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Volume 22, Number 2—February 2016
Research

Epidemiology of Serotype 1 Invasive Pneumococcal Disease, South Africa, 2003–2013

Claire von MollendorfComments to Author , Stefano Tempia, Cheryl Cohen, Susan Meiring, Linda de Gouveia, Vanessa Quan, Sarona Lengana, Alan Karstaedt, Halima Dawood, Sharona Seetharam, Ruth Lekalakala, Shabir A. Madhi, Keith P. Klugman, Anne von Gottberg, and for the Group for Enteric, Respiratory, and Meningeal Disease Surveillance in South Africa (GERMS-SA)
Author affiliations: National Institute for Communicable Diseases, Johannesburg, South Africa (C. von Mollendorf, C. Cohen, S. Tempia, S. Meiring, L. de Gouveia, V. Quan, S. Lengana, S.A. Madhi, K.P. Klugman, A. von Gottberg); University of the Witwatersrand, Johannesburg (C. von Mollendorf, C. Cohen, A. Karstaedt, S. Seetharam, S.A. Madhi, A. von Gottberg); Centers for Disease Control and Prevention, Atlanta, Georgia, USA (S. Tempia), and Pretoria, South Africa (S. Tempia); Chris Hani Baragwanath Academic Hospital, Johannesburg (A. Karstaedt, S. Seetharam); Pietermaritzburg Metropolitan Hospital, Pietermaritzburg, South Africa (H. Dawood); University of KwaZulu-Natal, Pietermaritzburg (H. Dawood); National Health Laboratory Service, Johannesburg (S. Seetharam); National Health Laboratory Service, Polokwane, South Africa (R. Lekalakala); University of Limpopo, Polokwane (R. Lekalakala); Emory University, Atlanta, Georgia, USA (K.P. Klugman)

Main Article

Table 1

Characteristics of 5,272 patients <5 years of age with invasive pneumococcal disease caused by serotype 1 or non–serotype 1 Streptococcus pneumoniae, South Africa, 2003–2013*

Variable No. cases/no. total (%)
Univariate analysis†
Multivariable analysis†
Serotype 1 Non–serotype 1 OR (95% CI) p value aOR (95% CI) p value
Age, y
<1 63/211 (30) 2,754/5,061 (54) Reference <0.001 Reference <0.001
1 35/211 (17) 1,155/5,061 (23) 1.32 (0.87–2.01) 2.36 (1.31–4.26)
2 43/211 (20) 519/5,061 (10) 3.62 (2.43–5.40) 6.91 (3.78–12.64)
3 37/211 (18) 355/5,061 (7) 4.56 (2.99–6.94) 12.03 (6.12–23.64)
4
33/211 (16)
278/5,061 (5)

5.19 (3.35–8.05)


7.13 (3.60–14.13)

Province
Gauteng 95/211 (45) 2,067/5,061 (41) Reference <0.001 Reference <0.001
Western Cape 11/211 (5) 1,158/5,061 (23) 0.21 (0.11–0.39) 0.11 (0.04–0.26)
KwaZulu-Natal 46/211 (22) 957/5,061 (19) 1.05 (0.73–1.50) 1.04 (0.59–1.84)
Eastern Cape 15/211 (7) 152/5,061 (3) 2.15 (1.22–3.79) 1.98 (0.74–5.28)
Free State 25/211 (12) 383/5,061 (8) 1.42 (0.90–2.24) 1.06 (0.56–2.00)
Mpumalanga 4/211 (2) 104/5,061 (2) 0.84 (0.30–2.32) 0.58 (0.07–4.86)
North-West 5/211 (2) 46/5,061 (1) 2.36 (0.92–6.09) 5.65 (1.33–24.05)
Limpopo 4/211 (2) 48/5,061 (1) 1.81 (0.64–5.13) 1.79 (0.41–7.90)
Northern Cape
6/211 (3)
146/5,061 (3)

0.89 (0.39–2.08)


0.50 (0.15–1.64)

Year of specimen collection
2003 31/211 (15) 544/5,061 (11) 1.20 (0.72–1.99) 0.004 1.10 (0.49–2.49) 0.05
2004 26/211 (12) 699/5,061 (14) 0.78 (0.46–1.32) 0.58 (0.25–1.34)
2005 32/211 (15) 672/5,061 (13) Reference Reference
2006 21/211 (10) 551/5,061 (11) 0.80 (0.46–1.40) 0.77 (0.34–1.72)
2007 15/211 (7) 547/5,061 (11) 0.58 (0.31–1.07) 0.67 (0.26–1.75)
2008 10/211 (5) 542/5,061 (11) 0.39 (0.19–0.80) 0.40 (0.15–1.03)
2009 23/211 (11) 494/5,061 (10) 0.98 (0.57–1.69) 1.43 (0.63–3.24)
2010 19/211 (9) 361/5,061 (7) 1.11 (0.62–1.98) 0.82 (0.33–2.08)
2011 19/211 (9) 240/5,061 (5) 1.66 (0.92–2.99) 1.04 (0.44–2.44)
2012 12/211 (6) 190/5,061 (4) 1.33 (0.67–2.63) 0.49 (0.18–1.33)
2013
3/211 (1)
221/5,061 (4)

0.29 (0.09–0.94)


0.12 (0.02–0.59)

Medical conditions/treatment
Length of hospital stay, d
<3 57/186 (31) 1,238/4,489 (28) Reference 0.09 Reference 0.04
4–14 96/186 (52) 2,138/4,489 (48) 0.98 (0.70–1.36) 0.58 (0.33–1.02)
>15 33/186 (18) 1,113/4,489 (25) 0.64 (0.42–1.00) 0.44 (0.23–0.85)
Previously hospitalized 39/164 (24) 1,676/4,110 (41) 0.45 (0.31–0.65) <0.001
Underlying medical condition‡ 27/114 (24) 1,321/3,371 (39) 0.48 (0.31–0.75) 0.001
Antimicrobial drug use in previous 2 mo§ 10/147 (7) 742/3,549 (21) 0.28 (0.14–0.53) <0.001
HIV infected 43/132 (33) 2,125/3,539 (60) 0.32 (0.22–0.47) <0.001 0.19 (0.12–0.31) <0.001
TB treatment in previous 3 mo 11/161 (7) 570/3,928 (15) 0.43 (0.23–0.80) 0.008
Malnourished¶ 24/95 (25) 1,109/2,619 (42) 0.46 (0.29–0.74) 0.001
Died during hospitalization
24/191 (13)
1,105/4,513 (24)

0.44 (0.29–0.68)
<0.001

0.38 (0.19–0.76)
0.006
Pneumococcal isolate characteristics
Penicillin nonsusceptible# 4/203 (2) 2,580/4,950 (52) 0.02 (0.01–0.05) <0.001 0.02 (0.01–0.05) <0.001
Previous invasive pneumococcal disease**
2/211 (1)
356/5,061 (7)

0.13 (0.03–0.51)
0.004



Clinical syndrome††
Meningitis 59/198 (30) 1,668/4,736 (35) Reference 0.001
Pneumonia 124/198 (63) 2,358/4,736 (50) 1.49 (1.08–2.04)
Bacteremia 15/198 (8) 710/4,736 (15) 0.60 (0.34–1.06)

*All patients were reported from the enhanced Group for Enteric, Respiratory, and Meningeal Disease Surveillance in South Africa (GERMS-SA) surveillance sites. aOR, adjusted odds ratio; OR, odds ratio; TB, tuberculosis.
†Only variables significant on univariate and multivariable analysis are shown. Variables not included are sex, race, Pitt bacteremia score, prematurity, antimicrobial drug use in previous 24 h, viable culture, and specimen type.
‡Includes asplenia or sickle cell anemia; chronic illness (i.e., chronic lung, renal, liver, cardiac disease, and diabetes); other immunocompromising conditions (i.e. including organ transplant, primary immunodeficiency, immunotherapy, and malignancy, but excluding HIV); and other risk factors (i.e., head injury with possible cerebral spinal fluid leak, neurologic disorders, burns, and chromosomal abnormalities). Excludes malnutrition.
§Use of any antimicrobial drug in 2 mo prior to admission.
¶Malnutrition was classified as a weight-for-age z-score of less than −2 (World Health Organization child growth standards 2009) (18), nutritional edema, or both.
#Considered penicillin nonsusceptible at MIC >0.12 μg/mL; intermediately resistant and resistant groups were combined into a nonsusceptible group.
**Invasive pneumococcal disease diagnosis >21 d before this episode.
††Clinical diagnoses were made on the basis of documented discharge diagnoses in patient medical records; clinical syndrome were separated into 3 groups: meningitis, bacteremic pneumonia, and bacteremia without focus or other diagnosis (e.g., septic arthritis, endopthalmitis, peritonitis, pericarditis).

Main Article

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