Improving Detection and Response to Respiratory Events - Kenya, April 2016-April 2020.

Respiratory pathogens, such as novel influenza A viruses, Middle East respiratory syndrome coronavirus (MERS-CoV), and now, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), are of particular concern because of their high transmissibility and history of global spread (1). Clusters of severe respiratory disease are challenging to investigate, especially in resource-limited settings, and disease etiology often is not well understood. In 2014, endorsed by the Group of Seven (G7),* the Global Health Security Agenda (GHSA) was established to help build country capacity to prevent, detect, and respond to infectious disease threats.† GHSA is a multinational, multisectoral collaboration to support countries towards full implementation of the World Health Organization's International Health Regulations (IHR).§ Initially, 11 technical areas for collaborator participation were identified to meet GHSA goals. CDC developed the Detection and Response to Respiratory Events (DaRRE) strategy in 2014 to enhance country capacity to identify and control respiratory disease outbreaks. DaRRE initiatives support the four of 11 GHSA technical areas that CDC focuses on: surveillance, laboratory capacity, emergency operations, and workforce development.¶ In 2016, Kenya was selected to pilot DaRRE because of its existing respiratory disease surveillance and laboratory platforms and well-developed Field Epidemiology and Laboratory Training Program (FELTP) (2). During 2016-2020, Kenya's DaRRE partners (CDC, the Kenya Ministry of Health [MoH], and Kenya's county public health officials) conceptualized, planned, and implemented key components of DaRRE. Activities were selected based on existing capacity and determined by the Kenya MoH and included 1) expansion of severe acute respiratory illness (SARI) surveillance sites; 2) piloting of community event-based surveillance; 3) expansion of laboratory diagnostic capacity; 4) training of public health practitioners in detection, investigation, and response to respiratory threats; and 5) improvement of response capacity by the national emergency operations center (EOC). Progress on DaRRE activity implementation was assessed throughout the process. This pilot in Kenya demonstrated that DaRRE can support IHR requirements and can capitalize on a country's existing resources by tailoring tools to improve public health preparedness based on countries' needs.

A comparison of smartphones to paper-based questionnaires for routine influenza sentinel surveillance, Kenya, 2011-2012.

BACKGROUND: For disease surveillance, manual data collection using paper-based questionnaires can be time consuming and prone to errors. We introduced smartphone data collection to replace paper-based data collection for an influenza sentinel surveillance system in four hospitals in Kenya. We compared the quality, cost and timeliness of data collection between the smartphone data collection system and the paper-based system. METHODS: Since 2006, the Kenya Ministry of Health (MoH) with technical support from the Kenya Medical Research Institute/Centers for Disease Control and Prevention (KEMRI/CDC) conducted hospital-based sentinel surveillance for influenza in Kenya. In May 2011, the MOH replaced paper-based collection with an electronic data collection system using Field Adapted Survey Toolkit (FAST) on HTC Touch Pro2 smartphones at four sentinel sites. We compared 880 paper-based questionnaires dated Jan 2010-Jun 2011 and 880 smartphone questionnaires dated May 2011-Jun 2012 from the four surveillance sites. For each site, we compared the quality, cost and timeliness of each data collection system. RESULTS: Incomplete records were more likely seen in data collected using pen-and-paper compared to data collected using smartphones (adjusted incidence rate ratio (aIRR) 7, 95% CI: 4.4-10.3). Errors and inconsistent answers were also more likely to be seen in data collected using pen-and-paper compared to data collected using smartphones (aIRR: 25, 95% CI: 12.5-51.8). Smartphone data was uploaded into the database in a median time of 7 days while paper-based data took a median of 21 days to be entered (p < 0.01). It cost USD 1,501 (9.4%) more to establish the smartphone data collection system ($17,500) than the pen-and-paper system (USD $15,999). During two years, however, the smartphone data collection system was $3,801 (7%) less expensive to operate ($50,200) when compared to pen-and-paper system ($54,001). CONCLUSIONS: Compared to paper-based data collection, an electronic data collection system produced fewer incomplete data, fewer errors and inconsistent responses and delivered data faster. Although start-up costs were higher, the overall costs of establishing and running the electronic data collection system were lower compared to paper-based data collection system. Electronic data collection using smartphones has potential to improve timeliness, data integrity and reduce costs.

Use of Sentinel Surveillance Platforms for Monitoring SARS-CoV-2 Activity: Evidence From Analysis of Kenya Influenza Sentinel Surveillance Data.

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.

Costs of seasonal influenza vaccine delivery in a pediatric demonstration project for children aged 6-23 months - Nakuru and Mombasa Counties, Kenya, 2019-2021.

BACKGROUND: During November 2019-October 2021, a pediatric influenza vaccination demonstration project was conducted in four sub-counties in Kenya. The demonstration piloted two different delivery strategies: year-round vaccination and a four-month vaccination campaign. Our objective was to compare the costs of both delivery strategies. METHODS: Cost data were collected using standardized questionnaires and extracted from government and project accounting records. We reported total costs and costs per vaccine dose administered by delivery strategy from the Kenyan government perspective in 2021 US$. Costs were separated into financial costs (monetary expenditures) and economic costs (financial costs plus the value of existing resources). We also separated costs by administrative level (national, regional, county, sub-county, and health facility) and program activity (advocacy and social mobilization; training; distribution, storage, and waste management; service delivery; monitoring; and supervision). RESULTS: The total estimated cost of the pediatric influenza demonstration project was US$ 225,269 (financial) and US$ 326,691 (economic) for the year-round delivery strategy (30,397 vaccine doses administered), compared with US$ 214,753 (financial) and US$ 242,385 (economic) for the campaign strategy (25,404 doses administered). Vaccine purchase represented the largest proportion of costs for both strategies. Excluding vaccine purchase, the cost per dose administered was US$ 1.58 (financial) and US$ 5.84 (economic) for the year-round strategy and US$ 2.89 (financial) and US$ 4.56 (economic) for the campaign strategy. CONCLUSIONS: The financial cost per dose was 83% higher for the campaign strategy than the year-round strategy due to larger expenditures for advocacy and social mobilization, training, and hiring of surge staff for service delivery. However, the economic cost per dose was more comparable for both strategies (year-round 22% higher than campaign), balanced by higher costs of operating equipment and monitoring activities for the year-round strategy. These delivery cost data provide real-world evidence to inform pediatric influenza vaccine introduction in Kenya.

Comparing performance of year-round and campaign-mode influenza vaccination strategies among children aged 6-23 months in Kenya: 2019-2021.

INTRODUCTION: In 2016, the Kenya National Immunization Technical Advisory Group requested additional programmatic and cost effectiveness data to inform the choice of strategy for a national influenza vaccination program among children aged 6-23 months of age. In response, we conducted an influenza vaccine demonstration project to compare the performance of a year-round versus campaign-mode vaccination strategy. Findings from this demonstration project will help identify essential learning lessons for a national program. METHODS: We compared two vaccine delivery strategies: (i) a year-round vaccination strategy where influenza vaccines were administered throughout the year at health facilities. This strategy was implemented in Njoro sub-county in Nakuru (November 2019 to October 2021) and Jomvu sub-county in Mombasa (December 2019 to October 2021), (ii) a campaign-mode vaccination strategy where vaccines were available at health facilities over four months. This strategy was implemented in Nakuru North sub-county in Nakuru (June to September 2021) and Likoni sub-county in Mombasa (July to October 2021). We assessed differences in coverage, dropout rates, vaccine wastage, and operational needs. RESULTS: We observed similar performance between strategies in coverage of the first dose of influenza vaccine (year-round strategy 59.7 %, campaign strategy 63.2 %). The coverage obtained in the year-round sub-counties was similar (Njoro 57.4 %; Jomvu 63.1 %); however, more marked differences between campaign sub-counties were observed (Nakuru North 73.4 %; Likoni 55.2 %). The campaign-mode strategy exceeded the cold chain capacity of participating health facilities, requiring thrice monthly instead of once monthly deliveries, and was associated with a two-fold increase in workload compared to the year-round strategy (168 vaccines administered per day in the campaign strategy versus 83 vaccines administered per day in the year-round strategy). CONCLUSION: Although both strategies had similar coverage levels, the campaign-mode strategy was associated with considerable operational needs that could significantly impact the immunization program.

Severe acute respiratory illness surveillance for influenza in Kenya: Patient characteristics and lessons learnt.

BACKGROUND: We describe the epidemiology and clinical features of Kenyan patients hospitalized with laboratory-confirmed influenza compared with those testing negative and discuss the potential contribution of severe acute respiratory illness (SARI) surveillance in monitoring a broader range of respiratory pathogens. METHODS: We described demographic and clinical characteristics of SARI cases among children (<18 years) and adults, separately. We compared disease severity (clinical features and treatment) of hospitalized influenza positive versus negative cases and explored independent predictors of death among SARI cases using a multivariable logistic regression model. RESULTS: From January 2014 to December 2018, 11,166 persons were hospitalized with SARI and overall positivity for influenza was ~10%. There were 10,742 (96%) children (<18 years)-median age of 1 year, interquartile range (IQR = 6 months, 2 years). Only 424 (4%) of the SARI cases were adults (≥18 years), with median age of 38 years (IQR 28 years, 52 years). There was no difference in disease severity comparing influenza positive and negative cases among children. Children hospitalized with SARI who had an underlying illness had greater odds of in-hospital death compared with those without (adjusted odds ratio 2.11 95% CI 1.09-4.07). No further analysis was done among adults due to the small sample size. CONCLUSION: Kenya's sentinel surveillance for SARI mainly captures data on younger children. Hospital-based platforms designed to monitor influenza viruses and associated disease burden may be adapted and expanded to other respiratory viruses to inform public health interventions. Efforts should be made to capture adults as part of routine respiratory surveillance.

Knowledge and attitude of Kenyan healthcare workers towards pandemic influenza disease and vaccination: 9 years after the last influenza pandemic.

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.

Investigation of a Cluster of Severe Respiratory Disease Referred from Uganda to Kenya, February 2017.

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°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°C) and cough or sore throat in a Uganda contact, and as fever (≥38°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.

Developing a seasonal influenza vaccine recommendation in Kenya: Process and challenges faced by the National Immunization Technical Advisory Group (NITAG).

BACKGROUND: In 2014 the Kenya National Immunization Technical Advisory Group (KENITAG) was asked by the Ministry of Health to provide an evidence-based recommendation on whether the seasonal influenza vaccine should be introduced into the national immunization program (NIP). METHODS: We reviewed KENITAG manuals, reports and meeting minutes generated between June 2014 and June 2016 in order to describe the process KENITAG used in arriving at that recommendation and the challenges encountered. RESULTS: KENITAG developed a recommendation framework to identify critical, important and non-critical data elements that would guide deliberations on the subject. Literature searches were conducted in several databases and the quality of scientific articles obtained was assessed using the Critical Appraisal Skills Programme tool. There were significant gaps in knowledge on the national burden of influenza disease among key risk groups, i.e., pregnant women, individuals with co-morbidities, the elderly and health care workers. Insufficient funding and limited work force hindered KENITAG activities. In 2016 KENITAG recommended introduction of the annual seasonal influenza vaccine among children 6 to 23 months of age. However, the recommendation was contingent on implementation of a pilot study to address gaps in local data on the socio-economic impact of influenza vaccination programs, strategies for vaccine delivery, and the impact of the vaccination program on the healthcare workforce and existing immunization program. KENITAG did not recommend the influenza vaccine for any other risk group due to lack of local burden of disease data. CONCLUSION: Local data are a critical element in NITAG deliberations, however, where local data and in particular burden of disease data are lacking, there is need to adopt scientifically acceptable methods of utilizing findings from other countries to inform local decisions in a manner that is valid and acceptable to decision makers.

Seroprevalence of Chikungunya virus (CHIKV) infection on Lamu Island, Kenya, October 2004.

An outbreak of Chikungunya virus (CHIKV) disease associated with high fever and severe protracted arthralgias was detected in Lamu, Kenya, peaking in July 2004. At least 1,300 cases were documented. We conducted a seroprevalence study to define the magnitude of transmission on Lamu Island. We conducted a systematic cross-sectional survey. We administered questionnaires and tested 288 sera from Lamu residents for IgM and IgG antibodies to CHIKV. Chikungunya virus infection (seropositivity) was defined as a person with IgG and/or IgM antibodies to CHIKV. IgM antibodies to CHIKV were detected in 18% (53/288) and IgG antibodies in 72% (206/288); IgM and/or IgG antibodies were present in 75% (215/288). The seroprevalence findings suggested that the outbreak was widespread, affecting 75% of the Lamu population; extrapolating the findings to the entire population, 13,500 (95% CI, 12,458-14328) were affected. Vector control strategies are needed to control the spread of this mosquito-borne infection.

Rapid spread of Vibrio cholerae O1 throughout Kenya, 2005.

Between January and June 2005, 5 distinct cholera outbreaks occurred in Kenya. Overall, 990 cases and 25 deaths (2.5%) were reported. Four outbreaks occurred in towns along major highways, and 1 occurred in a refugee camp near the Sudanese border, accessible to Nairobi by daily flights. Matched case-control studies from 2 outbreaks showed that failure to treat drinking water and storing drinking water in wide-mouthed containers were significantly associated with disease. Isolates from all 5 outbreaks were Vibrio cholerae O1, Inaba serotype, and had genetically similar PFGE patterns of SfiI-digested chromosomal DNA. Linkage of the outbreak locations by major transportation routes, their temporal proximity, and similar PFGE patterns of isolates suggests the outbreaks might have been linked epidemiologically, showing the speed and distance of cholera spread in countries like Kenya with pockets of susceptible populations connected by modern transportation. Prevention measures remain implementation of point-of-use safe water systems and case finding and referral.

Results from the first six years of national sentinel surveillance for influenza in Kenya, July 2007-June 2013.

BACKGROUND: Recent studies have shown that influenza is associated with significant disease burden in many countries in the tropics, but until recently national surveillance for influenza was not conducted in most countries in Africa. METHODS: In 2007, the Kenyan Ministry of Health with technical support from the CDC-Kenya established a national sentinel surveillance system for influenza. At 11 hospitals, for every hospitalized patient with severe acute respiratory illness (SARI), and for the first three outpatients with influenza-like illness (ILI) per day, we collected both nasopharyngeal and oropharyngeal swabs. Beginning in 2008, we conducted in-hospital follow-up for SARI patients to determine outcome. Specimens were tested by real time RT-PCR for influenza A and B. Influenza A-positive specimens were subtyped for H1, H3, H5, and (beginning in May 2009) A(H1N1)pdm09. RESULTS: From July 1, 2007 through June 30, 2013, we collected specimens from 24,762 SARI and 14,013 ILI patients. For SARI and ILI case-patients, the median ages were 12 months and 16 months, respectively, and 44% and 47% were female. In all, 2,378 (9.6%) SARI cases and 2,041 (14.6%) ILI cases were positive for influenza viruses. Most influenza-associated SARI cases (58.6%) were in children <2 years old. Of all influenza-positive specimens, 78% were influenza A, 21% were influenza B, and 1% were influenza A/B coinfections. Influenza circulated in every month. In four of the six years influenza activity peaked during July-November. Of 9,419 SARI patients, 2.7% died; the median length of hospitalization was 4 days. CONCLUSIONS: During six years of surveillance in Kenya, influenza was associated with nearly 10 percent of hospitalized SARI cases and one-sixth of outpatient ILI cases. Most influenza-associated SARI and ILI cases were in children <2 years old; interventions to reduce the burden of influenza, such as vaccine, could consider young children as a priority group.

Challenges of establishing the correct diagnosis of outbreaks of acute febrile illnesses in Africa: the case of a likely Brucella outbreak among nomadic pastoralists, northeast Kenya, March-July 2005.

An outbreak of acute febrile illness was reported among Somali pastoralists in remote, arid Northeast Kenya, where drinking raw milk is common. Blood specimens from 12 patients, collected mostly in the late convalescent phase, were tested for viral, bacterial, and parasitic pathogens. All were negative for viral and typhoid serology. Nine patients had Brucella antibodies present by at least one of the tests, four of whom had evidence suggestive of acute infection by the reference serologic microscopic agglutination test. Three patients were positive for leptospiral antibody by immunoglobulin M enzyme-linked immunosorbent assay, and two were positive for malaria. Although sensitive and specific point-of-care testing methods will improve diagnosis of acute febrile illness in developing countries, challenges of interpretation still remain when the outbreaks are remote, specimens collected too late, and positive results for multiple diseases are obtained. Better diagnostics and tools that can decipher overlapping signs and symptoms in such settings are needed.