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Authors: Justin Junsay ; Aaron Joaquin Lebumfacil ; Ivan George Tarun and William Emmanuel Yu

Affiliation: School of Science and Engineering, Ateneo de Manila University, Katipunan Avenue, Loyola Heights, Quezon City, Philippines

Keyword(s): Big Data, Data Science, Decision Support System, Pandemic Management.

Abstract: This study describes an activity based traffic indicator system to provide information for COVID-19 pandemic management. The activity based traffic indicator system does this by utilizing a social probability model based on the birthday paradox to determine the exposure risk, the probability of meeting someone infected (PoMSI). COVID-19 data, particularly the 7-day moving average of the daily growth rate of cases (7-DMA of DGR) and cumulative confirmed cases of next week covering a period from April to September 2020, were then used to test PoMSI using Pearson correlation to verify whether it can be used as a factor for the indicator. While there is no correlation for the 7-DMA of DGR, PoMSI is strongly correlated (0.671 to 0.996) with the cumulative confirmed cases and it can be said that as the cases continuously rise, the probability of meeting someone COVID positive will also be higher. This shows that indicator not only shows the current exposure risk of certain activities but i t also has a predictive nature since it correlates to cumulative confirmed cases of next week and can be used to anticipate the values of confirmed cumulative cases. This information can then be used for pandemic management. (More)

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Paper citation in several formats:
Junsay, J.; Lebumfacil, A.; Tarun, I. and Yu, W. (2021). Activity based Traffic Indicator System for Monitoring the COVID-19 Pandemic. In Proceedings of the 23rd International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-758-509-8; ISSN 2184-4992, SciTePress, pages 183-191. DOI: 10.5220/0010399201830191

@conference{iceis21,
author={Justin Junsay. and Aaron Joaquin Lebumfacil. and Ivan George Tarun. and William Emmanuel Yu.},
title={Activity based Traffic Indicator System for Monitoring the COVID-19 Pandemic},
booktitle={Proceedings of the 23rd International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2021},
pages={183-191},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010399201830191},
isbn={978-989-758-509-8},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 23rd International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - Activity based Traffic Indicator System for Monitoring the COVID-19 Pandemic
SN - 978-989-758-509-8
IS - 2184-4992
AU - Junsay, J.
AU - Lebumfacil, A.
AU - Tarun, I.
AU - Yu, W.
PY - 2021
SP - 183
EP - 191
DO - 10.5220/0010399201830191
PB - SciTePress

- Science and Technology Publications, Lda.
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