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.
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