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  RESEARCH 1162 Emerging Infectious Diseases ã www.cdc.gov/eid ã Vol. 20, No. 7, July 2014 Epidemiology of Infuenza Virus Types and Subtypes in South Africa, 2009–2012 1 Adam L. Cohen, Orienka Hellferscee, Marthi Pretorius, Florette Treurnicht, Sibongile Walaza, Shabir Madhi, Michelle Groome, Halima Dawood, Ebrahim Variava, Kathleen Kahn, Nicole Wolter, Anne von Gottberg, Stefano Tempia, Marietjie Venter, and Cheryl Cohen Medscape, LLC is pleased to provide online continuing medical education (CME) for this journal article, allowing clinicians the opportunity to earn CME credit. This activity has been planned and implemented in accordance with the Essential Areas and policies of the Accreditation Council for Continuing Medical Education through the joint providership of Medscape, LLC and Emerging Infectious Diseases. Medscape, LLC   is accredited by the ACCME to provide continuing medical education for physicians.   Medscape, LLC designates this Journal - based CME activity for a maximum of 1.0  AMA PRA Category 1 Credit(s) TM  . Physicians should claim only the credit commensurate with the extent of their participation in the activity.  All other clinicians completing this activity will be issued a certificate of participation. To participate in this journal C ME activity: (1) review the learning objectives and author disclosures; (2) study the education content; (3) take the post - test with a 75% minimum passing score and complete the evaluation at http://www.medscape.org/journal/eid; (4) view/print certificate.   Release date: June 16, 2014; Expiration date: June 16, 2015 Learning Objectives Upon completion of this activity, participants will be able to:   1.   Describe differences in characteristics of patients hospitalized with severe acute respiratory illness (SARI) in South  Africa by infection with different influenza types and subtypes, based on a surveillance study 2. Compare characteristics of patients hospitalized with SARI in South Africa by infection with different influenza types and subtypes during the first and second influenza A(H1N1)pdm09 waves   3.   Compare case fatality and severity rates among infections with different types and subtypes and between the first and second influenza A(H1N1)pdm09 waves . CME Editor P. Lynne Stockton, VMD, MS, ELS(D), Technical Writer/Editor, Emerging Infectious Diseases. Disclosure: P. Lynne Stockton, VMD, MS, ELS(D), has disclosed no relevant financial relationships.   CME Author Laurie Barclay, MD, freelance writer and reviewer, Medscape, LLC. Disclosure: Laurie Barclay, MD, has disclosed no relevant financial relationships. Authors Disclosures:  Adam L. Cohen, MD, MPH; Orienka Hellferscee, MSc; Marthi Pretorius, MSc; Florette Treurnicht, PhD; Sibongile Walaza, MBBCh, MSc; Michelle Groome, MD, MSc; Ebrahim Variava, MD; Kathleen Kahn, MBBCh, MPH, PhD; Nicole Wolter, PhD; Stefano Tempia, DVM, MSc, PhD; Marietjie Venter, PhD;  and Cheryl Cohen, MBBCh, FCPathSA(Micro), MSc,  have disclosed no relevant financial relationships. Shabir Madhi, MD,  PhD, has disclosed the following relevant financial relationships: served as an advisor or consultant for GlaxoSmithKline, Pfizer, Merck, Novartis; served as a speaker or a member of a speakers bureau for GlaxoSmithKline, Pfizer, Sanofi Pasteur; received grants for clinical research from GlaxoSmithKline, Pfizer, Novartis, Sanofi-Aventis. Halima Dawood, MBBCh, MSc, has disclosed the following relevant financial relationships: served as a speaker or a member of a speakers bureau for MSD, Novartis; owns stock, stock options, or bonds from Netcare Holdings; received a travel grant from Novartis.  Anne von Gottberg, MBBCh, FCPathSA(Micro), PhD,  has disclosed the following relevant financial relationships: served as an advisor or consultant for Pfizer, Novartis, GlaxoSmithKline; served as a speaker or a member of a speakers bureau for Pfizer, Novartis, GlaxoSmithKline; received grants for clinical research from Pfizer. 1 This information has been presented at Options for the Control of Inuenza VIII, Cape Town, South Africa, September 5–9, 2013. Author afliations: Centers for Disease Control and Prevention,  Atlanta, Georgia, USA, and Pretoria, South Africa (A.L. Cohen, S. Tempia, M. Venter); National Institute for Communicable Dis - eases, Sandringham, South Africa (O. Hellferscee, M. Pretorius, F. Treurnicht, S. Walaza, N. Wolter, A. von Gottberg, S. Tempia, M. Venter, C. Cohen); University of the Witwatersrand, Johannesburg, South Africa (S. Madhi, M. Groome, N. Wolter, A. von Gottberg, C. Cohen); Medical Research Council: Respiratory and, Meningeal Pathogens Research Unit, Johannesburg (S. Madhi, M. Groome); Pietermaritzburg Metropolitan Hospital Complex, Pietermaritzburg, South Africa (H. Dawood); University of KwaZulu-Natal, Durban, South Africa (H. Dawood); Klerksdorp Tshepong Hospital, Klerks - dorp, South Africa (E. Variava); University of the Witwatersrand, Johannesburg (K. Kahn); Umeå University, Umeå, Sweden (K. Kahn); INDEPTH Network, Accra, Ghana (K. Kahn); and University of Pretoria, Pretoria, (M. Venter)DOI: http://dx.doi.org/10.3201/eid2007.131869   Emerging Infectious Diseases ã www.cdc.gov/eid ã Vol. 20, No. 7, July 2014 1163 To determine clinical and epidemiologic differences between inuenza caused by different virus types and sub - types, we identied patients and tested specimens. Patients were children and adults hospitalized with conrmed inu - enza and severe acute respiratory illness (SARI) identied through active, prospective, hospital-based surveillance from 2009–2012 in South Africa. Respiratory specimens were tested, typed, and subtyped for inuenza virus by PCR. Of 16,005 SARI patients tested, 1,239 (8%) were pos - itive for inuenza virus. Patient age and co-infections varied according to virus type and subtype, but disease severity did not. Case-patients with inuenza B were more likely than patients with inuenza A to be HIV infected. A higher proportion of case-patients infected during the rst wave of the 2009 inuenza pandemic were 5–24 years of age (19%) than were patients infected during the second wave (9%).  Although clinical differences exist, treatment recommenda- tions do not differ according to subtype; prevention through vaccination is recommended. M ost inuenza in humans is caused by 2 types of in - uenza virus: A and B. On the basis of the hem -agglutinin and neuraminidase proteins on the surface of the virus, inuenza A viruses are further subdivided into subtypes, 2 of which have commonly caused disease in humans over the past century: H3N2 and H1N1. The pro-  portion of these 3 types and subtypes of inuenza virus— A(H3N2), A(H1N1), and B—that circulate among hu -mans varies each year. In 2009, a novel pandemic strain of inuenza A(H1N1) virus, now called inuenza A(H1N1)  pdm09 virus, became the dominant H1N1 virus strain cir-culating worldwide ( 1 ).It is generally not possible to distinguish infection caused by different inuenza types and subtypes by clini -cal features ( 2 , 3 ), although differences in severity have been observed ( 4  –  6  ). Analyses of vital statistics data from the United States and South Africa have suggested that the num-  bers of excess deaths associated with inuenza are higher in years when inuenza A(H3N2) virus is circulating than when inuenza B or prepandemic inuenza A(H1N1) virus is circulating ( 4 , 7  ). Some studies have suggested that inu -enza A(H1N1)pdm09 virus infection led to more severe out-comes than did other types and subtypes ( 8 , 9 ). In the rst 3 months after inuenza A(H1N1)pdm09 virus was identied in South Africa, 91 deaths among 12,331 patients with lab- oratory-conrmed cases were identied; rates of HIV infec -tion and pregnancy among those who died were high ( 10 ). After the inuenza pandemic, studies showed that A(H1N1)  pdm09 virus was more likely than previously circulating vi-rus types and subtypes to affect children and young adults and that severe disease was associated with clinical char-acteristics such as obesity ( 11 , 12 ). The data conict with regard to whether severity of disease increases with subse-quent waves of A(H1N1)pdm09 virus infection ( 13–17  ).Little data have been reported from Africa on clinical and epidemiologic differences caused by different inu -enza virus types and subtypes. The objective of our study was 2-fold. First, we sought to compare the demographic and clinical characteristics, factors associated with infection, and disease severity among case-patients hospitalized with severe acute respiratory illness (SARI) associated with in- uenza A(H1N1)pdm09, A(H3N2), and B viruses in South Africa during 2009–2012. Second, we sought to compare the characteristics of case-patients infected during the rst wave of inuenza A(H1N1)pdm09 infection in 2009 with those of case-patients infected during the subsequent wave in 2011. Because this surveillance was started in 2009, we did not include prepandemic A(H1N1) virus strains in this study. Materials and Methods Setting and Time The SARI program is an active, prospective, sentinel, hospital-based surveillance system that monitors children and adults hospitalized with pneumonia in 4 provinces in South Africa ( 18 ). In February 2009, SARI surveillance was implemented in 3 of the 9 provinces of South Africa (Chris Hani-Baragwanath Academic Hospital, an urban site in Gauteng Province; Edendale Hospital, a periurban site in KwaZulu-Natal Province; and Matikwana and Map-ulaneng Hospitals, rural sites in Mpumalanga Province). In June 2010, an additional surveillance site was introduced at Klerksdorp and Tshepong Hospitals, periurban sites in  Northwest Province. This surveillance, which includes testing for inuenza virus and HIV, has received human subjects review and approval by the University of Witswa-tersrand, South Africa. The US Centers for Disease Control and Prevention deemed this a nonresearch surveillance ac-tivity. The study was conducted during 2009–2012. Case Defnitions and Patient Enrollment A case of SARI was dened as acute lower respira -tory tract infection (or pneumonia) in a patient hospital-ized within 7 days of illness onset. Children 2 days through <3 months of age with physician-diagnosed sepsis or acute lower respiratory tract infection (including, for example  bronchitis, bronchiolitis, pneumonia, and pleural effu-sion) and children 3 months through <5 years of age with  physician-diagnosed acute lower respiratory tract infection were enrolled. Among patients >5 years of age, we enrolled those who met the World Health Organization case deni -tion of SARI: sudden onset of reported or measured fever (>38°C), cough or sore throat, and shortness of breath or difculty breathing ( 19 ).All patients admitted to a hospital during Monday– Friday were eligible for enrollment in the study; adult  patients at Chris Hani-Baragwanath Academic Hospital Inuenza Virus Types and Subtypes, South Africa  RESEARCH 1164 Emerging Infectious Diseases ã www.cdc.gov/eid ã Vol. 20, No. 7, July 2014 were systematically sampled 2 of every 5 working days  per week. Patients were enrolled within the rst 24 hours of admission. We determined the number of patients who were admitted, met study case denitions, and were en -rolled. Study staff were centrally trained and completed case report forms until discharge for all enrolled patients; staff collected respiratory (nasopharyngeal) aspirates from  patients <5 years of age and nasopharyngeal and throat swab specimens from patients >5 years of age and blood specimens from consenting patients. Patients were admit-ted to an intensive care unit, and specimens for bacterial culture and tuberculosis testing were collected at the dis-cretion of the attending physician. For children <5 years of age, we gathered data on additional clinical signs and symptoms; for adolescents and adults >12 years of age, we gathered information on smoking and alcohol use. In-formed consent was obtained for all enrollment, laboratory testing, and anonymized, linked HIV testing. Laboratory Methods Respiratory specimens were placed in viral transport media, kept at 4–8°C, and sent to the National Institute for Communicable Diseases in Johannesburg within 72 hours of collection. Respiratory specimens were tested by multi- plex real-time reverse transcription PCR for 10 respiratory viruses (inuenza A and B viruses; parainuenza viruses 1, 2, and 3; respiratory syncytial virus; enterovirus; hu-man metapneumovirus; adenovirus; and rhinovirus) ( 20 ). Inuenza-positive specimens were subtyped by using the Centers for Disease Control and Prevention real-time re-verse transcription PCR protocol for detection and char- acterization of inuenza virus ( 21 ). Streptococcus pneu-moniae  was identied by quantitative real-time PCR that detected the lytA  gene from whole-blood specimens ( 22 ). When available, data on HIV infection status were obtained through routine standard-of-care testing at the treating hos- pital. When those data were not available, HIV testing was implemented at the National Institute for Communicable Diseases through anonymized, linked, dried blood-spot specimen testing by HIV PCR for children <18 months of age and by ELISA for patients >18 months of age. Statistical Analyses We excluded from the analysis inuenza virus–positive case-patients for whom subtyping could not be performed  because of low concentration of virus. Univariate compari-sons were performed by using multinomial or logistic re-gression. We conducted multinomial regression to compare demographic and clinical characteristics, associated factors, and disease severity among patients infected with the 3 in- uenza types and subtypes. Multinomial regression enables modeling of outcome variables with >2 categories and re-lates the probability of being in a category (in this instance either inuenza A[H3N2] or B virus) to the probability of being in a baseline category (in this instance inuenza [H3N2] virus). A complete set of coefcients are estimated for each of the categories being compared with the baseline, and the effect of each predictor in the model is measured as relative risk ratio (RRR). For this analysis, we used the inu -enza virus A(H3N2)–infected group as the baseline category  because inuenza A(H3N2) virus is considered to induce more severe illness ( 4 , 7  ). We conducted 2 logistic regres- sion models to compare patients infected with inuenza A with those infected with inuenza B and to compare patients infected during the rst wave of inuenza A(H1N1)pdm09 with patients infected during subsequent waves of inuenza A(H1N1)pdm09. All models were built by using stepwise forward selection. Covariates for which p value was <0.2 at the univariate analysis were assessed for signicance with multivariable analysis, and statistical signicance was as -sessed at p<0.05 for all multivariable models. We assessed 2-way interactions by inclusion of product terms for all vari- ables remaining in the nal models. Additional modeling is shown in the online Technical Appendix (http://wwwnc.cdc.gov/EID/article/20/7/13-1869-Techapp1.pdf). Results From February 2009 through December 2012, a total of 21,792 patients hospitalized with lower respiratory tract infection were approached for enrollment in SARI surveil-lance. Of those, 16,005 (73%) were enrolled and 1,239 (8%) had positive inuenza virus test results. Of the 5,876  patients who were approached but not enrolled, the most common reasons for not enrolling were unavailability of a legal guardian (among children <5 years of age; 1,452 [25%]), refusal (1,296 [22%]), and being confused or too ill (431 [7%]). Of the inuenza-positive SARI cases, 463 (37%) were caused by inuenza A(H3N2), 338 (27%) by inuenza A(H1N1)pdm09, and 418 (34%) by inuenza B viruses; 20 (2%) inuenza A viruses could not be further subtyped because of low viral yield in the samples. Inu -enza epidemics occur annually during the colder months in South Africa (May–September), and little activity occurs during the rest of the year (Figure). The circulating types and subtypes varied between study years and within an- nual epidemics. During 2009, inuenza virus activity oc - curred in 2 peaks; the rst was caused by subtype A(H3N2) (194/379, 51%), which occurred earlier than in the other years, and the second was caused by subtype A(H1N1) pdm09 (160/379 42%) (Table 1 [an expanded version of this table is available in the online Technical Appendix]; Figure). The predominant inuenza virus types or sub -types in the other years were as follows: B (164/273, 60%) in 2010, A(H1N1)pdm09 (140/362, 39%) in 2011, and A(H3N2) (99/205, 48%) and B (105/205, 51%) in 2012. Most (71%) case-patients were at Chris Hani-Baragwanath   Emerging Infectious Diseases ã www.cdc.gov/eid ã Vol. 20, No. 7, July 2014 1165 Academic Hospital, which reects the higher number of SARI case-patients enrolled there. Of 12,494 SARI case- patients for whom treatment data were available, 7 (0.1%) received oseltamivir, 1 of whom had laboratory-conrmed inuenza. Of 12,173 SARI case-patients for whom inu -enza vaccine histories were available, 19 (0.2%) reported having been vaccinated. HIV test results were available for 947 (76%) of inuenza case-patients. Of those, 399 (42%) were positive for HIV: 377 (94%) from anonymized testing at the National Institute for Communicable Diseases and 22 (6%) from standard-of-care testing at the treating hospitals.The age distribution of SARI case-patients with in- uenza was bimodal: most of the 1,239 inuenza case-  patients were <5 years of age (613 [49.5%]), followed by those 25–44 years of age (306 [24.7% few patients were ³65 years of age (53 [4.3%]). This bimodal age distribu-tion is repeated for each of the types and subtypes (Table 1) except that the rst wave of A(H1N1)pdm09 infection disproportionately affected those 5–24 years of age (Table 2). According to univariate analysis, case-patients infected with inuenza A(H1N1)pdm09 virus were less likely than case-patients infected with inuenza A(H3N2) virus to be co-infected with another virus (crude RRR [cRRR] 0.6, 95% CI 0.4–0.8), and case-patients infected with inuenza B virus were more likely to be infected with HIV (cRRR 1.7, 95% CI 1.2–2.3), have stridor (cRRR 2.1, 95% CI 1.2– 3.6), have symptoms >3 days before admission (cRRR 1.6, 955 CI 1.2–2.1), and to have been hospitalized for >2 days (cRRR 1.6, 95% CI 1.2–2.2), and were less likely to have a measured fever of >38°C (cRRR 0.5, 95% CI 0.4–0.7) (Table 1). In the multivariate analysis model, only age and year remained statistically signicant (Table 1). We found no statistical difference in case-fatality rates between virus types and subtypes (2.8% for A[H3N2], 1.5% for A[H1N1] pdm09, and 3.9% for B) and no difference in other mark-ers of severity, such as admission to an intensive care unit, need for mechanical ventilation, need for supplemental oxygen, or prolonged hospitalization (Table 1). To further explore the association between inuenza types and characteristics such as HIV status, we conducted a univariate analysis and constructed a multivariable lo- gistic regression model comparing inuenza B virus with inuenza A (both A[H3N2] and A[H1N1]pdm09) viruses. Except for co-infection with any virus other than inuenza, the same variables were signicant on this univariate anal - ysis as were signicant on the previous analysis. According to multivariate analysis, only year and HIV status remained statistically signicant and were retained in the nal model. Because age group was not signicantly associated with vi -rus type and did not have an interaction with HIV infec-tion in the multivariate model, we did not include age in the nal model. When we controlled for year, this model showed that case-patients with inuenza B virus infection were more likely than patients with inuenza A virus infec -tion to also be infected with HIV (adjusted odds ratio 1.4, 95% CI 1.02–1.80).According to univariate analysis, case-patients in the second wave of the A(H1N1)pdm09 pandemic were less likely than case-patients in the rst wave to have had a mea -sured fever of >38°C (crude odds ratio [cOR] 0.2, 95% CI 0.1–0.4) and more likely to have been co-infected with re-spiratory syncytial virus (cOR 6.4, 95% CI 1.4–29.6), have had symptoms for >3 days at admission (cOR 2.0, 95% CI 1.2–3.1), and to have needed supplemental oxygen (cOR 2.6, 95% CI 1.6–4.2; Table 2). According to multivariable logistic regression, only age group and surveillance site re- mained statistically signicant (Table 2). Severity of hos - pitalization, as measured by admission to an intensive care unit, need for mechanical ventilation, need for supplemental oxygen, or prolonged hospitalization, did not differ between waves (Table 2). In addition, case-fatality rates did not dif- fer between the rst (1.3%) and second (1.5%) waves. Discussion The inuenza virus types and subtypes that circulated during the annual winter inuenza seasons in South Africa Figure. Number of case-patients hospitalized with inuenza-associated severe acute respiratory illness, by week and virus strain at 4 sites, South Africa, 2009–2012. Inuenza Virus Types and Subtypes, South Africa

14-0043

Jul 22, 2017

13-1923

Jul 22, 2017
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