Evidence map›Paper›PMID 27704330›Full record

ArticleBulletin of mathematical biology2016

Day-to-Day Population Movement and the Management of Dengue Epidemics.

Jorge A Falcón-Lezama, Ruth A Martínez-Vega, Pablo A Kuri-Morales, José Ramos-Castañeda, Ben Adams

Abstract read
In one paragraph

Article in Bulletin of mathematical biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–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

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. The impact of novel coronavirus (2019-One health (Amsterdam, Netherlands) · 2021
    Article
  8. Article
  9. Discrete epidemic models with two time scales.Advances in difference equations · 2021
    Article
  10. Article
  11. Article
  12. Seroprevalence of dengue in school children in Mexico ages 6-17 years, 2016.Transactions of the Royal Society of Tropical Medicine and Hygiene · 2018
    Article
  13. Article
  14. 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.

Jorge A Falcón-LezamaCentro de Investigaciones sobre Enfermedades Infecciosas, Instituto Nacional de Salud Publica, Universidad 655, Colonia Sta. Maria Ahuacatitlán, Cerrada Los Pinos y Caminera. C.P., 62100, Cuernavaca, Morelos, Mexico.
Ruth A Martínez-VegaOrganizacion Latinoamericana de Fomento a la Investigacion en Salud, Calle 110 No. 21-30, Of. 604, Bucaramanga, Santander, Colombia.
Pablo A Kuri-MoralesSubsecretaría de Prevención y Promoción de la Salud, Lieja 7, 1er piso, Colonia Juárez, Del. Cuauhtémoc, C.P. 06600, Ciudad de Mexico, Mexico.
José Ramos-CastañedaCentro de Investigaciones sobre Enfermedades Infecciosas, Instituto Nacional de Salud Publica, Universidad 655, Colonia Sta. Maria Ahuacatitlán, Cerrada Los Pinos y Caminera. C.P., 62100, Cuernavaca, Morelos, Mexico.
Ben AdamsDepartment of Mathematical Sciences, University of Bath, Bath, BA27AY, UK. b.adams@bath.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dengue is a growing public health problem in tropical and subtropical cities. It is transmitted by mosquitoes, and the main strategy for epidemic prevention and control is insecticide fumigation. Effective management is, however, proving elusive. People's day-to-day movement about the city is believed to be an important factor in the epidemiological dynamics. We use a simple model to examine the fundamental roles of broad demographic and spatial structures in epidemic initiation, growth and control. We show that the key factors are local dilution, characterised by the vector-host ratio, and spatial connectivity, characterised by the extent of habitually variable movement patterns. Epidemic risk in the population is driven by the demographic groups that frequent the areas with the highest vector-host ratio, even if they only spend some of their time there. Synchronisation of epidemic trajectories in different demographic groups is governed by the vector-host ratios to which they are exposed and the strength of connectivity. Strategies for epidemic prevention and management may be made more effective if they take into account the fluctuating landscape of transmission intensity associated with spatial heterogeneity in the vector-host ratio and people's day-to-day movement patterns.

Indexed as

EpidemicsAedesAnimalsBasic Reproduction NumberDengueHuman MigrationHumansMathematical ConceptsModels, BiologicalMosquito VectorsControlDemographyEpidemic modelHost–vectorMetapopulation

Identifiers

PMID27704330
PMCPMC5069346

What OpenQuestion holds

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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.