The impact of healthcare visit timing on reported pertussis cough duration: Selection bias and disease pattern from reported cases in Michigan, USA, 2000-2010.
BACKGROUND
Pertussis is a potentially serious respiratory illness characterized by cough of exceptionally long duration of up to approximately100 days. While macrolide antibiotics are an effective treatment, there is an ongoing debate whether they also shorten the length of cough symptoms. We investigated whether public health surveillance data for pertussis, in which cases are identified at diagnosis, are potentially affected by selection bias and the possible consequences for reported cough duration.


METHODS
Data on 4,794 pertussis cases reported during 2000-2010 were extracted from the Michigan Disease Surveillance System, a statewide, web-based communicable disease reporting system, to specifically investigate increased duration of cough observed in pertussis patients with delayed initial healthcare visit. A simulated population of cases was derived from the observed surveillance data and truncated week-by-week to evaluate the effects of bias associated with stratification on timing of antibiotics.


RESULTS
Cases presenting for medical evaluation later in the clinical course were more likely to have experienced delayed antibiotic therapy and longer average cough duration. A comparable magnitude of increasing cough duration was also observed in the simulated data. By stratifying on initial medical visit, selection bias effects based on timing of healthcare visit were demonstrated.


CONCLUSIONS
Stratifying or controlling for the timing of the initial case identification and accompanying antibiotic treatment can create artificial patterns of observed cough duration. In surveillance data, differences in symptom duration may arise from selection bias and should not be presumed to be related to early antibiotic treatment.
Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, 48109, Michigan, USA.
Jennifer K
JK
Knapp
Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, 48109, Michigan, USA.
Mark L
ML
Wilson
Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, 48109, Michigan, USA.
Susan
S
Murray
Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, 48109, Michigan, USA. MBoulton@umich.edu.|Department of Internal Medicine, Division of Infectious Diseases, University of Michigan Medical School, Ann Arbor, 48109, Michigan, USA. MBoulton@umich.edu.
Matthew L
ML
Boulton
Antibiotics; Cough; Epidemiology; Pertussis; Selection bias
Pediatrics. 1999 Oct;104(4):e42
10506267
J Infect Dis. 1988 Mar;157(3):434-40
3257783
Pediatr Infect Dis J. 1995 Oct;14(10):870-4
8584314
Cochrane Database Syst Rev. 2007 Jul 18;(3):CD004404
17636756
Am J Physiol Lung Cell Mol Physiol. 2008 Jul;295(1):L231-4
18487354
MMWR Recomm Rep. 1997 May 2;46(RR-10):1-55
9148133
J Infect Dis. 2001 May 1;183(9):1353-9
11294666
Pediatrics. 2004 Jul;114(1):e96-101
15231980
J Pediatr. 1969 Nov;75(5):768-81
4310467
MMWR Recomm Rep. 2005 Dec 9;54(RR-14):1-16
16340941
Curr Opin Pharmacol. 2007 Jun;7(3):272-8
17418639
Jpn J Infect Dis. 2014;67(5):345-8
25241683
J Pediatr. 1996 Nov;129(5):761-4
8917247
Pediatrics. 1978 Feb;61(2):224-30
204899