CDC grand rounds: Modeling and public health decision-making

Morbidity and Mortality Weekly Report

Volumn 65, Issue 48, 2016, Pages 1374-1375

  Fischer, Leah S ^a   Santibanez, Scott ^a   Hatchett, Richard J ^b   Jernigan, Daniel B ^c   Meyers, Lauren Ancel ^d   Thorpe, Phoebe G ^c   Meltzer, Martin I ^a  

^a NATIONAL CENTER FOR EMERGING AND ZOONOTIC INFECTIOUS DISEASES   (United States)

^b U S DEPARTMENT OF HEALTH AND HUMAN SERVICES   (United States)

^c CENTERS FOR DISEASE CONTROL AND PREVENTION   (United States)

^d UNIVERSITY OF TEXAS AT AUSTIN   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMMUNICABLE DISEASES; DECISION SUPPORT SYSTEM; DISASTER PLANNING; DISEASE OUTBREAKS; EMERGENCY; HUMAN; INTERPERSONAL COMMUNICATION; ORGANIZATION AND MANAGEMENT; PUBLIC HEALTH; PUBLIC HEALTH SERVICE; THEORETICAL MODEL; UNITED STATES;

CENTERS FOR DISEASE CONTROL AND PREVENTION (U.S.); COMMUNICABLE DISEASES; COMMUNICATION; DECISION SUPPORT TECHNIQUES; DISASTER PLANNING; DISEASE OUTBREAKS; EMERGENCIES; HUMANS; MODELS, THEORETICAL; PUBLIC HEALTH; UNITED STATES;

EID: 85005939436     PISSN: 01492195     EISSN: 1545861X     Source Type: Journal    
DOI: 10.15585/mmwr.mm6548a4     Document Type: Note

References (20)

1. Meltzer MI, Atkins CY, Santibanez S, et al. Estimating the future number of cases in the Ebola epidemic—Liberia and Sierra Leone, 2014–2015. MMWR Surveill Summ 2014;63(1).
2. Fraser C, Riley S, Anderson RM, Ferguson NM. Factors that make an infectious disease outbreak controllable. Proc Natl Acad Sci U S A 2004;101:6146–51. http://dx.doi.org/10.1073/pnas.0307506101
3. Meyers LA, Pourbohloul B, Newman MEJ, Skowronski DM, Brunham RC. Network theory and SARS: predicting outbreak diversity. J Theor Biol 2005;232:71–81. http://dx.doi.org/10.1016/j.jtbi.2004.07.026
4. 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:e16094. http://dx.doi.org/10.1371/journal.pone.0016094
5. Lipsitch M, Finelli L, Heffernan RT, Leung GM, Redd SC; 2009 H1n1 Surveillance Group. Improving the evidence base for decision making during a pandemic: the example of 2009 influenza A/H1N1. Biosecur Bioterror 2011;9:89–115.
6. Glasser JW, Hupert N, McCauley MM, Hatchett R. Modeling and public health emergency responses: lessons from SARS. Epidemics 2011;3:32–7. http://dx.doi.org/10.1016/j.epidem.2011.01.001
7. Cauchemez S, Epperson S, Biggerstaff M, Swerdlow D, Finelli L, Ferguson NM. Using routine surveillance data to estimate the epidemic potential of emerging zoonoses: application to the emergence of US swine origin influenza A H3N2v virus. PLoS Med 2013;10:e1001399. http://dx.doi.org/10.1371/journal.pmed.1001399
8. Biggerstaff M, Alper D, Dredze M, et al.; Influenza Forecasting Contest Working Group. Results from the Centers for Disease Control and Prevention’s predict the 2013–2014 Influenza Season Challenge. BMC Infect Dis 2016;16:357. http://dx.doi.org/10.1186/s12879-016-1669-x
9. CDC. CDC announces winner of the ‘Predict the Influenza Season Challenge.’ Atlanta, GA: US Department of Health and Human Services, CDC; 2015. http://www.cdc.gov/flu/news/predict-flu-challenge-winner.htm
10. Association of Public Health Laboratories. Influenza virologic surveillance right size roadmap. Silver Spring, MD: Association of Public Health Laboratories; 2013. https://www.aphl.org/AboutAPHL/publications/Documents/ID_July2013_Influenza-Virologic-Surveillance-Right-Size-Roadmap.pdf
11. Meltzer MI, Santibanez S, Fischer LS, et al. Modeling in real time during the Ebola response. MMWR Suppl 2016;65:85–9.
12. Rainisch G, Shankar M, Wellman M, Merlin T, Meltzer MI. Regional spread of Ebola virus, West Africa, 2014. Emerg Infect Dis 2015;21:444–7. http://dx.doi.org/10.3201/eid2103.141845
13. Scarpino SV, Iamarino A, Wells C, et al. Epidemiological and viral genomic sequence analysis of the 2014 Ebola outbreak reveals clustered transmission. Clin Infect Dis 2015;60:1079–82.
14. Shrestha SS, Swerdlow DL, Borse RH, et al. Estimating the burden of 2009 pandemic influenza A (H1N1) in the United States (April 2009– April 2010). Clin Infect Dis 2011;52(Suppl 1):S75–82. http://dx.doi.org/10.1093/cid/ciq012
15. Reed C, Angulo FJ, Swerdlow DL, et al. Estimates of the prevalence of pandemic (H1N1) 2009, United States, April–July 2009. Emerg Infect Dis 2009;15:2004–7. http://dx.doi.org/10.3201/eid1512.091413
16. Hatchett RJ, Mecher CE, Lipsitch M. Public health interventions and epidemic intensity during the 1918 influenza pandemic. Proc Natl Acad Sci U S A 2007;104:7582–7. http://dx.doi.org/10.1073/pnas.0610941104
17. Medlock J, Meyers LA, Galvani A. Optimizing allocation for a delayed influenza vaccination campaign. PLoS Curr 2009;1:RRN1134.
18. Rainisch G, Asher J, George D, et al. Estimating Ebola treatment needs, United States [letter]. Emerg Infect Dis 2015;21:1273–5. http://dx.doi.org/10.3201/eid2107.150286
19. Borse RH, Shrestha SS, Fiore AE, et al. Effects of vaccine program against pandemic influenza A(H1N1) virus, United States, 2009–2010. Emerg Infect Dis 2013;19:439–48. http://dx.doi.org/10.3201/eid1903.120394
20. Kostova D, Reed C, Finelli L, et al. Influenza illness and hospitalizations averted by influenza vaccination in the United States, 2005–2011. PLoS One 2013;8:e66312 http://dx.doi.org/10.1371/journal.pone.0066312.