Evidence map›Paper›PMID 42860967›Full record

ArticleTheoretical ecology2026

The effects of spatial structure on a host-parasite model with horizontal and vertical transmission.

Jack Woodruff, Alex Best

Abstract read
In one paragraph

Article in Theoretical ecology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Jack WoodruffSchool of Mathematical and Physical Sciences, University of Sheffield, Sheffield, UK.ORCID https://orcid.org/0009-0003-2209-4036
Alex BestSchool of Mathematical and Physical Sciences, University of Sheffield, Sheffield, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Vertical transmission of an infectious disease from parent to offspring is a common transmission route in many systems. However, the majority of vertical transmission modelling has assumed a well-mixed population, and we do not know how the spatial structure present in most real-world populations will impact the dynamics of these systems. Here we investigate how spatial structure affects the dynamics of a pathogen with both horizontal and vertical transmission. We introduce a lattice model with a pair approximation that includes both local and global transmission and reproduction. We find that vertical transmission's ability to determine pathogen invasion is dependant on spatial structure. When the majority of transmission and reproduction is local, vertical transmission can destabilise a host population to cause limit cycles. Given the advantages of a pathogen having both horizontal and vertical transmission routes, we extend the model to investigate the likelihood of a mutant strain with both transmission modes outcompeting a resident strain with only horizontal transmission. In the absence of cost the mutant always invades. When there is a trade-off between vertical and horizontal transmission, the mutant emerges when the cost to the horizontal transmission rate is not too large. Depending on how the mutant appears within the host population, it may have an initial advantage over the resident strain even if it cannot outcompete in the long-term. Our work demonstrates that the importance of vertical transmission within host-parasite dynamics is preserved when spatial structure is included. Supplementary Information: The online version contains supplementary material available at https://doi.org/10.1007/s12080-026-00645-y.

Indexed as

Horizontal transmissionPair approximationSpatial structureTrade-offVertical transmission

Identifiers

PMID42860967
PMCPMC13653842

What OpenQuestion holds

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Registered trials

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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.