7, 223–242.