INTRODUCTION: Data about healthcare workers' (HCW) willingness to accept and recommend seasonal influenza vaccination in countries without influenza vaccination programs are limited. METHODS: We conducted a cross-sectional survey in 7 of the 47 counties in Kenya to examine HCW's knowledge and perceptions of seasonal influenza disease and vaccination. We aimed to enroll all HCW who deliver clinical services directly or peripherally to patients from 5 health facilities in each county. We used chi-square tests and mixed effects logistic regression to identify variables associated with HCW's willingness to accept and recommend seasonal influenza vaccination. RESULTS: From May-June 2018, we enrolled 2035 HCW, representing 49.0 % of targeted respondents from 35 facilities. Most HCW (82.1 %) were from public health facilities. Among the HCW who had heard of seasonal influenza, 87.3 % (1420/1627) believed it can cause severe illness. Most HCW (1076/1209; 89.0 %) were willing to receive a seasonal influenza vaccine if it was recommended for them and provided for free, and 91.4 % (1441/1576) would vaccinate or recommend vaccination to their patients if vaccine was available. Only 17.6 % (213/1212) reported having ever received a seasonal influenza vaccine. HCW who believed that influenza could cause severe illness (aOR 1.8; 95 % CI 1.0-3.2) and that people around them would be better protected from influenza illness if HCW are vaccinated (aOR 3.1; 95 % CI 2.0-4.9) were more likely to report willingness to accept vaccination. HCW from private health facilities (aOR 2.2; 95 % CI 1.3-6.4), and those who believed that people around them are better protected if HCW are vaccinated (aOR 3.5; 95 % CI 2.2-5.8) were more likely to report willingness to vaccinate or recommend vaccination to patients. CONCLUSION: Our findings suggest favorable attitudes among HCW towards seasonal influenza vaccination, many of whom are motivated by the desire to protect the health of others around them.

BACKGROUND: Seasonal influenza illness and acute respiratory infections can impose a substantial economic burden in low- and middle-income countries (LMICs). We assessed the cost of influenza illness and acute respiratory infections across household income strata. METHODS: We conducted a secondary analysis of data from a prior systematic review of costs of influenza and other respiratory illnesses in LMICs and contacted authors to obtain data on cost of illness (COI) for laboratory-confirmed influenza-like illness and acute respiratory infection. We calculated the COI by household income strata and calculated the out-of-pocket (OOP) cost as a proportion of household income. RESULTS: We included 11 studies representing 11 LMICs. OOP expenses, as a proportion of annual household income, were highest among the lowest income quintile in 10 of 11 studies: in 4/4 studies among the general population, in 6/7 studies among children, 2/2 studies among older adults, and in the sole study for adults with chronic medical conditions. COI was generally higher for hospitalizations compared with outpatient illnesses; median OOP costs for hospitalizations exceeded 10% of annual household income among the general population and children in Kenya, as well as for older adults and adults with chronic medical conditions in China. CONCLUSIONS: The findings indicate that influenza and acute respiratory infections pose a considerable economic burden, particularly from hospitalizations, on the lowest income households in LMICs. Future evaluations could investigate specific drivers of COI in low-income household and identify interventions that may address these, including exploring household coping mechanisms. Cost-effectiveness analyses could incorporate health inequity analyses, in pursuit of health equity.

BACKGROUND: Little is known about the cocirculation of influenza and SARS-CoV-2 viruses during the COVID-19 pandemic and the use of respiratory disease sentinel surveillance platforms for monitoring SARS-CoV-2 activity in sub-Saharan Africa. OBJECTIVE: We aimed to describe influenza and SARS-CoV-2 cocirculation in Kenya and how the SARS-CoV-2 data from influenza sentinel surveillance correlated with that of universal national surveillance. METHODS: From April 2020 to March 2022, we enrolled 7349 patients with severe acute respiratory illness or influenza-like illness at 8 sentinel influenza surveillance sites in Kenya and collected demographic, clinical, underlying medical condition, vaccination, and exposure information, as well as respiratory specimens, from them. Respiratory specimens were tested for influenza and SARS-CoV-2 by real-time reverse transcription polymerase chain reaction. The universal national-level SARS-CoV-2 data were also obtained from the Kenya Ministry of Health. The universal national-level SARS-CoV-2 data were collected from all health facilities nationally, border entry points, and contact tracing in Kenya. Epidemic curves and Pearson r were used to describe the correlation between SARS-CoV-2 positivity in data from the 8 influenza sentinel sites in Kenya and that of the universal national SARS-CoV-2 surveillance data. A logistic regression model was used to assess the association between influenza and SARS-CoV-2 coinfection with severe clinical illness. We defined severe clinical illness as any of oxygen saturation <90%, in-hospital death, admission to intensive care unit or high dependence unit, mechanical ventilation, or a report of any danger sign (ie, inability to drink or eat, severe vomiting, grunting, stridor, or unconsciousness in children younger than 5 years) among patients with severe acute respiratory illness. RESULTS: Of the 7349 patients from the influenza sentinel surveillance sites, 76.3% (n=5606) were younger than 5 years. We detected any influenza (A or B) in 8.7% (629/7224), SARS-CoV-2 in 10.7% (768/7199), and coinfection in 0.9% (63/7165) of samples tested. Although the number of samples tested for SARS-CoV-2 from the sentinel surveillance was only 0.2% (60 per week vs 36,000 per week) of the number tested in the universal national surveillance, SARS-CoV-2 positivity in the sentinel surveillance data significantly correlated with that of the universal national surveillance (Pearson r=0.58; P<.001). The adjusted odds ratios (aOR) of clinical severe illness among participants with coinfection were similar to those of patients with influenza only (aOR 0.91, 95% CI 0.47-1.79) and SARS-CoV-2 only (aOR 0.92, 95% CI 0.47-1.82). CONCLUSIONS: Influenza substantially cocirculated with SARS-CoV-2 in Kenya. We found a significant correlation of SARS-CoV-2 positivity in the data from 8 influenza sentinel surveillance sites with that of the universal national SARS-CoV-2 surveillance data. Our findings indicate that the influenza sentinel surveillance system can be used as a sustainable platform for monitoring respiratory pathogens of pandemic potential or public health importance.

BACKGROUND: Healthcare workers (HCWs) are at high risk of exposure and transmission of infectious respiratory pathogens like influenza. Despite the potential benefits, safety and efficacy of influenza vaccination, vaccines are still underutilized in Africa, including among HCWs. METHOD: From May-June 2018, we conducted a cross-sectional, self-administered, written survey among HCWs from seven counties in Kenya and assessed their knowledge attitudes and perceptions towards pandemic influenza disease and vaccination. Using regression models, we assessed factors that were associated with the HCW's knowledge of pandemic influenza and vaccination. RESULTS: A total of 2,035 HCWs, representing 49% of the targeted respondents from 35 health facilities, completed the question. Sixty eight percent of the HCWs had ever heard of pandemic influenza, and 80.0% of these were willing to receive pandemic influenza vaccine if it was available. On average, Kenyan HCWs correctly answered 55.0% (95% CI 54.0-55.9) of the questions about pandemic influenza and vaccination. Physicians (65.6%, 95% CI 62.5-68.7) and pharmacists (61.7%, 95% CI 57.9-65.5) scored higher compared to nurses (53.1%, 95% CI 51.7-54.5). HCWs with 5 or more years of work experience (55.8, 95% CI 54.5-57.0) had marginally higher knowledge scores compared to those with less experience (53.9%, 95% CI 52.5-55.3). Most participants who were willing to receive pandemic influenza vaccine did so to protect their relatives (88.7%) or patients (85.9%). CONCLUSION: Our findings suggest moderate knowledge of pandemic influenza and vaccination by HCWs in Kenya, which varied by cadre and years of work experience. These findings highlight the need for continued in-service health education to increase the HCW's awareness and knowledge of pandemic influenza to increase acceptance of influenza vaccination in the case of a pandemic.

On February 22, 2017, Hospital X-Kampala and US CDC-Kenya reported to the Uganda Ministry of Health a respiratory illness in a 46-year-old expatriate of Company A. The patient, Mr. A, was evacuated from Uganda to Kenya and died. He had recently been exposed to dromedary camels (MERS-CoV) and wild birds with influenza A (H5N6). We investigated the cause of illness, transmission, and recommended control. We defined a suspected case of severe acute respiratory illness (SARI) as acute onset of fever (>/=38 degrees C) with sore throat or cough and at least one of the following: headache, lethargy, or difficulty in breathing. In addition, we looked at cases with onset between February 1 and March 31 in a person with a history of contact with Mr. A, his family, or other Company A employees. A confirmed case was defined as a suspected case with laboratory confirmation of the same pathogen detected in Mr. A. Influenza-like illness was defined as onset of fever (>/=38 degrees C) and cough or sore throat in a Uganda contact, and as fever (>/=38 degrees C) and cough lasting less than 10 days in a Kenya contact. We collected Mr. A's exposure and clinical history, searched for cases, and traced contacts. Specimens from the index case were tested for complete blood count, liver function tests, plasma chemistry, Influenza A(H1N1)pdm09, and MERS-CoV. Robust field epidemiology, laboratory capacity, and cross-border communication enabled investigation.

Background: The impact of influenza B virus circulation in Sub-Saharan Africa is not well described. Methods: We analyzed data from acute respiratory illness (ARI) in Kenya. We assessed clinical features and age-specific hospitalization and outpatient visit rates by person-years for influenza B/Victoria and B/Yamagata and the extent to which circulating influenza B lineages in Kenya matched the vaccine strain component of the corresponding season (based on Northern Hemisphere [October-March] and Southern Hemisphere [April-September] vaccine availability). Results: From 2012 to 2016, influenza B represented 31% of all influenza-associated ARIs detected (annual range, 13-61%). Rates of influenza B hospitalization and outpatient visits were higher for <5 vs >/=5 years. Among <5 years, B/Victoria was associated with pneumonia hospitalization (64% vs 44%; P = .010) and in-hospital mortality (6% vs 0%; P = .042) compared with B/Yamagata, although the mean annual hospitalization rate for B/Victoria was comparable to that estimated for B/Yamagata. The 2 lineages co-circulated, and there were mismatches with available trivalent influenza vaccines in 2/9 seasons assessed. Conclusions: Influenza B causes substantial burden in Kenya, particularly among children aged <5 years, in whom B/Victoria may be associated with increased severity. Our findings suggest a benefit from including both lineages when considering influenza vaccination in Kenya.

Background: We estimated the cost-per-episode and the annual economic burden associated with influenza in Kenya. Methods: From July 2013-August 2014, we recruited patients with severe acute respiratory illness (SARI) or influenza-like illness (ILI) associated with laboratory-confirmed influenza from 5 health facilities. A structured questionnaire was used to collect direct costs (medications, laboratory investigations, hospital bed fees, hospital management costs, transportation) and indirect costs (productivity losses) associated with an episode of influenza. We used published incidence of laboratory-confirmed influenza associated with SARI and ILI, and the national population census data from 2014, to estimate the annual national number of influenza-associated hospitalizations and outpatient visits and calculated the annual economic burden by multiplying cases by the mean cost. Results: We enrolled 275 patients (105 inpatients and 170 outpatients). The mean cost-per-episode of influenza was US$117.86 (standard deviation [SD], 88.04) among inpatients; US$114.25 (SD, 90.03) for children < 5 years, and US$137.45 (SD, 76.24) for persons aged ≥5 years. Among outpatients, the mean cost-per-episode of influenza was US$19.82 (SD, 27.29); US$21.49 (SD, 31.42) for children < 5 years, and US$16.79 (SD, 17.30) for persons aged ≥5 years. National annual influenza-associated cost estimates ranged from US$2.96-5.37 million for inpatients and US$5.96-26.35 million for outpatients. Conclusions: Our findings highlight influenza as causing substantial economic burden in Kenya. Further studies may be warranted to assess the potential benefit of targeted influenza vaccination strategies.

BACKGROUND: We evaluated the performance of the Becton Dickinson Veritor System Flu A + B rapid influenza diagnostic test (RIDT) to detect influenza viruses in respiratory specimens from patients enrolled at five surveillance sites in Kenya, a tropical country where influenza seasonality is variable. METHODS: Nasal swab (NS) and nasopharyngeal (NP)/oropharyngeal (OP) swabs were collected from patients with influenza like illness and/or severe acute respiratory infection. The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of the RIDT using NS specimens were evaluated against nasal swabs tested by real time reverse transcription polymerase chain reaction (rRT-PCR). The performance parameter results were expressed as 95% confidence intervals (CI) calculated using binomial exact methods, with P < 0.05 considered significant. Two-sample Z tests were used to test for differences in sample proportions. Analysis was performed using SAS software version 9.3. RESULTS: From July 2013 to July 2014, 3,569 patients were recruited, of which 78.7% were aged <5 years. Overall, 14.4% of NS specimens were influenza-positive by RIDT. RIDT overall sensitivity was 77.1% (95% CI 72.8-81.0%) and specificity was 94.9% (95% CI 94.0-95.7%) compared to rRT-PCR using NS specimens. RIDT sensitivity for influenza A virus compared to rRT-PCR using NS specimens was 71.8% (95% CI 66.7-76.4%) and was significantly higher than for influenza B which was 43.8% (95% CI 33.8-54.2%). PPV ranged from 30%-80% depending on background prevalence of influenza. CONCLUSION: Although the variable seasonality of influenza in tropical Africa presents unique challenges, RIDTs may have a role in making influenza surveillance sustainable in more remote areas of Africa, where laboratory capacity is limited.

BACKGROUND: Although health care-associated infections are an important cause of morbidity and mortality worldwide, the epidemiology and etiology of respiratory health care-associated infections (rHAIs) have not been documented in Kenya. In 2010, the Ministry of Health, Kenya Medical Research Institute, and Centers for Disease Control and Prevention initiated surveillance for rHAIs at 3 hospitals. METHODS: At each hospital, we surveyed intensive care units (ICUs), pediatric wards, and medical wards to identify patients with rHAIs, defined as any hospital-onset (≥3 days after admission) fever (≥38 degrees C) or hypothermia (<35 degrees C) with concurrent signs or symptoms of acute respiratory infection. Nasopharyngeal and oropharyngeal specimens were collected from these patients and tested by real-time reverse transcription polymerase chain reaction for influenza and 7 other viruses. RESULTS: From April 2010-September 2012, of the 379 rHAI cases, 60.7% were men and 57.3% were children <18 years old. The overall incidence of rHAIs was 9.2 per 10,000 patient days, with the highest incidence in the ICUs. Of all specimens analyzed, 45.7% had at least 1 respiratory virus detected; 92.2% of all positive viral specimens were identified in patients <18 years old. CONCLUSION: We identified rHAIs in all ward types under surveillance in Kenyan hospitals. Viruses may have a substantial role in these infections, particularly among pediatric populations. Further research is needed to refine case definitions and understand rHAIs in ICUs.