Exploring forms of disaggregating Covid-19 data: an example

Leal, Maria da Conceição Dias; Oliveira, Teresa; Mukherjee, Amitava; Oliveira, Amilcar

http://hdl.handle.net/10400.2/16497

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Authors

Leal, Maria da Conceição Dias

Oliveira, Teresa

Mukherjee, Amitava

Oliveira, Amilcar

Abstract(s)

COVID-19 data provided by Portuguese public health authorities lack consis tency in periodicity and metrics. To facilitate time series analysis, we transformed those data to achieve homogeneous periodicity and metrics. We present one method we used and assess the potential introduced bias and its impact on spatial distribution models of COVID-19 in Portugal, using spatial and non-spatial models. Comparing models fitted with transformed data to those with observed data for two specific days, we found no clear evidence of a worse fit for the disaggregated data.

Keywords

Times series disaggregation Modelling COVID-19 data Model fit

URI

http://hdl.handle.net/10400.2/16497

Citation

Leal. C.;Oliveira, T.A.; Mukherjee A.; Oliveira, A. (2024).EXPLORING FORMS OF DISAGGREGATING COVID-19 DATA: AN EXAMPLE. Extended Abstract in the Abstracts Book of the International Conference on Mathematical Analysis and Applications in Science and Engineering ICMA2 SC’24 . ISBN:978-989-35251-7-3 . ISEP Porto-Portugal, June 20 - 22, 2024.