scholarly journals Challenges to the system of reserve medical supplies for public health emergencies: reflections on the outbreak of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic in China

2020 ◽  
Vol 14 (1) ◽  
pp. 3-8 ◽  
Author(s):  
Xu Wang ◽  
Xiaoxi Zhang ◽  
Jiangjiang He
Author(s):  
Bryan P Bednarski ◽  
Akash Deep Singh ◽  
William M Jones

Abstract objective This work investigates how reinforcement learning and deep learning models can facilitate the near-optimal redistribution of medical equipment in order to bolster public health responses to future crises similar to the COVID-19 pandemic. materials and methods The system presented is simulated with disease impact statistics from the Institute of Health Metrics (IHME), Center for Disease Control, and Census Bureau[1, 2, 3]. We present a robust pipeline for data preprocessing, future demand inference, and a redistribution algorithm that can be adopted across broad scales and applications. results The reinforcement learning redistribution algorithm demonstrates performance optimality ranging from 93-95%. Performance improves consistently with the number of random states participating in exchange, demonstrating average shortage reductions of 78.74% (± 30.8) in simulations with 5 states to 93.50% (± 0.003) with 50 states. conclusion These findings bolster confidence that reinforcement learning techniques can reliably guide resource allocation for future public health emergencies.


2021 ◽  
Vol 105 (4) ◽  
pp. 868-871
Author(s):  
Ian Christopher N. Rocha ◽  
Mary Grace A. Pelayo ◽  
Sudhan Rackimuthu

ABSTRACT. The Kumbh Mela is a significant religious gathering of millions of Hindu devotees in India. It is celebrated on certain auspicious days in the Hindu calendar and attracts millions of pilgrims across the country. Despite the religious intention of millions of Hindu devotees, it raised public health concerns as it became a massive superspreading event for COVID-19. Being the second most populous country, India became the second most affected country during the COVID-19 pandemic. In addition to the arrival of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants and the presence of the double mutated variant, which was first identified in India, the Kumbh Mela probably aggravated the country’s COVID-19 situation which resulted in an uncontrollable second wave. Several cases of COVID-19 across India had been contact-traced to returnees from the event who acted as a nidus to help spread the infection. As a consequence, India’s healthcare system was severely challenged as a result of the overwhelming hospitalizations and increasing fatalities resulting in an acute manpower shortage in healthcare along with the depletion of drugs and medical supplies despite being one of the largest pharmaceutical hubs globally. Leaders and governments around the world should learn from India’s experience and thereby take preventive measures to manage potential superspreading events to curb the spike of COVID-19 cases.


2021 ◽  
Author(s):  
Peishan Ning ◽  
Peixia Cheng ◽  
Jie Li ◽  
Ming Zheng ◽  
David C Schwebel ◽  
...  

BACKGROUND Given the permeation of social media throughout society, rumors spread faster than ever before, which significantly complicates government responses to public health emergencies such as the COVID-19 pandemic. OBJECTIVE We aimed to examine the characteristics and propagation of rumors during the early months of the COVID-19 pandemic in China and evaluated the effectiveness of health authorities’ release of correction announcements. METHODS We retrieved rumors widely circulating on social media in China during the early stages of the COVID-19 pandemic and assessed the effectiveness of official government clarifications and popular science articles refuting those rumors. RESULTS We show that the number of rumors related to the COVID-19 pandemic fluctuated widely in China between December 1, 2019 and April 15, 2020. Rumors mainly occurred in 3 provinces: Hubei, Zhejiang, and Guangxi. Personal social media accounts constituted the major source of media reports of the 4 most widely distributed rumors (the novel coronavirus can be prevented with “Shuanghuanglian”: 7648/10,664, 71.7%; the novel coronavirus is the SARS coronavirus: 14,696/15,902, 92.4%; medical supplies intended for assisting Hubei were detained by the local government: 3911/3943, 99.2%; asymptomatically infected persons were regarded as diagnosed COVID-19 patients with symptoms in official counts: 322/323, 99.7%). The number of rumors circulating was positively associated with the severity of the COVID-19 epidemic (ρ=0.88, 95% CI 0.81-0.93). The release of correction articles was associated with a substantial decrease in the proportion of rumor reports compared to accurate reports. The proportions of negative sentiments appearing among comments by citizens in response to media articles disseminating rumors and disseminating correct information differ insignificantly (both correct reports: χ<sub>1</sub><sup>2</sup>=0.315, <i>P</i>=.58; both rumors: χ<sub>1</sub><sup>2</sup>=0.025, <i>P</i>=.88; first rumor and last correct report: χ<sub>1</sub><sup>2</sup>=1.287, <i>P</i>=.26; first correct report and last rumor: χ<sub>1</sub><sup>2</sup>=0.033, <i>P</i>=.86). CONCLUSIONS Our results highlight the importance and urgency of monitoring and correcting false or misleading reports on websites and personal social media accounts. The circulation of rumors can influence public health, and government bodies should establish guidelines to monitor and mitigate the negative impact of such rumors.


2003 ◽  
Vol 12 (3) ◽  
pp. 1-6 ◽  
Author(s):  
Deana Midmer

The SARS (Severe Acute Respiratory Syndrome) crisis in Toronto in the spring of 2003 had major consequences for prenatal learners. Classes in hospitals were cancelled; many couples were left without any prenatal education. This paper outlines the decision-making process of one programme that was determined to keep classes open. The impact of SARS on hospital procedures is also described. Childbirth educators are encouraged to prepare for future public health emergencies. Strategies to prepare for conducting childbirth education classes during times of crisis are outlined.


Author(s):  
Yuwei Zhang ◽  
Zhenping Li ◽  
Pengbo Jiao ◽  
Shen Zhu

AbstractAt the early stage of public health emergencies, when the conventional medical reserves prepared are insufficient, and productivity could temporarily not meet the surge in demand, donations can be used to cover excess demand for medical supplies to a large extent. This paper explicitly considers the allocation problem of limited medical reserves during a public health emergency, incorporating uncertainty in demand and donated supplies and the priorities of health care centers. The problem is formulated as a two-stage stochastic program that regards the donated supplies as an efficient recourse action, aiming to minimize the total losses. The optimal allocation strategy of limited medical reserves and donations is obtained by solving the model using Gurobi solver. Finally, the effectiveness of the proposed approach is verified by a series of computational results, which show that the solutions of our method not only benefit the emergency demand fulfill rate but reduce the total losses as well.


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