Real Time Forecasting of Measles Using Generation-dependent Mathematical Model in Japan, 2018

In conclusion, we demonstrated a simple generation-dependent model that was able to adequately capture an observed transmission pattern of the measles outbreak in Japan, 2018. The proposed model also helped predict the future incidence and evaluate public health control measures. Polishing the forecasting model further, we can achieve an eventual routine forecast and evaluation the outbreaks while maintaining the model structure as simple as possible.
Competing Interests
The authors declare no competing interests.
Data Availability
The code snippets used for simulations and generation of figures as well as the epidemiological count data are accessible from the GitHub repository: https://github.com/aakhmetz/MeaslesJapan2018.
Corresponding Author
Hiroshi Nishiura ([e-mail])
Appendix

A. Time-varying delay function
Here we describe the fitting procedure when the delay distribution function h is a mixture of two distributions. The first distribution describes all cases whose times of illness onset are prior to a calendar time τ. In our exposition, the delay function h follows a Weibull distribution with parameters θh(0) = {μh(0), νh(0)}. The second distribution describes all cases with the time of illness onset later than a calendar time τ. It also follows a Weibull distribution with a set of parameters θh(1) = {μh(1), νh(1)}. The likelihood to describe the time delay from illness onset to laboratory confirmation is given by the formula:

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Source: PLOS Currents Outbreaks - October 15, 2018 Category: Epidemiology Authors: Andrei R. Akhmetzhanov Source Type: research