Many measures are executed to control and prevent damage to infectious outbreaks and natural disasters. These measures are called Health Crisis Management （HCM）. Evidence-based policy Making （EBPM）, as a public policy approach, was discussed, but there are challenges in adopting HCM. in this research, I discuss how EBPM should be applied to HCM policy to improve its effectiveness and accountability.

 Other causes include natural disasters and this Basic Guideline noticed that “Regarding health crises caused by natural disasters, we will strive to promote comprehensive and systematic measures in accordance with the Ministry of Health, Labor and Welfare’s disaster prevention plan.” It can be said that the national government presents basic guidelines and coordinates among local governments through laws and ordinances, and local governments play a major role in implementing HCM. However, when implementing HCM, national and local governments find it difficult to respond when policy effects are little or no effect, or when they have never made this rehearsal.

 According to the Cabinet Office of Japan, EBPM is “Instead of relying on one-time episodes, policy planning should be based on information and data （evidence） that are important to measure policy impacts after clarifying policy objectives.” A logic model is a model of the logical cause-and-effect relationship that leads to the achievement of a certain policy, and this model is used for EBPM. But, Hansen said, “while we want to embrace evidence, the evidence seldom speaks for itself; typically, it requires a modeling or conceptual framework for interpretation.” In fact, the logic model is an execution management model and does not describe the mechanism by which policy is achieved. As such, EBPM should also explain the relationship between the evidence and the policy environment. As a corresponding method for such EBPMs challenges, I propose that an agent-based modeling/simulation and a gaming approach, and refer to considerations when use those approaches based on previous research. Furthermore, I suggest how prefectures would use these approaches in what sort of HCM policy for infectious outbreaks and natural disasters.

 ［Onuki 2023］ used open data on COVID-19 patients to estimate the relative risk of infection among physicians and nurses by sex and age group. They compared them with the same sex and age group of the general population, and covered the period from the third to the sixth wave of COVID-19 outbreak in Tokyo. In this paper, as a second report, estimates for the seventh wave period are presented, and the trends and patterns of relative risk by sex and age group across the first to seventh wave periods are analyzed.

 日本の総人口が減少し、東京圏への人口一極集中が大きな問題となる中、国策として地方への移住が推進されている。しかし、人口移動と諸要因との関連を分析した研究は、市区町村単位で分析したものは少なく、横断的な分析に留まるものが多い。そこで、本研究では、政令指定都市及び東京都特別区部から、大都市圏に属する周辺市町村を除く市町村への人口移動を対象に、ポアソン重力モデルに移動元、移動先ペアの固定効果、時点の固定効果を追加した固定効果モデルを用いて、縦断的分析を行った。その結果、移動先の総人口、第1次産業就業者比率、基準地価、幼稚園数が、大都市から地方への人口移動に正の影響をもつなど、各地域の社会経済的変数のうち、移動元、移動先合わせて11個の変数が、大都市から地方への人口移動と関連していることを明らかにした。

 This paper attempts to clarify what patterns of organizational change processes can be found based on an evolutionary framework. What is unique to this evolutionary framework is that it asserts that two types of entities, the replicator as a genealogical entity and the interactor as an ecological entity, give rise to the evolutionary processes of variation, selection, and retention in the socio-economic domain. Based on this evolutionary framework, we aim to elucidate the dynamics of social and economic systems, and to clarify patterns of organizational change processes. Before clarifying patterns of organizational change processes, we examine what are the basic aspects of organizations that actually cause patterns of organizational change processes. Then, this paper clarifies three patterns of organizational change processes: the external selection pattern, the practices emergence pattern, and the entrepreneurship pattern. Furthermore, these three patterns of organizational change processes are compared with each other.