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Título

Critical transitions in malaria transmission models are consistently generated by superinfection

AutorAlonso, David CSIC ORCID ; Dobson, A. P.; Pascual, Mercedes
Palabras claveMalaria dynamics
Critical transitions
Alternative steady states
Malaria superinfection
Backward bifurcation
Hysteresis in malaria model
Fecha de publicación2019
EditorRoyal Society (Great Britain)
CitaciónPhilosophical Transactions of the Royal Society-B 374: 20180275 (2019)
ResumenThe history of modelling vector-borne infections essentially begins with the papers by Ross on malaria. His models assume that the dynamics of malaria can most simply be characterized by two equations that describe the prevalence of malaria in the human and mosquito hosts. This structure has formed the central core of models for malaria and most other vector-borne diseases for the past century, with additions acknowledging important aetiological details.We partially add to this tradition by describing amalaria model that provides for vital dynamics in the vector and the possibility of superinfection in the human host: reinfection of asymptomatic hosts before they have cleared a prior infection. These key features of malaria aetiology create the potential for break points in the prevalence of infected hosts, sudden transitions that seem to characterize malaria’s response to control in different locations. We show that this potential for critical transitions is a general and underappreciated feature of any model for vector-borne diseases with incomplete immunity, including the canonical Ross–McDonald model. Ignoring these details of the host’s immune response to infection can potentially lead to serious misunderstanding in the interpretation of malaria distribution patterns and the design of control schemes for other vector-borne diseases. This article is part of the theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes’. This issue is linked with the subsequent theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control’.
DescripciónEste artículo contiene 11 páginas, 6 figuras, 1 tabla.
Versión del editorhttp://dx.doi.org/10.1098/rstb.2018.0275
URIhttp://hdl.handle.net/10261/181676
ISSN0080-4622
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