Evidence map›Paper›PMID 39146377›Full record

ArticlePLoS computational biology2024

Quantifying the risk of spillover reduction programs for human health.

Scott L Nuismer, Andrew J Basinski, Courtney L Schreiner, Evan A Eskew, Elisabeth Fichet-Calvet, Christopher H Remien

Abstract read
In one paragraph

Article in PLoS computational biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. How to write a scientific paper in fifteen steps.PLoS computational biology · 2025
    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

6 authors.

Scott L NuismerDepartment of Biological Sciences, University of Idaho, Moscow, Idaho, United States of America.ORCID 0000-0001-9817-0056
Andrew J BasinskiInstitute for Interdisciplinary Data Sciences, University of Idaho, Moscow, Idaho, United States of America.
Courtney L SchreinerDepartment of Ecology and Evolutionary Biology, University of Tennessee, Knoxville, Tennessee, United States of America.
Evan A EskewInstitute for Interdisciplinary Data Sciences, University of Idaho, Moscow, Idaho, United States of America.
Elisabeth Fichet-CalvetBernhard Nocht Institute for Tropical Medicine, Hamburg, Germany.
Christopher H RemienDepartment of Mathematics and Statistical Science, University of Idaho, Moscow, Idaho, United States of America.

Funding

COLLABORATIVE RESEARCH: A MATHEMATICAL THEORY OF TRANSMISSIBLE VACCINES R01GM122079 · NIGMS · UNIVERSITY OF IDAHO · PI SCOTT L NUISMER · 2016 to 2026
$2.2M
NIGMS NIH HHS R01 GM122079
6 · The paper itself

Abstract

Reducing spillover of zoonotic pathogens is an appealing approach to preventing human disease and minimizing the risk of future epidemics and pandemics. Although the immediate human health benefit of reducing spillover is clear, over time, spillover reduction could lead to counterintuitive negative consequences for human health. Here, we use mathematical models and computer simulations to explore the conditions under which unanticipated consequences of spillover reduction can occur in systems where the severity of disease increases with age at infection. Our results demonstrate that, because the average age at infection increases as spillover is reduced, programs that reduce spillover can actually increase population-level disease burden if the clinical severity of infection increases sufficiently rapidly with age. If, however, immunity wanes over time and reinfection is possible, our results reveal that negative health impacts of spillover reduction become substantially less likely. When our model is parameterized using published data on Lassa virus in West Africa, it predicts that negative health outcomes are possible, but likely to be restricted to a small subset of populations where spillover is unusually intense. Together, our results suggest that adverse consequences of spillover reduction programs are unlikely but that the public health gains observed immediately after spillover reduction may fade over time as the age structure of immunity gradually re-equilibrates to a reduced force of infection.

Indexed as

Computer SimulationZoonosesAfrica, WesternAnimalsComputational BiologyDisease OutbreaksHumansLassa FeverPublic HealthRisk Assessment

Identifiers

PMID39146377
PMCPMC11349207

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.