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Table 1 ARIMA model parameters and white noise test of natural focal diseases, malaria, SFTS and dengue

From: Impact of interventions on the incidence of natural focal diseases during the outbreak of COVID-19 in Jiangsu Province, China

Disease

Model and parameter test

White noise test

Model

Parameter

Estimates

Std Error

t

P

Ljung–Box

P

Natural focal diseases

ARIMA

(1,0,0) (0,1,0)12

AR

Non-seasonal lag 1

0.438

0.132

3.326

< 0.05

0.185

0.667

Seasonal difference

1

   

Malaria

ARIMA

(1,0,1) (1,1,0)12

AR

Non-seasonal lag 1

0.97

0.05

19.01

< 0.05

0.089

0.765

MA

Non-seasonal lag 1

0.79

0.12

6.37

< 0.05

AR

Seasonal lag 1

−0.44

0.14

−3.18

< 0.05

Seasonal difference

1

   

SFTS

ARIMA

(0,1,1) (1,0,0)12

AR

Non-seasonal lag 1

0.78

0.21

3.67

< 0.05

0.304

0.581

AR

Non-seasonal lag 1

0.98

0.22

4.47

< 0.05

Non-seasonal difference

1

   

Dengue

ARIMA

(1,1,1)

MA

Non-seasonal lag 1

0.44

0.12

3.70

< 0.05

1.171

0.279

AR

Seasonal lag 1

0.64

0.11

6.02

< 0.05

Non-seasonal difference

1

   
  1. ARIMA: autoregressive integrated moving average; AR: autoregressive; MA: moving average; SFTS: severe fever with thrombocytopenia syndrome
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Parasites & Vectors

ISSN: 1756-3305

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