publication . Preprint . 2018

Improved state-level influenza activity nowcasting in the United States leveraging Internet-based data sources and network approaches via ARGONet

Lu, Fred S.; Hattab, Mohammad W.; Clemente, Leonardo; Santillana, Mauricio;
Open Access
  • Published: 14 Jun 2018
  • Publisher: Cold Spring Harbor Laboratory
Abstract
<jats:title>Abstract</jats:title><jats:p>In the presence of population-level health threats, precision public health approaches seek to provide the right intervention to the right population at the right time. Accurate real-time surveillance methodologies that can estimate infectious disease activity ahead of official healthcare-based reports, in relevant spatial resolutions, are critical to eventually achieve this goal. We introduce a novel methodological framework for this task which dynamically combines two distinct flu tracking techniques, using ensemble machine learning approaches, to achieve improved flu activity estimates at the state level in the US. The...
Related Organizations
26 references, page 1 of 2

1. Collins FS, Varmus H. A new initiative on precision medicine. New England Journal of Medicine. 2015;372(9):793{795.

2. Khoury MJ, Iademarco MF, Riley WT. Precision public health for the era of precision medicine. American journal of preventive medicine. 2016;50(3):398{401.

3. Disease Burden of Influenza | Seasonal Influenza (Flu) | CDC; 2018. https://www.cdc.gov/flu/ about/disease/burden.htm.

4. Overview of Influenza Surveillance in the United States | Seasonal Influenza (Flu) | CDC; 2017. https://www.cdc.gov/flu/weekly/overview.htm.

5. Yang S, Santillana M, Brownstein JS, Gray J, Richardson S, Kou SC. Using electronic health records and Internet search information for accurate influenza forecasting. BMC Infect Dis. 2017;17(1):332.

6. Yang S, Santillana M, Kou SC. Accurate estimation of influenza epidemics using Google search data via ARGO. Proc Natl Acad Sci U S A. 2015;112(47):14473{14478.

7. Brooks LC, Farrow DC, Hyun S, Tibshirani RJ, Rosenfeld R. Flexible Modeling of Epidemics with an Empirical Bayes Framework. PLoS Comput Biol. 2015;11(8):e1004382.

8. Yang W, Karspeck A, Shaman J. Comparison of filtering methods for the modeling and retrospective forecasting of influenza epidemics. PLoS Comput Biol. 2014;10(4):e1003583.

9. Gog JR, Ballesteros S, Viboud C, Simonsen L, Bjornstad ON, Shaman J, et al. Spatial Transmission of 2009 Pandemic Influenza in the US. PLoS Comput Biol. 2014;10(6):e1003635.

10. Yang W, Lipsitch M, Shaman J. Inference of seasonal and pandemic influenza transmission dynamics. Proc Natl Acad Sci U S A. 2015;112(9):2723{2728.

11. Viboud C, Bj rnstad ON, Smith DL, Simonsen L, Miller MA, Grenfell BT. Synchrony, waves, and spatial hierarchies in the spread of influenza. Science. 2006;312(5772):447{451. [OpenAIRE]

12. Charu V, Zeger S, Gog J, Bj rnstad ON, Kissler S, Simonsen L, et al. Human mobility and the spatial transmission of influenza in the United States. PLoS Comput Biol. 2017;13(2):e1005382.

13. Davidson MW, Haim DA, Radin JM. Using networks to combine \big data" and traditional surveillance to improve influenza predictions. Sci Rep. 2015;5:8154.

14. Zou B, Lampos V, Cox I. Multi-Task Learning Improves Disease Models from Web Search. In: Proceedings of the 2018 World Wide Web Conference. International World Wide Web Conferences Steering Committee; 2018. p. 87{96.

15. Lampos V, Miller AC, Crossan S, Stefansen C. Advances in nowcasting influenza-like illness rates using search query logs. Sci Rep. 2015;5:12760.

26 references, page 1 of 2
Abstract
<jats:title>Abstract</jats:title><jats:p>In the presence of population-level health threats, precision public health approaches seek to provide the right intervention to the right population at the right time. Accurate real-time surveillance methodologies that can estimate infectious disease activity ahead of official healthcare-based reports, in relevant spatial resolutions, are critical to eventually achieve this goal. We introduce a novel methodological framework for this task which dynamically combines two distinct flu tracking techniques, using ensemble machine learning approaches, to achieve improved flu activity estimates at the state level in the US. The...
Related Organizations
26 references, page 1 of 2

1. Collins FS, Varmus H. A new initiative on precision medicine. New England Journal of Medicine. 2015;372(9):793{795.

2. Khoury MJ, Iademarco MF, Riley WT. Precision public health for the era of precision medicine. American journal of preventive medicine. 2016;50(3):398{401.

3. Disease Burden of Influenza | Seasonal Influenza (Flu) | CDC; 2018. https://www.cdc.gov/flu/ about/disease/burden.htm.

4. Overview of Influenza Surveillance in the United States | Seasonal Influenza (Flu) | CDC; 2017. https://www.cdc.gov/flu/weekly/overview.htm.

5. Yang S, Santillana M, Brownstein JS, Gray J, Richardson S, Kou SC. Using electronic health records and Internet search information for accurate influenza forecasting. BMC Infect Dis. 2017;17(1):332.

6. Yang S, Santillana M, Kou SC. Accurate estimation of influenza epidemics using Google search data via ARGO. Proc Natl Acad Sci U S A. 2015;112(47):14473{14478.

7. Brooks LC, Farrow DC, Hyun S, Tibshirani RJ, Rosenfeld R. Flexible Modeling of Epidemics with an Empirical Bayes Framework. PLoS Comput Biol. 2015;11(8):e1004382.

8. Yang W, Karspeck A, Shaman J. Comparison of filtering methods for the modeling and retrospective forecasting of influenza epidemics. PLoS Comput Biol. 2014;10(4):e1003583.

9. Gog JR, Ballesteros S, Viboud C, Simonsen L, Bjornstad ON, Shaman J, et al. Spatial Transmission of 2009 Pandemic Influenza in the US. PLoS Comput Biol. 2014;10(6):e1003635.

10. Yang W, Lipsitch M, Shaman J. Inference of seasonal and pandemic influenza transmission dynamics. Proc Natl Acad Sci U S A. 2015;112(9):2723{2728.

11. Viboud C, Bj rnstad ON, Smith DL, Simonsen L, Miller MA, Grenfell BT. Synchrony, waves, and spatial hierarchies in the spread of influenza. Science. 2006;312(5772):447{451. [OpenAIRE]

12. Charu V, Zeger S, Gog J, Bj rnstad ON, Kissler S, Simonsen L, et al. Human mobility and the spatial transmission of influenza in the United States. PLoS Comput Biol. 2017;13(2):e1005382.

13. Davidson MW, Haim DA, Radin JM. Using networks to combine \big data" and traditional surveillance to improve influenza predictions. Sci Rep. 2015;5:8154.

14. Zou B, Lampos V, Cox I. Multi-Task Learning Improves Disease Models from Web Search. In: Proceedings of the 2018 World Wide Web Conference. International World Wide Web Conferences Steering Committee; 2018. p. 87{96.

15. Lampos V, Miller AC, Crossan S, Stefansen C. Advances in nowcasting influenza-like illness rates using search query logs. Sci Rep. 2015;5:12760.

26 references, page 1 of 2
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