Epidemiological impact and cost-effectiveness analysis of COVID-19 vaccination in Kenya

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

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance.

Investment in Africa over the past year with regards to SARS-CoV-2 genotyping has led to a massive increase in the number of sequences, exceeding 100,000 genomes generated to track the pandemic on the continent. Our results show an increase in the number of African countries able to sequence within their own borders, coupled with a decrease in sequencing turnaround time. Findings from this genomic surveillance underscores the heterogeneous nature of the pandemic but we observe repeated dissemination of SARS-CoV-2 variants within the continent. Sustained investment for genomic surveillance in Africa is needed as the virus continues to evolve, particularly in the low vaccination landscape. These investments are very crucial for preparedness and response for future pathogen outbreaks. One-Sentence SummaryExpanding Africa SARS-CoV-2 sequencing capacity in a fast evolving pandemic.

Genomic surveillance reveals the spread patterns of SARS-CoV-2 in coastal Kenya during the first two waves

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.

COVID-19 Transmission Dynamics Underlying Epidemic Waves in Kenya

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

Detection of SARS-CoV-2 variant 501Y.V2 in Comoros Islands in January 2021

Phylogenetic analysis of six SARS-CoV-2 genomes collected from the Comoros islands confirmed local circulation of the 501Y.V2 variant of concern during the countrys first major SARS-CoV-2 wave in January 2021. These findings demonstrate the importance of SARS-CoV-2 genomic surveillance and have implications for ongoing COVID-19 control strategies on the islands. Article summary lineCirculation of SARS-CoV-2 501Y.V2 variant of concern in the Comoros Islands during a major COVID-19 infection wave in January 2021

Seroprevalence of Antibodies to SARS-CoV-2 among Health Care Workers in Kenya

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.

Tracking the introduction and spread of SARS-CoV-2 in coastal Kenya

We generated 274 SARS-CoV-2 genomes from samples collected during the early phase of the Kenyan pandemic. Phylogenetic analysis identified 8 global lineages and at least 76 independent SARS-CoV-2 introductions into Kenyan coast. The dominant B.1 lineage (European origin) accounted for 82.1% of the cases. Lineages A, B and B.4 were detected from screened individuals at the Kenya-Tanzania border or returning travellers but did not lead to established transmission. Though multiple lineages were introduced in coastal Kenya within three months following the initial confirmed case, none showed extensive local expansion other than cases characterised by lineage B.1, which accounted for 45 of the 76 introductions. We conclude that the international points of entry were important conduits of SARS-CoV-2 importations. We speculate that early public health responses prevented many introductions leading to established transmission, but nevertheless a few undetected introductions were sufficient to give rise to an established epidemic.

Revealing the extent of the COVID-19 pandemic in Kenya based on serological and PCR-test data

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.

Seroprevalence of anti-SARS-CoV-2 IgG antibodies in Kenyan blood donors

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.