Evidence map›Paper›PMID 31056048›Full record

ArticlePhilosophical transactions of the Royal Society of London. Series B, Biological sciences2019

Critical transitions in malaria transmission models are consistently generated by superinfection.

David Alonso, Andy Dobson, Mercedes Pascual

Open access · bronzeAbstract read
In one paragraph

Article in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
2.4field-weighted citation impact, top 12% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 24 citations in OpenAlex.

  1. Article
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  3. Article
  4. Review
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  6. Article
  7. An immune memory-structured SIS epidemiological model for hyperdiverse pathogens.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  8. Article
  9. Contact tracing-induced Allee effect in disease dynamics.Journal of theoretical biology · 2022
    Article
  10. Article
  11. Detection, forecasting and control of infectious disease epidemics: modelling outbreaks in humans, animals and plants.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2019
    Article
  12. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 2 countries.

David Alonso1 Theoretical and Computational Ecology, Center for Advanced Studies (CEAB-CSIC) , Blanes , Spain.
Andy Dobson2 Ecology and Evolutionary Biology, Eno Hall, Princeton University , NJ 08540 , USA.
Mercedes Pascual3 Santa Fe Institute , Hyde Park Road, Santa Fe, NM , USA.
Santa Fe Institute · USCentre d'Estudis Avançats de Blanes · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The 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 a malaria model that provides for vital dynamics in the vector and the possibility of super-infection 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'.

Indexed as

AnimalsCulicidaeHumansMalariaModels, StatisticalMosquito VectorsPopulation DynamicsSuperinfectionalternative steady statesbackward bifurcationcritical transitionshysteresis in malaria modelmalaria dynamicsmalaria superinfection

Identifiers

PMID31056048
PMCPMC6553601
OpenAlexW2951141074

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.