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Cited by 328SARS-CoV-2 and COVID-19 ResearchCOVID-19 epidemiological studiesSARS-CoV-2 detection and testing

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

Open access
Uyoga, Sophie, Adetifa, Ifedayo M. O., Karanja, Henry K., Nyagwange, James, Tuju, James, Wanjiku, Perpetual, Aman, Rashid, Mwangangi, Mercy +31 more·2021·Science
DOI 10.1126/science.abe1916PMC PMC7877494

Published version of a preprint

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Abstract

Pandemic progress in Kenya: By the end of July 2020, Kenya had reported only 341 deaths and ∼20,000 cases of COVID-19. This is in marked contrast to the tens of thousands of deaths reported in many higher-income countries. The true extent of COVID-19 in the community was unknown and likely to be higher than reports indicated. Uyoga et al. found an overall seroprevalence among blood donors of 4.3%, peaking in 35- to 44-year-old individuals (see the Perspective by Maeda and Nkengasong). The low mortality can be partly explained by the steep demographics in Kenya, where less than 4% of the population is 65 or older. These circumstances combine to result in Kenyan hospitals not currently being overwhelmed by patients with respiratory distress. However, the imposition of a strict lockdown in this country has shifted the disease burden to maternal and child deaths as a result of disruption to essential medical services. Science , this issue p. 79 ; see also p. 27

AI snapshot

Written from the paper’s full text.

TL;DR

In a national serosurvey of Kenyan blood transfusion donors from 30 April to 16 June 2020, anti–SARS-CoV-2 spike IgG seroprevalence was 5.6% crude and 4.3% after population weighting and test-performance adjustment. The authors conclude that SARS-CoV-2 exposure was considerably more widespread than reported case counts suggested, with higher seroprevalence in urban counties and younger/middle-aged adults.

Key findings

  • Among 3098 blood donor samples, 174 were seropositive, giving a crude seroprevalence of 5.6% (95% CI, 4.8 to 6.5%); the Bayesian population-weighted, test-adjusted seroprevalence was 4.3% (95% CI, 2.9 to 5.8%).
  • Crude seroprevalence varied by age (P = 0.046), ranging from 3.4 to 7.0% among adults 15 to 54 years, with all 71 donors aged 55 to 64 years seronegative; it did not vary by sex (P = 0.50) but varied geographically from 1.9% in Rift Valley to 10.0% in Western (P = 0.002).
  • County-level seroprevalence was 8.0% (95% CI, 5.5 to 11.1%) in Mombasa, 7.3% (95% CI, 4.2 to 11.4%) in Nairobi, and 5.5% (95% CI, 2.8 to 9.6%) in Kisumu.
  • The authors note that Kenya’s younger population structure, with only 3.9% aged ≥65 years, may partly explain lower severe outcomes, and estimate that applying 4.3% seroprevalence to all 15- to 64-year-olds would suggest approximately 1.3 million infections.

Methods

  • Residual blood samples from transfusion donors were collected from four Kenya National Blood Transfusion Service regional centers and satellites/hospitals between 30 April and 16 June 2020; after excluding duplicates, missing age/date records, and donors aged ≥65 years, 3098 samples from individuals aged 15 to 66 years were analyzed.
  • A validated ELISA for anti–SARS-CoV-2 spike IgG was used, with seropositivity defined as an optical density ratio >2; validation used 910 prepandemic serum samples, 174 sera from PCR-defined SARS-CoV-2 cases, and a five-sera NIBSC panel, yielding sensitivity 92.7% (95% CI, 87.9 to 96.1%) and specificity 99.0% (95% CI, 98.1 to 99.5%).
  • Prevalence was estimated using Bayesian multilevel regression and poststratification to reweight to the 2019 Kenya Population and Housing Census age, sex, and regional distribution, then adjusted for assay sensitivity and specificity.

Limitations

  • The paper states that blood donors are not representative of the Kenyan population; although estimates were standardized to age, sex, and region, 43% of Kenya’s population is outside the sampled 15- to 64-year age range, and seroprevalence in children <15 years and adults >65 years is often lower, so the donor estimate may be higher than the population-wide estimate.
  • The paper states that donor selection may bias estimates in both directions: potential donors are excluded if ill in the past 6 months, which may underestimate population prevalence, while people shielding at home are unlikely to be captured, which may overestimate seroprevalence; donor type also varied, with voluntary nonremunerated donors at 8.5% crude seroprevalence versus 5.4% for family replacement donors, though 92% of the sample came from the lower-seroprevalence group.
  • The paper states that it did not adjust for sample date because sampling periods varied by county; more broadly, the cross-sectional residual-sample design cannot establish incidence timing or individual exposure risk.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1126/science.abe1916

Cites

44 of 44 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

0 of 34 cited sources checked · 0 supported · 0 flagged

  • Findingown data

    Crude seroprevalence varied by age (P = 0.046).

    “Crude seroprevalence varied by age (P = 0.046), ranging between 3.4 to 7.0% among adults 15 to 54 years; all 71 donors aged 55 to 64 years were seronegative (Table 1).”
    Quote in the paperNot a substantial claim
  • Findingown data

    Using OD ratios, both RBD and spike ELISAs correctly classified 901 of 910 prepandemic samples as seronegative.

    “By using OD ratios, both RBD and spike ELISAs correctly classified 901 of 910 prepandemic samples as seronegative (table S1).”
    Quote in the paperSubstantial claim
  • Findingown data

    For either RBD or whole spike, specificity was higher when using a ratio of sample OD/negative control OD than when using raw sample OD plus 3 standard deviations to define seropositivity.

    “For either receptor-binding domain (RBD) or whole spike, specificity was higher when using a ratio of the sample optical density (OD)/negative control OD than when using the raw sample OD plus 3 standard deviations to define seropositivity (table S1).”
    Quote in the paperSubstantial claim
  • Findingown data

    The spike ELISA detected more seropositives (166 of 179) than the RBD ELISA (145 of 179) among sera from SARS-CoV-2 PCR-positive individuals.

    “However, the spike ELISA detected more seropositives (166 of 179 compared with 145 of 179 for RBD ELISA) among sera from SARS-CoV-2 PCR-positive individuals (fig. S2, A and B).”
    Quote in the paperSubstantial claim
  • Findingown data

    All 71 donors aged 55 to 64 years were seronegative.

    “all 71 donors aged 55 to 64 years were seronegative (Table 1).”
    Quote in the paperNot a substantial claim
  • May combine two claims. 27
  • Classified as probably not a substantial claim. 13

  • May combine two claims.

    Findingcitation

    The RBD and whole-spike ELISA responses were highly correlated, with very little interassay variation.

    “As previously noted (15), the RBD and whole-spike ELISA responses were highly correlated (fig. S3C), with very little interassay variation (fig. S4).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [15] 15. Amanat F., Stadlbauer D., Strohmeier S., Nguyen T. H. O., Chromikova V., McMahon M., Jiang K., Arunkumar G. A., Jurczyszak D., Polanco J., Bermudez-Gonzalez M., Kleiner G., Aydillo T., Miorin L., Fierer D. S., Lugo L. A., Kojic E. M., Stoever J., Liu S. T. H., Cunningham-Rundles C., Felgner P. L., Moran T., García-Sastre A., Caplivski D., Cheng A. C., Kedzierska K., Vapalahti O., Hepojoki J. M., Simon V., Krammer F., A serological assay to detect SARS-CoV-2 seroconversion in humans. Nat. Med. 26, 1033–1036 (2020). 10.1038/s41591-020-0913-5 source

      Not checked in the free run.

  • May combine two claims.

    Findingown data

    Of the 3098 samples, 174 were positive for anti-SARS-CoV-2 spike IgG, giving a crude seroprevalence of 5.6% (95% CI, 4.8 to 6.5%).

    “Of the 3098 samples, 174 were positive for anti–SARS-CoV-2 spike IgG, giving a crude seroprevalence of 5.6% (95% CI, 4.8 to 6.5%).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    At the OD ratio >2 threshold, the sensitivity was 92.7% (95% CI, 87.9 to 96.1%) and specificity was 99.0% (95% CI, 98.1 to 99.5%).

    “The sensitivity and specificity, at this threshold, were 92.7% [95% confidence interval (CI), 87.9 to 96.1%] and 99.0% [95% CI, 98.1 to 99.5%], respectively”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    The median sample date for VNRDs (14 June 2020) was 2 weeks later than that for FRDs (29 May 2020).

    “The median sample date for VNRDs (14 June 2020) was 2 weeks later than that for FRDs (29 May 2020).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Seroprevalence was higher (4.2 to 5.2%) in the younger age groups (15 to 44 years) and declined in the older age groups (45 to 64 years).

    “Seroprevalence was higher (4.2 to 5.2%) in the younger age groups (15 to 44 years) and declined in the older age groups (45 to 64 years) but was similar for both sexes.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    The three largest urban counties of Mombasa, Nairobi, and Kisumu had SARS-CoV-2 seroprevalence of 8.0% (95% CI, 5.5 to 11.1%), 7.3% (95% CI, 4.2 to 11.4%), and 5.5% (95% CI, 2.8 to 9.6%), respectively.

    “The three largest urban counties of Mombasa, Nairobi, and Kisumu had SARS-CoV-2 seroprevalence of 8.0% (95% CI, 5.5 to 11.1%), 7.3% (95% CI, 4.2 to 11.4%), and 5.5% (95% CI, 2.8 to 9.6%), respectively (table S4).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Compared with the 2019 Kenya Population and Housing Census, the study participants were more commonly male (82.0% vs 49.3%), had more persons aged 25 to 34 years (40.1% vs 27.3%), and more residents of coastal counties (49.2% vs 9.1%).

    “Compared with the 2019 Kenya Population and Housing Census, our participants were more commonly male (82.0% in our study versus 49.3% in the census), had more persons aged 25 to 34 years (40.1 versus 27.3%), and more residents of coastal counties (49.2 versus 9.1%) (Table 2).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The VNRD and FRD groups did not differ significantly by age (P = 0.15) or sex (P = 0.51).

    “The two groups did not differ significantly by age (P = 0.15) or sex (P = 0.51) (table S5).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    The frequency of blood donor sampling and crude seroprevalence estimates increased with time over the 7-week study period.

    “The frequency of blood donor sampling and crude seroprevalence estimates increased with time over the 7-week study period (Fig. 2).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Seroprevalence was highest for those living in Mombasa, Nairobi, and the Western region, although the number of observations for the Western region was small.

    “Seroprevalence was highest for those living in Mombasa, Nairobi, and the Western region, although the number of observations for the Western region was small.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    The posterior sensitivity and specificity estimates were 92.4% (95% CI, 88.0 to 95.6%) and 98.9% (95% CI, 98.2 to 99.5%), respectively.

    “the posterior sensitivity and specificity estimates were 92.4% (95% CI, 88.0 to 95.6%) and 98.9 (95% CI, 98.2 to 99.5%), respectively.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Voluntary nonremunerated donors (VNRDs) made up 7.6% (236 of 3098) of the sample; the remainder were family replacement donors (FRDs).

    “Voluntary nonremunerated donors (VNRDs), who donate blood at community-based “blood drives,” made up only 7.6% (236 of 3098) of our sample of donors; the remainder were family replacement donors (FRDs) who provide a unit of blood in compensation for a transfusion received by a sick relative.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Crude seroprevalence was 8.5% (20 of 236) for VNRDs and 5.4% (154 of 2862) for FRDs.

    “Crude seroprevalence was 8.5% (20 of 236) for VNRDs and 5.4% (154 of 2862) for FRDs.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Several countries have monitored seroprevalence in blood transfusion donors or expectant mothers attending antenatal clinics.

    “Several countries have monitored seroprevalence in blood transfusion donors (12, 13) or expectant mothers attending antenatal clinics (14).”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites [12] 12. L. Valenti et al., SARS-CoV-2 seroprevalence trends in healthy blood donors during the COVID-19 Milan outbreak. medRxiv 2020.2005.2011.20098442 [Preprint] 31 May 2020. 10.1101/2020.05.11.20098442 source

      Not checked in the free run.

    • cites [13] 13. Amorim Filho L., Szwarcwald C. L., Mateos S. O. G., Leon A. C. M. P., Medronho R. A., Veloso V. G., Lopes J. I. F., Porto L. C. M. S., Chieppe A., Werneck G. L.; Grupo Hemorio de Pesquisa em Covid-19, Seroprevalence of anti–SARS-CoV-2 among blood donors in Rio de Janeiro, Brazil. Rev. Saude Publica 54, 69 (2020). 10.11606/s1518-8787.2020054002643 source

      Not checked in the free run.

    • cites [14] 14. Flannery D. D., Gouma S., Dhudasia M. B., Mukhopadhyay S., Pfeifer M. R., Woodford E. C., Gerber J. S., Arevalo C. P., Bolton M. J., Weirick M. E., Goodwin E. C., Anderson E. M., Greenplate A. R., Kim J., Han N., Pattekar A., Dougherty J., Kuthuru O., Mathew D., Baxter A. E., Vella L. A., Weaver J., Verma A., Leite R., Morris J. S., Rader D. J., Elovitz M. A., Wherry E. J., Puopolo K. M., Hensley S. E., SARS-CoV-2 seroprevalence among parturient women in Philadelphia. Sci. Immunol. 5, eabd5709 (2020). 10.1126/sciimmunol.abd5709 source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    As the epidemic curve declined in Geneva, seroprevalence rose over 3 weeks from 4.8 to 10.9%.

    “As the epidemic curve declined in Geneva, seroprevalence rose over 3 weeks from 4.8 to 10.9% (10).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [10] 10. Stringhini S., Wisniak A., Piumatti G., Azman A. S., Lauer S. A., Baysson H., De Ridder D., Petrovic D., Schrempft S., Marcus K., Yerly S., Arm Vernez I., Keiser O., Hurst S., Posfay-Barbe K. M., Trono D., Pittet D., Gétaz L., Chappuis F., Eckerle I., Vuilleumier N., Meyer B., Flahault A., Kaiser L., Guessous I., Seroprevalence of anti–SARS-CoV-2 IgG antibodies in Geneva, Switzerland (SEROCoV-POP): A population-based study. Lancet 396, 313–319 (2020). 10.1016/S0140-6736(20)31304-0 source

      Not checked in the free run.

  • Classified as probably not a substantial claim. May combine two claims.

    Interpretationnone given

    The true extent of COVID-19 in the community was unknown and likely to be higher than reports indicated.

    “The true extent of COVID-19 in the community was unknown and likely to be higher than reports indicated.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    The disparity in COVID-19 burden between Africa and the rest of the world has been attributed to limited capacity for diagnosis, timely implementation of stringent containment measures, a younger population structure, and a predominance of asymptomatic and mild infections.

    “This disparity has been attributed to limited capacity for diagnosis, timely implementation of stringent containment measures, a younger population structure, and a predominance of asymptomatic and mild infections (3, 4).”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [3] 3. Diop B. Z., Ngom M., Pougué Biyong C., Pougué Biyong J. N., The relatively young and rural population may limit the spread and severity of COVID-19 in Africa: A modelling study. BMJ Glob. Health 5, e002699 (2020). 10.1136/bmjgh-2020-002699 source

      Not checked in the free run.

    • cites [4] 4. Dowd J. B., Andriano L., Brazel D. M., Rotondi V., Block P., Ding X., Liu Y., Mills M. C., Demographic science aids in understanding the spread and fatality rates of COVID-19. Proc. Natl. Acad. Sci. U.S.A. 117, 9696–9698 (2020). 10.1073/pnas.2004911117 source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    At the end of the epidemic wave in Spain, seropositivity was 5.0% in a random population sample of 60,897.

    “At the end of the epidemic wave in Spain, seropositivity was 5.0% in a random population sample of 60,897 (9).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [9] 9. Pollán M., Pérez-Gómez B., Pastor-Barriuso R., Oteo J., Hernán M. A., Pérez-Olmeda M., Sanmartín J. L., Fernández-García A., Cruz I., Fernández de Larrea N., Molina M., Rodríguez-Cabrera F., Martín M., Merino-Amador P., León Paniagua J., Muñoz-Montalvo J. F., Blanco F., Yotti R., ENE-COVID Study Group, Prevalence of SARS-CoV-2 in Spain (ENE-COVID): A nationwide, population-based seroepidemiological study. Lancet 396, 535–544 (2020). 10.1016/S0140-6736(20)31483-5 source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    By 31 July 2020, national surveillance in Kenya recorded 20,636 cases and 341 deaths.

    “By 31 July national surveillance recorded 20,636 cases and 341 deaths (6).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [6] 6. Ministry of Health Kenya, “COVID-19 Situation Reports (SITREP)” (2020); www.health.go.ke/#1591180376422-52af4c1e-256b.

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    At the release of lockdown in Wuhan, 9.6% of staff resuming work were found to have antibodies to SARS-CoV-2.

    “For example, at the release of lockdown in Wuhan, 9.6% of staff resuming work were found to have antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (8).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [8] 8. Wu X., Fu B., Chen L., Feng Y., Serological tests facilitate identification of asymptomatic SARS-CoV-2 infection in Wuhan, China. J. Med. Virol. 92, 1795–1796 (2020). 10.1002/jmv.25904 source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    Africa accounts for 17% of the global population but by late July 2020 accounted for only 5% of global COVID-19 cases and 3% of global COVID-19 deaths reported.

    “Africa accounts for 17% of the global population (1) but by late July 2020 accounted for only 5% of the global COVID-19 cases and 3% of global COVID-19 deaths reported (2).”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [1] 1. United Nations Department of Economic and Social Affairs Population Division, “World Urbanization Prospects: The 2018 Revision,” custom data acquired via (2018); https://population.un.org/wup/DataQuery.

      Not checked in the free run.

    • cites [2] 2. Africa Centres for Diseases Control and Prevention, “Coronavirus Disease 2019 (COVID-19)” (2020); https://africacdc.org/covid-19[accessed 21 July 2020].

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductown data

    The study did not adjust for sample date because the period of sampling varied for residents of different counties; instead, it shows the variation in crude prevalence over time.

    “We did not adjust for sample date because the period of sampling varied for residents of different counties (Fig. 2C); instead, we show the variation in crude prevalence over time (Fig. 2A).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning

    People who are shielding at home are unlikely to be captured in the sample, leading to an overestimate of seroprevalence.

    “however, people who are shielding at home are unlikely to be captured in our sample, leading to an overestimate of seroprevalence.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationown data

    Seroprevalence did not vary significantly by sex, consistent with other studies.

    “Consistent with other studies, seroprevalence did not vary significantly by sex (9, 10, 16); however, it peaked in 35- to 44-year-olds and was lowest for those ≥45 years, which is also consistent with existing reports in which seroprevalence was found to be lower in older adults (9, 10).”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites [9] 9. Pollán M., Pérez-Gómez B., Pastor-Barriuso R., Oteo J., Hernán M. A., Pérez-Olmeda M., Sanmartín J. L., Fernández-García A., Cruz I., Fernández de Larrea N., Molina M., Rodríguez-Cabrera F., Martín M., Merino-Amador P., León Paniagua J., Muñoz-Montalvo J. F., Blanco F., Yotti R., ENE-COVID Study Group, Prevalence of SARS-CoV-2 in Spain (ENE-COVID): A nationwide, population-based seroepidemiological study. Lancet 396, 535–544 (2020). 10.1016/S0140-6736(20)31483-5 source

      Not checked in the free run.

    • cites [10] 10. Stringhini S., Wisniak A., Piumatti G., Azman A. S., Lauer S. A., Baysson H., De Ridder D., Petrovic D., Schrempft S., Marcus K., Yerly S., Arm Vernez I., Keiser O., Hurst S., Posfay-Barbe K. M., Trono D., Pittet D., Gétaz L., Chappuis F., Eckerle I., Vuilleumier N., Meyer B., Flahault A., Kaiser L., Guessous I., Seroprevalence of anti–SARS-CoV-2 IgG antibodies in Geneva, Switzerland (SEROCoV-POP): A population-based study. Lancet 396, 313–319 (2020). 10.1016/S0140-6736(20)31304-0 source

      Not checked in the free run.

    • cites [16] 16. Huang A. T., Garcia-Carreras B., Hitchings M. D. T., Yang B., Katzelnick L. C., Rattigan S. M., Borgert B. A., Moreno C. A., Solomon B. D., Trimmer-Smith L., Etienne V., Rodriguez-Barraquer I., Lessler J., Salje H., Burke D. S., Wesolowski A., Cummings D. A. T., A systematic review of antibody mediated immunity to coronaviruses: Kinetics, correlates of protection, and association with severity. Nat. Commun. 11, 4704 (2020). 10.1038/s41467-020-18450-4 source

      Not checked in the free run.

  • May combine two claims.

    Interpretationown data

    Population exposure across Kenya, with a population-weighted test-adjusted seroprevalence of 4.3%, is considerably higher than was previously thought, on the basis of the cases and deaths reported to date.

    “Population exposure across Kenya, with a population-weighted test-adjusted seroprevalence of 4.3%, is considerably higher than was previously thought, on the basis of the cases and deaths reported to date.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Study design and conductnone given

    Although blood donors are not representative of the Kenyan population as a whole, the study adjusted for demographic bias in the sample structure by standardization against the age, sex, and regional distribution of the Kenyan population.

    “Although blood donors are not representative of the Kenyan population as a whole, we adjusted for demographic bias in the sample structure by standardization against the age, sex, and regional distribution of the Kenyan population.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationreasoning

    Potential donors are excluded from giving blood if they have been ill during the past 6 months, so the sample may underestimate the population prevalence of SARS-CoV-2 antibodies.

    “For example, potential donors are excluded from giving blood if they have been ill during the past 6 months, so the sample may underestimate the population prevalence of SARS-CoV-2 antibodies”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationcitation

    A substantial proportion (43%) of the Kenyan population is outside the age range (15 to 64 years) sampled in this study, and the seroprevalence in children <15 years and adults >65 years is often lower; thus the blood donor estimate may be higher than the estimate for the population as a whole.

    “A substantial proportion (43%) of the population of Kenya is outside the age range (15 to 64 years) sampled in this study, and the seroprevalence in children <15 years and adults >65 years is often lower (9, 10); our estimate for blood donors may be higher than the estimate for the population as a whole.”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites [9] 9. Pollán M., Pérez-Gómez B., Pastor-Barriuso R., Oteo J., Hernán M. A., Pérez-Olmeda M., Sanmartín J. L., Fernández-García A., Cruz I., Fernández de Larrea N., Molina M., Rodríguez-Cabrera F., Martín M., Merino-Amador P., León Paniagua J., Muñoz-Montalvo J. F., Blanco F., Yotti R., ENE-COVID Study Group, Prevalence of SARS-CoV-2 in Spain (ENE-COVID): A nationwide, population-based seroepidemiological study. Lancet 396, 535–544 (2020). 10.1016/S0140-6736(20)31483-5 source

      Not checked in the free run.

    • cites [10] 10. Stringhini S., Wisniak A., Piumatti G., Azman A. S., Lauer S. A., Baysson H., De Ridder D., Petrovic D., Schrempft S., Marcus K., Yerly S., Arm Vernez I., Keiser O., Hurst S., Posfay-Barbe K. M., Trono D., Pittet D., Gétaz L., Chappuis F., Eckerle I., Vuilleumier N., Meyer B., Flahault A., Kaiser L., Guessous I., Seroprevalence of anti–SARS-CoV-2 IgG antibodies in Geneva, Switzerland (SEROCoV-POP): A population-based study. Lancet 396, 313–319 (2020). 10.1016/S0140-6736(20)31304-0 source

      Not checked in the free run.

  • May combine two claims.

    Study design and conductreasoning

    The study adjusted the prevalence estimate for the demographics of the sample using poststratification, and for the sensitivity and specificity of the test.

    “We therefore adjusted the prevalence estimate for the demographics of the sample using poststratification, and for the sensitivity and specificity of the test.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim. May combine two claims.

    Premisecitation

    By the median sample date, 30 May 2020, only 2093 cases had been detected (of which approximately 90% were asymptomatic), and there were 71 deaths among all ages.

    “However, by the median sample date, 30 May 2020, only 2093 cases had been detected (of which approximately 90% were asymptomatic), and there were 71 deaths among all ages (6).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [6] 6. Ministry of Health Kenya, “COVID-19 Situation Reports (SITREP)” (2020); www.health.go.ke/#1591180376422-52af4c1e-256b.

      Not checked in the free run.

  • May combine two claims.

    Interpretationcitation

    The 4.3% prevalence in blood transfusion donors is in sharp contrast with the reported COVID-19 cases and deaths and supports the impression that disease may be attenuated in Africa.

    “The 4.3% prevalence in blood transfusion donors is in sharp contrast with the reported COVID-19 cases and deaths and supports the impression that disease may be attenuated in Africa (7).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [7] 7. Mbow M., Lell B., Jochems S. P., Cisse B., Mboup S., Dewals B. G., Jaye A., Dieye A., Yazdanbakhsh M., COVID-19 in Africa: Dampening the storm? Science 369, 624–626 (2020). 10.1126/science.abd3902 source

      Not checked in the free run.

    • Rests on an assumption: Kenyan hospitals were not overwhelmed by patients with respiratory distress.

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    The study adopted a conservative seropositivity threshold to optimize assay specificity and sensitivity for the setting.

    “In addition, we adopted a conservative seropositivity threshold to optimize assay specificity and sensitivity for our setting.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationcitation

    Seroprevalence peaked in 35- to 44-year-olds and was lowest for those ≥45 years, consistent with existing reports of lower seroprevalence in older adults.

    “it peaked in 35- to 44-year-olds and was lowest for those ≥45 years, which is also consistent with existing reports in which seroprevalence was found to be lower in older adults (9, 10).”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [9] 9. Pollán M., Pérez-Gómez B., Pastor-Barriuso R., Oteo J., Hernán M. A., Pérez-Olmeda M., Sanmartín J. L., Fernández-García A., Cruz I., Fernández de Larrea N., Molina M., Rodríguez-Cabrera F., Martín M., Merino-Amador P., León Paniagua J., Muñoz-Montalvo J. F., Blanco F., Yotti R., ENE-COVID Study Group, Prevalence of SARS-CoV-2 in Spain (ENE-COVID): A nationwide, population-based seroepidemiological study. Lancet 396, 535–544 (2020). 10.1016/S0140-6736(20)31483-5 source

      Not checked in the free run.

    • cites [10] 10. Stringhini S., Wisniak A., Piumatti G., Azman A. S., Lauer S. A., Baysson H., De Ridder D., Petrovic D., Schrempft S., Marcus K., Yerly S., Arm Vernez I., Keiser O., Hurst S., Posfay-Barbe K. M., Trono D., Pittet D., Gétaz L., Chappuis F., Eckerle I., Vuilleumier N., Meyer B., Flahault A., Kaiser L., Guessous I., Seroprevalence of anti–SARS-CoV-2 IgG antibodies in Geneva, Switzerland (SEROCoV-POP): A population-based study. Lancet 396, 313–319 (2020). 10.1016/S0140-6736(20)31304-0 source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    A key strength of this study is the rigorous validation that included testing positive and negative control samples from the target population, as well as reference plasma from the UK NIBSC as part of a WHO-coordinated effort on SARS-CoV-2 seroepidemiology.

    “A key strength of this study is the rigorous validation that included testing positive and negative control samples from the target population, as well as reference plasma from the UK NIBSC as part of a World Health Organization (WHO)–coordinated effort on SARS-CoV-2 seroepidemiology.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationcitation

    Other countries have relied on blood transfusion donors for an early estimate of seroprevalence, but later estimates from random population samples have not been substantially different.

    “Against these considerations, other countries have relied on blood transfusion donors for an early estimate of seroprevalence, but later estimates from random population samples have not been substantially different (25, 26).”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites [25] 25. H. Ward et al., Antibody prevalence for SARS-CoV-2 following the peak of the pandemic in England: REACT2 study in 100,000 adults. medRxiv 2020.2008.2012.20173690v20173692 [Preprint] 21 August 2020. 10.1101/2020.08.12.20173690

      Not checked in the free run.

    • cites [26] 26. Public Health England, National COVID-19 surveillance report week 40 (2020); https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/923668/Weekly_COVID19_Surveillance_Report_week_40.pdf.

      Not checked in the free run.

35 of 35

  • The paper relies on this without support.

    Movement restrictions in response to COVID-19 limited the conduct of fieldwork for population-based serosurveys.

    “Movement restrictions, in response to COVID-19, have limited the conduct of fieldwork for population-based serosurveys.”

  • The paper relies on this without support.

    Kenyan hospitals were not overwhelmed by patients with respiratory distress.

    “These circumstances combine to result in Kenyan hospitals not currently being overwhelmed by patients with respiratory distress.”
    “hospitals in Kenya were not overwhelmed by admissions with respiratory illness.”

  • The paper relies on this without support.

    The increase in COVID-19 cases in Kenya is notably slower than the epidemic in Wuhan, Europe, or the United States.

    “This increase in cases is notably slower than the epidemic in Wuhan, Europe, or the United States.”

  • The paper relies on this without support.

    The current PCR testing strategy in Kenya targets symptomatic individuals, health care workers, contacts of confirmed cases, international travelers, cross-border truck drivers, and residents of areas identified as hotspots.

    “The current PCR testing strategy targets symptomatic individuals, health care workers, contacts of confirmed cases, international travelers, cross-border truck drivers, and residents of areas identified as “hotspots.””
4 of 4

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Reliance on healthy blood donors and voluntary child participants did not result in a material underestimate of COVID-19 seroprevalence in the general population.

    “These independent estimates provide confidence that our reliance on healthy blood donors and voluntary child participants did not result in a material underestimate of COVID-19 seroprevalence in the general population.”

    From Real-world COVID-19 vaccine effectiveness against the Omicron BA.2 variant in a SARS-CoV-2 infection-naive population (2023) · cites this paper as [49]

    The passage on sample representativeness (indexed under Abstract; page unavailable) says that random-population estimates in other countries were not substantially different from blood-donor estimates. It also says Kenyan donors may underestimate or overestimate population seroprevalence. The paper did not study voluntary child participants, so it does not establish the sentence’s conclusion for both participant groups. (LLM, conf=0.86)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Rift Valley crude seroprevalence differs from Table 1

    Minor

    The text gives Rift Valley's crude seroprevalence as 1.9%, but Table 1 reports 1.7% (8 positives among 481 samples).

1 of 1

Cites

Flagged first, then by citations

Research works printed but not linked: 1

  1. Ministry of Health Kenya “Press Statement on the update of the coronavirus in the country and response measures” (2020); www.health.go.ke/wp-content/uploads/2020/03/Coronavirus-Press-Statement-March-17-2020.pdf.

Cited by

Sorted by citations

Authors
Uyoga, S., Adetifa, I. M. O., Karanja, H. K., Nyagwange, J., Tuju, J., Wanjiku, P., Aman, R., Mwangangi, M., Amoth, P., Kasera, K., Ng’ang’a, W., Rombo, C., Yegon, C., Kithi, K., Odhiambo, E., Rotich, T., Orgut, I., Kihara, S., Otiende, M., Bottomley, C., Mupe, Z. N., Kagucia, E. W., Gallagher, K. E., Etyang, A., Voller, S., Gitonga, J. N., Mugo, D., Agoti, C. N., Otieno, E., Ndwiga, L., Lambe, T., Wright, D., Barasa, E., Tsofa, B., Bejon, P., Ochola-Oyier, L. I., Agweyu, A., Scott, J. A. G., & Warimwe, G. M.
Affiliations
  • Kenya Medical Research Institute (KE)
  • Ministry of Health (KE)
  • Government of Kenya (KE)
  • Kenya National Blood Transfusion Services (KE)
  • London School of Hygiene & Tropical Medicine (GB)
  • University of Oxford (GB)
  • KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya.
Corresponding author
Uyoga, Sophie
ORCID
Venue
Science
Publisher
American Association for the Advancement of Science (AAAS)
Published
2021-01
Volume
371
Issue
6524
Pages
79-82
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
DOI
10.1126/science.abe1916
PMC
PMC7877494
OpenAlex
W3104471981
Cited by
328
References
38
Citations by year
2026: 13 · 2025: 26 · 2024: 23 · 2023: 39 · 2022: 84 · 2021: 122 · 2020: 20 · 2012: 1
FWCI
8.69
Type
journal article
Language
en
Open access
Licence
Locations
  • Science (publishedVersion, cc-by)
  • medRxiv (acceptedVersion)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam) (submittedVersion, cc-by)
  • LSHTM Research Online (London School of Hygiene and Tropical Medicine) (submittedVersion, cc-by)
  • Greater South Information System
Funders
  • Oak Foundation
  • Wellcome (220991/Z/20/Z, 203077/Z/16/Z, 107568/Z/15/Z, 214320)
  • Medical Research Council (MR/S005293/1)
  • African Academy of Sciences (DEL-15-003)
  • DFID and Wellcome (220985/Z/20/Z)
  • NIHR MPRU (2268427)
  • Department for International Development (MR/R006083/1)
  • NIHR Health Protection Research Unit in Immunisation
Topics
  • Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
  • Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
  • Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 detection and testing
Keywords
SARS-CoV-2, COVID-19 pandemic, seroprevalence, anti-SARS-CoV-2 IgG, blood donors, Kenya, SARS-CoV-2 exposure, urban-rural differences, pandemic response
MeSH terms
COVID-19, SARS-CoV-2, Adolescent, Adult, Aged, Antibodies, Viral, Blood Donors, Communicable Disease Control, Humans, Immunoglobulin G, Kenya, Middle Aged, Seroepidemiologic Studies, Young Adult

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-06.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-06.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

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