Evidence map›Paper›PMID 36060201›Full record

ArticleRevista panamericana de salud publica = Pan American journal of public health2022

Mathematical and statistical models for the control of mosquito-borne diseases: the experience of Costa Rica.

Paola Vásquez, Fabio Sanchez, Luis A Barboza, Yury E García, Juan G Calvo, Shu-Wei Chou-Chen, Gustavo Mery

Abstract read
In one paragraph

Article in Revista panamericana de salud publica = Pan American journal of public health, 2022. 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. 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

7 authors.

Paola VásquezUniversidad de Costa Rica San José Costa Rica Universidad de Costa Rica, San José, Costa Rica.
Fabio SanchezUniversidad de Costa Rica San José Costa Rica Universidad de Costa Rica, San José, Costa Rica.
Luis A BarbozaUniversidad de Costa Rica San José Costa Rica Universidad de Costa Rica, San José, Costa Rica.
Yury E GarcíaUniversity of California Davis DavisCalifornia United States of America University of California Davis, Davis, California, United States of America.
Juan G CalvoUniversidad de Costa Rica San José Costa Rica Universidad de Costa Rica, San José, Costa Rica.
Shu-Wei Chou-ChenUniversidad de Costa Rica San José Costa Rica Universidad de Costa Rica, San José, Costa Rica.
Gustavo MeryPan American Health Organization San José Costa Rica Pan American Health Organization, San José, Costa Rica.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To summarize the results of research conducted in Costa Rica in which mathematical and statistical methods were implemented to study the transmission dynamics of mosquito-borne diseases. Methods: Three articles with mathematical and statistical analysis on vector-borne diseases in Costa Rica were selected and reviewed. These papers show the value and relevance of using different quantitative methods to understand disease dynamics and support decision-making. Results: The results of these investigations: 1) show the impact on dengue case reports when a second pathogen emerges, such as chikungunya; 2) recover key parameters in Zika dynamics using Bayesian inference; and 3) show the use of machine learning algorithms and climatic variables to forecast the dengue relative risk in five different locations. Conclusions: Mathematical and statistical modeling enables the description of mosquito-borne disease transmission dynamics, providing quantitative information to support prevention/control methods and resource allocation planning.

Indexed as

Costa Ricamodels, theoreticalpublic healthVector-borne diseases

Identifiers

PMID36060201
PMCPMC9426954

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.