Wave Of Coronavirus Disease 2019 Research Articles

Beware of the second wave of COVID-19

The outbreak of coronavirus disease 2019 (COVID-19), which began in Wuhan, China, in late 2019, has spread to 203 countries as of March 30, 2020, and has been officially declared a global pandemic.1 With unprecedented public health interventions, local transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) appears now to have been contained in China. Multiple countries are now experiencing the first wave of the COVID-19 epidemic; thus, gaining an understanding of how these interventions prevented the transmission of SARS-CoV-2 in China is urgent.

Stemming the flow: how much can the Australian smartphone app help to control COVID-19?

Our objective is to assess the potential contribution of the Australian Government's mobile smartphone tracing app (COVIDSafe) to the sustained control of coronavirus disease 2019 (COVID-19). Development and analysis of a system dynamics model. To define the pandemic context and specify model-building parameters, we searched for literature on COVID-19, its epidemiology in Australia, case finding processes, and factors that might affect community acceptance of the COVIDSafe smartphone app for contact tracing. We then developed a system dynamics model of COVID-19 based on a modified susceptible-exposed-infected-recovered compartmental model structure, using initial pandemic data and published information on virus behaviour to determine parameter values. We applied the model to examine factors influencing the projected trends: the extent of viral testing, community participation in social distancing, and the level of uptake of the COVIDSafe app. Modelling suggests that a second COVID-19 wave will occur if social distancing declines (i.e. if the average number of contacts made by each individual each day increases) and the rate of testing declines. The timing and size of the second wave will depend on the rate of decrease in social distancing and the decline in testing rates. At the app uptake level of approximately 27% (current at 20 May 2020), with a monthly 50% reduction in social distancing (i.e. the average number of contacts per day doubling every 30 days until they reach pre-social distancing rates) and a 5% decline in testing, the app would reduce the projected total number of new cases during April-December 2020 by one-quarter. If uptake reaches the possible maximum of 61%, the reduction could be more than half. Maintenance of a large-scale testing regimen for COVID-19 and widespread community practice of social distancing are vital. The COVIDSafe smartphone app has the potential to be an important adjunct to testing and social distancing. Depending on the level of community uptake of the app, it could have a significant mitigating effect on a second wave of COVID-19 in Australia.

The Burden of Disease due to COVID-19 in Korea Using Disability-Adjusted Life Years.

BackgroundThe world is currently experiencing a pandemic of coronavirus disease 2019 (COVID-19). In Korea, as in other countries, the number of confirmed cases and deaths due to COVID-19 have been rising. This study aimed to calculate the burden of disease due to COVID-19 in Korea.MethodsWe used data on confirmed cases and deaths due to COVID-19 between January 20 and April 24, 2020 provided by the Korea Centers for Disease Control and Prevention, the local governments and the public media to determine disability-adjusted life years (DALYs) by sex and age. Morbidity was estimated directly among the confirmed, cured, and fatal cases. Disability weights were adopted from previous similar causes on the severity of COVID-19 for the years of life lived with disability (YLDs). The years of life lost (YLLs) were calculated using the standard life expectancy from the 2018 life tables for each sex and age.ResultsThe YLDs were higher in females (155.2) than in males (105.1), but the YLLs were higher in males (1,274.3) than in females (996.4). The total disease burden attributable to COVID-19 in Korea during the study period, was estimated to be 2,531.0 DALYs, and 4.930 DALYs per 100,000 population. The YLDs and the YLLs constituted 10.3% and 89.7% of the total DALYs, respectively. The DALYs per 100,000 population were highest in people aged ≥ 80 years, followed by those aged 70–79, 60–69, and 50–59 years, but the incidence was the highest in individuals aged 20–29 years.ConclusionThis study provided the estimates of DALYs due to COVID-19 in Korea. Most of the disease burden from COVID-19 was derived from YLL; this indicates that decision-makers should focus and make an effort on reducing fatality for preparing the second wave of COVID-19.

Current status and future perspective of coronavirus disease 2019: A review

A novel infectious disease named coronavirus disease-2019 (COVID-19) first emerged in Wuhan, China, in December 2019 and rapidly spread worldwide. In March 2020 the World Health Organization declared a global pandemic which is the worst global public health crisis in over 100 years. On 14 June 2020, almost eight million confirmed cases of COVID-19 and more than 430,000 deaths globally were reported. Over 200 countries have been affected so far. COVID-19 is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In the absence of specific therapy and vaccine, effective infection control intervention, particularly self-hygiene and social distancing, is the only way to prevent the spread of SARS-CoV-2. The lessons learned from this pandemic will be useful for successful management of the second wave of COVID-19 which is expected in autumn or winter.

JAAM nationwide survey on the response to the first wave of COVID-19 in Japan. Part II: how did medical institutions overcome the first wave and how should they prepare for the future?

To investigate and clarify the surge capacity of staff/equipment/space, and patient outcome in the first wave of coronavirus disease (COVID-19) in Japan. We analyzed questionnaire data from the end of May 2020 from 180 hospitals (total of 102,578 beds) with acute medical centers. A total of 4,938 hospitalized patients with COVID-19 were confirmed. Of 1,100 severe COVID-19 inpatients, 112 remained hospitalized and 138 died. There were 4,852 patients presumed to be severe COVID-19 patients who were confirmed later to be not infected. Twenty-seven hospitals (15% of 180 hospitals) converted their intensive care unit (ICU) to a unit for COVID-19 patients only, and 107 (59%) had to manage both severe COVID-19 patients and others in the same ICU. Restriction of ICU admission occurred in one of the former 27 hospitals and 21 of the latter 107 hospitals. Shortage of N95 masks was the most serious concern regarding personal protective equipment. As for issues that raised ICU bed occupancy, difficulty undertaking or progressing rehabilitation for severe patients (42%), and the improved patients (28%), long-lasting severely ill patients (36%), and unclear isolation criteria (34%) were mentioned. Many acute medicine physicians assisted regional governmental agencies, functioning as advisors and volunteer coordinators. The mortality rate of COVID-19 in this study was 4.1% of all hospitalized patients and 12.5% (one in eight) severe patients. The hospitals with dedicated COVID-19 ICUs accepted more patients with severe COVID-19 and had lower ICU admission restrictions, which could be helpful as a strategy in the next pandemic.

Estimating the Effectiveness of Non-Pharmaceutical Interventions on COVID-19 Control in Korea.

BackgroundThe coronavirus disease 2019 (COVID-19) pandemic has posed significant global public health challenges and created a substantial economic burden. Korea has experienced an extensive outbreak, which was linked to a religion-related super-spreading event. However, the implementation of various non-pharmaceutical interventions (NPIs), including social distancing, spring semester postponing, and extensive testing and contact tracing controlled the epidemic. Herein, we estimated the effectiveness of each NPI using a simulation model.MethodsA compartment model with a susceptible-exposed-infectious-quarantined-hospitalized structure was employed. Using the Monte-Carlo-Markov-Chain algorithm with Gibbs' sampling method, we estimated the time-varying effective contact rate to calibrate the model with the reported daily new confirmed cases from February 12th to March 31st (7 weeks). Moreover, we conducted scenario analyses by adjusting the parameters to estimate the effectiveness of NPI.ResultsRelaxed social distancing among adults would have increased the number of cases 27.4-fold until the end of March. Spring semester non-postponement would have increased the number of cases 1.7-fold among individuals aged 0–19, while lower quarantine and detection rates would have increased the number of cases 1.4-fold.ConclusionAmong the three NPI measures, social distancing in adults showed the highest effectiveness. The substantial effect of social distancing should be considered when preparing for the 2nd wave of COVID-19.