Mechanistic modelling of the large-scale Lassa fever epidemics in Nigeria from 2016 to 2019

Salihu S. Musa, Shi Zhao, Daozhou Gao, Qianying Lin, Gerardo Chowell, Daihai He

Research output: Journal article publicationJournal articleAcademic researchpeer-review

37 Citations (Scopus)


Lassa fever, also known as Lassa hemorrhagic fever, is a virus that has generated recurrent outbreaks in West Africa. We use mechanistic modelling to study the Lassa fever epidemics in Nigeria from 2016-19. Our model describes the interaction between human and rodent populations with the consideration of quarantine, isolation and hospitalization processes. Our model supports the phenomenon of forward bifurcation where the stability between disease-free equilibrium and endemic equilibrium exchanges. Moreover, our model captures well the incidence curves from surveillance data. In particular, our model is able to reconstruct the periodic rodent and human forces of infection. Furthermore, we suggest that the three major epidemics from 2016-19 can be modelled by properly characterizing the rodent (or human) force of infection while the estimated human force of infection also present similar patterns across outbreaks. Our results suggest that the initial susceptibility likely increased across the three outbreaks from 2016-19. Our results highlight the similarity of the transmission dynamics driving three major Lassa fever outbreaks in the endemic areas.

Original languageEnglish
Article number110209
Pages (from-to)1-16
Number of pages16
JournalJournal of Theoretical Biology
Publication statusPublished - 21 May 2020


  • Data fitting
  • Lassa fever
  • Mechanistic modelling
  • Stability analysis

ASJC Scopus subject areas

  • Statistics and Probability
  • Modelling and Simulation
  • General Biochemistry,Genetics and Molecular Biology
  • General Immunology and Microbiology
  • General Agricultural and Biological Sciences
  • Applied Mathematics


Dive into the research topics of 'Mechanistic modelling of the large-scale Lassa fever epidemics in Nigeria from 2016 to 2019'. Together they form a unique fingerprint.

Cite this