scholarly journals Investigation on COVID-19 Infection Cases in Korea

2020 ◽  
Author(s):  
Yun Jung Kang
Keyword(s):  
Public Health ◽  
Epidemiological Data ◽  
Health Policies ◽  
Personal Hygiene ◽  
Chinese Government ◽  
Close Attention ◽  
Patient Case ◽  
Public Health Policies ◽  
Pneumonia Case ◽  
Large Groups

Abstract On December 31st, 2019, the Chinese government announced officially that the country had a pneumonia case with an unknown cause. After that, Korea had 24 confirmed cases on February 8th, and the number has increased constantly since then. COVID-19, a highly contagious virus, infected another patient, Case No. 31, in Daegu; she was the first patient related to Sincheonji Church in Daegu. Later, the number of cases involved with Sincheonji skyrocketed. On March 6th, 2020, the accumulated number of confirmed cases was 6,284, with 42 dead among them. This study, through collecting epidemiological data about various COVID-19 infection cases, found out that getting together in large groups and religious ceremonies leads to massive infection, and that paying close attention to personal hygiene by wearing masks and sanitary gloves, etc., can prevent the spread of COVID-19. Additional epidemiological data and related studies on COVID-19 infections in Korea might either support or modify this conclusion. However, this study is significant in that it emphasizes the precautionary principle in preventing and managing infectious diseases, and that it has a suggestion for public health policies which are on urgent demand currently.

scholarly journals Lessons Learned From Cases of COVID-19 Infection in South Korea

2020 ◽  
pp. 1-8
Author(s):  
Yun-Jung Kang
Keyword(s):  
South Korea ◽  
Epidemiological Data ◽  
Lessons Learned ◽  
Health Policies ◽  
Personal Hygiene ◽  
Chinese Government ◽  
Close Attention ◽  
Public Health Policies ◽  
Infected Case ◽  
Large Groups

ABSTRACT On December 31, 2019, the Chinese government officially announced that the country had a single pneumonia case with an unknown cause. In the weeks after, South Korea had 24 confirmed cases by February 8, and the number has increased steadily since then. The highly contagious virus known as coronavirus disease 2019 (COVID-19) infected Case No. 31 in Daegu; she was the first patient related to Sincheonji Church. Later, the number of cases involved with Sincheonji skyrocketed. On March 6, 2020, the number of confirmed cases was 6284, with 42 dead. This study, through collecting epidemiological data about various COVID-19 infection cases, discovered that getting together in large groups leads to mass infection, and that paying close attention to personal hygiene by means of wearing masks, sanitary gloves, etc., can prevent the spread of COVID-19. Additional epidemiological data and related studies on COVID-19 infections in South Korea are likely to support or slightly modify this conclusion. However, this study is significant in that it emphasizes the precautionary principle in preventing and managing infectious diseases, and has a suggestion for public health policies, which are currently in high demand.

scholarly journals Revealing the influence of national public health policies for the outbreak of the SARS-CoV-2 epidemic in Wuhan, China through status dynamic modeling

2020 ◽  
Author(s):  
Tianyi Qiu ◽  
Han Xiao
Keyword(s):  
Public Health ◽  
Real Time ◽  
Dynamic Model ◽  
Health Policies ◽  
Chinese Government ◽  
Wuhan City ◽  
Public Health Policies ◽  
Infected People ◽  
End Point ◽  
National Public Health

SummaryBackgroundThe epidemic caused by SARS-CoV-2 was first reported in Wuhan, China, and now is spreading worldwide. The Chinese government responded to this epidemic with multiple public health policies including locking down the city of Wuhan, establishing multiple temporary hospitals, and prohibiting public gathering events. Here, we constructed a new real-time status dynamic model of SEIO (MH) to reveal the influence of national public health policies and to model the epidemic in Wuhan.MethodsA real-time status dynamic model was proposed to model the population of Wuhan in status Susceptible (S), Exposed (E), Infected with symptoms (I), with Medical care (M), and Out of the system (O) daily. Model parameters were fitted according to the daily report of new infections from Jan. 27th, 2020 to Feb. 2nd, 2020. Using the fitted parameters, the epidemic under different conditions was simulated and compared with the current situation.FindingAccording to our study, the first patient is most likely appeared on Nov. 29th, 2019. There had already been 4,153 infected people and 6,536 exposed ones with the basic reproduction number R0 of 2.65 before lockdown, whereas R0 dropped to 1.98 for the first 30 days after the lockdown. The peak point is Feb. 17th, 2020 with 24,115 infected people and the end point is Jun. 17th, 2020. In total, 77,453 people will be infected. If lockdown imposed 7 days earlier, the total number of infected people would be 21,508, while delaying the lockdown by 1-6 days would expand the infection scale 1.23 to 4.94 times. A delay for 7 days would make the epidemic finally out of control. Doubling the number of beds in hospitals would decrease the total infections by 28%, and further investment in bed numbers would yield a diminishing return. Last, public gathering events that increased the transmission parameter by 5% in one single day would increase 4,243 infected people eventually.InterpretationOur model forecasted that the peak time in Wuhan was Feb. 17th, 2020 and the epidemic in Wuhan is now under control. The outbreak of SARS-CoV-2 is currently a global public health threat for all nations. Multiple countries including South Korea, Japan, Iran, Italy, and the United States are suffering from SARS-CoV-2. Our study, which simulated the epidemic in Wuhan, the first city in the world fighting against SARS-CoV-2, may provide useful guidance for other countries in dealing with similar situations.FundingNational Natural Science Foundation of China (31900483) and Shanghai Sailing program (19YF1441100).Research in contextEvidence before this studyThe epidemic of SARS-CoV-2 has been currently believed to started from Wuhan, China. The Chinese government started to report the data including infected, cured and dead since Jan 20th, 2020. We searched PubMed and preprint archives for articles published up to Feb 28th, 2020, which contained information about the Wuhan outbreak using the terms of “SARS-CoV-2”, “2019-nCoV”, “COVID-19”, “public health policies”, “coronavirus”, “CoV”, “Wuhan”, “transmission model”, etc. And a number of articles were found to forecast the early dynamics of the SARS-CoV-2 epidemic and clinical characteristics of COVID-19. Several of them mentioned the influence of city lockdown, whereas lacked research focused on revealing the impact of public health policies for the outbreak of SARS-CoV-2 through modeling study.Added value of this studyAs the first study systemically analysis the effect of three major public health policies including 1) lockdown of Wuhan City, 2) construction of temporary hospitals and 3) reduction of crowed gathering events in Wuhan city. The results demonstrated the epidemic in Wuhan from the potential first patient to the end point as well as the influence of public health policies are expected to provide useful guidance for other countries in fighting against the epidemic of SRAS-CoV-2.Implications of all the available evidenceAvailable evidence illustrated the human-to-human transmission of SARS-CoV-2, in which the migration of people in China during the epidemic may quickly spread the epidemic to the rest of the nation. These findings also suggested that the lockdown of Wuhan city may slow down the spread of the epidemic in the rest of China.

scholarly journals Epidemiological observations on breaking COVID-19 transmission: from the experience of Taiwan

2021 ◽  
pp. jech-2020-216240
Author(s):  
Iona MacDonald ◽  
Jye-Lin Hsu
Keyword(s):  
Public Health ◽  
Infectious Diseases ◽  
Epidemiological Data ◽  
Health Policies ◽  
Minimal Impact ◽  
Public Health Policies ◽  
The Usa ◽  
The Government ◽  
Effective Public Health ◽  
Ongoing Monitoring

With almost no community-transmitted cases and without any complete lockdown throughout 2020, Taiwan is one of very few countries worldwide that has recorded minimal impact from the COVID-19 pandemic attack. This is despite being only 130 km from China and having frequent business communications with that country, where COVID-19 first emerged. At the end of December 2020, Taiwan had recorded just 873 cases and 7 deaths, in a country of around 24 million people. How to determine the effectiveness of public health policies is an important issue that must be resolved, especially in those countries that have experienced few cases of community-transmitted COVID-19. Our analysis of epidemiological data in Taiwan relating to influenza-like illness (ILI), enterovirus and diarrhoea from the past 3 years reveals dramatic reductions in the incidence of ILI and enterovirus in 2020, compared with 2018 and 2019. These reductions occurred within 2 weeks of the government issuing public health policies for COVID-19 and indicate that such policies can effectively reduce infectious diseases overall. In contrast, no such reduction in ILI activity was observed in 2020 after the first COVID-19 case was reported in the USA. We suggest that infectious diseases data can be used to inform effective public health policies needed to break the transmission chain of COVID-19 and that ongoing monitoring of infectious diseases data can provide confidence about nationwide health.

scholarly journals Modeling the impact of public response on the COVID-19 pandemic in Ontario

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0249456
Author(s):  
Brydon Eastman ◽  
Cameron Meaney ◽  
Michelle Przedborski ◽  
Mohammad Kohandel
Keyword(s):  
Public Health ◽  
Reproduction Number ◽  
Transmission Rate ◽  
Epidemiological Data ◽  
Health Policies ◽  
Machine Learning Techniques ◽  
Model Parameters ◽  
Public Health Policies ◽  
Variable Transmission ◽  
The Impact

The outbreak of SARS-CoV-2 is thought to have originated in Wuhan, China in late 2019 and has since spread quickly around the world. To date, the virus has infected tens of millions of people worldwide, compelling governments to implement strict policies to counteract community spread. Federal, provincial, and municipal governments have employed various public health policies, including social distancing, mandatory mask wearing, and the closure of schools and businesses. However, the implementation of these policies can be difficult and costly, making it imperative that both policy makers and the citizenry understand their potential benefits and the risks of non-compliance. In this work, a mathematical model is developed to study the impact of social behaviour on the course of the pandemic in the province of Ontario. The approach is based upon a standard SEIRD model with a variable transmission rate that depends on the behaviour of the population. The model parameters, which characterize the disease dynamics, are estimated from Ontario COVID-19 epidemiological data using machine learning techniques. A key result of the model, following from the variable transmission rate, is the prediction of the occurrence of a second wave using the most current infection data and disease-specific traits. The qualitative behaviour of different future transmission-reduction strategies is examined, and the time-varying reproduction number is analyzed using existing epidemiological data and future projections. Importantly, the effective reproduction number, and thus the course of the pandemic, is found to be sensitive to the adherence to public health policies, illustrating the need for vigilance as the economy continues to reopen.

scholarly journals Population simulations of COVID-19 outbreaks provide tools for risk assessment and continuity planning

JAMIA Open ◽  
2021 ◽  
Author(s):  
Bo Peng ◽  
Rowland W Pettit ◽  
Christopher I Amos
Keyword(s):  
Public Health ◽  
Risk Assessment ◽  
Emergency Response ◽  
Robustness Analysis ◽  
Health Policies ◽  
Command Line ◽  
Public Health Policies ◽  
Continuity Planning ◽  
Quantitative Estimates ◽  
Community Infection

Abstract Objectives We developed COVID-19 Outbreak Simulator (https://ictr.github.io/covid19-outbreak-simulator/) to quantitatively estimate the effectiveness of preventative and interventive measures to prevent and battle COVID-19 outbreaks for specific populations. Materials and methods Our simulator simulates the entire course of infection and transmission of the virus among individuals in heterogeneous populations, subject to operations and influences, such as quarantine, testing, social distancing, and community infection. It provides command-line and Jupyter notebook interfaces and a plugin system for user-defined operations. Results The simulator provides quantitative estimates for COVID-19 outbreaks in a variety of scenarios and assists the development of public health policies, risk-reduction operations, and emergency response plans. Discussion Our simulator is powerful, flexible, and customizable, although successful applications require realistic estimation and robustness analysis of population-specific parameters. Conclusion Risk assessment and continuity planning for COVID-19 outbreaks are crucial for the continued operation of many organizations. Our simulator will be continuously expanded to meet this need.

scholarly journals Characterization of death from colorectal cancer in Mato Grosso State/Legal Amazon/Brazil, 2000-2016

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
R S Caló ◽  
B S N Souza ◽  
N D Galvão ◽  
R A G Souza ◽  
J C S Oliveira ◽  
...  
Keyword(s):  
Public Health ◽  
Colorectal Cancer ◽  
International Classification Of Diseases ◽  
Health Policies ◽  
Rectosigmoid Junction ◽  
Mato Grosso ◽  
Public Health Policies ◽  
Goods And Services ◽  
Classification Of Diseases ◽  
Using Data

Abstract Background Colorectal cancer has been one of the cancers that most contributed to mortality, in both sexes in the world. In Brazil, cancer is among the top five causes of death and colorectal cancer is ranked on the fifth position. Of the Federative Units belonging to the Legal Amazon, Mato Grosso stands out for the higher adjusted incidence of colorectal cancer for both sexes. Thus, the objective is to characterize deaths from colorectal cancer, according to sociodemographic variables in Mato Grosso from 2000 to 2016. Methods A descriptive study was carried out, using data from the Mortality Information System, made available by the Department of Health of the Mato Grosso State. Deaths of all ages were selected, whose basic cause was identified by the codes from the International Classification of Diseases: (C.18) colon cancer, (C.19) rectosigmoid junction cancer, (C.20) rectal cancer or (C.21) anus cancer. Results Between 2000 and 2016, 31,607 deaths from cancer were registered. Of these, 1,750 (5.6%) were due to colorectal cancer. An increased number of deaths was observed at the end of the period, with a variation from 46 deaths in 2000 from 173 in 2016. Highest frequency was verified in men (51.3%), people aged 60 years or older (59.7%), black (54.6%), married (52.3%) and those with primary education (55.2%). According to Brazilian occupation classification options or those answers filled out on the death certificate, highest frequency were for “Retired” (26.2%), “Housewife” (23.1%), Agricultural/Forestry and Fisheries” (11.3%) and “Production of Industrial Goods and Services” (10.3%). Conclusions This study evidenced the increased number of deaths due to colorectal cancer in Mato Grosso State, and identified priority groups for interventions through public health policies which should include screening and early diagnosis to cope with the disease. Key messages Evidenced the increased number of deaths due to colorectal cancer in Mato Grosso State. Identified priority groups for interventions through public health policies.

Epidemiological surveillance and performance assessment: the two roles of health indicators during the COVID-19 pandemic

2021 ◽  
Vol 17 (2) ◽  
pp. 186-203
Author(s):  
Nathan Genicot
Keyword(s):  
Public Health ◽  
Performance Assessment ◽  
Health Indicators ◽  
Health Policies ◽  
Epidemiological Surveillance ◽  
Public Health Policies ◽  
History Of ◽  
And Performance ◽  
The One ◽  
Massive Development

AbstractThe COVID-19 pandemic has given rise to the massive development and use of health indicators. Drawing on the history of international public health and of the management of infectious disease, this paper attempts to show that the normative power acquired by metrics during the pandemic can be understood in light of two rationales: epidemiological surveillance and performance assessment. On the one hand, indicators are established to evaluate and rank countries’ responses to the outbreak; on the other, the evolution of indicators has a direct influence on the content of public health policies. Although quantitative data are an absolute necessity for coping with such disasters, it is critical to bear in mind the inherent partiality and precarity of the information provided by health indicators. Given the growing importance of normative quantitative devices during the pandemic, and assuming that their influence is unlikely to decrease in the future, they call for close scrutiny.

scholarly journals A Strong Seasonality Pattern for Covid-19 Incidence Rates Modulated by UV Radiation Levels

Viruses ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 574
Author(s):  
Christos Karapiperis ◽  
Panos Kouklis ◽  
Stelios Papastratos ◽  
Anastasia Chasapi ◽  
Antoine Danchin ◽  
...  
Keyword(s):  
Public Health ◽  
Uv Radiation ◽  
Initial Conditions ◽  
Face Mask ◽  
Incidence Rates ◽  
Personal Hygiene ◽  
Public Health Policies ◽  
Community Transmission ◽  
Nonpharmaceutical Interventions ◽  
Strong Seasonality

The Covid-19 pandemic has required nonpharmaceutical interventions, primarily physical distancing, personal hygiene and face mask use, to limit community transmission, irrespective of seasons. In fact, the seasonality attributes of this pandemic remain one of its biggest unknowns. Early studies based on past experience from respiratory diseases focused on temperature or humidity, with disappointing results. Our hypothesis that ultraviolet (UV) radiation levels might be a factor and a more appropriate parameter has emerged as an alternative to assess seasonality and exploit it for public health policies. Using geographical, socioeconomic and epidemiological criteria, we selected twelve North-equatorial-South countries with similar characteristics. We then obtained UV levels, mobility and Covid-19 daily incidence rates for nearly the entire 2020. Using machine learning, we demonstrated that UV radiation strongly associated with incidence rates, more so than mobility did, indicating that UV is a key seasonality indicator for Covid-19, irrespective of the initial conditions of the epidemic. Our findings can inform the implementation of public health emergency measures, partly based on seasons in the Northern and Southern Hemispheres, as the pandemic unfolds into 2021.

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