- 著者
- Kenji Karako Peipei Song Yu Chen Wei Tang
- 出版者
- International Research and Cooperation Association for Bio & Socio-Sciences Advancement
- 雑誌
- BioScience Trends (ISSN:18817815)
- 巻号頁・発行日
- vol.14, no.2, pp.134-138, 2020-04-30 (Released:2020-05-21)
- 参考文献数
- 21
- 被引用文献数
- 8 68
To assess the effectiveness of response strategies of avoiding large gatherings or crowded areas and to predict the spread of COVID-19 infections in Japan, we developed a stochastic transmission model by extending the Susceptible-Infected-Removed (SIR) epidemiological model with an additional modeling of the individual action on whether to stay away from the crowded areas. The population were divided into three compartments: Susceptible, Infected, Removed. Susceptible transitions to Infected every hour with a probability determined by the ratio of Infected and the congestion of area. The total area consists of three zones crowded zone, mid zone and uncrowded zone, with different infection probabilities characterized by the number of people gathered there. The time for each people to spend in the crowded zone is curtailed by 0, 2, 4, 6, 7, and 8 hours, and the time spent in mid zone is extended accordingly. This simulation showed that the number of Infected and Removed will increase rapidly if there is no reduction of the time spent in crowded zone. On the other hand, the stagnant growth of Infected can be observed when the time spent in the crowded zone is reduced to 4 hours, and the growth number of Infected will decrease and the spread of the infection will subside gradually if the time spent in the crowded zone is further cut to 2 hours. In conclusions The infection spread in Japan will be gradually contained by reducing the time spent in the crowded zone to less than 4 hours.
- 著者
- Kenji Karako Peipei Song Yu Chen Wei Tang
- 出版者
- International Research and Cooperation Association for Bio & Socio-Sciences Advancement
- 雑誌
- BioScience Trends (ISSN:18817815)
- 巻号頁・発行日
- pp.2020.01482, (Released:2020-03-19)
- 参考文献数
- 21
- 被引用文献数
- 5 68
To assess the effectiveness of response strategies of avoiding large gatherings or crowded areas and to predict the spread of COVID-19 infections in Japan, we developed a stochastic transmission model by extending the Susceptible-Infected-Removed (SIR) epidemiological model with an additional modeling of the individual action on whether to stay away from the crowded areas. The population were divided into three compartments: Susceptible, Infected, Removed. Susceptible transitions to Infected every hour with a probability determined by the ratio of Infected and the congestion of area. The total area consists of three zones crowded zone, mid zone and uncrowded zone, with different infection probabilities characterized by the number of people gathered there. The time for each people to spend in the crowded zone is curtailed by 0, 2, 4, 6, 7, and 8 hours, and the time spent in mid zone is extended accordingly. This simulation showed that the number of Infected and Removed will increase rapidly if there is no reduction of the time spent in crowded zone. On the other hand, the stagnant growth of Infected can be observed when the time spent in the crowded zone is reduced to 4 hours, and the growth number of Infected will decrease and the spread of the infection will subside gradually if the time spent in the crowded zone is further cut to 2 hours. In conclusions The infection spread in Japan will be gradually contained by reducing the time spent in the crowded zone to less than 4 hours.
- 著者
- Kenji Karako Peipei Song Yu Chen Takashi Karako
- 出版者
- International Research and Cooperation Association for Bio & Socio-Sciences Advancement
- 雑誌
- BioScience Trends (ISSN:18817815)
- 巻号頁・発行日
- pp.2022.01390, (Released:2022-09-12)
- 参考文献数
- 8
- 被引用文献数
- 6
During a six-week period from July 20 to August 31, 2022, Japan experienced its highest level of COVID-19 infection ever, with an average of nearly 200,000 new infections per day nationwide. Cases requiring inpatient care peaked at 1,993,062. Twenty-seven prefectures (out of 47 prefectures) had an average hospital bed occupancy of 50% or higher, and bed occupancy in Kanagawa in particular reached 98% in mid-August. In Tokyo, bed occupancy by patients with severe COVID-19 reached 57% and peaked at 64% in mid-August. Although the number of new infections per day has decreased since September, hospital bed occupancy, the number of severe cases, and deaths remain high nationwide. Efforts including vaccination campaigns, domestic surveillance, and routine infection control measures based on the varied knowledge that the Japanese public already has should be thoroughly implemented to reduce the number of the infected in order to avoid an increase the number of serious cases and deaths.
- 著者
- Kenji Karako
- 出版者
- International Research and Cooperation Association for Bio & Socio-Sciences Advancement
- 雑誌
- Drug Discoveries & Therapeutics (ISSN:18817831)
- 巻号頁・発行日
- pp.2022.01073, (Released:2022-09-06)
- 参考文献数
- 6
- 被引用文献数
- 1
Japan is facing the largest outbreak of COVID-19 in history in 2022. The number of new infections per day surpassed 200,000 for the first time in July and peaked in August. Japan has required the reporting of information on all infected persons, but maintaining this system is difficult. Starting in September 2, 2022, four prefectures have implemented a trial policy to limit the infected that must be reported in order to reduce the burden on medical personnel. The policy obliges medical facilities to report only people with a high-risk infection, but the number of the infected will continue to be counted regardless of whether they have a high-risk or low-risk infection. More prefectures are expected to adopt this policy in the future.
- 著者
- Kenji Karako Peipei Song Yu Chen Wei Tang
- 出版者
- International Research and Cooperation Association for Bio & Socio-Sciences Advancement
- 雑誌
- BioScience Trends (ISSN:18817815)
- 巻号頁・発行日
- vol.16, no.1, pp.4-6, 2022-02-28 (Released:2022-03-11)
- 参考文献数
- 14
- 被引用文献数
- 8
As the number of people with COVID-19 increases daily around the world, point-of-care testing (POCT) is gaining attention as a tool that can provide immediate test results and greatly help to deter infection and determine what to do next. POCT has several drawbacks such as a low sensitivity and specificity, but according to studies POCT has increased sensitivity on par with that of polymerase chain reaction testing. The advantage of POCT is that the results can be obtained quickly, regardless of the location. To further enhance its benefits, POCT is being developed and researched in conjunction with the Internet of medical things (IoMT), which allows POCT results to be collected, recorded, and managed over a network. IoMT will be beneficial not only for the use of POCT simply as a testing tool but also for its integration into diagnostic and health management systems. IoMT will enable people to regularly receive their test results in their daily lives and to provide personalized diagnosis and treatment of individual conditions, which will be beneficial in terms of disease prevention and maintenance of health.
- 著者
- Tatsuo Sawakami Kenji Karako Peipei Song
- 出版者
- National Center for Global Health and Medicine
- 雑誌
- Global Health & Medicine (ISSN:24349186)
- 巻号頁・発行日
- vol.3, no.3, pp.125-128, 2021-06-30 (Released:2021-07-05)
- 参考文献数
- 21
- 被引用文献数
- 18
Respiratory disease deaths associated with seasonal influenza are estimated to be 290,000 to 650,000 per year globally. In Japan, seasonal influenza affects more than 10 million people per year, and especially children, the elderly, and patients with underlying medical conditions, and seasonal influenza can cause severe illness. As SARS-CoV-2 continues to spread, the combined risk of concurrent influenza epidemics and the COVID-19 pandemic are a concern. When the status of influenza virus infections during the 2020-2021 flu season was compared to the 2011 to 2020 flu seasons, data indicated the absence of seasonal influenza outbreaks in Japan during the COVID-19 pandemic. The number of flu patients was roughly estimated to be 14,000 nationwide from September 2020 to March 2021, which marks the first sharp decrease since national influenza surveillance started in 1987 in conjunction with National Epidemiological Surveillance of Infectious Diseases (NESID). Moreover, approximately 500 sentinel sites (designated medical facilities) nationwide reported only 112 patients with severe influenza who required hospitalization. Since prevention and control measures amidst the COVID-19 pandemic have become the "new normal", one can reasonably assume that the absence of a seasonal influenza outbreak is related to prevention and control measures implemented in response to the COVID-19 pandemic. Basic infection prevention measures were thoroughly implemented, such as wearing masks, handwashing, and avoiding confined spaces, crowded places, and close-contact settings. More importantly, the behavioral changes adopted to constrain COVID-19 during three declared states of emergency reduced population density and contact with people, including closing schools, asking restaurants to reduce their business hours, teleworking, curbing the flow of people during vacation week, etc. These behavioral changes will serve as a valuable reference to reduce the spread of seasonal influenza in the future.
- 著者
- Tatsuo Sawakami Kenji Karako Peipei Song Wataru Sugiura Norihiro Kokudo
- 出版者
- International Research and Cooperation Association for Bio & Socio-Sciences Advancement
- 雑誌
- BioScience Trends (ISSN:18817815)
- 巻号頁・発行日
- pp.2021.01269, (Released:2021-07-13)
- 参考文献数
- 26
- 被引用文献数
- 10
In Japan, the Law Concerning the Prevention of Infectious Diseases and Medical Care for Patients with Infectious Diseases (the "Infectious Diseases Control Law") classifies infectious diseases as category I-V infectious diseases, pandemic influenza, and designated infectious diseases based on their infectivity, severity, and impact on public health. COVID-19 was designated as a designated infectious disease as of February 1, 2020 and then classified under pandemic influenza as of February 13, 2021. According to national reports from sentinel surveillance, some infectious diseases transmitted by droplets, contact, or orally declined during the COVID-19 epidemic in Japan. As of week 22 (June 6, 2021), there were 704 cumulative cases of seasonal influenza, 8,144 cumulative cases of chickenpox, 356 cumulative cases of mycoplasma pneumonia, and 45 cumulative cases of rotavirus gastroenteritis; these numbers were significantly lower than those last year, with 563,487 cumulative cases of seasonal influenza, 31,785 cumulative cases of chickenpox, 3,518 cumulative cases of mycoplasma pneumonia, and 250 cumulative cases of rotavirus gastroenteritis. Similarly, many infectious diseases transmitted by droplets or contact declined in other countries and areas during the COVID-19 pandemic. One can reasonably assume that various measures adopted to control the transmission of COVID-19 have played a role in reducing the spread of other infectious diseases, and especially those transmitted by droplets or contact. Extensive and thorough implementation of personal protective measures and behavioral changes may serve as a valuable reference when identifying ways to reduce the spread of infectious diseases transmitted by droplets or contact in the future.
- 著者
- Kenji Karako Peipei Song Yu Chen Wei Tang Norihiro Kokudo
- 出版者
- International Research and Cooperation Association for Bio & Socio-Sciences Advancement
- 雑誌
- BioScience Trends (ISSN:18817815)
- 巻号頁・発行日
- pp.2021.01019, (Released:2021-01-29)
- 参考文献数
- 40
- 被引用文献数
- 76
The first case of COVID-19 in Japan was reported on 16 January 2020. The total number of the infected has reached 313,844 and the number of deaths has reached 4,379 as of 16 January 2021. This article reviews the characteristics of and responses to the three waves of COVID-19 in Japan during 2020-2021 in order to provide a reference for the next step in epidemic prevention and control. The Japanese Government declared a state of emergency on 7 April 2020, which suppressed the increase in the number of the infected by curtailing economic activity. The first wave peaked at 701 new cases a day and it decreased to 21 new cases on May 25 when the state of emergency was lifted. However, the number of the infected increased again due to the resumption of economic activity, with a peak of 1,762 new cases a day during the second wave. Although the situation was worse than that during the first wave, the government succeeded in limiting the increase without declaring a state of emergency again, and that may be attributed to a decrease in crowd activities and an increase in the number of inspections. During the third wave, the number of the infected continued to exceed the peak during previous waves for two months. Major factors for this rise include the government’s implementation of further policies to encourage certain activities, relaxed immigration restrictions, and people not reducing their level of activity. An even more serious problem is the bed usage for patients with COVID-19; bed usage exceeds 50% not only in major cities but also in various areas. On 7 January 2021, 5,953 new cases were reported a day; this greatly exceeded the previous peak, and the state of emergency was declared again. Although Japan has been preparing its medical system since the first wave, maintaining that system has imposed a large economic burden on medical facilities, hence stronger measures and additional support are urgently needed to combat COVID-19 in the coming few months.
- 著者
- Kenji Karako Yu Chen Wei Tang
- 出版者
- International Research and Cooperation Association for Bio & Socio-Sciences Advancement
- 雑誌
- BioScience Trends (ISSN:18817815)
- 巻号頁・発行日
- pp.2018.01264, (Released:2018-12-17)
- 参考文献数
- 57
- 被引用文献数
- 14
Neural networks have garnered attention over the past few years. A neural network is a typical model of machine learning that is used to identify visual patterns. Neural networks are used to solve a wide variety of problems, including image recognition problems and time series prediction problems. In addition, neural networks have been applied to medicine over the past few years. This paper classifies the ways in which neural networks have been applied to medicine based on the type of data used to train those networks. Applications of neural networks to medicine can be categorized two types: automated diagnosis and physician aids. Considering the number of patients per physician, neural networks could be used to diagnose diseases related to the vascular system, heart, brain, spinal column, head, neck, and tumors/cancer in three fields: vascular and interventional radiology, interventional cardiology, and neuroradiology. Lastly, this paper also considers areas of medicine where neural networks can be effectively applied in the future.