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Table 2 Effect of diagnostic testing on paediatric fever treatment in 12 studied countries in 2010-2012

From: Effect of diagnostic testing on medicines used by febrile children less than five years in 12 malaria-endemic African countries: a mixed-methods study

Country

n Febrile under-fives taken to any care

n any anti-malarial drug use

Any anti-malarial use

n ACT use

ACT use

n any antibiotic drug use

Any antibiotic use

COR (95% CI)

AOR (95% CI)

p value

COR (95% CI)

AOR (95% CI)

p value

COR (95% CI)

AOR (95% CI)

p value

Benin

620

298

2.61 (1.51-4.51)

1.65 (0.92-2.98)

0.096

109

2.37 (1.20-4.70)

1.96 (0.91-4.19)

0.084

177

1.83 (1.06-3.17)

1.15 (0.64-2.08)

0.636

Burkina Faso

1,823

875

2.08 (1.39-3.11)

1.32 (0.84-2.05)

0.225

228

1.64 (0.99-2.71)

1.45 (0.84-2.52)

0.180

803

1.22 (0.82-1.81)

0.89 (0.57-1.40)

0.616

Burundi

1,432

371

3.62 (2.64-4.96)

3.71 (2.63-5.25)

<0.001

258

2.62 (1.79-3.83)

2.78 (1.81-4.27)

<0.001

782

0.62 (0.47-0.81)

0.53 (0.40-0.72)

<0.001

Cote d’Ivoire*

965

220

3.29 (2.05-5.25)

1.89 (1.14-3.13)

0.013

32

7.09 (2.45-20.54)

16.83 (1.03-276.13)

0.048

334

1.99 (1.31-3.01)

1.08 (0.68-1.74)

0.737

Gabon

738

194

2.25 (1.40-3.61)

2.00 (1.16-3.44)

0.013

78

2.74 (1.45-5.16)

2.45 (1.13-5.33)

0.024

436

0.88 (0.58-1.35)

0.84 (0.52-1.35)

0.467

Guinea*

931

412

1.70 (1.08-2.67)

1.28 (0.78-2.11)

0.330

20

4.29 (1.25-14.68)

2.42 (0.43-13.68)

0.319

378

1.76 (1.11-2.78)

1.05 (0.63-1.75)

0.862

Malawi

4,337

2,384

1.65 (1.40-1.94)

1.34 (1.11-1.61)

0.002

2,019

1.26 (1.07-1.48)

1.12 (0.94-1.34)

0.206

1,285

1.12 (0.94-1.33)

1.00 (0.82-1.22)

1.000

Mozambique

888

371

2.85 (2.02-4.02)

2.79 (1.92-4.05)

<0.001

225

3.65 (2.45-5.42)

3.54 (2.33-5.39)

<0.001

107

1.04 (0.67-1.61)

1.01 (0.64-1.59)

0.966

Rwanda*

657

134

0.93 (0.57-1.52)

0.83 (0.48-1.44)

0.506

129

0.96 (0.59-1.56)

0.88 (0.51-1.51)

0.633

322

3.70 (2.38-5.74)

2.95 (1.82-4.79)

<0.001

Senegal

1,275

180

1.75 (1.11-2.75)

1.69 (1.04-2.76)

0.036

70

2.54 (1.24-5.19)

2.99 (1.32-6.79)

0.009

547

1.90 (1.27-2.85)

1.50 (0.97-2.31)

0.070

Uganda

2,440

1,704

1.50 (1.19-1.89)

1.24 (0.96-1.61)

0.097

1,158

1.13 (0.92-1.39)

0.84 (0.66-1.06)

0.133

860

1.45 (1.18-1.78)

1.37 (1.09-1.72)

0.007

Zimbabwe*

217

11

13.23 (1.56-112.52)

170.9 (0.30-98480.04)

0.113

6

12.18 (1.94-76.45)

25.55 (1.69-385.68)

0.019

84

0.62 (0.24-1.60)

0.55 (0.20-1.51)

0.244

  1. CI = confidence interval. AOR = adjusted odds ratio. COR = crude odds ratio. AORs based on mixed-effects logistic regression models in individual country datasets adjusted for data clustering and confounding covariates (malaria endemicity; transmission season; public/private source; level of care; child’s age and sex; maternal age and education; residence; household wealth and size; health care access (money); health care access (distance); symptoms; health card).
  2. *Rwanda’s model does not include the ‘level of care’ covariate due to multi-collinearity with the public/private source covariate. Guinea’s model does not include ‘money or distance as problems accessing care’ covariates. Some results should be interpreted with caution due to few observations and few positive outcomes (e.g., Cote d’Ivoire, Guinea, Zimbabwe).
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Malaria Journal

ISSN: 1475-2875

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