Evidence map›Paper›PMID 34587957›Full record

ArticleBMC medicine2021

Estimating the annual dengue force of infection from the age of reporting primary infections across urban centres in endemic countries.

Joseph R Biggs, Ava Kristy Sy, Katharine Sherratt, Oliver J Brady, Adam J Kucharski, Sebastian Funk, Mary Anne Joy Reyes, Mary Ann Quinones, William Jones-Warner, Ferchito L Avelino and 7 more

Abstract read
In one paragraph

Article in BMC medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. Reconciling heterogeneous dengue virus infection risk estimates from different study designs.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  5. Article
  6. Article
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  8. From serological surveys to disease burden: a modelling pipeline for Chagas disease.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023
    Article
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  10. Review
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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

17 authors.

Joseph R Biggs *Department of Infection Biology, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK. Joseph.Biggs1@lshtm.ac.uk.ORCID 0000-0001-7273-874X
Ava Kristy Sy *Department of Virology, Research Institute for Tropical Medicine, Manila, Philippines.
Katharine SherrattDepartment of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK.
Oliver J BradyDepartment of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK.
Adam J KucharskiDepartment of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK.
Sebastian FunkDepartment of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK.
Mary Anne Joy ReyesDepartment of Virology, Research Institute for Tropical Medicine, Manila, Philippines.
Mary Ann QuinonesDepartment of Virology, Research Institute for Tropical Medicine, Manila, Philippines.
William Jones-WarnerDepartment of Infection Biology, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK.
Ferchito L AvelinoDepartment of Health, Philippine Epidemiology Bureau, Manila, Philippines.
Nemia L SucalditoDepartment of Health, Philippine Epidemiology Bureau, Manila, Philippines.
Amado O TandocDepartment of Virology, Research Institute for Tropical Medicine, Manila, Philippines.
Eva Cutiongco-de la PazInstitute of Human Genetics, National Institute of Health, University of the Philippines, Manila, Philippines.
Maria Rosario Z CapedingDengue Study Group, Research Institute for Tropical Medicine, Manila, Philippines.
Carmencita D PadillaInstitute of Human Genetics, National Institute of Health, University of the Philippines, Manila, Philippines.
Julius Clemence R HafallaDepartment of Infection Biology, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK.
Martin L HibberdDepartment of Infection Biology, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK.

Funding

Medical Research Council MR/V031112/1Wellcome Trust 206250/Z/17/ZWellcome Trust 206471/Z/17/ZWellcome Trust 210758/Z/18/Z
6 · The paper itself

Abstract

backgroundStratifying dengue risk within endemic countries is crucial for allocating limited control interventions. Current methods of monitoring dengue transmission intensity rely on potentially inaccurate incidence estimates. We investigated whether incidence or alternate metrics obtained from standard, or laboratory, surveillance operations represent accurate surrogate indicators of the burden of dengue and can be used to monitor the force of infection (FOI) across urban centres.

methodsAmong those who reported and resided in 13 cities across the Philippines, we collected epidemiological data from all dengue case reports between 2014 and 2017 (N 80,043) and additional laboratory data from a cross-section of sampled case reports (N 11,906) between 2014 and 2018. At the city level, we estimated the aggregated annual FOI from age-accumulated IgG among the non-dengue reporting population using catalytic modelling. We compared city-aggregated FOI estimates to aggregated incidence and the mean age of clinically and laboratory diagnosed dengue cases using Pearson's Correlation coefficient and generated predicted FOI estimates using regression modelling.

resultsWe observed spatial heterogeneity in the dengue average annual FOI across sampled cities, ranging from 0.054 [0.036-0.081] to 0.249 [0.223-0.279]. Compared to FOI estimates, the mean age of primary dengue infections had the strongest association (ρ -0.848, p value<0.001) followed by the mean age of those reporting with warning signs (ρ -0.642, p value 0.018). Using regression modelling, we estimated the predicted annual dengue FOI across urban centres from the age of those reporting with primary infections and revealed prominent spatio-temporal heterogeneity in transmission intensity.

conclusionsWe show the mean age of those reporting with their first dengue infection or those reporting with warning signs of dengue represent superior indicators of the dengue FOI compared to crude incidence across urban centres. Our work provides a framework for national dengue surveillance to routinely monitor transmission and target control interventions to populations most in need.

Indexed as

DengueCitiesHumansIncidenceLaboratoriesPhilippinesDengueFlavivirusPhilippinesPrimarySerologySurveillance

Identifiers

PMID34587957
PMCPMC8482604

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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.