2014.ISDS.Abstracts.Final.pdf


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ISDS 2014 Conference Abstracts

Adjustment for Baseline Level of Dengue Cases Due to 
Increased Testing in Singapore

Li Wei Ang*, Cindy Thiow Koon Lim, Stefan Ma, Joanne Tay and Jeffery Cutter

MInistry of Health, Singapore

Objective
To make adjustment of historical trends to accurately reflect the 

baseline level of dengue cases in Singapore, in view of increased 
testing for dengue in 2013.

Introduction
Dengue is endemic in Singapore, with epidemics of increasing 

magnitude occurring on a six-year cycle in 1986/7, 1992, 1998, 
2004/5, 2007 and 2013. The incidence per 100,000 population ranged 
from 87.2 to 105.6 in 2009-20121, and surged to 410.6 in 2013. The 
mean weekly number of dengue cases over a five-year period provides 
an indication of the baseline level. We illustrate an adjustment that has 
been made to the computation of the baseline level due to increased 
testing for dengue in 2013.

Methods
Dengue is a legally notifiable disease in Singapore. In any given 

year, a subset of dengue infected cases is laboratory-confirmed and 
notified to the Ministry of Health, Singapore. The remaining cases 
may not be tested as the medical practitioner has clinically diagnosed 
them to have dengue based on their presenting signs and symptoms, or 
they may have mild symptoms or are asymptomatic and are not tested 
for dengue. In 2013, some of these mild, asymptomatic or clinically 
diagnosed cases may have been “uncovered” and laboratory-
confirmed, due to increased testing for dengue in that year (Fig. 1).

Adjustment factor
We assumed that the proportion of hospitalizations among 

laboratory-confirmed dengue cases remained constant between 2012 
and 2013. The proportion hospitalized was 0.40 in 2012.

Assuming there was no increased testing and no change in dengue 
severity, the proportion hospitalized in 2013 should remain the same 
at 0.40. Hence, the expected number of notified laboratory-confirmed 
dengue cases in each week could be derived by dividing the weekly 
number of hospital admissions by 0.40. Any increase in observed 
numbers over the expected numbers would represent an adjustment 
due to increased testing. As such, the weekly adjustment factor due 
to increased testing for each week could be derived by dividing the 
observed weekly number of cases by the expected weekly number.

We also assumed that dengue testing practices had stabilized 
since epidemiological week (E-week) 29, from 14 to 20 July 2013. 
The average 4-weekly moving adjustment factor from E-week 29 to 
E-week 52 in 2013 was 1.54.

Removal of outliers
Weekly number of cases which exceeded mean + 2 standard 

deviations (SD) for each of the four years from 2009 to 2012 were 
deemed as outliers and removed. For 2013, outliers exceeding 1.54 x 
(mean + 2 SD) were removed.

Computation of baseline levels for 2014
The adjustment factor of 1.54 was applied to the remaining weekly 

data from 2009 to 2012 after outliers had been removed. For 2014, 
the mean was then computed using the adjusted weekly numbers from 
2009 to 2012 and remaining data points in 2013.

Results
For 2013, the previous mean reflecting the baseline level of dengue 

was 97, which was computed based on weekly numbers of dengue 
cases over a five-year period from 2008 to 2012.

For 2014, the baseline level of dengue with adjustment for 
increased laboratory testing was higher at 143 cases per week.

Conclusions
When there are changes to existing public health surveillance 

such as increased testing for dengue in 2013, there is a need to make 
adjustment to the computation of baseline level so as to better reflect 
the underlying disease trends. The mean for 2014 would be lower 
if the adjustment factor to inflate the weekly numbers from 2009 
to 2012 was not incorporated, which would then result in an under-
estimation of the baseline level for 2014.

Keywords
dengue; endemic; epidemic; laboratory-confirmed; baseline

References

1. Ministry of Health, Singapore. Communicable Diseases Surveillance in 
Singapore 2012. Singapore, 2013.

*Li Wei Ang

E-mail: ang_li_wei@moh.gov.sg    

Online Journal of Public Health Informatics * ISSN 1947-2579 * http://ojphi.org * (1):e104, 201