学位の種別:課程博士University of Tokyo(東京大学

EJIMA KEISUKE

江島 啓介

UTokyo Repository

論文の内容の要旨 
 
Mathematical Modeling of Disease 
Transmission Dynamics with Data 
Generating Processes 
(データ生成過程を伴う疾病伝播ダイナミクス
の数理モデリング) 
 
氏名 江島啓介 
 
 
 In history, fight against infectious diseases has never ended since the dawn 
of human being, and infectious diseases acted as the leading cause of death. To 
overcome the diseases, pharmaceutical approaches have been invented. However, 
even at the present moment emerging infectious diseases such as HIV/AIDS, 
Middle East respiratory syndrome coronavirus (MERS-CoV), Severe Acute 
Respiratory Syndrome (SARS), influenza continuously cause epidemics across the 
world. Accordingly, we confront with the needs to evaluate the efficacy and 
effectiveness of pharmaceutical or non-pharmaceutical interventions (e.g. school 
closure during influenza epidemic) in quantitative and qualitative manners. 
Despite the importance of modeling approaches to infectious disease control, the 
methodology has not been straightforward. The most popular and classical model 
that describes an infectious disease epidemic was developed by Kermac and 
McKendrick (hereafter I call the model as SIR (Susceptible-Infectious-Recovered) 
model), and the SIR model has been extended to practical problems in many ways. 
Apart from these progresses, a lot of quantitative questions have remained in public 
health. To answer the questions, this thesis has focused on the data generating 
process of epidemics in order to fit models to limited data that is empirically 
observed. Moreover, the infectious disease modelling framework has been further 
extended to other health related problems that are known to be contagious. 
 The main contributions of this thesis are summarized as follows; (1) I 
constructed a transmission model of influenza during the early phase of an epidemic, 
investigating the required length of time to reliably estimate case fatality ratio 
(CFR) of influenza. The study suggested that 2-3 month would be required to 
reliably compare the estimated CFR with the pre-specified CFR value such as those 
defined by US Pandemic Severity Index. (2) I proposed a modeling method to 
estimate the vaccine efficacy against measles, jointly quantifying parameters 
governing the temporal dynamics of measles (e.g. R0). The study suggested that 
population aged from 5-19 year should be (re-) vaccinated to prevent further 
epidemic in Japan. (3) I discussed the use of chance-adjusted agreement coefficients 
to measure the assortativity of both contact and transmission of an infectious 
disease. I have demonstrated that the proportion of contacts that are reserved for 
within group mixing, p in the preferential mixing assumption has excellently 
corresponded to the Newman's assortativity coefficient (or the so-called Cohen's 
kappa). Subsequently, I have explicitly distinguished the transmission assortativity 
from contact assortativity, because the former captures not only the contact 
heterogeneity but also many other intrinsic and extrinsic factors characterizing the 
frequency of within- and between- group transmission. (4) I have emphasized that 
an appropriate model would be essential to answer public health question including 
vaccination problems. Examining the validity of incorporation of vaccine effect 
against clinical disease in epidemic models, I have shown that an explicit 
formulation would also help to clarify underlying assumptions that tend to be 
hidden in common model structures. (5) I investigated epidemiological model that 
describes an obesity epidemic which is known to spread via social contact and can 
also be acquired in a non-contagious manner. I compared the effectiveness of 
different types of intervention programs against obesity, identifying associated data 
gaps in empirical observation. 
 Through these five original studies, I have shown that appropriate model 
building approaches that explicitly account for data generating process would be 
essential not only for modeling researchers but also for public health practitioners. 
The needs for sound model building approaches have been emphasized. 


データ生成過程を伴う疾病伝播ダイナミクスの数理モデリング

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データ生成過程を伴う疾病伝播ダイナミクスの数理モデリング

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