Kenya's experience implementing event-based surveillance during the COVID-19 pandemic.

Event-based surveillance (EBS) can be implemented in most settings for the detection of potential health threats by recognition and immediate reporting of predefined signals. Such a system complements existing case-based and sentinel surveillance systems. With the emergence of the COVID-19 pandemic in early 2020, the Kenya Ministry of Health (MOH) modified and expanded an EBS system in both community and health facility settings for the reporting of COVID-19-related signals. Using an electronic reporting tool, m-Dharura, MOH recorded 8790 signals reported, with 3002 (34.2%) verified as events, across both community and health facility sites from March 2020 to June 2021. A subsequent evaluation found that the EBS system was flexible enough to incorporate the addition of COVID-19-related signals during a pandemic and maintain high rates of reporting from participants. Inadequate resources for follow-up investigations to reported events, lack of supportive supervision for some community health volunteers and lack of data system interoperability were identified as challenges to be addressed as the EBS system in Kenya continues to expand to additional jurisdictions.

Africa CDC's blueprint to enhance early warning surveillance: accelerating implementation of event-based surveillance in Africa.

Event-based surveillance (EBS) is a core component of early warning surveillance. In 2018, Africa CDC developed the first edition of an event-based surveillance framework to guide African Union Member States in implementing EBS. Country experiences during the COVID-19 pandemic demonstrated the value of data from non-traditional sources for real time situational awareness; at the same time revealed the huge gaps in strengthening this arm of surveillance. Learning from these lessons and to begin to close those gaps, Africa CDC convened subject matter experts from African Union Member States and technical partners to develop the second edition of the EBS framework, 2023 and its training materials. The revised version includes additional sections such as, the multi-sectoral one health collaboration in EBS, monitoring and evaluation, cross border EBS, and use of event management systems. The current manuscript provides an overview of the 2023 Africa CDC EBS framework and highlights experience in two countries that have successfully employed this resource in their implementation efforts.

Characterization of COVID-19 cases in the early phase (March to July 2020) of the pandemic in Kenya.

Background: Kenya detected the first case of COVID-19 on March 13, 2020, and as of July 30, 2020, 17 975 cases with 285 deaths (case fatality rate (CFR) = 1.6%) had been reported. This study described the cases during the early phase of the pandemic to provide information for monitoring and response planning in the local context. Methods: We reviewed COVID-19 case records from isolation centres while considering national representation and the WHO sampling guideline for clinical characterization of the COVID-19 pandemic within a country. Socio-demographic, clinical, and exposure data were summarized using median and mean for continuous variables and proportions for categorical variables. We assigned exposure variables to socio-demographics, exposure, and contact data, while the clinical spectrum was assigned outcome variables and their associations were assessed. Results: A total of 2796 case records were reviewed including 2049 (73.3%) male, 852 (30.5%) aged 30-39 years, 2730 (97.6%) Kenyans, 636 (22.7%) transporters, and 743 (26.6%) residents of Nairobi City County. Up to 609 (21.8%) cases had underlying medical conditions, including hypertension (n = 285 (46.8%)), diabetes (n = 211 (34.6%)), and multiple conditions (n = 129 (21.2%)). Out of 1893 (67.7%) cases with likely sources of exposure, 601 (31.8%) were due to international travel. There were 2340 contacts listed for 577 (20.6%) cases, with 632 contacts (27.0%) being traced. The odds of developing COVID-19 symptoms were higher among case who were aged above 60 years (odds ratio (OR) = 1.99, P = 0.007) or had underlying conditions (OR = 2.73, P < 0.001) and lower among transport sector employees (OR = 0.31, P < 0.001). The odds of developing severe COVID-19 disease were higher among cases who had underlying medical conditions (OR = 1.56, P < 0.001) and lower among cases exposed through community gatherings (OR = 0.27, P < 0.001). The odds of survival of cases from COVID-19 disease were higher among transport sector employees (OR = 3.35, P = 0.004); but lower among cases who were aged ≥60 years (OR = 0.58, P = 0.034) and those with underlying conditions (OR = 0.58, P = 0.025). Conclusion: The early phase of the COVID-19 pandemic demonstrated a need to target the elderly and comorbid cases with prevention and control strategies while closely monitoring asymptomatic cases.

Imported SARS-COV-2 Variants of Concern Drove Spread of Infections Across Kenya During the Second Year of the Pandemic.

Background: Using classical and genomic epidemiology, we tracked the COVID-19 pandemic in Kenya over 23 months to determine the impact of SARS-CoV-2 variants on its progression. Methods: SARS-CoV-2 surveillance and testing data were obtained from the Kenya Ministry of Health, collected daily from 306 health facilities. COVID-19-associated fatality data were also obtained from these health facilities and communities. Whole SARS-CoV-2 genome sequencing were carried out on 1241 specimens. Results: Over the pandemic duration (March 2020 - January 2022) Kenya experienced five waves characterized by attack rates (AR) of between 65.4 and 137.6 per 100,000 persons, and intra-wave case fatality ratios (CFR) averaging 3.5%, two-fold higher than the national average COVID-19 associated CFR. The first two waves that occurred before emergence of global variants of concerns (VoC) had lower AR (65.4 and 118.2 per 100,000). Waves 3, 4, and 5 that occurred during the second year were each dominated by multiple introductions each, of Alpha (74.9% genomes), Delta (98.7%), and Omicron (87.8%) VoCs, respectively. During this phase, government-imposed restrictions failed to alleviate pandemic progression, resulting in higher attack rates spread across the country. Conclusions: The emergence of Alpha, Delta, and Omicron variants was a turning point that resulted in widespread and higher SARS-CoV-2 infections across the country.

High incidence of human brucellosis in a rural Pastoralist community in Kenya, 2015.

BACKGROUND: Brucellosis occurs globally with highly variable incidence in humans from very low in North America and Western Europe to high in the Middle East and Asia. There are few data in Sub-Saharan Africa. This study estimated the incidence of human brucellosis in a pastoralist community in Kenya. METHODS: Between February 2015 and January 2016, we enrolled persons living in randomly selected households in Kajiado County. Free health care was offered at three facilities in the study area. Those who met the study clinical case definition completed a standardized questionnaire on demographics, clinical history and presentation. A blood sample was collected and tested by Rose Bengal test (RBT), then later tested at the Kenya Medical Research Institute laboratory for Brucella IgG and IgM by ELISA. Those who tested positive by both RBT and ELISA (IgG or IgM antibodies) were classified as confirmed while those that only tested positive for IgG or IgM antibodies were classified as probable. Further, sera were tested by polymerase chain reaction using a TaqMan Array Card (TAC) for a panel of pathogens causing AFI including Brucella spp. Annual incidence of brucellosis was calculated as the number of confirmed cases in one year/total number in the study population. RESULTS: We enrolled a cohort of 4746 persons in 804 households. Over half (52.3%) were males and the median age was 18 years (Interquartile range (IQR) 9 months- 32 years). A total of 236 patients were enrolled at three health facilities; 64% were females and the median age was 40.5 years (IQR 28-53 years). Thirty-nine (16.5%) were positive for Brucella antibodies by IgG ELISA, 5/236 (2.1%) by IgM ELISA and 4/236 (1.7%) by RBT. Ten percent (22/217) were positive by TAC. We confirmed four (1.7%) brucellosis cases giving an annual incidence of 84/100,000 persons/year (95% CI 82, 87). The incidence did not significantly vary by gender, age and location of residence. CONCLUSION: We report a high incidence of brucellosis in humans among members of this pastoralist community. Brucellosis was the most common cause of febrile illness in this community.