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Table 4 DLNM model results for separate and cumulative effects of environmental variables on the RR of malaria burden in high transmission settings of Uganda

From: Associations between environmental covariates and temporal changes in malaria incidence in high transmission settings of Uganda: a distributed lag nonlinear analysis

Effect type

Specification

Statistic

Variable

Temperature

Rainfall

NDVI

Separate effect

Low

Variable value

26

3

0.24

Peak month

4

4

2

IRR at peak month

1.22 (0.68–2.16)

4.05 (1.40–11.54)a

1.80 (0.35–9.43)

High

Variable value

35

200

0.72

Peak month

2

0

2

IRR at peak month

2.00 (1.42–2.83)a

1.24 (1.01–1.52)a

1.31 (1.04–1.65)a

Cumulative effect

Month lag 1

Variable value

26

3

0.24

IRR

0.69 (0.31–1.62)

2.52 (0.72–8.56)

0.44 (0.08–2.36)

Variable value

35

200

0.72

IRR

2.19 (1.21–3.89)a

1.50 (1.12–2.00)a

1.09 (0.87–1.38)

Month lag 2

Variable value

26

3

0.24

IRR

0.43 (0.14–1.42)

3.16 (0.57–17.41)

0.79 (0.13–4.78)

Variable value

35

200

0.72

IRR

4.39 (2.09–9.21)a

1.87 (1.31–2.69)a

1.42 (1.06–1.89)a

Month lag 3

Variable value

26

3

0.24

IRR

0.36 (0.10–1.55)

6.73 (0.64–68.29)

0.54 (0.06–4.68)

Variable value

35

200

0.72

IRR

8.08 (3.41–20.26)a

1.95 (1.28–2.97)a

1.42 (1.04–1.95)a

Month lag 4

Variable value

26

3

0.24

IRR

0.44 (0.10–2.19)

26.70 (1.82–397.00)a

0.83 (0.09–7.18)

Variable value

35

200

0.72

 

IRR

8.16 (3.41–20.26)a

1.99 (1.22–2.27)a

1.57 (1.09–2.25)a

  1. Peak month is the month corresponding to the highest IRR of malaria
  2. astatistically significant
  3. IRR Incidence risk ratio
  4. NDVI Normalized difference vegetation index