Preetha Iyengar1, Claire von Mollendorf2, Stefano Tempia3, Alexandra Moerdyk4, Ziyaad Valley-Omar4, Orienka Hellferscee4, Neil Martinson5, Meera Chhagan6, Meredith McMorrow7, Manoj Gambhir8, Simon Cauchemez9, Ebrahim Variava10, Katlego Masonoke5, Adam L Cohen11, Cheryl Cohen12. 1. Epidemic Intelligence Service, Centers for Disease Control and Prevention, 1600 Clifton Rd, Atlanta, GA, USA; Global Disease Detection Branch, Division of Global Health Protection, Centers for Disease Control and Prevention, 1600 Clifton Rd, Atlanta, GA, USA; US Public Health Service, 5600 Fishers Ln, Rockville, MD, USA. Electronic address: piyengar@gmail.com. 2. Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases, 1 Modderfontein Rd, Sandringham, Johannesburg, South Africa; School of Public Health, Faculty of Health Science, University of the Witwatersrand, 1 Jan Smuts Avenue, Braamfontein, Johannesburg, South Africa. 3. Influenza Program, Centers for Disease Control and Prevention-South Africa, PO Box 9536, Pretoria, South Africa; Influenza Division, Centers for Disease Control and Prevention, 1600 Clifton Rd, Atlanta, GA, USA. 4. Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases, 1 Modderfontein Rd, Sandringham, Johannesburg, South Africa. 5. Perinatal HIV Research Unit, University of the Witwatersrand, Johns Hopkins University Center for TB Research, 1550 Orleans Street, Baltimore, MD, USA. 6. Department of Pediatrics, University of KwaZulu-Natal, King George V Ave, Glenwood, Durban, South Africa. 7. US Public Health Service, 5600 Fishers Ln, Rockville, MD, USA; Influenza Division, Centers for Disease Control and Prevention, 1600 Clifton Rd, Atlanta, GA, USA. 8. Modeling Unit, National Center for Immunization and Respiratory Disease, Centers for Disease Control and Prevention, 1600 Clifton Rd, Atlanta, GA, USA; Epidemiological Modelling Unit, Department of Epidemiology and Preventive Medicine, Monash University, 99 Commercial Road, Melbourne, Australia. 9. Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, 28 rue du Docteur Roux, Paris, France. 10. Department of Medicine, Klerksdorp Tshepong Hospital Complex and University of the Witwatersrand, Corner of OR Tambo and John Orr Street, Klerksdorp, South Africa. 11. US Public Health Service, 5600 Fishers Ln, Rockville, MD, USA; Influenza Program, Centers for Disease Control and Prevention-South Africa, PO Box 9536, Pretoria, South Africa; Influenza Division, Centers for Disease Control and Prevention, 1600 Clifton Rd, Atlanta, GA, USA. 12. Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases, 1 Modderfontein Rd, Sandringham, Johannesburg, South Africa; School of Public Health, Faculty of Health Science, University of the Witwatersrand, 1 Jan Smuts Avenue, Braamfontein, Johannesburg, South Africa. Electronic address: cherylc@nicd.ac.za.
Abstract
OBJECTIVES: The household is important in influenza transmission due to intensity of contact. Previous studies reported secondary attack rates (SAR) of 4-10% for laboratory-confirmed influenza in the household. Few have been conducted in middle-income countries. METHODS: We performed a case-ascertained household transmission study during May-October 2013. Index cases were patients with influenza-like-illness (cough and self-reported or measured fever (≥38 °C)) with onset in the last 3 days and no sick household contacts, at clinics in South Africa. Household contacts of index cases with laboratory-confirmed influenza were followed for 12 days. RESULTS: Thirty index cases in 30 households and 107/110 (97%) eligible household contacts were enrolled. Assuming those not enrolled were influenza negative, 21/110 household contacts had laboratory-confirmed influenza (SAR 19%); the mean serial interval was 2.1 days (SD = 0.35, range 2-3 days). Most (62/82; 76%) household contacts who completed the risk factor questionnaire never avoided contact and 43/82 (52%) continued to share a bed with the index case after illness onset. CONCLUSION: SAR for laboratory-confirmed influenza in South Africa was higher than previously reported SARs. Household contacts did not report changing behaviors to prevent transmission. These results can be used to understand and predict influenza transmission in similar middle-income settings. Published by Elsevier Ltd.
OBJECTIVES: The household is important in influenza transmission due to intensity of contact. Previous studies reported secondary attack rates (SAR) of 4-10% for laboratory-confirmed influenza in the household. Few have been conducted in middle-income countries. METHODS: We performed a case-ascertained household transmission study during May-October 2013. Index cases were patients with influenza-like-illness (cough and self-reported or measured fever (≥38 °C)) with onset in the last 3 days and no sick household contacts, at clinics in South Africa. Household contacts of index cases with laboratory-confirmed influenza were followed for 12 days. RESULTS: Thirty index cases in 30 households and 107/110 (97%) eligible household contacts were enrolled. Assuming those not enrolled were influenza negative, 21/110 household contacts had laboratory-confirmed influenza (SAR 19%); the mean serial interval was 2.1 days (SD = 0.35, range 2-3 days). Most (62/82; 76%) household contacts who completed the risk factor questionnaire never avoided contact and 43/82 (52%) continued to share a bed with the index case after illness onset. CONCLUSION: SAR for laboratory-confirmed influenza in South Africa was higher than previously reported SARs. Household contacts did not report changing behaviors to prevent transmission. These results can be used to understand and predict influenza transmission in similar middle-income settings. Published by Elsevier Ltd.
Entities:
Keywords:
Household transmission; Influenza; Secondary infection risk; Serial interval; South Africa
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