Mathematical modeling of the West Africa Ebola epidemic

  1. Jean-Paul Chretien  Is a corresponding author
  2. Steven Riley
  3. Dylan B George
  1. Armed Forces Health Surveillance Center, United States
  2. Imperial College London, United Kingdom
  3. United States Department of Health and Human Services, United States

Abstract

As of November 2015, the Ebola virus disease (EVD) epidemic that began in West Africa in late 2013 is waning. The human toll includes more than 28,000 Ebola virus disease (EVD) cases and 11,000 deaths in Guinea, Liberia, and Sierra Leone, the most heavily-affected countries. We reviewed 66 mathematical modeling studies of the EVD epidemic published in the peer-reviewed literature to assess the key uncertainties models addressed, data used for modeling, public sharing of data and results, and model performance. Based on the review, we suggest steps to improve the use of modeling in future public health emergencies.

Article and author information

Author details

  1. Jean-Paul Chretien

    Division of Integrated Biosurveillance, Armed Forces Health Surveillance Center, Silver Spring, United States
    For correspondence
    JPChretien@gmail.com
    Competing interests
    The authors declare that no competing interests exist.
  2. Steven Riley

    MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  3. Dylan B George

    Biomedical Advanced Research and Development Authority, United States Department of Health and Human Services, Washington, DC, United States
    Competing interests
    The authors declare that no competing interests exist.

Reviewing Editor

  1. Mark Jit, London School of Hygiene & Tropical Medicine, and Public Health England, United Kingdom

Version history

  1. Received: June 2, 2015
  2. Accepted: November 19, 2015
  3. Accepted Manuscript published: December 8, 2015 (version 1)
  4. Version of Record published: February 16, 2016 (version 2)

Copyright

© 2015, Chretien et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 6,275
    views
  • 1,035
    downloads
  • 100
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Jean-Paul Chretien
  2. Steven Riley
  3. Dylan B George
(2015)
Mathematical modeling of the West Africa Ebola epidemic
eLife 4:e09186.
https://doi.org/10.7554/eLife.09186

Share this article

https://doi.org/10.7554/eLife.09186

Further reading

    1. Cancer Biology
    2. Epidemiology and Global Health
    Lijun Bian, Zhimin Ma ... Guangfu Jin
    Research Article

    Background:

    Age is the most important risk factor for cancer, but aging rates are heterogeneous across individuals. We explored a new measure of aging-Phenotypic Age (PhenoAge)-in the risk prediction of site-specific and overall cancer.

    Methods:

    Using Cox regression models, we examined the association of Phenotypic Age Acceleration (PhenoAgeAccel) with cancer incidence by genetic risk group among 374,463 participants from the UK Biobank. We generated PhenoAge using chronological age and nine biomarkers, PhenoAgeAccel after subtracting the effect of chronological age by regression residual, and an incidence-weighted overall cancer polygenic risk score (CPRS) based on 20 cancer site-specific polygenic risk scores (PRSs).

    Results:

    Compared with biologically younger participants, those older had a significantly higher risk of overall cancer, with hazard ratios (HRs) of 1.22 (95% confidence interval, 1.18–1.27) in men, and 1.26 (1.22–1.31) in women, respectively. A joint effect of genetic risk and PhenoAgeAccel was observed on overall cancer risk, with HRs of 2.29 (2.10–2.51) for men and 1.94 (1.78–2.11) for women with high genetic risk and older PhenoAge compared with those with low genetic risk and younger PhenoAge. PhenoAgeAccel was negatively associated with the number of healthy lifestyle factors (Beta = –1.01 in men, p<0.001; Beta = –0.98 in women, p<0.001).

    Conclusions:

    Within and across genetic risk groups, older PhenoAge was consistently related to an increased risk of incident cancer with adjustment for chronological age and the aging process could be retarded by adherence to a healthy lifestyle.

    Funding:

    This work was supported by the National Natural Science Foundation of China (82230110, 82125033, 82388102 to GJ; 82273714 to MZ); and the Excellent Youth Foundation of Jiangsu Province (BK20220100 to MZ).

    1. Epidemiology and Global Health
    Yuchen Zhang, Yitang Sun ... Kaixiong Ye
    Research Article

    Background:

    Circulating omega-3 and omega-6 polyunsaturated fatty acids (PUFAs) have been associated with various chronic diseases and mortality, but results are conflicting. Few studies examined the role of omega-6/omega-3 ratio in mortality.

    Methods:

    We investigated plasma omega-3 and omega-6 PUFAs and their ratio in relation to all-cause and cause-specific mortality in a large prospective cohort, the UK Biobank. Of 85,425 participants who had complete information on circulating PUFAs, 6461 died during follow-up, including 2794 from cancer and 1668 from cardiovascular disease (CVD). Associations were estimated by multivariable Cox proportional hazards regression with adjustment for relevant risk factors.

    Results:

    Risk for all three mortality outcomes increased as the ratio of omega-6/omega-3 PUFAs increased (all Ptrend <0.05). Comparing the highest to the lowest quintiles, individuals had 26% (95% CI, 15–38%) higher total mortality, 14% (95% CI, 0–31%) higher cancer mortality, and 31% (95% CI, 10–55%) higher CVD mortality. Moreover, omega-3 and omega-6 PUFAs in plasma were all inversely associated with all-cause, cancer, and CVD mortality, with omega-3 showing stronger effects.

    Conclusions:

    Using a population-based cohort in UK Biobank, our study revealed a strong association between the ratio of circulating omega-6/omega-3 PUFAs and the risk of all-cause, cancer, and CVD mortality.

    Funding:

    Research reported in this publication was supported by the National Institute of General Medical Sciences of the National Institute of Health under the award number R35GM143060 (KY). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.