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1.
Epidemiol Health ; 42: e2020045, 2020.
Article in English | MEDLINE | ID: covidwho-2267694

ABSTRACT

OBJECTIVE: In 2020, the coronavirus disease 2019 (COVID-19) respiratory infection is spreading in Korea. In order to prevent the spread of an infectious disease, infected people must be quickly identified and isolated, and contact with the infected must be blocked early. This study attempted to verify the intervention effects on the spread of an infectious disease by using these measures in a mathematical model. METHODS: We used the susceptible-infectious-recovery (SIR) model for a virtual population group connected by a special structured network. In the model, the infected state (I) was divided into I in which the infection is undetected and Ix in which the infection is detected. The probability of transitioning from an I state to Ix can be viewed as the rate at which an infected person is found. We assumed that only those connected to each other in the network can cause infection. In addition, this study attempted to evaluate the effects of isolation by temporarily removing the connection among these people. RESULTS: In Scenario 1, only the infected are isolated; in Scenario 2, those who are connected to an infected person and are also found to be infected are isolated as well. In Scenario 3, everyone connected to an infected person are isolated. In Scenario 3, it was possible to effectively suppress the infectious disease even with a relatively slow rate of diagnosis and relatively high infection rate. CONCLUSION: During the epidemic, quick identification of the infected is helpful. In addition, it was possible to quantitatively show through a simulation evaluation that the management of infected individuals as well as those who are connected greatly helped to suppress the spread of infectious diseases.


Subject(s)
Clinical Laboratory Techniques/statistics & numerical data , Coronavirus Infections/diagnosis , Coronavirus Infections/prevention & control , Epidemics/prevention & control , Pandemics/prevention & control , Patient Isolation/statistics & numerical data , Pneumonia, Viral/diagnosis , Pneumonia, Viral/prevention & control , COVID-19 , COVID-19 Testing , Coronavirus Infections/epidemiology , Coronavirus Infections/transmission , Humans , Models, Theoretical , Pneumonia, Viral/epidemiology , Pneumonia, Viral/transmission , Republic of Korea/epidemiology
2.
Medicine (Baltimore) ; 100(28): e26634, 2021 Jul 16.
Article in English | MEDLINE | ID: covidwho-1494087

ABSTRACT

ABSTRACT: Emergency departments (EDs) are on the frontline of the coronavirus disease (COVID-19) outbreak. To resolve the abrupt overloading of COVID-19-suspected patients in a community, each ED needs to respond in various ways. In our hospital, we increased the isolation beds through temporary remodeling and by performing in-hospital COVID-19 polymerase chain reaction testing rather than outsourcing them. The aim of this study was to verify the effects of our response to the newly developed viral outbreak.The medical records of patients who presented to an ED were analyzed retrospectively. We divided the study period into 3: pre-COVID-19, transition period of response (the period before fully implementing the response measures), and post-response (the period after complete response). We compared the parameters of the National Emergency Department Information System and information about isolation and COVID-19.The number of daily ED patients was 86.8 ±â€Š15.4 in the pre-COVID-19, 36.3 ±â€Š13.6 in the transition period, and 67.2 ±â€Š10.0 in the post-response period (P < .001). The lengths of stay in the ED were significantly higher in transition period than in the other periods [pre-COVID-19 period, 219.0 (121.0-378.0) min; transition period, 301 (150.0-766.5) min; post-response period, 281.0 (114.0-575.0) min; P < .001]. The ratios of use of an isolation room and fever (≥37.5°C) were highest in the post-response period [use of isolation room: pre-COVID-19 period, 0.6 (0.7%); transition period, 1.2 (3.3%); post-response period, 16.1 (24.0%); P < .001; fever: pre-COVID-19 period, 14.8(17.3%); transition period, 6.8 (19.1%); post-response period, 14.5 (21.9%), P < .001].During an outbreak of a novel infectious disease, increasing the number of isolation rooms in the ED and applying a rapid confirmation test would enable the accommodation of more suspected patients, which could help reduce the risk posed to the community and thus prevent strain on the local emergency medical system.


Subject(s)
COVID-19 , Disease Outbreaks/statistics & numerical data , Emergency Medical Services/statistics & numerical data , Emergency Service, Hospital/statistics & numerical data , Infection Control/statistics & numerical data , Adult , Aged , Continuity of Patient Care/statistics & numerical data , Female , Humans , Male , Middle Aged , Patient Isolation/statistics & numerical data , Republic of Korea , Retrospective Studies , SARS-CoV-2
3.
PLoS One ; 16(7): e0254012, 2021.
Article in English | MEDLINE | ID: covidwho-1311284

ABSTRACT

BACKGROUND: In response to the spread of the coronavirus disease 2019 (COVID-19), plenty of control measures were proposed. To assess the impact of current control measures on the number of new case indices 14 countries with the highest confirmed cases, highest mortality rate, and having a close relationship with the outbreak's origin; were selected and analyzed. METHODS: In the study, we analyzed the impact of five control measures, including centralized isolation of all confirmed cases, closure of schools, closure of public areas, closure of cities, and closure of borders of the 14 targeted countries according to their timing; by comparing its absolute effect average, its absolute effect cumulative, and its relative effect average. RESULTS: Our analysis determined that early centralized isolation of all confirmed cases was represented as a core intervention in significantly disrupting the pandemic's spread. This strategy helped in successfully controlling the early stage of the outbreak when the total number of cases were under 100, without the requirement of the closure of cities and public areas, which would impose a negative impact on the society and its economy. However, when the number of cases increased with the apparition of new clusters, coordination between centralized isolation and non-pharmaceutical interventions facilitated control of the crisis efficiently. CONCLUSION: Early centralized isolation of all confirmed cases should be implemented at the time of the first detected infectious case.


Subject(s)
COVID-19/prevention & control , Patient Isolation/statistics & numerical data , Quarantine/statistics & numerical data , COVID-19/transmission , Disease Notification/statistics & numerical data , Disease Transmission, Infectious/statistics & numerical data , Humans , Models, Statistical
4.
Infect Control Hosp Epidemiol ; 42(3): 344-347, 2021 03.
Article in English | MEDLINE | ID: covidwho-1131957

ABSTRACT

We describe an approach to the evaluation and isolation of hospitalized persons under investigation (PUIs) for coronavirus disease 2019 (COVID-19) at a large US academic medical center. Only a small proportion (2.9%) of PUIs with 1 or more repeated severe acute respiratory coronavirus virus 2 (SARS-CoV-2) nucleic acid amplification tests (NAATs) after a negative NAAT were diagnosed with COVID-19.


Subject(s)
COVID-19 Testing/statistics & numerical data , COVID-19/diagnosis , Patient Isolation/statistics & numerical data , Practice Patterns, Physicians'/standards , Academic Medical Centers , Boston , Communicable Disease Control/methods , Hospitalization , Humans , Nucleic Acid Amplification Techniques , Practice Patterns, Physicians'/organization & administration , Retrospective Studies , SARS-CoV-2
6.
J Med Syst ; 45(4): 42, 2021 Feb 19.
Article in English | MEDLINE | ID: covidwho-1092039

ABSTRACT

In confronting the sudden epidemic of COVID-19, China and other countries have been under great deal of pressure to block virus transmission and reduce death cases. Fangcang shelter hospital, which is converted from large-scale public venue, is proposed and proven to be an effective way for administering medical care and social isolation. This paper presents the practice in information technology support for a Fangcang shelter hospital in Wuhan, China. The experiences include the deployment strategy of IT infrastructure, the redesign of function modules in the hospital information system (HIS), equipment maintenance and medical staff training. The deployment strategy and HIS modules have ensured smoothness and efficiency of clinical work. The team established a quick response mechanism and adhered to the principle of nosocomial infection control. Deployment of network and modification of HIS was finished in the 48 hours before patient admittance. A repair hotline and remote support for equipment and software were available whenever medical workers met with any questions. No engineer ever entered the contaminated areas and no one was infected by the coronavirus during the hospital operation. Up to now, Fangcang shelter hospital is adopted by many regions around the world facing the collapse of their medical systems. This valuable experience in informatization construction and service in Wuhan may help participators involving in Fangcang shelter hospital get better information technology support, and find more practical interventions to fight the epidemic.


Subject(s)
COVID-19/therapy , Emergency Shelter/organization & administration , Hospitals, Special/organization & administration , Mobile Health Units/organization & administration , Patient Isolation/statistics & numerical data , COVID-19/epidemiology , China , Emergencies , Facility Design and Construction , Hospitals, Isolation , Humans , Information Technology , Risk Factors
7.
Int J Health Policy Manag ; 9(11): 475-483, 2020 11 01.
Article in English | MEDLINE | ID: covidwho-1068326

ABSTRACT

BACKGROUND: Allocation of adequate healthcare facilities is one of the most important factors that public health policymakers consider when preparing for infectious disease outbreaks. Negative pressure isolation rooms (NPIRs) are one of the critical resources for control of infectious respiratory diseases, such as the novel coronavirus disease 2019 (COVID-19) outbreak. However, there is insufficient attention to efficient allocation of NPIR-equipped hospitals. METHODS: We aim to explore any insufficiency and spatial disparity of NPIRs in South Korea in response to infectious disease outbreaks based on a simple analytic approach. We examined the history of installing NPIRs in South Korea between the severe acute respiratory syndrome (SARS) outbreak in 2003 and the Middle East respiratory syndrome coronavirus (MERS-Cov) in 2015 to evaluate the allocation process and spatial distribution of NPIRs across the country. Then, for two types of infectious diseases (a highly contagious disease like COVID-19 vs. a hospital-based transmission like MERS-Cov), we estimated the level of disparity between NPIR capacity and demand at the sub-regional level in South Korea by applying the two-step floating catchment area (2SFCA) method. RESULTS: Geospatial information system (GIS) mapping reveals a substantial shortage and misallocation of NPIRs, indicating that the Korean government should consider a simple but evidence-based spatial method to identify the areas that need NPIRs most and allocate funds wisely. The 2SFCA method suggests that, despite the recent addition of NPIRs across the country, there should still be more NPIRs regardless of the spread pattern of the disease. It also illustrates high levels of regional disparity in allocation of those facilities in preparation for an infectious disease, due to the lack of evidence-based approach. CONCLUSION: These findings highlight the importance of evidence-based decision-making processes in allocating public health facilities, as misallocation of facilities could impede the responsiveness of the public health system during an epidemic. This study provides some evidence to be used to allocate the resources for NPIRs, the urgency of which is heightened in the face of rapidly evolving threats from the novel COVID-19 outbreak.


Subject(s)
COVID-19/therapy , Health Care Rationing/methods , Hospitals/statistics & numerical data , Patient Isolation/methods , Patient Isolation/statistics & numerical data , COVID-19/prevention & control , Coronavirus Infections/prevention & control , Coronavirus Infections/therapy , Disease Outbreaks , Humans , Republic of Korea , SARS-CoV-2
8.
J Prim Care Community Health ; 12: 2150132720987711, 2021.
Article in English | MEDLINE | ID: covidwho-1060256

ABSTRACT

SARS-CoV-2 initially emerged in Wuhan, China in late 2019. It has since been recognized as a pandemic and has led to great social and economic disruption globally. The Reverse Transcriptase Real-Time Polymerase Chain Reaction (rtRT-PCR) has become the primary method for COVID-19 testing worldwide. The method requires a specialized laboratory set up. Long-term persistence of SARS-CoV-2 RNA in nasopharyngeal secretion after full clinical recovery of the patient is regularly observed nowadays. This forces the patients to spend a longer period in isolation and test repeatedly to obtain evidence of viral clearance. Repeated COVID-19 testing in asymptomatic or mildly symptomatic cases often leads to extra workload for laboratories that are already struggling with a high specimen turnover. Here, we present 5 purposively selected cases with different patterns of clinical presentations in which nasopharyngeal shedding of SARS-CoV-2 RNA was observed in patients for a long time. From these case studies, we emphasized the adoption of a symptom-based approach for discontinuing transmission-based precautions over a test-based strategy to reduce the time spent by asymptomatic and mildly symptomatic COVID-19 patients in isolation. A symptom-based approach will also help reduce laboratory burden for COVID-19 testing as well as conserve valuable resources and supplies utilized for rtRT-PCR testing in an emerging lower-middle-income setting. Most importantly, it will also make room for critically ill COVID-19 patients to visit or avail COVID-19 testing at their convenience.


Subject(s)
COVID-19 Testing/methods , COVID-19/diagnosis , Health Care Rationing/methods , Symptom Assessment , Adult , COVID-19/complications , COVID-19 Testing/statistics & numerical data , Developing Countries , Female , Humans , Laboratories/statistics & numerical data , Male , Patient Isolation/statistics & numerical data , RNA, Viral/isolation & purification , Reverse Transcriptase Polymerase Chain Reaction , SARS-CoV-2/genetics , SARS-CoV-2/isolation & purification , Young Adult
10.
Cochrane Database Syst Rev ; 8: CD013699, 2020 08 18.
Article in English | MEDLINE | ID: covidwho-777340

ABSTRACT

BACKGROUND: Reducing the transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a global priority. Contact tracing identifies people who were recently in contact with an infected individual, in order to isolate them and reduce further transmission. Digital technology could be implemented to augment and accelerate manual contact tracing. Digital tools for contact tracing may be grouped into three areas: 1) outbreak response; 2) proximity tracing; and 3) symptom tracking. We conducted a rapid review on the effectiveness of digital solutions to contact tracing during infectious disease outbreaks. OBJECTIVES: To assess the benefits, harms, and acceptability of personal digital contact tracing solutions for identifying contacts of an identified positive case of an infectious disease. SEARCH METHODS: An information specialist searched the literature from 1 January 2000 to 5 May 2020 in CENTRAL, MEDLINE, and Embase. Additionally, we screened the Cochrane COVID-19 Study Register. SELECTION CRITERIA: We included randomised controlled trials (RCTs), cluster-RCTs, quasi-RCTs, cohort studies, cross-sectional studies and modelling studies, in general populations. We preferentially included studies of contact tracing during infectious disease outbreaks (including COVID-19, Ebola, tuberculosis, severe acute respiratory syndrome virus, and Middle East respiratory syndrome) as direct evidence, but considered comparative studies of contact tracing outside an outbreak as indirect evidence. The digital solutions varied but typically included software (or firmware) for users to install on their devices or to be uploaded to devices provided by governments or third parties. Control measures included traditional or manual contact tracing, self-reported diaries and surveys, interviews, other standard methods for determining close contacts, and other technologies compared to digital solutions (e.g. electronic medical records). DATA COLLECTION AND ANALYSIS: Two review authors independently screened records and all potentially relevant full-text publications. One review author extracted data for 50% of the included studies, another extracted data for the remaining 50%; the second review author checked all the extracted data. One review author assessed quality of included studies and a second checked the assessments. Our outcomes were identification of secondary cases and close contacts, time to complete contact tracing, acceptability and accessibility issues, privacy and safety concerns, and any other ethical issue identified. Though modelling studies will predict estimates of the effects of different contact tracing solutions on outcomes of interest, cohort studies provide empirically measured estimates of the effects of different contact tracing solutions on outcomes of interest. We used GRADE-CERQual to describe certainty of evidence from qualitative data and GRADE for modelling and cohort studies. MAIN RESULTS: We identified six cohort studies reporting quantitative data and six modelling studies reporting simulations of digital solutions for contact tracing. Two cohort studies also provided qualitative data. Three cohort studies looked at contact tracing during an outbreak, whilst three emulated an outbreak in non-outbreak settings (schools). Of the six modelling studies, four evaluated digital solutions for contact tracing in simulated COVID-19 scenarios, while two simulated close contacts in non-specific outbreak settings. Modelling studies Two modelling studies provided low-certainty evidence of a reduction in secondary cases using digital contact tracing (measured as average number of secondary cases per index case - effective reproductive number (R eff)). One study estimated an 18% reduction in R eff with digital contact tracing compared to self-isolation alone, and a 35% reduction with manual contact-tracing. Another found a reduction in R eff for digital contact tracing compared to self-isolation alone (26% reduction) and a reduction in R eff for manual contact tracing compared to self-isolation alone (53% reduction). However, the certainty of evidence was reduced by unclear specifications of their models, and assumptions about the effectiveness of manual contact tracing (assumed 95% to 100% of contacts traced), and the proportion of the population who would have the app (53%). Cohort studies Two cohort studies provided very low-certainty evidence of a benefit of digital over manual contact tracing. During an Ebola outbreak, contact tracers using an app found twice as many close contacts per case on average than those using paper forms. Similarly, after a pertussis outbreak in a US hospital, researchers found that radio-frequency identification identified 45 close contacts but searches of electronic medical records found 13. The certainty of evidence was reduced by concerns about imprecision, and serious risk of bias due to the inability of contact tracing study designs to identify the true number of close contacts. One cohort study provided very low-certainty evidence that an app could reduce the time to complete a set of close contacts. The certainty of evidence for this outcome was affected by imprecision and serious risk of bias. Contact tracing teams reported that digital data entry and management systems were faster to use than paper systems and possibly less prone to data loss. Two studies from lower- or middle-income countries, reported that contact tracing teams found digital systems simpler to use and generally preferred them over paper systems; they saved personnel time, reportedly improved accuracy with large data sets, and were easier to transport compared with paper forms. However, personnel faced increased costs and internet access problems with digital compared to paper systems. Devices in the cohort studies appeared to have privacy from contacts regarding the exposed or diagnosed users. However, there were risks of privacy breaches from snoopers if linkage attacks occurred, particularly for wearable devices. AUTHORS' CONCLUSIONS: The effectiveness of digital solutions is largely unproven as there are very few published data in real-world outbreak settings. Modelling studies provide low-certainty evidence of a reduction in secondary cases if digital contact tracing is used together with other public health measures such as self-isolation. Cohort studies provide very low-certainty evidence that digital contact tracing may produce more reliable counts of contacts and reduce time to complete contact tracing. Digital solutions may have equity implications for at-risk populations with poor internet access and poor access to digital technology. Stronger primary research on the effectiveness of contact tracing technologies is needed, including research into use of digital solutions in conjunction with manual systems, as digital solutions are unlikely to be used alone in real-world settings. Future studies should consider access to and acceptability of digital solutions, and the resultant impact on equity. Studies should also make acceptability and uptake a primary research question, as privacy concerns can prevent uptake and effectiveness of these technologies.


Subject(s)
Contact Tracing/methods , Disease Outbreaks/prevention & control , Mobile Applications/statistics & numerical data , Botswana/epidemiology , COVID-19/epidemiology , COVID-19/prevention & control , Cohort Studies , Contact Tracing/instrumentation , Coronavirus Infections/epidemiology , Hemorrhagic Fever, Ebola/epidemiology , Hemorrhagic Fever, Ebola/prevention & control , Humans , Models, Theoretical , Patient Isolation/statistics & numerical data , Privacy , Quarantine/statistics & numerical data , Secondary Prevention/methods , Secondary Prevention/statistics & numerical data , Sierra Leone/epidemiology , Tuberculosis/epidemiology , Tuberculosis/prevention & control , United States/epidemiology , Whooping Cough/epidemiology , Whooping Cough/prevention & control
11.
Math Biosci Eng ; 17(4): 4165-4183, 2020 06 15.
Article in English | MEDLINE | ID: covidwho-750588

ABSTRACT

In this paper we develop a compartmental epidemic model to study the transmission dynamics of the COVID-19 epidemic outbreak, with Mexico as a practical example. In particular, we evaluate the theoretical impact of plausible control interventions such as home quarantine, social distancing, cautious behavior and other self-imposed measures. We also investigate the impact of environmental cleaning and disinfection, and government-imposed isolation of infected individuals. We use a Bayesian approach and officially published data to estimate some of the model parameters, including the basic reproduction number. Our findings suggest that social distancing and quarantine are the winning strategies to reduce the impact of the outbreak. Environmental cleaning can also be relevant, but its cost and effort required to bring the maximum of the outbreak under control indicate that its cost-efficacy is low.


Subject(s)
Betacoronavirus , Coronavirus Infections/transmission , Models, Biological , Pandemics , Pneumonia, Viral/transmission , Basic Reproduction Number/statistics & numerical data , Bayes Theorem , COVID-19 , Computer Simulation , Coronavirus Infections/epidemiology , Coronavirus Infections/prevention & control , Disinfection/statistics & numerical data , Epidemics/prevention & control , Epidemics/statistics & numerical data , Humans , Infection Control/methods , Infection Control/statistics & numerical data , Mathematical Concepts , Mexico/epidemiology , Pandemics/prevention & control , Pandemics/statistics & numerical data , Patient Isolation/statistics & numerical data , Pneumonia, Viral/epidemiology , Pneumonia, Viral/prevention & control , Quarantine/statistics & numerical data , SARS-CoV-2
12.
Emerg Med Australas ; 32(6): 1034-1039, 2020 12.
Article in English | MEDLINE | ID: covidwho-713982

ABSTRACT

OBJECTIVE: The number of patients with suspected COVID-19 presenting to Australian EDs continues to impose a burden on healthcare services. Isolation is an important aspect of infection prevention and control, but has been associated with undesirable consequences among hospital inpatients. The aim of the present study was to determine if isolation is associated with an increased length of stay (LOS) in the ED. METHODS: The Registry for Emergency Care Project is a prospective cohort study with a series of nested sub-studies. The present study was a retrospective analysis of adult patients allocated an Australasian Triage Scale category of 1 or 2 who presented to a tertiary ED between 18 and 31 May 2020. The primary outcome was ED LOS. Regression methods were used to determine the independent association between ED isolation and LOS. RESULTS: There were 447 patients who met inclusion criteria, of which 123 (28%) were managed in isolation. The median (interquartile range) ED LOS was 259 (210-377) min for the isolation group and 204 (126-297) min for the non-isolation group, a difference in median ED LOS of 55 min (P < 0.001). Isolation was independently associated with a 23% increase in ED LOS (P = 0.002) and doubled the odds of an ED stay of more than 4 h (adjusted odds ratio 2.2 [1.4-3.4], P = 0.001). CONCLUSION: Consistent with the anecdotal experience of Australian ED clinicians, the present study demonstrated an increased ED LOS for patients managed in isolation. Enhanced infection prevention and control precautions will be required during and beyond the current pandemic, creating significant ongoing challenges for emergency care systems.


Subject(s)
Coronavirus Infections/epidemiology , Emergency Service, Hospital/statistics & numerical data , Length of Stay/statistics & numerical data , Patient Isolation/statistics & numerical data , Pneumonia, Viral/epidemiology , Australia/epidemiology , COVID-19 , Female , Humans , Male , Middle Aged , Pandemics , Registries , Retrospective Studies
13.
Eur J Pediatr ; 179(12): 1949-1955, 2020 Dec.
Article in English | MEDLINE | ID: covidwho-695417

ABSTRACT

Since February 21, 2020, SARS-CoV-2 has spread exponentially worldwide. Neonatal patients needing intensive care are considered a vulnerable population. To report the results of a policy based on multi-timepoint surveillance for SARS-CoV-2 of all neonates admitted to the neonatal intensive care unit (NICU), their parents, and all healthcare providers in a part of Italy with a high prevalence of the infection. Observational study conducted from 21 February to 21 April 2020. Intervention consisted of (a) parental triage on arrival at the neonatal ward; (b) universal testing with nasopharyngeal swabs and blood testing for SARS-CoV-2 IgM and IgG antibodies; (c) use of continuous personal protective equipment at the NICU by parents and staff. A total of 6726 triage procedures were performed on 114 parents, and 954 nasopharyngeal swabs were collected from 226 individuals. Five (2.2%) asymptomatic individuals (2 parents and 3 healthcare providers) tested positive on nasopharyngeal swabs and were kept isolated for 14 days. Of 75 admitted newborn, no one tested positive on nasopharyngeal swabs or antibody tests. Three parents presented with fever or flu-like symptoms at triage; they tested negative on swabs.Conclusion: With universal screening of neonates, parents, and staff, there were no cases of SARS-CoV-2 infection among the neonates admitted to a NICU in an area with a high incidence of SARS-CoV-2. Our experience could be usefully compared with other strategies with a view to developing future evidence-based guidelines for managing high-risk neonates in case of new epidemics. What is Known: • The novel coronavirus named SARS-CoV-2 has since spread worldwide at a remarkable rate, with more than 2.5 million confirmed cases. • Pediatric population may be less affected from COVID-19 than adult population but infants and newborn babies seem to be more vulnerable to SARS-CoV-2 infection. What is New: • Using an approach based on triage; testing with nasopharyngeal swabs and serology; and use of personal protective equipment, there were no cases of SARS-CoV-2 infection among neonates in a NICU in a high incidence of SARS-CoV-2 area. • Positive and asymptomatic individuals were identified and isolated early allowing the containment of infection's spread among healthcare providers and parents.


Subject(s)
Coronavirus Infections/diagnosis , Disease Transmission, Infectious/prevention & control , Infant, Premature , Infection Control/methods , Intensive Care Units, Neonatal/statistics & numerical data , Neonatal Screening/methods , Pneumonia, Viral/diagnosis , COVID-19 , Coronavirus Infections/epidemiology , Female , Health Personnel/statistics & numerical data , Humans , Infant, Newborn , Italy , Male , Pandemics/prevention & control , Pandemics/statistics & numerical data , Parents , Patient Isolation/statistics & numerical data , Pneumonia, Viral/epidemiology , Prevalence , Risk Assessment , Severe Acute Respiratory Syndrome/diagnosis , Severe Acute Respiratory Syndrome/epidemiology , Triage , Vulnerable Populations
16.
Infect Dis Poverty ; 9(1): 104, 2020 Jul 23.
Article in English | MEDLINE | ID: covidwho-672011

ABSTRACT

From December 25, 2019 to January 31, 2020, 33 cases of the coronavirus disease 2019 (COVID-19) were identified in the Department of Respiratory and Critical Care Medicine of Zhongnan Hospital of Wuhan University, China, yet none of the affiliated HCWs was infected. Here we analyzed the infection control measures used in three different departments in the Zhongnan Hospital of Wuhan University and correlated the measures with the corresponding infection data of HCWs affiliated with these departments. We found that three infection control measures, namely the isolation of the presumed positive patients, the use of facemasks and intensified hand hygiene play important roles in preventing nosocomial transmission of COVID-19.


Subject(s)
Coronavirus Infections/prevention & control , Cross Infection/prevention & control , Hand Hygiene/statistics & numerical data , Health Personnel/statistics & numerical data , Masks/statistics & numerical data , Pandemics/prevention & control , Patient Isolation/statistics & numerical data , Pneumonia, Viral/prevention & control , Adult , Aged , Betacoronavirus/physiology , COVID-19 , China , Coronavirus Infections/transmission , Cross Infection/transmission , Female , Hospitals, University , Humans , Male , Middle Aged , Pneumonia, Viral/transmission , SARS-CoV-2 , Young Adult
17.
JAMA Intern Med ; 180(9): 1156-1163, 2020 09 01.
Article in English | MEDLINE | ID: covidwho-154897

ABSTRACT

Importance: The dynamics of coronavirus disease 2019 (COVID-19) transmissibility are yet to be fully understood. Better understanding of the transmission dynamics is important for the development and evaluation of effective control policies. Objective: To delineate the transmission dynamics of COVID-19 and evaluate the transmission risk at different exposure window periods before and after symptom onset. Design, Setting, and Participants: This prospective case-ascertained study in Taiwan included laboratory-confirmed cases of COVID-19 and their contacts. The study period was from January 15 to March 18, 2020. All close contacts were quarantined at home for 14 days after their last exposure to the index case. During the quarantine period, any relevant symptoms (fever, cough, or other respiratory symptoms) of contacts triggered a COVID-19 test. The final follow-up date was April 2, 2020. Main Outcomes and Measures: Secondary clinical attack rate (considering symptomatic cases only) for different exposure time windows of the index cases and for different exposure settings (such as household, family, and health care). Results: We enrolled 100 confirmed patients, with a median age of 44 years (range, 11-88 years), including 44 men and 56 women. Among their 2761 close contacts, there were 22 paired index-secondary cases. The overall secondary clinical attack rate was 0.7% (95% CI, 0.4%-1.0%). The attack rate was higher among the 1818 contacts whose exposure to index cases started within 5 days of symptom onset (1.0% [95% CI, 0.6%-1.6%]) compared with those who were exposed later (0 cases from 852 contacts; 95% CI, 0%-0.4%). The 299 contacts with exclusive presymptomatic exposures were also at risk (attack rate, 0.7% [95% CI, 0.2%-2.4%]). The attack rate was higher among household (4.6% [95% CI, 2.3%-9.3%]) and nonhousehold (5.3% [95% CI, 2.1%-12.8%]) family contacts than that in health care or other settings. The attack rates were higher among those aged 40 to 59 years (1.1% [95% CI, 0.6%-2.1%]) and those aged 60 years and older (0.9% [95% CI, 0.3%-2.6%]). Conclusions and Relevance: In this study, high transmissibility of COVID-19 before and immediately after symptom onset suggests that finding and isolating symptomatic patients alone may not suffice to contain the epidemic, and more generalized measures may be required, such as social distancing.


Subject(s)
Asymptomatic Infections/epidemiology , Communicable Disease Control/organization & administration , Contact Tracing/methods , Coronavirus Infections , Disease Transmission, Infectious , Pandemics , Pneumonia, Viral , Adult , Betacoronavirus , COVID-19 , Coronavirus Infections/epidemiology , Coronavirus Infections/prevention & control , Coronavirus Infections/transmission , Disease Transmission, Infectious/prevention & control , Disease Transmission, Infectious/statistics & numerical data , Female , Humans , Incidence , Male , Pandemics/prevention & control , Patient Isolation/methods , Patient Isolation/statistics & numerical data , Pneumonia, Viral/epidemiology , Pneumonia, Viral/prevention & control , Pneumonia, Viral/transmission , Prospective Studies , Risk Assessment , Risk Factors , SARS-CoV-2 , Taiwan/epidemiology
18.
Emerg Infect Dis ; 26(8): 1740-1748, 2020 08.
Article in English | MEDLINE | ID: covidwho-133150

ABSTRACT

By April 2, 2020, >1 million persons worldwide were infected with severe acute respiratory syndrome coronavirus 2. We used a mathematical model to investigate the effectiveness of social distancing interventions in a mid-sized city. Interventions reduced contacts of adults >60 years of age, adults 20-59 years of age, and children <19 years of age for 6 weeks. Our results suggest interventions started earlier in the epidemic delay the epidemic curve and interventions started later flatten the epidemic curve. We noted that, while social distancing interventions were in place, most new cases, hospitalizations, and deaths were averted, even with modest reductions in contact among adults. However, when interventions ended, the epidemic rebounded. Our models suggest that social distancing can provide crucial time to increase healthcare capacity but must occur in conjunction with testing and contact tracing of all suspected cases to mitigate virus transmission.


Subject(s)
Betacoronavirus/pathogenicity , Contact Tracing/statistics & numerical data , Coronavirus Infections/epidemiology , Coronavirus Infections/prevention & control , Hospitalization/statistics & numerical data , Models, Statistical , Pandemics/prevention & control , Pneumonia, Viral/epidemiology , Pneumonia, Viral/prevention & control , Adolescent , Adult , Age Factors , Aged , Aged, 80 and over , COVID-19 , COVID-19 Testing , Child , Child, Preschool , Cities , Clinical Laboratory Techniques/methods , Communicable Disease Control/methods , Communicable Disease Control/statistics & numerical data , Coronavirus Infections/diagnosis , Coronavirus Infections/mortality , Female , Humans , Incidence , Infant , Infant, Newborn , Infectious Disease Incubation Period , Male , Middle Aged , Patient Isolation/methods , Patient Isolation/statistics & numerical data , Physical Distancing , Pneumonia, Viral/diagnosis , Pneumonia, Viral/mortality , SARS-CoV-2 , Severity of Illness Index , Survival Analysis , United States/epidemiology
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