Human Respiratory Syncytial Virus, Human Parainfluenza Virus and Human Adenoviruses’ Epidemiology, Clinical Characteristics and Associated Factors in Kenya: a Retrospective Investigation 2007-2013

Abstract

Background: Acute respiratory tract infections (ARTIs) of viral origin lead to substantial morbidity and mortality. Human respiratory syncytial virus (HRSV), human parainfluenza virus(HPIV), and human Adenoviruses (HAdV) have been frequently identified in the ARTIs. These viruses have severely threatened young children, the elderly, and immunocompromised people, causing significant public health burdens and outbreaks. HRSV, HPIV, and HAdV triggered epidemics vary by geographical location, time, and virus type. The epidemiological evidence of HRSV, HPIV and HAdV are scarce in Kenya and the East Africa Community (EAC) region generally. Objective: This retrospective investigation was conducted to define morbidity burden, estimate prevalence, and determine socio-demographic, clinical characteristics and climatic factors associated with HRSV, HPIV and HAdVs infections in Kenya. Besides, it assesses seasonality and described the spatiotemporal distribution of HRSV, HPIV and HAdVs. Methods: A retrospective cross-sectional investigation was designed for the study period of 2007 – 2013. Secondary data of influenza-like illness (ILI) participants were gathered from the ILI surveillance system of Kenya. A convenience sampling strategy was done, ILI participants N= 17,261 from surveillance program of influenza and other respiratory viruses consisted this investigation target population. Prior, a systematic review and meta-analysis were carried out in EAC with a particular focus on Kenya for the period of 2007-2020 to pool the prevalence for HRSV, HPIV and HAdVs. To define morbidity burden, estimate prevalence, and assess seasonality, an exploratory analysis was performed based on the ILI dataset, followed by a descriptive analysis. Furthermore, a fitted logistic regression model was applied to determine significant factors associated with HRSV, HPIV, and HAdV infections. Kulldorff's spatial scan statistic and geographical information system (GIS) were used to describe HRSV, HPIV and HAdVs distribution patterns over time and space.

Results: For the systematic review, a total of 12 studies met the eligibility criteria among the studies documented from 2007 to 2020. The pooled prevalence was 13% HAdVs, 11% HRSV and 9% HPIV in the EAC partner states with available data. In Kenya, the ILI surveillance program had eight surveillance sites from January 2007 to December 2013. The ILI morbidity burden for HRSV was 3.1%, HPIV 5.3%, and HAdV 3.3%. Infants (OR>1) were more likely to be infected with these viruses compared to other age groups. The participants’ enrolled in the ILI surveillance system presented with several clinical signs. After adjusting for age, none of the clinical characteristics, except for fever and cough, were significantly associated with HRSV, HPIV, and HAdV infections. HRSV exhibited seasonality with high occurrence in January-March (Odds Ratio [OR] =2.73) and April-June (OR=3.01). Hot land surface temperature (≥40°C) was also associated with HRSV infections (OR=2.75), as was warmer air temperature (19-22.9°C) (OR=1.68) compared to cooler air temperature (<19°C). Moderate rainfall (150-200mm) areas had greater odds of HSRV infection (OR=1.32) than low rainfall (<150mm) areas. HRSV, HPIV, and HAdV cases were distributed in several counties and varied geographically. The HRSV cases were densely found in Western, and Coastal regions. Whereas, HPIV and HAdVs were identified in the coastal, central, and western regions. Furthermore, the three respiratory viruses had local clusters with significant positive autocorrelation in the Western region of the country with (P<0.05). The primary purely spatial clusters of HRSV, HPIV and HAdV occurrence were found in the Western region. Besides, the space-time analysis indicated that HPIV primary cluster persisted in the Western region over the study period of 2007 to 2013. However, HAdV and HRSV primary clusters were observed in the Coastal region during 2008-09 and 2009-11 respectively. These results should be interpreted with caution because they were limited to the time of the study and could not be extrapolated to the actual population. Nevertheless, this investigation had the capability of including a large sample size, a lengthy study period, and a broad geographic region covering the entire country. The findings filled a substantial gap in the understanding of HRSV, HPIV, and HAdV epidemiology, providing resourceful information for intervention planning.

Conclusions and recommendations: Based on the systematic review of studies in EAC, the findings of this investigation indicated that human adenoviruses, human respiratory syncytial virus and human parainfluenza virus are prevalent in Kenya, Tanzania, and Uganda. These three respiratory viruses contribute substantially to ARTIs in the EAC partner states with available data, particularly among those with severe disease and those aged five and above. However, ILI surveillance in Kenya for HRSV, HPIV, and HAdVs indicated that these three respiratory viruses contributed to ILI morbidity burden, and infants were significantly affected. HRSV had a clear seasonal pattern and was associated with climate parameters, contrary to HPIV and HAdVs in Kenya. Fever, cough and runny nose were at a high proportion among the ILI participants. Also, the findings of this investigation suggested that the hotspots (clusters) for RSV, HPIV, and HAdV occurred in the Western and Coastal regions of Kenya from 2007 to 2013. The Western region appeared more prone to the occurrence of the three respiratory viruses irrespective of the time. Continued surveillance for HRSV, HPIV, and HAdVs is recommended to monitor changes in morbidity caused by these non-influenza respiratory viruses to the population in Kenya. Also, an event-based surveillance system should be established in the western and Coast regions to capture the occurrence of HRSV, HPIV, and HAdVs outbreaks. Furthermore, surveillance should include the population of all age categories with a particular focus on the elderly because there is a shortage of knowledge relating to this population.