Parainfluenza Virus Infection Among Human Immunodeficiency Virus (HIV)-Infected and HIV-Uninfected Children and Adults Hospitalized for Severe Acute Respiratory Illness in South Africa, 2009–2014

Cohen, Adam L.; Sahr, Philip K.; Treurnicht, Florette; Walaza, Sibongile; Groome, Michelle J.; Kahn, Kathleen; Dawood, Halima; Variava, Ebrahim; Tempia, Stefano; Pretorius, Marthi; Moyes, Jocelyn; Olorunju, Steven A. S.; Malope-Kgokong, Babatyi; Kuonza, Lazarus; Wolter, Nicole; von Gottberg, Anne; Madhi, Shabir A.; Venter, Marietjie; Cohen, Cheryl

We conducted 3 multivariable logistic regression models. In our first analysis, we implemented univariate and multivariable logistic regression models to determine the association of PIV infection with SARI (for all types together and for each viral type separately) compared with controls enrolled from May 2012 to December 2014 at the sites in KwaZulu-Natal and North West Provinces. For the estimation of association with SARI, we conducted an overall analysis adjusting for age, HIV serostatus, respiratory viral coinfection, and underlying illness and subanalyses stratifying by age and HIV serostatus and adjusting for respiratory viral coinfection and underlying illness. Then, we estimated the attributable fraction (AF) from the odds ratio (OR) obtained from the multivariable model using the following formula: AF = (OR-1)/OR × 100. In our second analysis, univariate and multivariable logistic regression was used to determine factors associated with HIV infection among patients with PIV-associated SARI from January 2009 to December 2014 at all SARI sites. In our third analysis, we used multinomial regression to compare and contrast demographic and clinical characteristics and severity among patients infected with the 3 PIV types. For the multinomial analysis, we used PIV type 3 as the baseline category because type 3 is most common.