Epidemiological impact of travel enhancement on the inter-prefectural importation dynamics of COVID-19 in Japan, 2020

Mobility restrictions were widely practiced to reduce contact with others and prevent the spatial spread of COVID-19 infection. Using inter-prefectural mobility and epidemiological data, a statistical model was devised to predict the number of imported cases in each Japanese prefecture. The number of imported cases crossing prefectural borders in 2020 was predicted using inter-prefectural mobility rates based on mobile phone data and prevalence estimates in the origin prefectures. The simplistic model was quantified using surveillance data of cases with an inter-prefectural travel history. Subsequently, simulations were carried out to understand how imported cases vary with the mobility rate and prevalence at the origin. Overall, the predicted number of imported cases qualitatively captured the observed number of imported cases over time. Although Hokkaido and Okinawa are the northernmost and the southernmost prefectures, respectively, they were sensitive to differing prevalence rate in Tokyo and Osaka and the mobility rate. Additionally, other prefectures were sensitive to mobility change, assuming that an increment in the mobility rate was seen in all prefectures. Our findings indicate the need to account for the weight of an inter-prefectural mobility network when implementing countermeasures to restrict human movement. If the mobility rates were maintained lower than the observed rates, then the number of imported cases could have been maintained at substantially lower levels than the observed, thus potentially preventing the unnecessary spatial spread of COVID-19 in late 2020.

Research on the sustainable development of tourism coupled with economic and environment data--a case study of Hangzhou

The scale of tourism has continued to expand in recent years, and many associated activities cause damage to the natural environment. The tourism, economy and natural environment constitute a system: destruction of the natural environment reduces the value of tourism and a lack of tourism affects the development of the economy. To explore the relationship between the tourism, economy and natural environment, and to explore possibilities for sustainable development, this paper takes Hangzhou, a tourist city in China, as a research object. An analysis of time series data is carried out. First, the tourism, economy and natural environment subsystems are constructed by extracting time series data acquired between 2010 and 2020. Second, a tourism evaluation model with coupled economic and natural environment data is constructed and the coupling degree and coupling coordination level in Hangzhou are evaluated. Third, the time series of each subsystem and the coupling coordination level of the whole system are analyzed. Finally, an optimization strategy is proposed for the coupled coordinated development of the tourism, economy and natural environment in Hangzhou. A key result is that the tertiary industry represented by tourism has become the main source of local income. Hangzhou's tourism coupling coordination level has changed from slight disorder in 2010 to good in 2020. It is also found that the COVID-19 pandemic has become a major factor restricting the development of tourism. Before the outbreak of COVID-19, Hangzhou's tourism industry and economy were synchronized. After the outbreak of COVID-19, both the number of tourists and tourism revenue in Hangzhou fell by nearly 15%.