This dataset consists of respiratory diseases hospitalization in Sorocaba, São Paulo, Brazil. The details of the statistical modeling using the APLMS-AR(p) approach can be found in Chou-Chen, et al. (2024). doi:10.1007/s00362-024-01590-w . The hospitalization data of respiratory diseases in Sorocaba city, São Paulo, Brazil are obtained from the Hospital Information System of Brazil’s Unified National Health System (SIH-SUS), and the climatic and pollution data are provided by the QUALAR system.
Usage
data(hospitalization)Format
The "data" slot is a data frame with 932 weekly data on the following 29 variables.
- date, year, epi.week, tdate
Date, year, epidemiologic weeks, and time index.
- y
Respiratory hospitalization count.
- MP10_max, MP10_min, MP10_avg
Maximum, minimum and average of \(MP10\).
- NO_max,NO_min,NO_avg
Maximum, minimum and average of \(NO\).
- NO2_max, NO2_min, NO2_avg
Maximum, minimum and average of \(NO_2\).
- NOx_max, NOx_min, NOx_avg
Maximum, minimum and average of \(NO_x\).
- O3_max, O3_min, O3_avg
Maximum, minimum and average of \(O_3\).
- TEMP_max, TEMP_min, TEMP_avg
Maximum, minimum and average of temperature.
- RH_max, RH_min, RH_avg
Maximum, minimum and average of relative humidity.
- ampl_max, ampl_min, ampl_avg
Maximum, minimum and average of daily temperature amplitude.
References
Chou-Chen, S.W., Oliveira, R.A., Raicher, I. et al. (2024) Additive partial linear models with autoregressive symmetric errors and its application to the hospitalizations for respiratory diseases. Stat Papers 65, 5145–5166. doi:10.1007/s00362-024-01590-w
Examples
data(hospitalization)
head(hospitalization)
#> date year epi.week tdate y MP10_max MP10_min MP10_avg NO_max NO_min
#> 1 2005-01-03 2005 1 1 64 167.9242 11.65520 44.51816 28 0
#> 2 2005-01-10 2005 2 2 58 159.9140 12.58550 46.16039 20 0
#> 3 2005-01-17 2005 3 3 62 158.2932 12.04895 45.28987 61 0
#> 4 2005-01-24 2005 4 4 53 169.7507 12.23643 45.59006 56 0
#> 5 2005-01-31 2005 5 5 52 181.2455 13.03868 48.15511 39 0
#> 6 2005-02-07 2005 6 6 47 161.9691 12.68160 47.74442 37 0
#> NO_avg NO2_max NO2_min NO2_avg NOx_max NOx_min NOx_avg O3_max O3_min
#> 1 4.886598 37 5 15.649485 42 3 12.360825 77 1
#> 2 2.664596 41 4 14.857143 38 2 10.105590 124 1
#> 3 4.956522 36 3 13.000000 62 2 11.012422 114 1
#> 4 6.579710 48 2 15.413043 51 1 13.550725 78 0
#> 5 2.732919 24 1 8.118012 44 1 6.596273 119 2
#> 6 3.496894 72 3 13.472050 54 2 10.099379 157 2
#> O3_avg TEMP_max TEMP_min TEMP_avg RH_max RH_min RH_avg ampl_max ampl_min
#> 1 25.25000 30.7 19.1 23.25119 99 55 92.04167 11.3 4.9
#> 2 41.54375 32.2 17.1 24.47844 99 52 84.89881 13.3 4.8
#> 3 26.22981 29.5 20.1 23.06071 99 70 95.29762 8.2 2.3
#> 4 26.74534 30.8 17.8 22.13929 99 67 92.19643 11.3 3.3
#> 5 25.32298 30.3 18.1 22.86190 98 51 85.04790 10.9 6.0
#> 6 47.27950 29.6 16.7 21.99821 99 44 74.63095 11.9 9.0
#> ampl_avg
#> 1 7.800000
#> 2 8.857143
#> 3 5.600000
#> 4 6.314286
#> 5 7.400000
#> 6 10.557143