Evidence map›Paper›PMID 30586381›Full record

ArticlePLoS computational biology2018

Hosts mobility and spatial spread of Rickettsia rickettsii.

Gina Polo, Carlos Mera Acosta, Marcelo B Labruna, Fernando Ferreira, Dirk Brockmann

Abstract read
In one paragraph

Article in PLoS computational biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Bayesian spatial modeling of COVID-19 case-fatality rate inequalities.Spatial and spatio-temporal epidemiology · 2022
    Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Epidemiology of capybara-associated Brazilian spotted fever.PLoS neglected tropical diseases · 2019
    Article
  10. 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

5 authors.

Gina PoloLaboratory of Epidemiology and Biostatistics. Department of Preventive Veterinary Medicine and Animal Health. University of São Paulo, São Paulo, Brazil.ORCID 0000-0001-5569-7392
Carlos Mera AcostaPhysics Institute, University of São Paulo, São Paulo, Brazil.
Marcelo B LabrunaLaboratory of Parasitic Diseases. Department of Preventive Veterinary Medicine and Animal Health. University of São Paulo, São Paulo, Brazil.
Fernando FerreiraLaboratory of Epidemiology and Biostatistics. Department of Preventive Veterinary Medicine and Animal Health. University of São Paulo, São Paulo, Brazil.
Dirk BrockmannRobert Koch-Institute, Berlin, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There are a huge number of pathogens with multi-component transmission cycles, involving amplifier hosts, vectors or complex pathogen life cycles. These complex systems present challenges in terms of modeling and policy development. A lethal tick-borne infectious disease, the Brazilian Spotted Fever (BSF), is a relevant example of that. The current increase of human cases of BSF has been associated with the presence and expansion of the capybara Hydrochoerus hydrochaeris, amplifier host for the agent Rickettsia rickettsii and primary host for the tick vector Amblyomma sculptum. We introduce a stochastic dynamical model that captures the spatial distribution of capybaras and ticks to gain a better understanding of the spatial spread of the R. rickettsii and potentially predict future epidemic outcomes. We implemented a reaction-diffusion process in which individuals were divided into classes denoting their state with respect to the disease. The model considered bidirectional movements between base and destination locations limited by the carrying capacity of the environment. We performed systematic stochastic simulations and numerical analysis of the model and investigate the impact of potential interventions to mitigate the spatial spread of the disease. The mobility of capybaras and their attached ticks was significantly influenced by the birth rate of capybaras and therefore, disease propagation velocity was higher in places with higher carrying capacity. Some geographical barriers, generated for example by riparian reforesting, can impede the spatial spread of BSF. The results of this work will allow the formulation of public actions focused on the prevention of BSF human cases.

Indexed as

Models, BiologicalAnimalsArachnid VectorsBrazilComputational BiologyComputer SimulationConservation of Natural ResourcesHost Microbial InteractionsHumansIxodidaeRickettsia rickettsiiRocky Mountain Spotted FeverRodentiaStochastic ProcessesZoonoses

Identifiers

PMID30586381
PMCPMC6324817

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.