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BackgroundThe impact of COVID-19 in Africa remains poorly defined. We sought to describe trends in hospitalisation due to all medical causes, pneumonia-specific admissions, and inpatient mortality in Kenya before and during the first five waves of the COVID-19 pandemic in Kenya. MethodsWe conducted a hospital-based, multi-site, longitudinal observational study of patients admitted to 13 public referral facilities in Kenya from January 2018 to December 2021. The pre-COVID population included patients admitted before 1 March 2020. We fitted time series models to compare observed and predicted trends for each outcome. To estimate the impact of the COVID-19 pandemic, we calculated incidence rate ratios (IRR) and corresponding 95% confidence intervals (CI) from negative binomial mixed-effects models. ResultsOut of 302,703 patients hospitalised across the 13 surveillance sites (range 11547 to 57011), 117642 (39%) were admitted to adult wards. Compared with the pre-COVID period, hospitalisations declined markedly among adult (IRR 0.68, 95% CI 0.63 to 0.73) and paediatric (IRR 0.67, 95% CI 0.62 to 0.73) patients. Adjusted in-hospital mortality also declined among both adult (IRR 0.83, 95% CI 0.77 to 0.89) and paediatric (IRR 0.85, 95% CI 0.77 to 0.94) admissions. Pneumonia-specific admissions among adults increased during the pandemic (IRR 1.75, 95% CI 1.18 to 2.59). Paediatric pneumonia cases were lower than pre-pandemic levels in the first year of the pandemic and elevated in late 2021 (IRR 0.78, 95% CI 0.51 to 1.20). ConclusionsContrary to initial predictions, the COVID-19 pandemic was associated with lower hospitalisation rates and in-hospital mortality, despite increased pneumonia admissions among adults. These trends were sustained after the withdrawal of containment measures that disrupted essential health services, suggesting a role for additional factors that warrant further investigation.
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BackgroundThere is uncertainty about the mortality impact of the COVID-19 pandemic in Africa because of poor ascertainment of cases and limited national civil vital registration. We analysed excess mortality from 1st January 2020-5th May 2022 in a Health and Demographic Surveillance Study in Coastal Kenya where the SARS-CoV-2 seroprevalence reached 75% among adults in March 2022 despite vaccine uptake of only 17%. MethodsWe modelled expected mortality in 2020-2022 among a population of 306,000 from baseline surveillance data between 2010-2019. We calculated excess mortality as the ratio of observed/expected deaths in 5 age strata for each month and for each national wave of the pandemic. We estimated cumulative mortality risks as the total number of excess deaths in the pandemic per 100,000 population. We investigated observed deaths using verbal autopsy. FindingWe observed 16,236 deaths among 3,410,800 person years between 1st January 2010 and 5th May 2022. Across 5 waves of COVID-19 cases during 1st April 2020-16th April 2022, population excess mortality was 4.1% (95% PI -0.2%, 7.9%). Mortality was elevated among those aged [≥]65 years at 14.3% (95% PI 7.4%, 21.6%); excess deaths coincided with wave 2 (wild-type), wave 4 (Delta) and wave 5 (Omicron BA1). Among children aged 1-14 years there was negative excess mortality of -20.3% (95% PI -29.8%, -8.1%). Verbal autopsy data showed a transient reduction in deaths from acute respiratory infections in 2020 at all ages. For comparison with other studies, cumulative excess mortality risk for January 2020-December 2021, age-standardized to the Kenyan population, was 47.5/100,000. InterpretationNet excess mortality during the pandemic was substantially lower in Coastal Kenya than in many high income countries. However, adults, aged [≥]65 years, experienced substantial excess mortality suggesting that targeted COVID-19 vaccination of older persons may limit further COVID-19 deaths by protecting the residual pool of naive individuals. FundingWellcome Trust
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BackgroundAccurate and timely diagnosis is essential in limiting the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Real-time reverse transcription-polymerase chain reaction (rRT-PCR), the reference standard, requires specialized laboratories, costly reagents, and a long turnaround time. Antigen rapid diagnostic tests (Ag RDTs) provide a feasible alternative to rRT-PCR since they are quick, relatively inexpensive, and do not require a laboratory. The WHO requires that Ag RDTs have a sensitivity [≥]80% and specificity [≥]97%. MethodsThis evaluation was conducted at 11 health facilities in Kenya between March and July 2021. We enrolled persons of any age with respiratory symptoms and asymptomatic contacts of confirmed COVID-19 cases. We collected demographic and clinical information and two nasopharyngeal specimens from each participant for Ag RDT testing and rRT-PCR. We calculated the diagnostic performance of the Panbio Ag RDT against the US Centers for Disease Control and Preventions (CDC) rRT-PCR test. ResultsWe evaluated the Ag RDT in 2,245 individuals where 551 (24.5%, 95% CI: 22.8-26.3%) tested positive by rRT-PCR. Overall sensitivity of the Ag RDT was 46.6% (95% CI: 42.4-50.9%), specificity 98.5% (95% CI: 97.8-99.0%), PPV 90.8% (95% CI: 86.8-93.9%) and NPV 85.0% (95% CI: 83.4-86.6%). Among symptomatic individuals, sensitivity was 60.6% (95% CI: 54.3-66.7%) and specificity was 98.1% (95% CI: 96.7-99.0%). Among asymptomatic individuals, sensitivity was 34.7% (95% CI 29.3-40.4%) and specificity was 98.7% (95% CI: 97.8-99.3%). In persons with onset of symptoms <5 days (594/876, 67.8%), sensitivity was 67.1% (95% CI: 59.2-74.3%), and 53.3% (95% CI: 40.0-66.3%) among those with onset of symptoms >7 days (157/876, 17.9%). The highest sensitivity was 87.0% (95% CI: 80.9-91.8%) in symptomatic individuals with cycle threshold (Ct) values [≤]30. ConclusionThe overall sensitivity and NPV of the Panbio Ag RDT were much lower than expected. The specificity of the Ag RDT was high and satisfactory; therefore, a positive result may not require confirmation by rRT-PCR. The kit may be useful as a rapid screening tool for only symptomatic patients in high-risk settings with limited access to RT-PCR. A negative result should be interpreted based on clinical and epidemiological information and may require retesting by rRT-PCR.
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BackgroundFew studies have assessed the benefits of COVID-19 vaccines in settings where most of the population had been exposed to SARS-CoV-2 infection. MethodsWe conducted a cost-effectiveness analysis of COVID-19 vaccine in Kenya from a societal perspective over a 1.5-year time frame. An age-structured transmission model assumed at least 80% of the population to have prior natural immunity when an immune escape variant was introduced. We examine the effect of slow (18 months) or rapid (6 months) vaccine roll-out with vaccine coverage of 30%, 50% or 70% of the adult (> 18 years) population prioritizing roll-out in over 50-year olds (80% uptake in all scenarios). Cost data were obtained from primary analyses. We assumed vaccine procurement at $7 per dose and vaccine delivery costs of $3.90-$6.11 per dose. The cost-effectiveness threshold was USD 919. FindingsSlow roll-out at 30% coverage largely targets over 50-year-olds and resulted in 54% fewer deaths (8,132(7,914 to 8,373)) than no vaccination and was cost-saving (ICER=US$-1,343 (-1,345 to - 1,341) per DALY averted). Increasing coverage to 50% and 70%, further reduced deaths by 12% (810 (757 to 872) and 5% (282 (251 to 317) but was not cost-effective, using Kenyas cost-effectiveness threshold ($ 919.11). Rapid roll-out with 30% coverage averted 63% more deaths and was more cost-saving (ICER=$-1,607 (-1,609 to -1,604) per DALY averted) compared to slow roll-out at the same coverage level, but 50% and 70% coverage scenarios were not cost-effective. InterpretationWith prior exposure partially protecting much of the Kenyan population, vaccination of young adults may no longer be cost-effective. KEY QUESTIONSO_ST_ABSWhat is already known?C_ST_ABSO_LIThe COVID-19 pandemic has led to a substantial number of cases and deaths in low-and middle-income countries. C_LIO_LICOVID-19 vaccines are considered the main strategy of curtailing the pandemic. However, many African nations are still at the early phase of vaccination. C_LIO_LIEvidence on the cost-effectiveness of COVID-19 vaccines are useful in estimating value for money and illustrate opportunity costs. However, there is a need to balance these economic outcomes against the potential impact of vaccination. C_LI What are the new findings?O_LIIn Kenya, a targeted vaccination strategy that prioritizes those of an older age and is deployed at a rapid rollout speed achieves greater marginal health impacts and is better value for money. C_LIO_LIGiven the existing high-level population protection to COVID-19 due to prior exposure, vaccination of younger adults is less cost-effective in Kenya. C_LI What do the new findings imply?O_LIRapid deployment of vaccines during a pandemic averts more cases, hospitalisations, and deaths and is more cost-effective. C_LIO_LIAgainst a context of constrained fiscal space for health, it is likely more prudent for Kenya to target those at severe risk of disease and possibly other vulnerable populations rather than to the whole population. C_LI
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BackgroundThe impact of COVID-19 on all-cause mortality in sub-Saharan Africa remains unknown. MethodsWe monitored mortality among 306,000 residents of Kilifi Health and Demographic Surveillance System, Kenya, through four COVID-19 waves from April 2020-September 2021. We calculated expected deaths using negative binomial regression fitted to baseline mortality data (2010-2019) and calculated excess mortality as observed-minus-expected deaths. We excluded deaths in infancy because of under-ascertainment of births during lockdown. In February 2021, after two waves of wild-type COVID-19, adult seroprevalence of anti-SARS-CoV-2 was 25.1%. We predicted COVID-19-attributable deaths as the product of age-specific seroprevalence, population size and global infection fatality ratios (IFR). We examined changes in cause of death by Verbal Autopsy (VA). ResultsBetween April 2020 and February 2021, we observed 1,000 deaths against 1,012 expected deaths (excess mortality -1.2%, 95% PI -6.6%, 5.8%). Based on SARS-CoV-2 seroprevalence, we predicted 306 COVID-19-attributable deaths (a predicted excess mortality of 30.6%) within this period. Monthly mortality analyses showed a significant excess among adults aged [≥]45 years in only two months, July-August 2021, coinciding with the fourth (Delta) wave of COVID-19. By September 2021, overall excess mortality was 3.2% (95% PI -0.6%, 8.1%) and cumulative excess mortality risk was 18.7/100,000. By VA, there was a transient reduction in deaths attributable to acute respiratory infections in 2020. ConclusionsNormal mortality rates during extensive transmission of wild-type SARS-CoV-2 through February 2021 suggests that the IFR for this variant is lower in Kenya than elsewhere. We found excess mortality associated with the Delta variant but the cumulative excess mortality risk remains low in coastal Kenya compared to global estimates.
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BackgroundUsing 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. MethodsSARS-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. ResultsOver 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. ConclusionsThe emergence of Alpha, Delta, and Omicron variants was a turning point that resulted in widespread and higher SARS-CoV-2 infections across the country.
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BackgroundMost of the studies that have informed the public health response to the COVID-19 pandemic in Kenya have relied on samples that are not representative of the general population. We conducted population-based serosurveys at three Health and Demographic Surveillance Systems (HDSSs) to determine the cumulative incidence of infection with SARS-CoV-2. MethodsWe selected random age-stratified population-based samples at HDSSs in Kisumu, Nairobi and Kilifi, in Kenya. Blood samples were collected from participants between 01 Dec 2020 and 27 May 2021. No participant had received a COVID-19 vaccine. We tested for IgG antibodies to SARS-CoV-2 spike protein using ELISA. Locally-validated assay sensitivity and specificity were 93% (95% CI 88-96%) and 99% (95% CI 98-99.5%), respectively. We adjusted prevalence estimates using classical methods and Bayesian modelling to account for the sampling scheme and assay performance. ResultsWe recruited 2,559 individuals from the three HDSS sites, median age (IQR) 27 (10-78) years and 52% were female. Seroprevalence at all three sites rose steadily during the study period. In Kisumu, Nairobi and Kilifi, seroprevalences (95% CI) at the beginning of the study were 36.0% (28.2-44.4%), 32.4% (23.1-42.4%), and 14.5% (9.1-21%), and respectively; at the end they were 42.0% (34.7-50.0%), 50.2% (39.7-61.1%), and 24.7% (17.5-32.6%), respectively. Seroprevalence was substantially lower among children (<16 years) than among adults at all three sites (p[≤]0.001). ConclusionBy May 2021 in three broadly representative populations of unvaccinated individuals in Kenya, seroprevalence of anti-SARS-CoV-2 IgG was 25-50%. There was wide variation in cumulative incidence by location and age.
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BackgroundThe transmission networks of SARS-CoV-2 in sub-Saharan Africa remain poorly understood. MethodsWe undertook phylogenetic analysis of 747 SARS-CoV-2 positive samples collected across six counties in coastal Kenya during the first two waves (March 2020 - February 2021). Viral imports and exports from the region were inferred using ancestral state reconstruction (ASR) approach. ResultsThe genomes were classified into 35 Pango lineages, six of which accounted for 79% of the sequenced infections: B.1 (49%), B.1.535 (11%), B.1.530 (6%), B.1.549 (4%), B.1.333 (4%) and B.1.1 (4%). Four identified lineages were Kenya specific. In a contemporaneous global subsample, 990 lineages were documented, 261 for Africa and 97 for Eastern Africa. ASR analysis identified >300 virus location transition events during the period, these comprising: 69 viral imports into Coastal Kenya; 93 viral exports from coastal Kenya; and 191 inter-county import/export events. Most international viral imports (58%) and exports (92%) occurred through Mombasa City, a key touristic and commercial Coastal Kenya center; and many occurred prior to June 2020, when stringent local COVID-19 restriction measures were enforced. After this period, local virus transmission dominated, and distinct local phylogenies were seen. ConclusionsOur analysis supports moving control strategies from a focus on international travel to local transmission. FundingThis work was funded by Wellcome (grant#: 220985) and the National Institute for Health Research (NIHR), project references: 17/63/and 16/136/33 using UK aid from the UK Government to support global health research, The UK Foreign, Commonwealth and Development Office.
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In tropical Africa, SARS-CoV-2 epidemiology is poorly described because of lack of access to testing and weak surveillance systems. Since April 2020, we followed SARS-CoV-2 seroprevalence in plasma samples across the Kenya National Blood Transfusion Service. We developed an IgG ELISA against full length spike protein. Validated in locally-observed, PCR-positive COVID-19 cases and in pre-pandemic sera, sensitivity was 92.7% and specificity was 99.0%. Using sera from 9,922 donors, we estimated national seroprevalence of SARS-CoV-2 antibodies at 4.3% in April-June 2020 and 9.1% in August-September 2020. Kenyas second COVID-19 wave peaked in November 2020. Here we estimate national seroprevalence in early 2021. Between January 3 and March 15, 2021, we collected 3,062 samples from donors aged 16-64 years. Among 3,018 samples that met our study criteria, 1,333 were seropositive (crude seroprevalence 44.2%, 95% CI 42.4-46.0%). After Bayesian test-performance adjustment and population weighting to represent the national population distribution, the national estimate of seroprevalence was 48.5% (95% CI 45.2-52.1%). Seroprevalence varied little by age or sex but was higher in Nairobi (61.8%), the capital city, and lower in two rural regions. Almost half of Kenyas adult donors had evidence of past SARS-CoV-2 infection by March 2021. Although high, the estimate is corroborated by other population-specific estimates in country. Between March and June, 2% of the population were vaccinated against COVID-19 and the country experienced a third epidemic wave. Natural infection is outpacing vaccine delivery substantially in Africa, and this reality needs to be considered as objectives of the vaccine programme are set.
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Policy decisions on COVID-19 interventions should be informed by a local, regional and national understanding of SARS-CoV-2 transmission. Epidemic waves may result when restrictions are lifted or poorly adhered to, variants with new phenotypic properties successfully invade, or when infection spreads to susceptible sub-populations. Three COVID-19 epidemic waves have been observed in Kenya. Using a mechanistic mathematical model we explain the first two distinct waves by differences in contact rates in high and low social-economic groups, and the third wave by the introduction of a new higher-transmissibility variant. Reopening schools led to a minor increase in transmission between the second and third waves. Our predictions of current population exposure in Kenya ([~]75% June 1st) have implications for a fourth wave and future control strategies. One Sentence SummaryCOVID-19 spread in Kenya is explained by mixing heterogeneity and a variant less constrained by high population exposure
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BackgroundFew studies have assessed the seroprevalence of antibodies against SARS-CoV-2 among Health Care Workers (HCWs) in Africa. We report findings from a survey among HCWs in three counties in Kenya. MethodsWe recruited 684 HCWs from Kilifi (rural), Busia (rural) and Nairobi (urban) counties. The serosurvey was conducted between 30th July 2020 and 4th December 2020. We tested for IgG antibodies to SARS-CoV-2 spike protein using ELISA. Assay sensitivity and specificity were 93% (95% CI 88-96%) and 99% (95% CI 98-99.5%), respectively. We adjusted prevalence estimates using Bayesian modeling to account for assay performance. ResultsCrude overall seroprevalence was 19.7% (135/684). After adjustment for assay performance seroprevalence was 20.8% (95% CI 17.5-24.4%). Seroprevalence varied significantly (p<0.001) by site: 43.8% (CI 35.8-52.2%) in Nairobi, 12.6% (CI 8.8-17.1%) in Busia and 11.5% (CI 7.2-17.6%) in Kilifi. In a multivariable model controlling for age, sex and site, professional cadre was not associated with differences in seroprevalence. ConclusionThese initial data demonstrate a high seroprevalence of antibodies to SARS-CoV-2 among HCWs in Kenya. There was significant variation in seroprevalence by region, but not by cadre.
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In October 2020, anti-SARS-CoV-2 IgG seroprevalence among truck drivers and their assistants (TDA) in Kenya was 42.3%, higher than among other key populations. TDA transport essential supplies during the COVID-19 pandemic, placing them at increased risk of being infected and of transmitting SARS-CoV-2 infection over a wide geographical area.
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BackgroundMore than 49,000 cases of infection and 900 deaths from COVID-19 have been recorded in the Kenya. However, the characteristics and risk factors for severe outcomes among hospitalized COVID-19 patients in this setting have not been described. MethodsWe extracted demographic, laboratory, clinical and outcome data from medical records of RT-PCR confirmed SARS-CoV2 patients admitted in six hospitals in Kenya between March and September, 2020. We used Cox proportional hazards regressions to determine factors related to in-hospital mortality. ResultsData from 787 COVID-19 patients was available. The median age was 43 years (IQR 30-53), with 505 (64%) males. At admission, 455 (58%) were symptomatic. The commonest symptoms were cough (337, 43%), loss of taste or smell (279, 35%), and fever (126, 16%). Co-morbidities were reported in 340 (43%), with cardiovascular disease, diabetes and HIV documented in 130 (17%), 116 (15%), 53 (7%) respectively. 90 (11%) were admitted to ICU for a mean of 11 days, 52 (7%) were ventilated with a mean of 10 days, 107 (14%) died. The risk of death increased with age [hazard ratio (HR) 1.57 (95% CI 1.13 - 2.19)] for persons >60 years compared to those <60 years old; having co-morbidities [HR 2.34 (1.68 - 3.25)]; and among males [HR 1.76 (1.27, 2.44)] compared to females. Elevated white blood cell count and aspartate aminotransferase were associated with higher risk of death. ConclusionsWe identify the risk factors for mortality that may guide stratification of high risk patients.
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Policy makers in Africa need robust estimates of the current and future spread of SARS-CoV-2. Data suitable for this purpose are scant. We used national surveillance PCR test, serological survey and mobility data to develop and fit a county-specific transmission model for Kenya. We estimate that the SARS-CoV-2 pandemic peaked before the end of July 2020 in the major urban counties, with 34 - 41% of residents infected, and will peak elsewhere in the country within 2-3 months. Despite this penetration, reported severe cases and deaths are low. Our analysis suggests the COVID-19 disease burden in Kenya may be far less than initially feared. A similar scenario across sub-Saharan Africa would have implications for balancing the consequences of restrictions with those of COVID-19.
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BackgroundThere are no data on SARS-CoV-2 seroprevalence in Africa though the COVID-19 epidemic curve and reported mortality differ from patterns seen elsewhere. We estimated the anti-SARS-CoV-2 antibody prevalence among blood donors in Kenya. MethodsWe measured anti-SARS-CoV-2 spike IgG prevalence by ELISA on residual blood donor samples obtained between April 30 and June 16, 2020. Assay sensitivity and specificity were 83% (95% CI 59-96%) and 99.0% (95% CI 98.1-99.5%), respectively. National seroprevalence was estimated using Bayesian multilevel regression and post-stratification to account for non-random sampling with respect to age, sex and region, adjusted for assay performance. ResultsComplete data were available for 3098 of 3174 donors, aged 15-64 years. By comparison with the Kenyan population, the sample over- represented males (82% versus 49%), adults aged 25-34 years (40% versus 27%) and residents of coastal Counties (49% versus 9%). Crude overall seroprevalence was 5.6% (174/3098). Population-weighted, test- adjusted national seroprevalence was 5.2% (95% CI 3.7- 7.1%). Seroprevalence was highest in the 3 largest urban Counties - Mombasa (9.3% [95% CI 6.4-13.2%)], Nairobi (8.5% [95% CI 4.9-13.5%]) and Kisumu (6.5% [95% CI 3.3-11.2%]). ConclusionsWe estimate that 1 in 20 adults in Kenya had SARS-CoV-2 antibodies during the study period. By the median date of our survey, only 2093 COVID-19 cases and 71 deaths had been reported through the national screening system. This contrasts, by several orders of magnitude, with the numbers of cases and deaths reported in parts of Europe and America when seroprevalence was similar.