Medical Education in Turkey in Time of COVID-19
We Need to Rethink on Medical Education for Pandemic Preparedness: Lessons Learnt From COVID-19
Real-time monitoring the transmission potential of COVID-19 in Singapore, March 2020.
Singapore, Reproduction number, transmission potential, cluster distribution, SARS-CoV-2, COVID-19, reporting delay, Transmission heterogeneity
As of March 31, 2020, the ongoing COVID-19 epidemic that started in China in December 2019 is now generating local transmission around the world. The geographic heterogeneity and associated intervention strategies highlight the need to monitor in real time the transmission potential of COVID-19. Singapore provides a unique case example for monitoring transmission, as there have been multiple disease clusters, yet transmission remains relatively continued. Here we estimate the effective reproduction number, Rt, of COVID-19 in Singapore from the publicly available daily case series of imported and autochthonous cases by date of symptoms onset, after adjusting the local cases for reporting delays as of March 17, 2020. We also derive the reproduction number from the distribution of cluster sizes using a branching process analysis that accounts for truncation of case counts. The local incidence curve displays sub-exponential growth dynamics, with the reproduction number following a declining trend and reaching an estimate at 0.7 (95% CI 0.3, 1.0) during the first transmission wave by February 14, 2020, while the overall R based on the cluster size distribution as of March 17, 2020, was estimated at 0.6 (95% CI 0.4, 1.02). The overall mean reporting delay was estimated at 6.4 days (95% CI 5.8, 6.9), but it was shorter among imported cases compared to local cases (mean 4.3 vs. 7.6 days, Wilcoxon test, p < 0.001). The trajectory of the reproduction number in Singapore underscores the significant effects of successful containment efforts in Singapore, but it also suggests the need to sustain social distancing and active case finding efforts to stomp out all active chains of transmission.
Ping Yan, Gerardo Chowell, Seth Blumberg, Stefan Ma, Amna Tariq, Kimberlyn Roosa, Yiseul Lee
Short-Term Effects of Ambient Ozone, PM2.5, and Meteorological Factors on COVID-19 Confirmed Cases and Deaths in Queens, New York.
temperature, air pollution, PM2.5, Humidity, coronavirus, ozone, meteorological factors, Respiratory viral infections, SARS-CoV-2, COVID-19
The outbreak of coronavirus disease 2019 (COVID-19), caused by the virus SARS-CoV-2, has been rapidly increasing in the United States. Boroughs of New York City, including Queens county, turn out to be the epicenters of this infection. According to the data provided by the New York State Department of Health, most of the cases of new COVID-19 infections in New York City have been found in the Queens county where 42,023 people have tested positive, and 3221 people have died as of 20 April 2020. Person-to-person transmission and travels were implicated in the initial spread of the outbreaks, but factors related to the late phase of rapidly spreading outbreaks in March and April are still uncertain. A few previous studies have explored the links between air pollution and COVID-19 infections, but more data is needed to understand the effects of short-term exposures of air pollutants and meteorological factors on the spread of COVID-19 infections, particularly in the U.S. disease epicenters. In this study, we have focused on ozone and PM2.5, two major air pollutants in New York City, which were previously found to be associated with respiratory viral infections. The aim of our regression modeling was to explore the associations among ozone, PM2.5, daily meteorological variables (wind speed, temperature, relative humidity, absolute humidity, cloud percentages, and precipitation levels), and COVID-19 confirmed new cases and new deaths in Queens county, New York during March and April 2020. The results from these analyses showed that daily average temperature, daily maximum eight-hour ozone concentration, average relative humidity, and cloud percentages were significantly and positively associated with new confirmed cases related to COVID-19; none of these variables showed significant associations with new deaths related to COVID-19. The findings indicate that short-term exposures to ozone and other meteorological factors can influence COVID-19 transmission and initiation of the disease, but disease aggravation and mortality depend on other factors.
International Journal of Environmental Research and Public Health
Covid-19: a survey on knowledge, awareness and hygiene practices among dental health professionals in an Indian scenario.
Knowledge, dentists, coronavirus, Emergencies, Pandemics, SARS-CoV-2, COVID-19
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 or COVID-19) continues to spread globally. It has become a major cause of concern for health care professionals all over the world. The aim of this study was to assess knowledge, awareness and hygiene practices regarding COVID-19 among private dental practitioners practicing in Tricity (Chandigarh, Panchkula and Mohali) in India during these critical times. A total of 245 private dentists participated in this cross-sectional survey and finally 215 constituted the final sample size. A self-administered, multiple choice type questionnaire (verified by a specialist) was administered to obtain information from the subjects. The questionnaire was divided into two parts and included 15 questions on knowledge and awareness regarding COVID-19. Statistical analysis was done using ANOVA and Student’s t-test. Percentage of subjects who answered correctly regarding main symptoms of COVID-19 and primary mode of transmission was 87% and 82.5% respectively. One-third of the subjects were not aware regarding Personal Protective Equipment (PPE) to be used while rendering dental treatment. 75% of subjects were of the opinion that supportive care is the current treatment regime for COVID-19. Less than one-third of subjects (30.2%) reported high scores. Education level (p=0.018) and health sector profile (p=0.024) of the subjects were significantly associated with mean knowledge scores. The findings of the present study showed that some notable deficiencies in knowledge existed among dental professionals regarding some vital aspects of COVID-19. Therefore, there is an urgent need for improving dentists’knowledge via health education and training programs. Further studies on the subject are also warranted once the situation normalizes.
Ramandeep Singh Gambhir, Amit Aggarwal, Jagjit Singh Dhaliwal, Samir Anand, Vaibhav Anand, Amanpreet Kaur Bhangu
National Institute of Public Health - National Institute of Hygiene
Amplifying the role of knowledge translation platforms in the COVID-19 pandemic response.
research, Data, Knowledge Translation, evidence, Evidence-informed policy-making, COVID-19 pandemic
The COVID-19 pandemic presents the worst public health crisis in recent history. The response to the COVID-19 pandemic has been challenged by many factors, including scientific uncertainties, scarcity of relevant research, proliferation of misinformation and fake news, poor access to actionable evidence, time constraints, and weak collaborations among relevant stakeholders. Knowledge translation (KT) platforms, composed of organisations, initiatives and networks supporting evidence-informed policy-making, can play an important role in providing relevant and timely evidence to inform pandemic responses and bridge the gap between science, policy, practice and politics. In this Commentary, we highlight the emerging roles of KT platforms in light of the COVID-19 pandemic. We also reflect on the lessons learned from the efforts of a KT platform in a middle-income country to inform decision-making and practice during the COVID-19 pandemic. The lessons learned can be integrated into strengthening the role, structures and mandates of KT platforms as hubs for trustworthy evidence that can inform policies and practice during public health crises and in promoting their integration and institutionalisation within the policy-making processes.
Racha Fadlallah, Lama Bou-Karroum, Fadi El-Jardali
Prediction of Epidemic Peak and Infected Cases for COVID-19 Disease in Malaysia, 2020.
ANFIS, infection rate, GA, basic reproductive number, SEIR model, Epidemic peak, COVID-19
The coronavirus COVID-19 has recently started to spread rapidly in Malaysia. The number of total infected cases has increased to 3662 on 05 April 2020, leading to the country being placed under lockdown. As the main public concern is whether the current situation will continue for the next few months, this study aims to predict the epidemic peak using the Susceptible-Exposed-Infectious-Recovered (SEIR) model, with incorporation of the mortality cases. The infection rate was estimated using the Genetic Algorithm (GA), while the Adaptive Neuro-Fuzzy Inference System (ANFIS) model was used to provide short-time forecasting of the number of infected cases. The results show that the estimated infection rate is 0.228 ± 0.013, while the basic reproductive number is 2.28 ± 0.13. The epidemic peak of COVID-19 in Malaysia could be reached on 26 July 2020, with an uncertain period of 30 days (12 July-11 August). Possible interventions by the government to reduce the infection rate by 25% over two or three months would delay the epidemic peak by 30 and 46 days, respectively. The forecasting results using the ANFIS model show a low Normalized Root Mean Square Error (NRMSE) of 0.041; a low Mean Absolute Percentage Error (MAPE) of 2.45%; and a high coefficient of determination (R2) of 0.9964. The results also show that an intervention has a great effect on delaying the epidemic peak and a longer intervention period would reduce the epidemic size at the peak. The study provides important information for public health providers and the government to control the COVID-19 epidemic.
Hasan Sari, Abdallah Alsayed, Hayder Sadir, Raja Kamil
Predictors of fatality including radiographic findings in adults with COVID-19.
predictor, Fatality, radiographic findings, COVID-19
Older age and elevated d-dimer are reported risk factors for coronavirus disease 2019 (COVID-19). However, whether early radiographic change is a predictor of fatality remains unknown. We retrospectively reviewed records of all laboratory-confirmed patients admitted to a quarantine unit at Tongji Hospital, a large regional hospital in Wuhan, China, between January 31 and March 5, 2020. Confirmed cases were defined by positive RT-PCR detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in throat-swab specimens. Chest CT images were reviewed independently by two radiologists. The Tongji Hospital ethics committee approved this study. A total of 102 patients were confirmed to have SARS-CoV-2 infection. As of March 25, 85 confirmed patients were discharged, 15 died, and 2 remained hospitalized. When compared with survivors, non-survivors were older (median age, 69 [interquartile range, 58-77] vs. 55 [44-66], p = 0.003), and more likely to have decreased lymphocyte count (0.5 vs. 0.9 × 109/L, p = 0.006), elevated lactate dehydrogenase (LDH) (569.0 vs. 272.0 U/L, p < 0.001), elevated d-dimer (> 1 μg/mL, 86% vs. 37%, p = 0.002) on admission. Older age and elevated LDH were independent risk factors for fatality in a multivariate regression model included the above variables. In a subset of patients with CT images within the first week, higher total severity score, and more involved lung lobes (5 involved lobes) in CT images within the first week were significantly associated with fatality. Moreover, in this subset of patients, higher total severity score was the only independent risk factor in a multivariate analysis incorporating the above mentioned variables. Older age, elevated LDH on admission, and higher severity score of CT images within the first week are potential predictors of fatality in adults with COVID-19. These predictors may help clinicians identify patients with a poor prognosis at an early stage.
Nan Wang, Zi Wang, Dian Chen, Yuchen Feng, Guohua Zhen, Kaiyan Li, Shengchong Chen, Chenli Chang
Adoption and impact of non-pharmaceutical interventions for COVID-19.
nonpharmaceutical interventions, COVID-19
Background: Several non-pharmaceutical interventions (NPIs) have been implemented across the world to control the coronavirus disease (COVID-19) pandemic. Social distancing (SD) interventions applied so far have included school closures, remote working and quarantine. These measures have been shown to have large impacts on pandemic influenza transmission. However, there has been comparatively little examination of such measures for COVID-19. Methods: We examined the existing literature, and collated data, on implementation of NPIs to examine their effects on the COVID-19 pandemic so far. Data on NPIs were collected from official government websites as well as from media sources. Results: Measures such as travel restrictions have been implemented in multiple countries and appears to have slowed the geographic spread of COVID-19 and reduced initial case numbers. We find that, due to the relatively sparse information on the differences with and without interventions, it is difficult to quantitatively assess the efficacy of many interventions. Similarly, whilst the comparison to other pandemic diseases such as influenza can be helpful, there are key differences that could affect the efficacy of similar NPIs. Conclusions: The timely implementation of control measures is key to their success and must strike a balance between early enough application to reduce the peak of the epidemic and ensuring that they can be feasibly maintained for an appropriate duration. Such measures can have large societal impacts and they need to be appropriately justified to the population. As the pandemic of COVID-19 progresses, quantifying the impact of interventions will be a vital consideration for the appropriate use of mitigation strategies.
Neil M. Ferguson, Katy A M Gaythorpe, Natsuko Imai, Sam Abbott, Sangeeta Bhatia, Sabine van Elsland, Kiesha Prem, Yang Liu
Broad-Spectrum Host-Based Antivirals Targeting the Interferon and Lipogenesis Pathways as Potential Treatment Options for the Pandemic Coronavirus Disease 2019 (COVID-19).
treatment, coronavirus, interferon, 25-hydroxycholesterol, COVID-19, AM580
The ongoing Coronavirus Disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) signals an urgent need for an expansion in treatment options. In this study, we investigated the anti-SARS-CoV-2 activities of 22 antiviral agents with known broad-spectrum antiviral activities against coronaviruses and/or other viruses. They were first evaluated in our primary screening in VeroE6 cells and then the most potent anti-SARS-CoV-2 antiviral agents were further evaluated using viral antigen expression, viral load reduction, and plaque reduction assays. In addition to remdesivir, lopinavir, and chloroquine, our primary screening additionally identified types I and II recombinant interferons, 25-hydroxycholesterol, and AM580 as the most potent anti-SARS-CoV-2 agents among the 22 antiviral agents. Betaferon (interferon-β1b) exhibited the most potent anti-SARS-CoV-2 activity in viral antigen expression, viral load reduction, and plaque reduction assays among the recombinant interferons. The lipogenesis modulators 25-hydroxycholesterol and AM580 exhibited EC50 at low micromolar levels and selectivity indices of >10.0. Combinational use of these host-based antiviral agents with virus-based antivirals to target different processes of the SARS-CoV-2 replication cycle should be evaluated in animal models and/or clinical trials.
Kelvin Kai-Wang To, Kwok-yung Yuen, Fei-fei Yin, Jian-Piao Cai, Ivan Fan-Ngai Hung, Kenn Ka-Heng Chik, Zi-Wei Ye, Kai-ming Tang, Jianli Cao, Chris Chun-Yiu Chan, Ronghui Liang, Jasper Fuk-Woo Chan, Dong-Yan Jin, Shuofeng Yuan, Jessica Oi-Ling Tsang, Hin Chu