1. Epidemiology and Global Health
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Nationally-representative serostudy of dengue in Bangladesh allows generalizable disease burden estimates

  1. Henrik Salje  Is a corresponding author
  2. Kishor Kumar Paul
  3. Repon Paul
  4. Isabel Rodriguez-Barraquer
  5. Ziaur Rahman
  6. Mohammad Shafiul Alam
  7. Mahmadur Rahman
  8. Hasan Mohammad Al-Amin
  9. James Heffelfinger
  10. Emily Gurley
  1. Institut Pasteur, UMR2000, CNRS, France
  2. Johns Hopkins Bloomberg School of Public Health, United States
  3. International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Bangladesh
  4. University of California, San Francisco, United States
  5. Institute of Epidemiology, Disease Control and Research (IEDCR), Bangladesh
  6. Centers for Disease Control and Prevention, United States
Research Article
Cite this article as: eLife 2019;8:e42869 doi: 10.7554/eLife.42869
4 figures, 2 tables and 2 additional files

Figures

Figure 1 with 3 supplements
Dengue seropositivity in the sampled communities.

(A) Locations of sampled communities and the estimated seroprevalence by community. (B) Proportion seropositive by age and sex with 95% confidence intervals. (C) Seropositivity in Y1 compared to seropositivity in Y2 for each community.

https://doi.org/10.7554/eLife.42869.003
Figure 1—figure supplement 1
Participants included in study.
https://doi.org/10.7554/eLife.42869.004
Figure 1—figure supplement 2
Distribution of age groups in years and sex (solid bars) in the study population compared to the 2011 census (lines).
https://doi.org/10.7554/eLife.42869.005
Figure 1—figure supplement 3
Histogram of PanBio Units derived from the optical densities of the PanBio assay with the manufacturer recommended cutpoint (PanBio Unit of 11) in dashed red.

Those to the left of the dashed line are considered seronegative and those to the right of the line are considered seropositive.

https://doi.org/10.7554/eLife.42869.006
Figure 2 with 4 supplements
Modelled dengue seropositivity across Bangladesh and across age groups.

(A) Spatial predictions of seropositivity for the whole country. Kh. = Khulna, Dh. = Dhaka, Ch. = Chittagong (B) Semivariogram showing spatial dependence between the proportion seropositive between communities as a function of distance between them. (C) Observed versus predicted levels of seropositivity by community from leave one out cross validation. (D) Observed (points) and fitted seropositivity by age for the sampled communities within the three largest cities (Khulna, Chittagong and Dhaka) for both males and females. (E) Observed and fitted seropositivity for the remaining communities by sex.

https://doi.org/10.7554/eLife.42869.009
Figure 2—figure supplement 1
Relative risk of being seropositive for males versus females as a function of the overall proportion seropositive in the community.

The red line represents a LOESS curve fit through the 70 points.

https://doi.org/10.7554/eLife.42869.010
Figure 2—figure supplement 2
Differences in coefficient estimates in multivariable models run using logistic regression with no random intercept or spatial covariance (blue), with random intercepts at the household and community level (red) and with random intercepts at the household and community level and a Matern spatial covariance matrix (black, base model).

In addition the results of the spatial field model but restricted to individuals over 20y is shown (grey). The bars represent 95% confidence intervals each time.

https://doi.org/10.7554/eLife.42869.011
Figure 2—figure supplement 3
Comparison of risk maps using different prediction methods.

(A) Spatial prediction map using age, sex and population size and a Matern covariance structure. (B). Spatial prediction using a Matern spatial covariance only.

https://doi.org/10.7554/eLife.42869.012
Figure 2—figure supplement 4
Observed proportion seropositive by age group with 95% confidence intervals (black) and the fit using the force of infection estimated by the catalytic model (red).

We used the probability of being seropositive as a function of age from the whole country to estimate the proportion of the susceptible population (individuals that have never been exposed to dengue) that get infected each year.

https://doi.org/10.7554/eLife.42869.013
Accuracy of estimates for different number of sampled communities (top row) and different numbers of sampled individuals per community (bottom row) using different estimation methods.

(A) 95% range of estimates of overall seroprevalence from 100 repeated iterations when data from a random subset of communities is used. (B) Mean absolute error among heldout communities over repeated iterations. (C) Mean correlation between predicted and observed seroprevalence among heldout communities. (D) 95% range of estimates of overall seroprevalence from 100 repeated iterations when data from a random number of individuals from 50 communities is used. (E) Mean absolute error among 20 randomly selected heldout communities over repeated iterations. (F) Mean correlation between predicted and observed seroprevalence among 20 randomly selected heldout communities. The different estimation methods are overall proportion seropositive (black), spatial correlation model using Matern covariance structure and no covariates (blue), spatial correlation model using Matern covariance structure and age, sex and population size as covariates, logistic regression using age, sex and population size as covariates with no spatial component (orange).

https://doi.org/10.7554/eLife.42869.014

Tables

Table 1
Individual-, household- and community-level characteristics of participants, stratified by serostatus to dengue.
https://doi.org/10.7554/eLife.42869.007
Serum obtained
(N = 5,866)
Seropositive
(N = 1,403)
Seronegative
(N = 4,463)
Individual levelnn (%)n (%)
Year of study
20142911704 (24)2207 (76)
20152955699 (24)2256 (76)
Age group (years) in 2014:
<1083288 (11)744 (89)
11–201062314 (30)748 (70)
21–301402228 (16)1174 (84)
31–40818261 (32)557 (68)
41–50679197 (29)482 (71)
51–60541144 (27)397 (73)
>60525171 (33)354 (67)
Sex:
Male2821761 (27)2060 (73)
Female3044642 (21)2402 (79)
Heard of dengue:
No772115 (15)657 (85)
Yes20931288 (25)3805 (75)
Reported having had dengue:
No58271387 (24)4440 (76)
Yes3816 (42)22 (58)
Last time left community:
<7 days773269 (35)504 (65)
7d-1 month1198311 (26)887 (74)
1–6 months1142285 (25)857 (75)
>6 months2753538 (20)2215 (80)
Household level
Electricity in home
No780149 (19)631 (81)
Yes50751253 (25)3822 (75)
Access to water in home*
No301125 (42)176 (58)
Yes2599578 (22)2021 (78)
Own home
No444239 (54)205 (46)
Yes54081161 (21)4247 (79)
Own land away from home
No1303373 (29)930(71)
Yes45521029 (23)3523 (77)
Mosquito control used
No2185512 (23)1673 (77)
Yes3670890 (24)2780 (76)
Household head education:
No education1034306 (30)728 (70)
Primary school1574362 (23)1212 (77)
High school1407320 (23)1087 (77)
Higher1840414 (22)1426 (78)
Household income
(Taka, 100 Taka = 1.2 USD):
<7000921212 (23)709 (77)
7,000–99991176229 (19)947 (81)
10000–20,0001980509 (26)1471 (74)
>20,0001766452 (26)1314 (74)
Community level
Aedes aegypti mosquitos captured
No3931668 (17)3263 (83)
Yes1935735 (38)1200 (62)
Aedes albopictus mosquitos captured
No3416941 (28)2475 (72)
Yes2450462 (19)1988 (81)
Type of community
Urban1505557 (37)948 (63)
Rural4361846 (19)3515 (81)
Division:
Dhaka1484407 (27)1077 (73)
Chittagong1533382 (25)1151 (75)
Barisal32968 (21)261 (79)
Khulna672302 (45)370 (55)
Rajshahi668152 (23)516 (77)
Rangpur92080 (9)840 (91)
Sylhet26012 (5)248 (95)
Table 2
Regression results.
https://doi.org/10.7554/eLife.42869.008
UnadjustedMultivariable
Individual levelOdds ratio (95% confidence interval)Adjusted odds ratio (95% confidence interval)
Year of study (vs Y1)1.0 (0.8–1.1)1.0 (0.9–1.2)
Age group (years) in 2014:
<10RefRef
11–201.9 (1.4–2.6)2.0 (1.4–2.7)
21–305.2 (3.8–7.1)5.5 (4.1–7.6)
31–405.9 (4.3–8.1)6.2 (4.5–8.6)
41–505.5 (4.0–7.7)5.8 (4.2–8.2)
51–605.1 (3.6–7.1)5.1 (3.6–7.2)
>607.5 (5.4–10.6)7.7 (5.4–10.8)
Male1.6 (1.4–1.9)1.7 (1.5–2.0)
Last time left community:
<7 days1.9 (1.5–2.4)1.4 (1.1–1.8)
7d-1 month1.4 (1.2–1.7)1.2 (0.9–1.4)
1–6 months1.1 (0.9–1.3)1.0 (0.8–1.2)
>6 monthsRefRef
Household level
Electricity in home1.0 (0.8–1.2)0.9 (0.7–1.2)
Water in home1.0 (0.7–1.4)- (1)
Own home0.9 (0.7–1.3)0.9 (0.7–1.4)
Own land0.9 (0.8–1.1)0.9 (0.7–1.1)
Mosquito control used0.9 (0.8–1.1)0.9 (0.7–1.1)
Household head education:
No educationRefRef
Primary school0.9 (0.7–1.1)0.9 (0.7–1.1)
High school0.9 (0.7–1.1)1.0 (0.7–1.2)
Higher0.8 (0.7–1.0)0.8 (0.6–1.0)
Household income (Taka):
<7000RefRef
7,000–99990.9 (0.7–1.2)0.9 (0.7–1.1)
10000–20,0001.0 (0.8–1.2)1.0 (0.7–1.2)
>20,0000.8 (0.6–1.0)0.8 (0.6–1.0)
Community level
Population density (log scale)1.3 (1.2–1.5)1.3 (1.1–1.8)
Aedes aegypti mosquitos captured1.8 (1.2–2.8)1.4 (0.9–2.2)
Aedes albopictus mosquitos captured1.1 (0.7–1.6)1.0 (0.7–1.6)

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