| Literature DB >> 21390158 |
Timothy P Endy1, Kathryn B Anderson, Ananda Nisalak, In-Kyu Yoon, Sharone Green, Alan L Rothman, Stephen J Thomas, Richard G Jarman, Daniel H Libraty, Robert V Gibbons.
Abstract
BACKGROUND: Dengue viruses are a major cause of morbidity in tropical and subtropical regions of the world. Inapparent dengue is an important component of the overall burden of dengue infection. It provides a source of infection for mosquito transmission during the course of an epidemic, yet by definition is undetected by health care providers. Previous studies of inapparent or subclinical infection have reported varying ratios of symptomatic to inapparent dengue infection. METHODOLOGY/PRINCIPALEntities:
Mesh:
Year: 2011 PMID: 21390158 PMCID: PMC3046956 DOI: 10.1371/journal.pntd.0000975
Source DB: PubMed Journal: PLoS Negl Trop Dis ISSN: 1935-2727
Figure 1Flow diagram of study population and data analysis.
Flow diagram that demonstrates the population enrolled and disease outcomes used in the analysis.
Figure 2Symptomatic to inapparent ratio for all schools by year.
Figure that demonstrates the S:I ratio for all schools in a given year.
Figure 3Symptomatic to inapparent ratio by age.
Figure that demonstrates the S:I ratio for each age.
Figure 4Symptomatic to Inapparent Ratio by Year and School.
Figure that demonstrates the temporal and spatial variation of the S:I ratio. Of note the error bars show 95% confidence intervals for the SI ratio. The upper limits that extend to 10 have actual upper limits of 999 (indicating that the upper limit for the probability of symptomatic infection was greater than one) and were therefore adjusted to be 9.9 to make the upper limit estimable. A value of zero indicates that all cases were inapparent in that school. Missing values indicates there were no acute dengue infections for that school and year.
Figure 5Symptomatic to Inapparent Ratio for Schools 1 to 12 by Year.
Figure that demonstrates the individual experience of each school in the yearly variation of the S:I ratio. Similar to figure 4 the error bars show 95% confidence intervals for the SI ratio. The upper limits that extend to 10 have actual upper limits of 999 (indicating that the upper limit for the probability of symptomatic infection was greater than one) and were therefore adjusted to be 9.9 to make the upper limit estimable. A value of zero indicates that all cases were inapparent in that school. Missing values indicates there were no acute dengue infections for that school and year.
Associations of the probability of subclinical dengue infection with epidemic characteristics.*
| Present year's epidemic characteristics | |||
| Regression coefficient (beta) | OR for a one unit increase in the variable(95% CI) | Median(Range) | |
| Dengue incidence |
|
| 0.06(0–0.41) |
| Proportion DENV-1 | −0.016 | 0.98(0.90–1.07) | 0(0–1) |
| Proportion DENV-2 | 0.111 | 1.12(0.98–1.28) | 0.64(0–1) |
| Proportion DENV-3 |
|
| 0(0–1) |
| Proportion DENV-4 | 0.130 | 1.14(0.39–3.32) | 0(0–1) |
| Number of DENV serotypes in circulation |
|
| 1(1–3) |
*Epidemic characteristics at a given school, for a given epidemic year. Performed as individual logistic regression models with subclinical infection as the outcome variable and each epidemic characteristic as a single exposure variable, and incorporating random effects for the individual and the individual's school of attendance.
**. Each exposure variable was aggregated across each school and for each year. The median represents the midpoint of these aggregated values.
†: A one-unit increase for proportions (incidence, proportion DENV-1 etc) was defined as a one-quartile increase in value. Quartiles were calculated based upon the range of values (e.g., if incidence had a range of 0–40%, the upper limit for calculating quartiles of incidence was 40%, not 100%). A one-unit increase in the number of serotypes in circulation compared 2 serotypes in circulation to 1 serotype in circulation, for example.
Figure 6Proportion of infections that were inapparent by school and year.
Figure that demonstrates the proportion of inapparent infections during a given dengue virus transmission season.