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Using Hawkes Processes to model imported and local malaria cases in near-elimination settings

  • H. Juliette T. Unwin*
  • , Isobel Routledge
  • , Seth Flaxman
  • , Marian-Andrei Rizoiu
  • , Shengjie Lai
  • , Justin Cohen
  • , Daniel J. Weiss
  • , Swapnil Mishra
  • , Samir Bhatt
  • *Corresponding author for this work

Research output: Contribution to journal › Article (Academic Journal) › peer-review

22 Citations (Scopus)

Abstract

Developing new methods for modelling infectious diseases outbreaks is important for monitoring transmission and developing policy. In this paper we propose using semi-mechanistic Hawkes Processes for modelling malaria transmission in near-elimination settings. Hawkes Processes are well founded mathematical methods that enable us to combine the benefits of both statistical and mechanistic models to recreate and forecast disease transmission beyond just malaria outbreak scenarios. These methods have been successfully used in numerous applications such as social media and earthquake modelling, but are not yet widespread in epidemiology. By using domain-specific knowledge, we can both recreate transmission curves for malaria in China and Eswatini and disentangle the proportion of cases which are imported from those that are community based.
Original languageEnglish
Article numbere1008830
JournalPLOS Computational Biology
Volume17
Issue number4
DOIs
Publication statusPublished - 1 Apr 2021

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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