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2.
PLoS One ; 17(3): e0264232, 2022.
Article in English | MEDLINE | ID: covidwho-1753189

ABSTRACT

BACKGROUND: Health care workers (HCWs) are particularly exposed to COVID-19 and therefore it is important to study preventive measures in this population. AIM: To investigate socio-demographic factors and professional practice associated with the risk of COVID-19 among HCWs in health establishments in Normandy, France. METHODS: A cross-sectional and 3 case-control studies using bootstrap methods were conducted in order to explore the possible risk factors that lead to SARS-CoV2 transmission within HCWs. Case-control studies focused on risk factors associated with (a) care of COVID-19 patients, (b) care of non COVID-19 patients and (c) contacts between colleagues. PARTICIPANTS: 2,058 respondents, respectively 1,363 (66.2%) and 695 (33.8%) in medical and medico-social establishments, including HCW with and without contact with patients. RESULTS: 301 participants (14.6%) reported having been infected by SARS-CoV2. When caring for COVID-19 patients, HCWs who declared wearing respirators, either for all patient care (ORa 0.39; 95% CI: 0.29-0.51) or only when exposed to aerosol-generating procedures (ORa 0.56; 95% CI: 0.43-0.70), had a lower risk of infection compared with HCWs who declared wearing mainly surgical masks. During care of non COVID-19 patients, wearing mainly a respirator was associated with a higher risk of infection (ORa 1.84; 95% CI: 1.06-3.37). An increased risk was also found for HCWs who changed uniform in workplace changing rooms (ORa 1.93; 95% CI: 1.63-2.29). CONCLUSION: Correct use of PPE adapted to the situation and risk level is essential in protecting HCWs against infection.


Subject(s)
COVID-19/prevention & control , Communicable Disease Control/instrumentation , Disease Transmission, Infectious/prevention & control , Health Personnel/classification , Occupational Exposure/prevention & control , Adult , COVID-19/epidemiology , Case-Control Studies , Cross-Sectional Studies , Disease Transmission, Infectious/statistics & numerical data , Female , France , Humans , Male , Middle Aged , Occupational Exposure/statistics & numerical data , Personal Protective Equipment , Professional Practice , Risk Reduction Behavior
3.
Sci Rep ; 12(1): 4025, 2022 03 07.
Article in English | MEDLINE | ID: covidwho-1730321

ABSTRACT

Computational fluid dynamics (CFD) modelling and 3D simulations of the air flow and dispersion of droplets or drops in semi-confined ventilated spaces have found topical applications with the unfortunate development of the Covid-19 pandemic. As an illustration of this scenario, we have considered the specific situation of a railroad coach containing a seated passenger infected with the SARS-CoV-2 virus (and not wearing a face mask) who, by breathing and coughing, releases droplets and drops that contain the virus and that present aerodynamic diameters between 1 and 1000 µm. The air flow is generated by the ventilation in the rail coach. While essentially 3D, the flow is directed from the bottom to the top of the carriage and comprises large to small eddies visualised by means of streamlines. The space and time distribution of the droplets and drops is computed using both an Eulerian model and a Lagrangian model. The results of the two modelling approaches are fully consistent and clearly illustrate the different behaviours of the drops, which fall down close to the infected passenger, and the droplets, which are carried along with the air flow and invade a large portion of the rail coach. This outcome is physically sound and demonstrates the relevance of CFD for simulating the transport and dispersion of droplets and drops with any diameter in enclosed ventilated spaces. As coughing produces drops and breathing produces droplets, both modes of transmission of the SARS-CoV-2 virus in human secretions have been accounted for in our 3D numerical study. Beyond the specific, practical application of the rail coach, this study offers a much broader scope by demonstrating the feasibility and usefulness of 3D numerical simulations based on CFD. As a matter of fact, the same computational approach that has been implemented in our study can be applied to a huge variety of ventilated indoor environments such as restaurants, performance halls, classrooms and open-plan offices in order to evaluate if their occupation could be critical with respect to the transmission of the SARS-CoV-2 virus or to other airborne respiratory infectious agents, thereby enabling relevant recommendations to be made.


Subject(s)
COVID-19/transmission , Railroads , SARS-CoV-2/metabolism , COVID-19/virology , Computer Simulation , Disease Transmission, Infectious/statistics & numerical data , Humans , Imaging, Three-Dimensional
5.
Sci Rep ; 11(1): 24171, 2021 12 17.
Article in English | MEDLINE | ID: covidwho-1593554

ABSTRACT

The transmission of COVID-19 is dependent on social mixing, the basic rate of which varies with sociodemographic, cultural, and geographic factors. Alterations in social mixing and subsequent changes in transmission dynamics eventually affect hospital admissions. We employ these observations to model and predict regional hospital admissions in Sweden during the COVID-19 pandemic. We use an SEIR-model for each region in Sweden in which the social mixing is assumed to depend on mobility data from public transport utilisation and locations for mobile phone usage. The results show that the model could capture the timing of the first and beginning of the second wave of the pandemic 3 weeks in advance without any additional assumptions about seasonality. Further, we show that for two major regions of Sweden, models with public transport data outperform models using mobile phone usage. We conclude that a model based on routinely collected mobility data makes it possible to predict future hospital admissions for COVID-19 3 weeks in advance.


Subject(s)
Algorithms , COVID-19/transmission , Cell Phone/statistics & numerical data , Hospitalization/statistics & numerical data , Models, Theoretical , Patient Admission/statistics & numerical data , COVID-19/epidemiology , COVID-19/virology , Disease Transmission, Infectious/statistics & numerical data , Forecasting/methods , Geography , Hospitalization/trends , Humans , Pandemics/prevention & control , Patient Admission/trends , Retrospective Studies , SARS-CoV-2/physiology , Sweden/epidemiology , Travel/statistics & numerical data
6.
PLoS One ; 16(11): e0259970, 2021.
Article in English | MEDLINE | ID: covidwho-1526691

ABSTRACT

The COVID-19 pandemic has been particularly threatening to patients with end-stage kidney disease (ESKD) on intermittent hemodialysis and their care providers. Hemodialysis patients who receive life-sustaining medical therapy in healthcare settings, face unique challenges as they need to be at a dialysis unit three or more times a week, where they are confined to specific settings and tended to by dialysis nurses and staff with physical interaction and in close proximity. Despite the importance and critical situation of the dialysis units, modelling studies of the SARS-CoV-2 spread in these settings are very limited. In this paper, we have used a combination of discrete event and agent-based simulation models, to study the operations of a typical large dialysis unit and generate contact matrices to examine outbreak scenarios. We present the details of the contact matrix generation process and demonstrate how the simulation calculates a micro-scale contact matrix comprising the number and duration of contacts at a micro-scale time step. We have used the contacts matrix in an agent-based model to predict disease transmission under different scenarios. The results show that micro-simulation can be used to estimate contact matrices, which can be used effectively for disease modelling in dialysis and similar settings.


Subject(s)
COVID-19/transmission , Contact Tracing/statistics & numerical data , Disease Transmission, Infectious/statistics & numerical data , Hemodialysis Units, Hospital/statistics & numerical data , Computer Simulation , Humans , Models, Statistical
7.
Clin Pediatr (Phila) ; 61(2): 177-183, 2022 02.
Article in English | MEDLINE | ID: covidwho-1523150

ABSTRACT

The coronavirus disease 2019 (COVID-19) pandemic became an important public health problem affecting all age groups. The aim of this study was to evaluate clinical and laboratory findings of newborns born to mothers with COVID-19. Thirty pregnant women with COVID-19 were admitted to Turgut Ozal University Hospital for delivery. Fourteen pregnant women had at least one symptom associated with COVID-19. Positive polymerase chain reaction (PCR) results were seen in only 3 (9.7%) of 31 newborns. A statistically significant difference was observed between PCR-positive and PCR-negative newborns in terms of any adverse pregnancy outcomes. Neonatal lymphocyte count and partial arterial oxygen pressure were significantly lower in the PCR-positive group. Results were also compared according to the interval from the maternal diagnosis time to delivery. Hemoglobin and hematocrit levels in newborns born to mothers diagnosed more than 7 days before delivery were significantly lower. Neonates born to mothers with COVID-19 had mild clinical symptoms and favorable outcomes.


Subject(s)
COVID-19/complications , Pregnancy Outcome/epidemiology , Pregnant Women , Adult , COVID-19/epidemiology , Disease Transmission, Infectious/statistics & numerical data , Female , Humans , Pregnancy , Tertiary Care Centers/organization & administration , Tertiary Care Centers/statistics & numerical data
11.
Sci Rep ; 11(1): 18891, 2021 09 23.
Article in English | MEDLINE | ID: covidwho-1437692

ABSTRACT

The complexities involved in modelling the transmission dynamics of COVID-19 has been a roadblock in achieving predictability in the spread and containment of the disease. In addition to understanding the modes of transmission, the effectiveness of the mitigation methods also needs to be built into any effective model for making such predictions. We show that such complexities can be circumvented by appealing to scaling principles which lead to the emergence of universality in the transmission dynamics of the disease. The ensuing data collapse renders the transmission dynamics largely independent of geopolitical variations, the effectiveness of various mitigation strategies, population demographics, etc. We propose a simple two-parameter model-the Blue Sky model-and show that one class of transmission dynamics can be explained by a solution that lives at the edge of a blue sky bifurcation. In addition, the data collapse leads to an enhanced degree of predictability in the disease spread for several geographical scales which can also be realized in a model-independent manner as we show using a deep neural network. The methodology adopted in this work can potentially be applied to the transmission of other infectious diseases and new universality classes may be found. The predictability in transmission dynamics and the simplicity of our methodology can help in building policies for exit strategies and mitigation methods during a pandemic.


Subject(s)
COVID-19/prevention & control , COVID-19/transmission , Disease Transmission, Infectious/statistics & numerical data , COVID-19/metabolism , Disease Transmission, Infectious/prevention & control , Humans , Models, Statistical , Models, Theoretical , Pandemics , SARS-CoV-2/metabolism , SARS-CoV-2/pathogenicity
12.
Ghana Med J ; 54(4 Suppl): 5-15, 2020 Dec.
Article in English | MEDLINE | ID: covidwho-1436189

ABSTRACT

OBJECTIVE: Describe the epidemiology of COVID-19 cases detected in the first four months of the pandemic in Ghana by person, place and time to provide an understanding of the local epidemiology of the disease. METHODS: We conducted an exploratory descriptive study of all confirmed COVID-19 cases in Ghana from March 12 to June 30, 2020. Data was merged from the country's electronic databases, cleaned and summarized using medians, proportions and geospatial analysis. DESIGN: A cross-sectional study design. SETTING: Ghana. PARTICIPANTS: All confirmed COVID-19 cases in Ghana from March 12 to June 30, 2020. INTERVENTIONS: None. MAIN OUTCOME MEASURES: Epidemiological characterization of all confirmed COVID-19 cases recorded from March 12 - June 30, 2020 in Ghana by person, place and time. RESULTS: A total of 17,763 cases were recorded with median age (IQR) of 33years (One month to 85 years). Among the confirmed cases, 10,272 (57.8%) were males and 3,521 (19.8%) were symptomatic with cough recorded in 1,420 (40.3%) cases. The remaining 14,242 (80.2%) were asymptomatic. Greater Accra region recorded the highest number of confirmed cases 11,348 (63.9%). All 16 administrative regions had recorded cases of COVID-19 by June 30, 2020 due to internal migration between the hotspots and other regions. The epidemiological curve showed a propagated outbreak with 117 deaths (CFR= 0.67%) recorded. CONCLUSION: A propagated outbreak of COVID - 19 was confirmed in Ghana on March 12, 2020. Internal migration from hotspots to other regions led to the spread of the virus across the nation. Majority of cases were asymptomatic. FUNDING: The COVID-19 pandemic response and writing workshop by the Ghana Field Epidemiology and Laboratory Training Programme (GFELTP) was supported with funding from President Malaria Initiative - CDC, and Korea International Cooperation Agency (on CDC CoAg 6NU2GGH001876) through AFENET.


Subject(s)
COVID-19/epidemiology , Disease Outbreaks , Disease Transmission, Infectious/statistics & numerical data , SARS-CoV-2 , Adolescent , Adult , Aged , Aged, 80 and over , Child , Child, Preschool , Cross-Sectional Studies , Emigration and Immigration/statistics & numerical data , Female , Ghana/epidemiology , Humans , Infant , Infant, Newborn , Male , Middle Aged , Young Adult
15.
Clin Infect Dis ; 71(9): 2482-2487, 2020 12 03.
Article in English | MEDLINE | ID: covidwho-1387742

ABSTRACT

BACKGROUND: Previous reports have suggested that transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is reduced by higher temperatures and higher humidity. We analyzed case data from the United States to investigate the effects of temperature, precipitation, and ultraviolet (UV) light on community transmission of SARS-CoV-2. METHODS: Daily reported cases of SARS-CoV-2 across the United States from 22 January 2020 to 3 April 2020 were analyzed. We used negative binomial regression modeling to determine whether daily maximum temperature, precipitation, UV index, and the incidence 5 days later were related. RESULTS: A maximum temperature above 52°F on a given day was associated with a lower rate of new cases at 5 days (incidence rate ratio [IRR], 0.85 [0.76, 0.96]; P = .009). Among observations with daily temperatures below 52°F, there was a significant inverse association between the maximum daily temperature and the rate of cases at 5 days (IRR, 0.98 [0.97, 0.99]; P = .001). A 1-unit higher UV index was associated with a lower rate at 5 days (IRR, 0.97 [0.95, 0.99]; P = .004). Precipitation was not associated with a greater rate of cases at 5 days (IRR, 0.98 [0.89, 1.08]; P = .65). CONCLUSIONS: The incidence of disease declines with increasing temperature up to 52°F and is lower at warmer vs cooler temperatures. However, the association between temperature and transmission is small, and transmission is likely to remain high at warmer temperatures.


Subject(s)
COVID-19/epidemiology , Disease Transmission, Infectious/statistics & numerical data , SARS-CoV-2 , Weather , COVID-19/transmission , Humans , Incidence , Regression Analysis , Sunlight , Temperature , Ultraviolet Rays , United States/epidemiology
17.
PLoS One ; 16(1): e0244983, 2021.
Article in English | MEDLINE | ID: covidwho-1388896

ABSTRACT

Here we look into the spread of aerosols indoors that may potentially carry viruses. Many viruses, including the novel SARS-CoV-2, are known to spread via airborne and air-dust pathways. From the literature data and our research on the propagation of fine aerosols, we simulate herein the carryover of viral aerosols in indoor air. We demonstrate that a lot of fine droplets released from an infected person's coughing, sneezing, or talking propagate very fast and for large distances indoors, as well as bend around obstacles, lift up and down over staircases, and so on. This study suggests equations to evaluate the concentration of those droplets, depending on time and distance from the source of infection. Estimates are given for the safe distance to the source of infection, and available methods for neutralizing viral aerosols indoors are considered.


Subject(s)
COVID-19/transmission , Disease Transmission, Infectious/prevention & control , Aerosols/analysis , Air Microbiology , Air Pollution, Indoor/analysis , COVID-19/metabolism , COVID-19/virology , Cough , Disease Transmission, Infectious/statistics & numerical data , Dust , Humans , Models, Theoretical , SARS-CoV-2/isolation & purification , Sneezing/physiology , Virus Diseases/prevention & control
18.
Virol J ; 18(1): 109, 2021 06 02.
Article in English | MEDLINE | ID: covidwho-1388777

ABSTRACT

BACKGROUND: The ongoing SARS-CoV-2 pandemic has spread rapidly worldwide and disease prevention is more important than ever. In the absence of a vaccine, knowledge of the transmission routes and risk areas of infection remain the most important existing tools to prevent further spread. METHODS: Here we investigated the presence of the SARS-CoV-2 virus in the hospital environment at the Uppsala University Hospital Infectious Disease ward by RT-qPCR and determined the infectivity of the detected virus in vitro on Vero E6 cells. RESULTS: SARS-CoV-2 RNA was detected in several areas, although attempts to infect Vero E6 cells with positive samples were unsuccessful. However, RNase A treatment of positive samples prior to RNA extraction did not degrade viral RNA, indicating the presence of SARS-CoV-2 nucleocapsids or complete virus particles protecting the RNA as opposed to free viral RNA. CONCLUSION: Our results show that even in places where a moderate concentration (Ct values between 30 and 38) of SARS-CoV-2 RNA was found; no infectious virus could be detected. This suggests that the SARS-CoV-2 virus in the hospital environment subsides in two states; as infectious and as non-infectious. Future work should investigate the reasons for the non-infectivity of SARS-CoV-2 virions.


Subject(s)
COVID-19/transmission , Cross Infection/epidemiology , Disease Transmission, Infectious/statistics & numerical data , Environmental Monitoring/methods , Animals , Cell Line , Chlorocebus aethiops , Confined Spaces , Cross Infection/virology , Hospitals , Humans , Risk , SARS-CoV-2/growth & development , Ventilation/methods , Vero Cells
20.
JAMA Netw Open ; 4(4): e218184, 2021 04 01.
Article in English | MEDLINE | ID: covidwho-1384070

ABSTRACT

Importance: Digital contact tracing (DCT) apps have been released in several countries to help interrupt SARS-CoV-2 transmission chains. However, the effect of DCT on pandemic mitigation remains to be demonstrated. Objective: To estimate key populations and performance indicators along the exposure notification cascade of the SwissCovid DCT app in a clearly defined regional and temporal context. Design, Setting, and Participants: This comparative effectiveness study was based on a simulation informed by measured data from issued quarantine recommendations and positive SARS-CoV-2 test results after DCT exposure notifications in the canton of Zurich. A stochastic model was developed to re-create the DCT notification cascade for Zurich. Population sizes at each cascade step were estimated using triangulation based on publicly available administrative and observational research data for the study duration from September 1 to October 31, 2020. The resultant estimates were checked for internal consistency and consistency with upstream or downstream estimates in the cascade. Stochastic sampling from data-informed parameter distributions was performed to explore the robustness of results. Subsequently, key performance indicators were evaluated to assess the potential contribution of DCT compared with manual contact tracing. Main Outcomes and Measures: Receiving a voluntary quarantine recommendation and/or a positive SARS-CoV-2 test result after exposure notification. Results: In September 2020, 537 app users received a positive SARS-CoV-2 test result in Zurich, 324 of whom received and entered an upload authorization code. This code triggered an app notification for an estimated 1374 (95% simulation interval [SI], 932-2586) proximity contacts and led to 722 information hotline calls, with an estimated 170 callers (95% SI, 154-186) receiving a quarantine recommendation. An estimated 939 (95% SI, 720-1127) notified app users underwent testing for SARS-CoV-2, of whom 30 (95% SI, 23-36) had positive results after an app notification. Key indicator evaluations revealed that the DCT app triggered quarantine recommendations for the equivalent of 5% of all exposed contacts placed in quarantine by manual contact tracing. For every 10.9 (95% SI, 7.6-15.6) upload authorization codes entered in the app, 1 contact had positive test results for SARS-CoV-2 after app notification. Longitudinal indicator analyses demonstrated bottlenecks in the notification cascade, because capacity limits were reached owing to an increased incidence of SARS-CoV-2 infection in October 2020. Conclusions and Relevance: In this simulation study of the notification cascade of the SwissCovid DCT app, receipt of exposure notifications was associated with quarantine recommendations and identification of SARS-CoV-2-positive cases. These findings in notified proximity contacts reflect important intermediary steps toward transmission prevention.


Subject(s)
COVID-19 , Computer Simulation , Contact Tracing , Disease Notification , Disease Transmission, Infectious , Mobile Applications , Adult , COVID-19/diagnosis , COVID-19/epidemiology , COVID-19/prevention & control , COVID-19/transmission , Communicable Disease Control/methods , Communicable Disease Control/organization & administration , Contact Tracing/methods , Contact Tracing/statistics & numerical data , Disease Notification/methods , Disease Notification/statistics & numerical data , Disease Transmission, Infectious/prevention & control , Disease Transmission, Infectious/statistics & numerical data , Female , Humans , Male , Quarantine , SARS-CoV-2/isolation & purification , Switzerland/epidemiology
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