ArticleEpidemiology and infection2018
Assessing the relationship between epidemic growth scaling and epidemic size: The 2014-16 Ebola epidemic in West Africa.
Article in Epidemiology and infection, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed, 12 citations in OpenAlex.
- A Class of Deterministic and Stochastic Fractional Epidemic Models with Vaccination.Computational and mathematical methods in medicine · 2022Article
- Forecasting the final disease size: comparing calibrations of Bertalanffy-Pütter models.Epidemiology and infection · 2020Article
- COVID-19, flattening the curve, and Benford's law.Physica A · 2020Article
- Short-term Forecasts of the COVID-19 Epidemic in Guangdong and Zhejiang, China: February 13-23, 2020.Journal of clinical medicine · 2020Article
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Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
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Abstract
We assess the relationship between epidemic size and the scaling of epidemic growth of Ebola epidemics at the level of administrative areas during the 2014-16 Ebola epidemic in West Africa. For this purpose, we quantify growth scaling parameters from the ascending phase of Ebola outbreaks comprising at least 7 weeks of epidemic growth. We then study how these parameters are associated with observed epidemic sizes. For validation purposes, we also analyse two historic Ebola outbreaks. We find a high monotonic association between the scaling of epidemic growth parameter and the observed epidemic size. For example, scaling of growth parameters around 0.3-0.4, 0.4-0.6 and 0.6 are associated with epidemic sizes on the order of 350-460, 460-840 and 840-2500 cases, respectively. These results are not explained by differences in epidemic onset across affected areas. We also find the relationship between the scaling of epidemic growth parameter and the observed epidemic size to be consistent for two past Ebola outbreaks in Congo (1976) and Uganda (2000). Signature features of epidemic growth could become useful to assess the risk of observing a major epidemic outbreak, generate improved diseases forecasts and enhance the predictive power of epidemic models. Our results indicate that the epidemic growth scaling parameter is a useful indicator of epidemic size, which may have significant implications to guide control of Ebola outbreaks and possibly other infectious diseases.
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