Mortality amongst patients with influenza-associated severe acute respiratory illness, South Africa, 2009-2013

Introduction: Data on the burden and risk groups for influenza-associated mortality from Africa are limited. We aimed to estimate the incidence and risk-factors for in-hospital influenza-associated severe acute respiratory illness (SARI) deaths. Methods: Hospitalised patients with SARI were enrolled prospectively in four provinces of South Africa from 2009- 2013. Using polymerase chain reaction, respiratory samples were tested for ten respiratory viruses and blood for pneumococcal DNA. The incidence of influenza-associated SARI deaths was estimated at one urban hospital with a defined catchment population. Results: We enrolled 1376 patients with influenza-associated SARI and 3% (41 of 1358 with available outcome data) died. In patients with available HIV-status, the case-fatality proportion (CFP) was higher in HIV-infected (5%, 22/419) than HIV-uninfected individuals (2%, 13/620; p = 0.006). CFPs varied by age group, and generally increased with increasing age amongst individuals >5 years (p<0.001). On multivariable analysis, factors associated with death were age-group 45-64 years (odds ratio (OR) 4.0, 95% confidence interval (CI) 1.01-16.3) and ≥65 years (OR 6.5, 95%CI 1.2-34.3) compared to 1-4 year age-group who had the lowest CFP, HIV-infection (OR 2.9, 95%CI 1.1-7.8), underlying medical conditions other than HIV (OR 2.9, 95%CI 1.2-7.3) and pneumococcal co-infection (OR 4.1, 95%CI 1.5-11.2). The estimated incidence of influenza-associated SARI deaths per 100,000 population was highest in children <1 year (20.1, 95%CI 12.1-31.3) and adults aged 45-64 years (10.4, 95%CI 8.4-12.9). Adjusting for age, the rate of death was 20-fold (95%CI 15.0-27.8) higher in HIV-infected individuals than HIV-uninfected individuals. Conclusion: Influenza causes substantial mortality in urban South Africa, particularly in infants aged <1 year and HIV-infected individuals. More widespread access to antiretroviral treatment and influenza vaccination may reduce this burden. The protocol was approved by the Research Ethics Committees of the Universities of the Witwatersrand (reference number M081042) and KwaZulu-Natal (reference number BF157/08). This surveillance was deemed non-research by the U.S. CDC and did not need human subjects review by that institution. All participants provided written informed consent to participate in the study. From February 2009 through December 2013, active, prospective, hospital-based surveillance for SARI was implemented in three of the nine provinces of South Africa (Chris Hani-Baragwanath Academic Hospital (CHBAH) in an urban area of Gauteng Province, Edendale Hospital in a peri-urban area of KwaZulu-Natal Province and Matikwana and Mapulaneng Hospitals in a rural area of Mpumalanga Province). In June 2010, an additional surveillance site was introduced at Klerksdorp and Tshepong Hospitals in a peri-urban area of the Northwest Province[7]. A case of SARI was defined as a hospitalised individual with illness onset within seven days of admission meeting age-specific inclusion criteria. We included children aged two days through <3 months with physician-diagnosed sepsis or acute lower respiratory tract infection (ALRI), children aged three months through <5 years with physician-diagnosed ALRI (including, for example bronchitis, bronchiolitis, pneumonia and pleural effusion) and patients aged ≥5 years meeting a modified World Health Organization (WHO) case definition for severe acute respiratory illness: (1) sudden onset of fever (>38°C) or reported fever, (2) cough or sore throat, and (3) shortness of breath, or difficulty breathing[8]. All patients admitted during Monday through Friday were eligible, except for adult patients at CHBAH where enrolment occurred for two of every five working days (selected days varied systematically) per week due to large patient numbers and limited resources. In 2013, enrolment at CHBAH was down-scaled: paediatric patients were then enrolled on 2 of the 5 working days and adult patients on 1 of the 5 working days. Numbers of patients admitted, numbers meeting study case definitions and numbers enrolled were collected. Demographics, socio-economic factors, medical history, clinical presentation and outcome were recorded by means of interview and hospital record review. Study staff completed case report forms until discharge and collected respiratory (nasopharyngeal [NP] and throat swabs from patients aged ≥5 years or NP aspirates from patients aged <5 years) and blood specimens from consenting patients. Hospital and intensive care unit (ICU) admission and collection of specimens for bacterial culture, tuberculosis testing and CD4+ T-cell counts were performed according to attending-physician discretion. All patients enrolled into SARI surveillance were monitored until discharge or death to determine in-hospital outcome. Patients were not followed for outcome following discharge from hospital. HIV-infection status was obtained based on testing undertaken as part of standard-of-care,[9] or through anonymised linked dried blood spot specimen testing by HIV polymerase chain reaction (PCR) assay for children aged <18 months and by ELISA for individuals aged ≥18 months. CD4+ T-cell counts were determined by flow cytometry[10]. Patients were categorised into two immunosuppression categories: (1) no or mild immunosupression (CD4+ T-lymphocytes ≥200/mm3or equivalent age-appropriate CD4+ percentage for children aged <5 years), or (2) severe immunosuppression (CD4+ T-lymphocytes <200/mm3 or equivalent age-appropriate CD4+ percentage for children aged <5 years)[11]. Underlying medical conditions were defined as asthma, other chronic lung disease, chronic heart disease, liver disease, renal disease, diabetes mellitus, immunocompromising conditions excluding HIV infection, neurological disease or pregnancy and were considered absent if indicated in medical records or when there was no direct reference to that condition. Respiratory specimens were transported in viral transport medium at 4–8°C to the National Institute for Communicable Diseases (NICD) of the National Health Laboratory Services (NHLS) within 72 hours of collection. Respiratory specimens were tested by a multiplex real-time reverse-transcription PCR assay for 10 respiratory viruses (influenza A and B viruses, parainfluenza virus 1, 2 and 3; respiratory syncytial virus; enterovirus; human metapneumovirus; adenovirus and rhinovirus)[12]. Influenza positive specimens were subtyped using the U.S. Centers for Disease Control and Prevention (CDC) real-time reverse-transcription PCR protocol for characterisation of influenza virus[13]. Streptococcus pneumoniae was identified by quantitative real-time PCR detecting the lytA gene from whole blood specimens[14]. We assessed risk factors for death among influenza-positive SARI patients from 2009 through 2013. Missing data among influenza-positive SARI patients were imputed using chained equations over 10 imputation runs. Variables included in the multiple imputation model were HIV-status, sex, in-hospital outcome, presence of underlying illness, ventilation, use of oxygen, duration of hospitalisation, duration of symptoms, receipt of antibiotics on admission and pneumococcal lytA PCR positivity. Data were missing for 24% (329/1376) of individuals on HIV status, 24% (331/1376) for pneumococcal PCR and 5% (72/1376) for antibiotics given on admission. For all other variables missing data were ≤2%. Variables potentially on the causal path to death such as intensive care unit (ICU) admission and mechanical ventilation were not evaluated in the model of risk factors for death, but used as predictors during multiple imputation. Because initiation of tuberculosis treatment (in the absence of laboratory confirmation) may be more likely in patients who appear sicker and only a small percentage of patients (<30%) were tested for tuberculosis, receipt of tuberculosis treatment was also not evaluated in the model of risk factors for death. Univariate and multivariable logistic regression analyses were performed after multiple imputation. Multivariable logistic regression models were evaluated, starting with all variables that were significant at p<0.1 on univariate analysis, and dropping non-significant factors with stepwise backward selection. All two-way interactions of the variable significant at the final additive model were evaluated. Two-sided p values <0.05 were considered significant throughout. Age group, hospital, duration of hospitalisation and year were defined as categorical variables in multiple levels. All other variables were defined as the presence or absence of the attribute. The statistical analysis was implemented using Stata version 12 (StataCorp Limited, Texas, United States of America). Calculation of mortality rate was conducted at one surveillance site (CHBAH) from 2009–2012 where population denominator data were available. This hospital is the only public hospital serving a community of about 1.3 million persons in 2011of whom an estimated 10% have private medical insurance[15]. Most (>80%) uninsured persons and approximately10% of insured persons seek care at public hospitals; consequently, we assumed that most persons requiring hospitalisation from this community are admitted to CHBAH. To estimate the number and rate of in-hospital deaths associated with influenza for the period 2009–2012 (2013 was not included as enrolment was down-scaled in this year), we first estimated the age-specific (<1 year, 1–4 years, 5–24 years, 25–44 years, 45–64 years and > = 65 years) number of hospitalisations for SARI. We also separately estimated the rate of death for children aged <6 months as this age group could be potentially targeted through maternal influenza immunization. We used numbers of enrolled SARI patients and adjusted for non-enrollment in three of five adult wards and during weekends as well as refusal to participate using information from study logs. We then multiplied the SARI hospitalisations by the age-specific influenza detection ratio and the case-fatality proportion (CFP) amongst patients with influenza to obtain the estimated number of deaths in patients hospitalized with influenza. To obtain the number of HIV-specific influenza—associated deaths we assumed that the HIV prevalence was similar amongst influenza-positive patients who died and were tested for HIV and those not tested. Because in South Africa a large proportion of deaths occurs outside of hospital, we used the age-specific proportion of in-hospital deaths among individuals that died of pneumonia and influenza (International Classification of Diseases, 10th revision [ICD-10] code: J10-J18) from vital statistics data to estimate the age-specific number of influenza-associated deaths occurring out-of hospital[16]. We chose to use pneumonia and influenza deaths because these are the ICD-10 codes most comparable to individuals with SARI, and we assumed that the proportion of in-hospital (vs out-of hospital) influenza-associated SARI deaths was similar to those of pneumonia and influenza. In 2009 (the most recent year for which vital statistics data were available), 29% of pneumonia and influenza deaths in Gauteng province (where CHBAH is located) occurred outside of the hospital (ranging from 24%-49% depending on the age group)[16]. We obtained the rate of influenza-associated SARI deaths per 100,000 person-years by age groups and HIV status using the estimated number of influenza-associated deaths (in and out of hospital) by HIV status divided by the mid-year population estimates for region D of Soweto, multiplied by 100,000[17]. The age- and year—specific HIV prevalence in the study population was obtained from the projections of the Actuarial Society of South Africa AIDS and Demographic model[18]. Confidence intervals for incidence estimates were calculated using the Poisson distribution. Age-specific and overall age-adjusted risk of influenza associated deaths in HIV-infected and-uninfected persons was determined using log-binomial regression.