Pandemic response management framework based on efficiency of COVID-19 control and treatment
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ABSTRACT:
SUBMITTER: Ibrahim M
PROVIDER: S-EPMC7740003 | biostudies-literature | 2020 Dec
REPOSITORIES: biostudies-literature
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Project description:Purpose: This article measured the performance of 32 states and union territories (UTs) of India against COVID-19 disease using efficiency score which was calculated by data envelopment analysis (DEA) and compared the efficiency score with the different models which are used in many articles to evaluate the efficiency of healthcare system. Here the input parameters are taken as public health expenditure in a million, number of hospitals, number of hospital beds, percentage of health workers, population density, and number of infected, and output parameters divided into good and bad categories such as the number of recovered are taken as good output. The number of death is taken as bad outputs. The modified undesirable output model is used to calculate efficiency score and compared the efficiency score with Charnes, Cooper, and Rhodes (CCR) and Banker, Charnes, and Cooper (BCC) models. Finally, the states & UTs are completely ranked with the help of efficiency score and Maximal Balance Index, and evaluated benchmarking for each states & UTs. Data Source: Secondary data were collected from Census 2011 and the Ministry of health & family welfare, Government of India on 32 stats & UTs (NHAC, 2018; NHP, 2019; COVID19India, 2021). Results: According to Undesirable model results, 16 (50%) of 32 Indian states & UTs s were found to be efficient. Among the efficient DMUs, Chandigarh is the most efficient unit and Meghalaya is the most inefficient unit. Rajasthan was the most referenced state for inefficient states. Limitation: The efficiency score is affected by changing the number of inputs and outputs. The lack of more effective parameters are used to evaluate performance and enable qualitative variable comparison.
| S-EPMC8556177 | biostudies-literature
Project description:Coronavirus disease 2019 (COVID-19) outbreaks have occurred in many countries around the world. The numbers of confirmed cases and deaths continue to increase. It is increasingly likely that COVID-19 patients will require emergency surgeries in the operating room (OR). As COVID-19 can easily be transmitted to healthcare workers and other patients during surgery, it is important to establish a set of infection prevent and control management strategy to prevent COVID-19 from spreading in the OR. Based on our experience in COVID-19 prevention and control in the OR, we introduce this COVID-19 prevention and control management strategy for preventing COVID-19 from spreading in the OR. This management strategy includes a number of COVID-19 prevention and control procedures including (I) conduct COVID-19 knowledge training at the early stage of outbreak, (II) formulate the surgery arrangement procedures and suspend the elective surgery if the patient confirmed to COVID-19, (III) divide an isolated OR area for COVID-19 surgery, (IV) preoperative preparation procedures, (V) procedures for wearing and removing personal protective equipment, (VI) anesthesia management, intraoperative management, (VII) post-operative disposable waste management and disinfection. This management strategy has worked very effectively since the outbreak of COVID-19 in Wuhan at the end of 2019. We have performed emergency surgeries on several COVID-19 confirmed patient and dozens of COVID-19 suspected patients under this COVID-19 prevention and control management strategy, and have achieved an excellent result of zero COVID-19 infection in the OR.
| S-EPMC9761131 | biostudies-literature
Project description:The COVID-19 pandemic has led to considerable morbidity and mortality, and consumed enormous resources (e.g. energy) to control and prevent the disease. It is crucial to balance infection risk and energy consumption when reducing the spread of infection. In this study, a quantitative human, behavior-based, infection risk-energy consumption model for different indoor environments was developed. An optimal balance point for each indoor environment can be obtained using the anti-problem method. For this study we selected Wangjing Block, one of the most densely populated places in Beijing, as an example. Under the current ventilation standard (30 m3/h/person), prevention and control of the COVID-19 pandemic would be insufficient because the basic reproduction number (R0 ) for students, workers and elders are greater than 1. The optimal required fresh air ventilation rates in most indoor environments are near or below 60 m3/h/person, after considering the combined effects of multiple mitigation measures. In residences, sports buildings and restaurants, the demand for fresh air ventilation rate is relatively high. After our global optimization of infection risk control (R0 ≤ 1), energy consumption can be reduced by 13.7% and 45.1% on weekdays and weekends, respectively, in contrast to a strategy of strict control (R0 = 1 for each indoor environment).
| S-EPMC8848536 | biostudies-literature
Project description: Not available
| S-BSST1055 | biostudies-other
Project description:To understand and analyse the global impact of COVID-19 on outpatient services, inpatient care, elective surgery, and perioperative colorectal cancer care, a DElayed COloRectal cancer surgery (DECOR-19) survey was conducted in collaboration with numerous international colorectal societies with the objective of obtaining several learning points from the impact of the COVID-19 outbreak on our colorectal cancer patients which will assist us in the ongoing management of our colorectal cancer patients and to provide us safe oncological pathways for future outbreaks.
| 2346925 | ecrin-mdr-crc
Project description: Not available
| S-EPMC8032908 | biostudies-literature
Project description:Following the emergence of severe acute respiratory syndrome (SARS) in 2002 and the Middle East respiratory syndrome (MERS) in 2012, the world is now combating a third large-scale outbreak caused by a coronavirus, the coronavirus disease 2019 (COVID-19). After the rapid spread of SARS-coronavirus (CoV)-2 (the virus causing COVID-19) from its origin in China, the World Health Organization (WHO) declared a Public Health Emergency of International Concern (PHEIC) on January 30, 2020. From the beginning of the COVID-19 pandemic, a significant number of studies have been conducted to better understand the biology and pathogenesis of the novel coronavirus, and to aid in developing effective treatment regimens, therapeutics, and vaccines. This review focuses on the recent advancements in the rapidly evolving areas of clinical care and management of COVID-19. The emerging strategies for the diagnosis and treatment of this disease are explored, and the development of effective vaccines is reviewed.
| S-EPMC7883285 | biostudies-literature
Project description:The SARS-CoV-2 pandemic triggered substantial economic and social disruptions. Mitigation policies varied across countries based on resources, political conditions, and human behavior. In the absence of widespread vaccination able to induce herd immunity, strategies to coexist with the virus while minimizing risks of surges are paramount, which should work in parallel with reopening societies. To support these strategies, we present a predictive control system coupled with a nonlinear model able to optimize the level of policies to stop epidemic growth. We applied this system to study the unfolding of COVID-19 in Bahia, Brazil, also assessing the effects of varying population compliance. We show the importance of finely tuning the levels of enforced measures to achieve SARS-CoV-2 containment, with periodic interventions emerging as an optimal control strategy in the long-term.
| S-EPMC8239053 | biostudies-literature
Project description:BackgroundThe COVID-19 pandemic yielded a substantial increase in worldwide prevalence and severity of anxiety, but less is known about effects on anxiety treatment.ObjectiveWe evaluated effects of the COVID-19 pandemic on responses to Cognitive Behavioral Therapy for anxiety, in a clinically heterogeneous sample of patients.MethodsA sample of 764 outpatients were separated into four groups: (1) Pre-pandemic (start date on or prior to 12/31/2019), (2) Pandemic-Onset (start date from 01/01/2020 to 03/31/2020), (3) During-Pandemic (start date from 04/01/2020 through 12/31/2020), and (4) Post-Pandemic (start date on or after 01/01/2021). We subsequently compared treatment trajectories and effects within and between these groups over 5621 total time points (mean of 7.38 measurements per patient).ResultsOverall, patients presented with moderate levels of anxiety (M = 13.25, 95%CI: 12.87, 13.62), which rapidly decreased for 25 days (M = 9.46, 95%CI: 9.09, 9.83), and thereafter slowly declined into the mild symptom range over the remainder of the study period (M = 7.36, 95%CI: 6.81, 7.91), representing clinically as well as statistically significant change. A series of conditional multilevel regression models indicated that there were no substantive differences between groups, and no increase in anxiety during the acute pandemic phase.ConclusionsOur results suggest that responses to treatment for anxiety were equivalent before, during, and after the COVID-19 pandemic. Among patients who were in treatment prior to the pandemic, we failed to detect an increase in anxiety during the pandemic's acute phase (March 20th, 2020 through July 1st, 2020).
| S-EPMC10936764 | biostudies-literature
Project description:The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic is responsible for generating a global effort to discover urgent therapeutic solutions to limit the human damage caused by COVID-19. In the period of April to June 2020, 105 patients diagnosed with COVID-19 met the conditions for inclusion in the present study. They were treated with antiviral therapy according to local guidelines: D group (53 cases), treated with darunavir/ritonavir (DRV/r); and K group (52 cases), treated with lopinavir/ritonavir (LPV/r). Patients from the K group required 7.5 days of hospitalization less compared to those from the D group (P<0.001). The blood oxygen saturation values recorded in the groups were statistically different [K group (94.02±3.12%) vs. D group (92.13±4.24%), P=0.010]. The percentage of patients with unsatisfactory clinical evolution were non-significantly higher in the D group compared with the K group [20 (37.74%) vs. 12 (23.08%), P=0.157]. We did not note statistically significant differences between the two groups tracked considering the values for the Brescia-COVID Respiratory Severity Scale (BCRSS) of the patients with unsatisfactory clinical evolution, nor of the chest CT' evolution after 10 days of therapy. We did not register significant adverse effects after antiviral therapy in the two groups. Antiviral therapy with LPV/r had some favorable results compared to DRV/r in patients with COVID-19. Both therapies were well tolerated.
| S-EPMC8097236 | biostudies-literature