Table 1 Crude, age/sex standardised and Bayesian-weighted test-adjusted SARS-CoV-2 anti-spike protein IgG seroprevalence across the whole study duration.

From: Temporal trends of SARS-CoV-2 seroprevalence during the first wave of the COVID-19 epidemic in Kenya

 

Kenya population

All samples (%)

Sero-positive

Crude seroprevalence

Bayesian weighted, test-adjusted seroprevalencea

    

%

95% CI

%

95% CI

Age

 15–24 years

9,733,174

2763 (27.8)

241

8.7

7.7–9.8

7.5

6.2–8.8

 25–34 years

7,424,967

3902 (39.3)

379

9.7

8.8–10.7

8.5

7.2–9.8

 35–44 years

4,909,191

2261 (22.8)

224

9.9

8.7–11.2

8.3

6.9–9.8

 45–54 years

3,094,771

794 (8.0)

66

8.3

6.5–10.5

7.3

5.5–8.9

 55–64 years

1,988,062

202 (2.1)

18

8.9

5.4–13.7

7.2

5.2–9.1

Sex

 Male

13,388,243

8019 (80.8)

762

9.5

8.9–10.2

8.4

7.2–9.5

 Female

13,761,922

1903 (19.2)

166

8.7

7.5–10.1

7.4

5.9–8.9

Region

 Central

3,452,213

606 (6.1)

38

6.3

4.5–8.5

5.8

3.7–8.0

 Coast

1,671,097

1680 (16.9)

137

8.2

6.9–9.6

7.2

5.6–8.9

 Eastern/N. Eastern

5,176,080

1482 (14.9)

108

7.3

6.0–8.7

6.5

4.9–8.2

 Mombasa

792,072

1654 (16.7)

239

14.4

12.8–16.2

13.8

11.7–16

 Nairobi

3,002,314

607 (6.1)

107

17.6

14.7–20.9

16.7

13.4–20.2

 Nyanza

3,363,813

1433 (14.4)

131

9.1

7.7–10.8

8.3

6.6–10.2

 Rift Valley

7,035,581

2138 (21.6)

145

6.8

5.8–7.9

5.9

4.5–7.4

 Western

2,656,995

322 (3.3)

23

7.1

4.6–10.5

6.6

3.9–9.7

 National

27,150,165

9922 (100)

928

9.4

8.8–9.9

7.9

6.7–9.0

  1. aBayesian Multi-level Regression with Post-stratification (MRP) accounts for differences in the age and sex distribution of blood donors and regional differences in the numbers of samples collected over time. The model also adjusts for sensitivity (93%) and specificity (99%) of the ELISA.