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Authors: Wei Ping Goh 1 ; Shu-Chen Tsai 1 ; Hung-Jui Chang 2 ; Ting-Yu Lin 1 ; Chien-Chi Chang 1 ; Mei-Lien Pan 3 ; Da-Wei Wang 1 and Tsan-Sheng Hsu 1

Affiliations: 1 Institute of Information Science, Academia Sinica, Taiwan, Republic of China ; 2 Department of Applied Mathematics, Chung Yuan Christian University, Taiwan, Republic of China ; 3 Information Technology Service Center, National Yang Ming Chiao Tung University, Taiwan

Keyword(s): Household Structure Projection, Monte-Carlo, Agent-based Simulation.

Abstract: The kernel of an agent based simulation system for spreading of infectious disease needs a so called household structure (HSD) of the area being simulated which contains a list of households with the age of each member in the household being recorded. Such a household structure is available in a Census that is usually released every 10 years. Previous researches have shown the changing of the household structure has a great impact on disease spreading patterns. It is observed that the changing of the household structure e.g., the average citizen ages and household size, is at a faster speed. However, serious infectious diseases, such as SARS (year 2002), H1N1 (year 2009) and COVID-19 (year 2019), occur with a higher frequency now than previous eras. For example, it would be bad to use HSD2010 built using Census 2010 to simulate COVID-19. In view of this situation, we need a better way to obtain a good household structure in between the Census years in order for an agent-base d simulation system to be effective. Note that though a detailed Census is not available every year, aggregated information such as the number of households with a particular size, and the number of people of a particular age are usually available almost monthly. Given HSDx, the household structure for year x, and the aggregated information from year y where y > x, we propose a Monte-Carlo based approach “patching” HSDx to get an approximated HSDy. To validate our algorithm, we pick x and y = x+10 which both Censuses are available and find out the root-mean-square error (RMSE) between Census’s HSDy and generated HSDy is fairly small for x = 1990 and 2000. The spreading patterns obtained by our simulation system have good matches. We hence obtain HSD2020 to be used in your system for studying the spreading of COVID-19. (More)

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Paper citation in several formats:
Goh, W.; Tsai, S.; Chang, H.; Lin, T.; Chang, C.; Pan, M.; Wang, D. and Hsu, T. (2022). Household Structure Projection: A Monte-Carlo based Approach. In Proceedings of the 12th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - SIMULTECH; ISBN 978-989-758-578-4; ISSN 2184-2841, SciTePress, pages 70-79. DOI: 10.5220/0011270100003274

@conference{simultech22,
author={Wei Ping Goh. and Shu{-}Chen Tsai. and Hung{-}Jui Chang. and Ting{-}Yu Lin. and Chien{-}Chi Chang. and Mei{-}Lien Pan. and Da{-}Wei Wang. and Tsan{-}Sheng Hsu.},
title={Household Structure Projection: A Monte-Carlo based Approach},
booktitle={Proceedings of the 12th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - SIMULTECH},
year={2022},
pages={70-79},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011270100003274},
isbn={978-989-758-578-4},
issn={2184-2841},
}

TY - CONF

JO - Proceedings of the 12th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - SIMULTECH
TI - Household Structure Projection: A Monte-Carlo based Approach
SN - 978-989-758-578-4
IS - 2184-2841
AU - Goh, W.
AU - Tsai, S.
AU - Chang, H.
AU - Lin, T.
AU - Chang, C.
AU - Pan, M.
AU - Wang, D.
AU - Hsu, T.
PY - 2022
SP - 70
EP - 79
DO - 10.5220/0011270100003274
PB - SciTePress