A surge in respiratory syncytial virus infection-related hospitalizations associated with the COVID-19 pandemic: An observational study at pediatric emergency referral hospitals in Tokushima Prefecture.

The outbreak of coronavirus disease (COVID-19) resulted in implementation of social distancing and other public health measures to control the spread of infection and improve prevention, resulting in a decrease in respiratory syncytial virus (RSV) and pediatric respiratory tract infection rates. However, there was a rapid and large re-emergence of RSV infection in Japan. Notably, we were faced with a difficult situation wherein there was a shortage of hospital beds. This study aimed to examine the epidemiological patterns of RSV-related hospitalizations among children before and after the COVID-19 pandemic onset at two pediatric emergency referral hospitals covering the entire Tokushima Prefecture. Data were extracted from electronic medical records of children hospitalized with RSV infection between January 1, 2018, and December 31, 2021. All patients meeting the eligibility criteria were included in this study. The rates of study outcomes were documented annually during 2018-2021 and compared between the 2018-2020 and 2021 periods. In 2020, there was no RSV infection outbreak. Hospitalizations at the peak week in 2021 were 2.2- and 2.8-fold higher than those in 2018 and 2019, respectively. Hospitalizations in 2021 were concentrated within a short period. In addition, there was a significant increase in hospitalizations among children aged 3-5 months and those older than 24 months. The high-flow nasal cannula (HFNC) use rate nearly doubled in 2021. A new pandemic in the future may cause an outbreak of RSV infection that can result in an intensive increase in the number of hospitalizations of pediatric patients requiring respiratory support, especially in infants aged <6 months. There is an urgent need to improve the preparedness of medical systems, particularly in terms of the number of inpatient beds and the immediate availability of HFNC.

Visualizing Social and Behavior Change due to the Outbreak of COVID-19 Using Mobile Phone Location Data.

We visualize the rates of stay-home for residents by region using the difference between day-time and night-time populations to detect residential areas, and then observing the numbers of people leaving residential areas. There are issues with measuring stay-home rates by observing numbers of people visiting downtown areas, such as central urban shopping centers and major train stations. The first is that we cannot eliminate the possibility that people will avoid areas being observed and go to other areas. The second is that for people visiting downtown areas, we cannot know where they reside. These issues can be resolved if we quantify the degree of stay-home using the number of people leaving residential areas. There are significant differences in stay-home levels by region throughout Japan. By this visualization, residents of each region can see whether their level of stay-home is adequate or not, and this can provide incentive toward compliance suited to the residents of the region.

Visualizing Social and Behavior Change due to the Outbreak of COVID-19 Using Mobile Phone Location Data

We visualize the rates of stay-home for residents by region using the difference between day-time and night-time populations to detect residential areas, and then observing the numbers of people leaving residential areas. There are issues with measuring stay-home rates by observing numbers of people visiting downtown areas, such as central urban shopping centers and major train stations. The first is that we cannot eliminate the possibility that people will avoid areas being observed and go to other areas. The second is that for people visiting downtown areas, we cannot know where they reside. These issues can be resolved if we quantify the degree of stay-home using the number of people leaving residential areas. There are significant differences in stay-home levels by region throughout Japan. By this visualization, residents of each region can see whether their level of stay-home is adequate or not, and this can provide incentive toward compliance suited to the residents of the region.

Japan's voluntary lockdown: further evidence based on age-specific mobile location data.

Changes in people's behavior during the COVID-19 pandemic can be regarded as the result of two types of effects: the "intervention effect" (changes resulting from government orders for people to change their behavior) and the "information effect" (voluntary changes in people's behavior based on information about the pandemic). Using age-specific mobile location data, we examine how the intervention and information effects differ across age groups. Our main findings are as follows. First, the age profile of the intervention effect shows that the degree to which people refrained from going out was smaller for older age groups, who are at a higher risk of serious illness and death, than for younger age groups. Second, the age profile of the information effect shows that the degree to which people stayed at home tended to increase with age for weekends and holidays. Thus, while Acemoglu et al. (2020) proposed targeted lockdowns requiring stricter lockdown policies for the oldest group in order to protect those at a high risk of serious illness and death, our findings suggest that Japan's government intervention had a very different effect in that it primarily reduced outings by the young, and what led to the quarantining of older groups at higher risk instead was people's voluntary response to information about the pandemic. Third, the information effect has been on a downward trend since the summer of 2020. It is relatively more pronounced among the young, so that the age profile of the information effect remains upward sloping.

Japan's voluntary lockdown.

Japan's government has taken a number of measures, including declaring a state of emergency, to combat the spread COVID-19. We examine the mechanisms through which the government's policies have led to changes in people's behavior. Using smartphone location data, we construct a daily prefecture-level stay-at-home measure to identify the following two effects: (1) the effect that citizens refrained from going out in line with the government's request, and (2) the effect that government announcements reinforced awareness with regard to the seriousness of the pandemic and people voluntarily refrained from going out. Our main findings are as follows. First, the declaration of the state of emergency reduced the number of people leaving their homes by 8.5% through the first channel, which is of the same order of magnitude as the estimates obtained for lockdowns in the United States. Second, a 1% increase in new infections in a prefecture reduces people's outings in that prefecture by 0.027%. Third, the government's requests are responsible for about one quarter of the decrease in outings in Tokyo, while the remaining three quarters are the result of citizens obtaining new information through government announcements and the daily release of the number of infections. The findings suggest that what mattered for containing the spread of COVID-19 was not strong, legally binding measures but the provision of appropriate information that encouraged people to change their behavior.