BMC Medicine (Sep 2021)

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,
  • Nemia L. Sucaldito,
  • Amado O. Tandoc,
  • Eva Cutiongco-de la Paz,
  • Maria Rosario Z. Capeding,
  • Carmencita D. Padilla,
  • Julius Clemence R. Hafalla,
  • Martin L. Hibberd

DOI
https://doi.org/10.1186/s12916-021-02101-6
Journal volume & issue
Vol. 19, no. 1
pp. 1 – 14

Abstract

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Abstract Background Stratifying 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. Methods Among 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. Results We 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. Conclusions We 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.

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