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Immune status alters the probability of apparent illness due to dengue virus infection: Evidence from a pooled analysis across multiple cohort and cluster studies.
PLoS Negl Trop Dis. 2017 Sep; 11(9):e0005926.PN

Abstract

Dengue is an important vector-borne pathogen found across much of the world. Many factors complicate our understanding of the relationship between infection with one of the four dengue virus serotypes, and the observed incidence of disease. One of the factors is a large proportion of infections appear to result in no or few symptoms, while others result in severe infections. Estimates of the proportion of infections that result in no symptoms (inapparent) vary widely from 8% to 100%, depending on study and setting. To investigate the sources of variation of these estimates, we used a flexible framework to combine data from multiple cohort studies and cluster studies (follow-up around index cases). Building on previous observations that the immune status of individuals affects their probability of apparent disease, we estimated the probability of apparent disease among individuals with different exposure histories. In cohort studies mostly assessing infection in children, we estimated the proportion of infections that are apparent as 0.18 (95% Credible Interval, CI: 0.16, 0.20) for primary infections, 0.13 (95% CI: 0.05, 0.17) for individuals infected in the year following a first infection (cross-immune period), and 0.41 (95% CI: 0.36, 0.45) for those experiencing secondary infections after this first year. Estimates of the proportion of infections that are apparent from cluster studies were slightly higher than those from cohort studies for both primary and secondary infections, 0.22 (95% CI: 0.15, 0.29) and 0.57 (95% CI: 0.49, 0.68) respectively. We attempted to estimate the apparent proportion by serotype, but current published data were too limited to distinguish the presence or absence of serotype-specific differences. These estimates are critical for understanding dengue epidemiology. Most dengue data come from passive surveillance systems which not only miss most infections because they are asymptomatic and often underreported, but will also vary in sensitivity over time due to the interaction between previous incidence and the symptomatic proportion, as shown here. Nonetheless the underlying incidence of infection is critical to understanding susceptibility of the population and estimating the true burden of disease, key factors for effectively targeting interventions. The estimates shown here help clarify the link between past infection, observed disease, and current transmission intensity.

Authors+Show Affiliations

Department of Epidemiology, School of Public Health, Johns Hopkins University, Baltimore, MD, United States of America.Department of Epidemiology, School of Public Health, Johns Hopkins University, Baltimore, MD, United States of America.Dengue Branch, Division of Vector-Borne Diseases, Centers for Disease Control and Prevention, San Juan, PR. Center for Communicable Disease Dynamics, Harvard TH Chan School of Public Health, Boston, MA, United States of America.

Pub Type(s)

Journal Article
Meta-Analysis

Language

eng

PubMed ID

28953902

Citation

Clapham, Hannah E., et al. "Immune Status Alters the Probability of Apparent Illness Due to Dengue Virus Infection: Evidence From a Pooled Analysis Across Multiple Cohort and Cluster Studies." PLoS Neglected Tropical Diseases, vol. 11, no. 9, 2017, pp. e0005926.
Clapham HE, Cummings DAT, Johansson MA. Immune status alters the probability of apparent illness due to dengue virus infection: Evidence from a pooled analysis across multiple cohort and cluster studies. PLoS Negl Trop Dis. 2017;11(9):e0005926.
Clapham, H. E., Cummings, D. A. T., & Johansson, M. A. (2017). Immune status alters the probability of apparent illness due to dengue virus infection: Evidence from a pooled analysis across multiple cohort and cluster studies. PLoS Neglected Tropical Diseases, 11(9), e0005926. https://doi.org/10.1371/journal.pntd.0005926
Clapham HE, Cummings DAT, Johansson MA. Immune Status Alters the Probability of Apparent Illness Due to Dengue Virus Infection: Evidence From a Pooled Analysis Across Multiple Cohort and Cluster Studies. PLoS Negl Trop Dis. 2017;11(9):e0005926. PubMed PMID: 28953902.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Immune status alters the probability of apparent illness due to dengue virus infection: Evidence from a pooled analysis across multiple cohort and cluster studies. AU - Clapham,Hannah E, AU - Cummings,Derek A T, AU - Johansson,Michael A, Y1 - 2017/09/27/ PY - 2017/05/25/received PY - 2017/09/02/accepted PY - 2017/10/09/revised PY - 2017/9/28/pubmed PY - 2017/10/14/medline PY - 2017/9/28/entrez SP - e0005926 EP - e0005926 JF - PLoS neglected tropical diseases JO - PLoS Negl Trop Dis VL - 11 IS - 9 N2 - Dengue is an important vector-borne pathogen found across much of the world. Many factors complicate our understanding of the relationship between infection with one of the four dengue virus serotypes, and the observed incidence of disease. One of the factors is a large proportion of infections appear to result in no or few symptoms, while others result in severe infections. Estimates of the proportion of infections that result in no symptoms (inapparent) vary widely from 8% to 100%, depending on study and setting. To investigate the sources of variation of these estimates, we used a flexible framework to combine data from multiple cohort studies and cluster studies (follow-up around index cases). Building on previous observations that the immune status of individuals affects their probability of apparent disease, we estimated the probability of apparent disease among individuals with different exposure histories. In cohort studies mostly assessing infection in children, we estimated the proportion of infections that are apparent as 0.18 (95% Credible Interval, CI: 0.16, 0.20) for primary infections, 0.13 (95% CI: 0.05, 0.17) for individuals infected in the year following a first infection (cross-immune period), and 0.41 (95% CI: 0.36, 0.45) for those experiencing secondary infections after this first year. Estimates of the proportion of infections that are apparent from cluster studies were slightly higher than those from cohort studies for both primary and secondary infections, 0.22 (95% CI: 0.15, 0.29) and 0.57 (95% CI: 0.49, 0.68) respectively. We attempted to estimate the apparent proportion by serotype, but current published data were too limited to distinguish the presence or absence of serotype-specific differences. These estimates are critical for understanding dengue epidemiology. Most dengue data come from passive surveillance systems which not only miss most infections because they are asymptomatic and often underreported, but will also vary in sensitivity over time due to the interaction between previous incidence and the symptomatic proportion, as shown here. Nonetheless the underlying incidence of infection is critical to understanding susceptibility of the population and estimating the true burden of disease, key factors for effectively targeting interventions. The estimates shown here help clarify the link between past infection, observed disease, and current transmission intensity. SN - 1935-2735 UR - https://www.unboundmedicine.com/medline/citation/28953902/full_citation L2 - http://dx.plos.org/10.1371/journal.pntd.0005926 DB - PRIME DP - Unbound Medicine ER -
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