Enhancing healthcare planning using population data generated from mobile phone networks in Futaba County after the Great East Japan earthquake DOI Creative Commons
Asaka Higuchi, Hiroki Yoshimura, Hiroaki Saito

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Nov. 22, 2024

After the Great East Japan Earthquake, planning appropriate healthcare resource allocation was crucial. However, accurately estimating medical care demand challenging due to substantial population fluctuations caused by extensive evacuations, compounded inaccuracy of conventional Resident Resister data in this context. This study employs generated from mobile phone network 2019 2020 conduct a detailed temporal and spatial estimation Futaba County, originally complete evacuation zone. To enhance precision estimates, independently collected each municipality were used as reference process. Further, utility estimated for calculating emergency transport rates assessed. Our findings revealed discrepancies between daytime nighttime populations within Okuma Town, where median day/night ratio exceeded three across both weekdays weekends. Additionally, sex–age-adjusted calculated using demonstrated closer alignment with national average compared those based on census data. demonstrates importance considering dynamic data, such that networks, enhancing ensuring resources are efficiently allocated meet communities' evolving needs during recovery periods.

Language: Английский

Mobile Spatial Statistics Key to Enhancing Healthcare Planning in Futaba County with Complex Population Flows after the Great East Japan Earthquake DOI Creative Commons
Asaka Higuchi, Hiroki Yoshimura, Hiroaki Saito

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: May 21, 2024

Abstract After the Great East Japan Earthquake, planning appropriate allocation of healthcare resources is crucial. However, accurately estimating medical care demand was challenging due to substantial population fluctuations caused by extensive evacuations. This study employs mobile spatial statistics using NTT DoCoMo’s phone data conduct a detailed temporal and estimation (PE) in Futaba County from 2019 2020. Originally complete evacuation zone, area saw partially lifted order. The suitability estimated for calculating emergency transport (ET) rates also examined. Our findings reveal that day-to-night ratios were significantly high some areas; Okuma Town Town, daytime substantially larger than nighttime throughout two years, with median day/night ratio being more three both weekdays weekends. Additionally, sex-age-adjusted ET area, based on population, consistent national average those calculated census data. demonstrates critical role PE considering changes enhancing ensuring are efficiently allocated meet evolving needs communities during recovery periods.

Language: Английский

Citations

0
Population shifts during the reconstruction period in areas marked as evacuation zones after the Fukushima Daiichi nuclear power plant accident: a mobile spatial statistics data-based time-series clustering analysis DOI Creative Commons
Toshiki Abe, Hiroki Yoshimura, Hiroaki Saito

et al.

Journal of Radiation Research, Journal Year: 2024, Volume and Issue: 65(Supplement_1), P. i106 - i116

Published: Dec. 1, 2024

Abstract An accurate understanding of the population is essential for development medical care and social resources. However, transportation networks has increased temporal spatial fluctuations in population, making it difficult to accurately forecast demand, especially during disaster recovery. This study examined movement areas affected by Fukushima Daiichi nuclear power plant accident using demographic data. The target area includes two cities, seven towns, three villages that are evacuation zone. Using a estimation reflects changes time day, which was obtained from mobile phone company (NTT DOCOMO), we applied clustering analysis examine dynamics over 4-year period. From 2019 2022, eight decreased four areas. further classified into five groups, identifying unique characteristics each group. Different regions had different percentages groups reflecting their populations. differences among transition showed potential understand challenges recovery use data inform healthcare planning policies. method, utilizes estimated data, also applicable resources policies event future disasters may be useful analyzing regional detail.

Language: Английский

Citations

0
Association of Ambient Temperature and Absolute Humidity with the Effective Reproduction Number of COVID-19 in Japan DOI Creative Commons
Keita Wagatsuma

Pathogens, Journal Year: 2023, Volume and Issue: 12(11), P. 1307 - 1307

Published: Nov. 1, 2023

This study aimed to quantify the exposure-lag-response relationship between short-term changes in ambient temperature and absolute humidity transmission dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Japan. The prefecture-specific daily time-series newly confirmed cases, meteorological variables, retail recreation mobility, Government Stringency Index were collected for all 47 prefectures Japan period from 15 February 2020 October 2022. Generalized conditional Gamma regression models formulated with distributed lag nonlinear by adopting case-time-series design assess independent interactive effects on relative risk (RR) time-varying effective reproductive number (Rt). With reference 17.8 °C, corresponding cumulative RRs (95% confidence interval) at a mean temperatures 5.1 °C 27.9 1.027 (1.016–1.038) 0.982 (0.974–0.989), respectively, whereas those an 4.2 m/g3 20.6 1.026 (1.017–1.036) 0.995 (0.985–1.006), 10.6 m/g3. Both extremely hot humid conditions synergistically slightly reduced Rt. Our findings provide better understanding how drivers shape complex heterogeneous SARS-CoV-2

Language: Английский

Citations

1
Vaccine-induced reduction of COVID-19 clusters in school settings in Japan during the epidemic wave caused by B.1.1.529 (Omicron) BA.2, 2022 DOI Creative Commons
Yuta Okada, Hiroshi Nishiura

Mathematical Biosciences & Engineering, Journal Year: 2024, Volume and Issue: 21(9), P. 7087 - 7101

Published: Jan. 1, 2024

<p>Clusters of COVID-19 in high-risk settings, such as schools, have been deemed a critical driving force the major epidemic waves at societal level. In Japan, vaccination coverage among students remained low up to early 2022, especially for 5–11-year-olds. The student population only started February 2022. Given this background and considering that vaccine effectiveness against school transmission has not intensively studied, paper proposes mathematical model links occurrence clustering case count populations aged 0–19, 20–59, 60+ years age. We first estimated protected (immune) fraction each age group either by infection or then linked number clusters via time series regression accounts time-varying hazard per infector. From January 3 May 30, there were 4,722 reported settings. Our suggests immunity offered averted 226 (95% credible interval: 219–232) clusters. Counterfactual scenarios assuming elevated with faster roll-out reveal additional could averted. study indicates even relatively substantially lower risk through vaccine-induced immunity. results also suggest antigenically updated vaccines are more effective variant responsible ongoing may greatly help decrease incidence but unnecessary loss learning opportunities school-age students.</p>

Language: Английский

Citations

0
Local effects of non-pharmaceutical interventions on mitigation of COVID-19 spread through decreased human mobilities in Japan: a prefecture-level mediation analysis DOI Creative Commons
Shohei Nagata, Yuta Takahashi, Hiroki M. Adachi

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Nov. 6, 2024

Abstract To control the COVID-19 epidemic, Japanese government and local governments have repeatedly implemented non-pharmaceutical interventions (NPIs) throughout 2020–2022. Using Bayesian state-space mediation models, we examined effect of repeated NPIs on infection spread mitigation, mediated by human mobility changes in each prefecture during three epidemic phases: from April 1, 2020 to February 28, 2021; March 2021 December 16, 17, 31, 2022. In first phase, controlling downtown populations at nighttime was effective mitigating almost all prefectures. second third phases, not clear, especially metropolitan Controlling visitors central prefectures areas surrounding phases. These results suggest that can be mitigated focusing before spreads widely transmission routes become more diverse, geospatial prevented flows people large cities other areas.

Language: Английский

Citations

0
Enhancing healthcare planning using population data generated from mobile phone networks in Futaba County after the Great East Japan earthquake DOI Creative Commons
Asaka Higuchi, Hiroki Yoshimura, Hiroaki Saito

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Nov. 22, 2024

After the Great East Japan Earthquake, planning appropriate healthcare resource allocation was crucial. However, accurately estimating medical care demand challenging due to substantial population fluctuations caused by extensive evacuations, compounded inaccuracy of conventional Resident Resister data in this context. This study employs generated from mobile phone network 2019 2020 conduct a detailed temporal and spatial estimation Futaba County, originally complete evacuation zone. To enhance precision estimates, independently collected each municipality were used as reference process. Further, utility estimated for calculating emergency transport rates assessed. Our findings revealed discrepancies between daytime nighttime populations within Okuma Town, where median day/night ratio exceeded three across both weekdays weekends. Additionally, sex–age-adjusted calculated using demonstrated closer alignment with national average compared those based on census data. demonstrates importance considering dynamic data, such that networks, enhancing ensuring resources are efficiently allocated meet communities' evolving needs during recovery periods.

Language: Английский

Citations

0