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Sarah A Hopkins, Roberta Lovick, Louisa Polak, Ben Bowers, Tessa Morgan, Michael P Kelly, Stephen Barclay
Paolo Immovilli, Nicola Morelli, Elio Antonucci, Guido Radaelli, Mario Barbera & Donata Guidetti
Michael Krausz, Jean Nicolas Westenberg ,Daniel Vigo, Richard Trafford Spence, Damon Ramsey
Background: Public health emergencies like epidemics put enormous pressure on health care systems while revealing deep structural and functional problems in the organization of care. The current coronavirus disease (COVID-19) pandemic illustrates this at a global level. The sudden increased demand on delivery systems puts unique pressures on pre-established care pathways. These extraordinary times require efficient tools for smart governance and resource allocation.
Objective: The aim of this study is to develop an innovative web-based solution addressing the seemingly insurmountable challenges of triaging, monitoring, and delivering nonhospital services unleashed by the COVID-19 pandemic.
Methods: An adaptable crisis management digital platform was envisioned and designed with the goal of improving the system’s response on the basis of the literature; an existing shared health record platform; and discussions between health care providers, decision makers, academia, and the private sector in response to the COVID 19 epidemic.
Results: The Crisis Management Platform was developed and offered to health authorities in Ontario on a nonprofit basis. It has the capability to dramatically streamline patient intake, triage, monitoring, referral, and delivery of nonhospital services. It decentralizes the provision of services (by moving them online) and centralizes data gathering and analysis, maximizing the use of existing human resources, facilitating evidence-based decision making, and minimizing the risk to both users and providers. It has unlimited scale-up possibilities (only constrained by human health risk resource availability) with minimal marginal cost. Similar web-based solutions have the potential to fill an urgent gap in resource allocation, becoming a unique asset for health systems governance and management during critical times. They highlight the potential effectiveness of web-based solutions if built on an outcome-driven architecture.
Conclusions: Data and web-based approaches in response to a public health crisis are key to evidence-driven oversight and management of public health emergencies
Inga Holmdahl, S.M., and Caroline Buckee, D.Phil
Jeremy Samuel Faust, Carlos del Rio
Marco Piccininni, Jessica L Rohmann, Luca Foresti, Caterina Lurani, Tobias Kurth
To quantify the impact of coronavirus disease 2019
(covid-19) on all cause mortality in Nembro, an Italian
city severely affected by the covid-19 pandemic.
Nembro, in the Bergamo province of Lombardy,
Residents of Nembro.
MAIN OUTCOME MEASURES
Monthly all cause mortality between January 2012
and April 2020 (data to 11 April), number of confirmed
deaths from covid-19 to 11 April 2020, and weekly
absolute number of deaths between 1 January and 4
April across recent years by age group and sex.
Nembro had 11505 residents as of 1 January 2020.
Monthly all cause mortality between January 2012 and
February 2020 fluctuated around 10 per 1000 person
years, with a maximum of 21.5 per 1000 person years. In
March 2020, monthly all cause mortality reached a peak
of 154.4 per 1000 person years. For the first 11 days
in April, this rate decreased to 23.0 per 1000 person
years. The observed increase in mortality was driven
by the number of deaths among older people (≥65
years), especially men. From the outbreak onset until 11
April 2020, only 85 confirmed deaths from covid-19 in
Nembro were recorded, corresponding to about half of
the 166 deaths from all causes observed in that period.
The study findings show how covid-19 can have
a considerable impact on the health of a small
community. Furthermore, the results suggest that the
full implications of the covid-19 pandemic can only
be completely understood if, in addition to confirmed
deaths related to covid-19, consideration is also given
to all cause mortality in a given region and time frame.
Rodrigo de Oliveira Andrade
F.A. Klok, G.J.A.M. Boon, S. Barco, M. Endres, J.J.M. Geelhoed, S. Knauss, S.A. Rezek, M.A. Spruit, J. Vehreschild, B. Siegerink
Stefano Nava, Roberto Tonelli, Enrico Clini
Myron S. Cohen, Lawrence Corey
Thomas A Treibel, Charlotte Manisty, Maudrian Burton, Áine McKnight, Jonathan Lambourne, João B Augusto, Xosé Couto-Parada, Teresa Cutino-Moguel, Mahdad Noursadeghi, James C Moon
Chris White, Vahé Nafilyan
Yen-Chin Liu, Rei-Lin Kuo, Shin-Ru Shih
The novel human coronavirus disease COVID-19 has become the fifth documented pandemic since the 1918 flu pandemic. COVID-19 was first reported in Wuhan, China, and subsequently spread worldwide. The coronavirus was officially named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by the International Committee on Taxonomy of Viruses based on phylogenetic analysis. SARS-CoV-2 is believed to be a spillover of an animal coronavirus and later adapted the ability of human-to-human transmission. Because the virus is highly contagious, it rapidly spreads and continuously evolves in the human population. In this review article, we discuss the basic properties, potential origin, and evolution of the novel human coronavirus. These factors may be critical for studies of pathogenicity, antiviral designs, and vaccine development against the virus.
Harald Walach & Stefan Hockertz
Thomas V. Inglesby
Giulia Lorenzoni, Corrado Lanera, Danila Azzolina, Paola Berchialla, Dario Gregori
Thushara Galbadage, Brent M. Peterson, Richard S. Gunasekera
Anna Odone, Davide Delmonte, Thea Scognamiglio, Carlo Signorelli
Mariangela Valentina Puci, Federica Loi, Ottavia Eleonora Ferraro, Stefano Cappai, Sandro Rolesu, Cristina Montomoli
Sangchul Park, Gina Jeehyun Choi, Haksoo Ko
David A Leon, Vladimir M Shkolnikov, Liam Smeeth, Per Magnus, Markéta Pechholdová, Christopher I Jarvis
At the end of December 2019, coronavirus disease 2019 (COVID-19) appeared in Wuhan city, China. As of April 15, 2020, >1.9 million COVID-19 cases were confirmed worldwide, including >120,000 deaths. There is an urgent need to monitor and predict COVID-19 prevalence to control this spread more effectively. Time series models are significant in predicting the impact of the COVID-19 outbreak and taking the necessary measures to respond to this crisis. In this study, Auto-Regressive Integrated Moving Average (ARIMA) models were developed to predict the epidemiological trend of COVID-19 prevalence of Italy, Spain, and France, the most affected countries of Europe. The prevalence data of COVID-19 from 21 February 2020 to 15 April 2020 were collected from the World Health Organization website. Several ARIMA models were formulated with different ARIMA parameters. ARIMA (0,2,1), ARIMA (1,2,0), and ARIMA (0,2,1) models with the lowest MAPE values (4.7520, 5.8486, and 5.6335) were selected as the best models for Italy, Spain, and France, respectively. This study shows that ARIMA models are suitable for predicting the prevalence of COVID-19 in the future. The results of the analysis can shed light on understanding the trends of the outbreak and give an idea of the epidemiological stage of these regions. Besides, the prediction of COVID-19 prevalence trends of Italy, Spain, and France can help take precautions and policy formulation for this epidemic in other countries.
Sarah Ee Fang Yong, Danielle Elizabeth Anderson, Wycliffe E Wei, Junxiong Pang, Wan Ni Chia, Chee Wah Tan, Yee Leong Teoh,
Priyanka Rajendram, Matthias Paul Han Sim Toh, Cuiqin Poh, Valerie T J Koh, Joshua Lum, Nur-Afidah Md Suhaimi, Po Ying Chia,
Mark I-Cheng Chen, Shawn Vasoo, Benjamin Ong, Yee Sin Leo, Linfa Wang, Vernon J M Lee
Elucidation of the chain of disease transmission and identification of the source of coronavirus disease 2019 (COVID-19) infections are crucial for effective disease containment. We describe an epidemiological investigation that, with use of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) serological assays, established links between three clusters of COVID-19.
In Singapore, active case-finding and contact tracing were undertaken for all COVID-19 cases. Diagnosis for acute disease was confirmed with RT-PCR testing. When epidemiological information suggested that people might have been nodes of disease transmission but had recovered from illness, SARS-CoV-2 IgG serology testing was used to establish past infection.
Three clusters of COVID-19, comprising 28 locally transmitted cases, were identified in Singapore; these clusters were from two churches (Church A and Church B) and a family gathering. The clusters in Church A and Church B were linked by an individual from Church A (A2), who transmitted SARS-CoV-2 infection to the primary case from Church B (F1) at a family gathering they both attended on Jan 25, 2020. All cases were confirmed by RT-PCR testing because they had active disease, except for A2, who at the time of testing had recovered from their illness and tested negative. This individual was eventually diagnosed with past infection by serological testing. ELISA assays showed an optical density of more than 1·4 for SARS-CoV-2 nucleoprotein and receptor binding domain antigens in titres up to 1/400, and viral neutralisation was noted in titres up to 1/320.
Development and application of a serological assay has helped to establish connections between COVID-19 clusters in Singapore. Serological testing can have a crucial role in identifying convalescent cases or people with milder disease who might have been missed by other surveillance methods.
National Research Foundation (Singapore), National Natural Science Foundation (China), and National Medical Research Council (Singapore).
Tim K Tsang, Peng Wu, Yun Lin, Eric H Y Lau, Gabriel M Leung, Benjamin J Cowling
When a new infectious disease emerges, appropriate case definitions are important for clinical diagnosis and for public health surveillance. Tracking case numbers over time is important to establish the speed of spread and the effectiveness of interventions. We aimed to assess whether changes in case definitions affected inferences on the transmission dynamics of coronavirus disease 2019 (COVID-19) in China.
We examined changes in the case definition for COVID-19 in mainland China during the first epidemic wave. We used exponential growth models to estimate how changes in the case definitions affected the number of cases reported each day. We then inferred how the epidemic curve would have appeared if the same case definition had been used throughout the epidemic.
From Jan 15 to March 3, 2020, seven versions of the case definition for COVID-19 were issued by the National Health Commission in China. We estimated that when the case definitions were changed, the proportion of infections being detected as cases increased by 7·1 times (95% credible interval [CrI] 4·8–10·9) from version 1 to 2, 2·8 times (1·9–4·2) from version 2 to 4, and 4·2 times (2·6–7·3) from version 4 to 5. If the fifth version of the case definition had been applied throughout the outbreak with sufficient testing capacity, we estimated that by Feb 20, 2020, there would have been 232 000 (95% CrI 161 000–359 000) confirmed cases in China as opposed to the 55 508 confirmed cases reported.
The case definition was initially narrow and was gradually broadened to allow detection of more cases as knowledge increased, particularly milder cases and those without epidemiological links to Wuhan, China, or other known cases. These changes should be taken into account when making inferences on epidemic growth rates and doubling times, and therefore on the reproductive number, to avoid bias.
Health and Medical Research Fund, Hong Kong.
Wafaa M. El‐Sadr, Jessica Justman
Benjamin J Cowling, Sheikh Taslim Ali, Tiffany W Y Ng, Tim K Tsang, Julian C M Li, Min Whui Fong, Qiuyan Liao, Mike YW Kwan, So Lun Lee,
Susan S Chiu, Joseph T Wu, Peng Wu, Gabriel M Leung
A range of public health measures have been implemented to suppress local transmission of coronavirus disease 2019 (COVID-19) in Hong Kong. We examined the effect of these interventions and behavioural changes of the public on the incidence of COVID-19, as well as on influenza virus infections, which might share some aspects of transmission dynamics with COVID-19.
We analysed data on laboratory-confirmed COVID-19 cases, influenza surveillance data in outpatients of all ages, and influenza hospitalisations in children. We estimated the daily effective reproduction number (Rt) for COVID-19 and influenza A H1N1 to estimate changes in transmissibility over time. Attitudes towards COVID-19 and changes in population behaviours were reviewed through three telephone surveys done on Jan 20–23, Feb 11–14, and March 10–13, 2020.
COVID-19 transmissibility measured by Rt has remained at approximately 1 for 8 weeks in Hong Kong. Influenza transmission declined substantially after the implementation of social distancing measures and changes in population behaviours in late January, with a 44% (95% CI 34–53%) reduction in transmissibility in the community, from an estimated Rt of 1·28 (95% CI 1·26–1·30) before the start of the school closures to 0·72 (0·70–0·74) during the closure weeks. Similarly, a 33% (24–43%) reduction in transmissibility was seen based on paediatric hospitalisation rates, from an Rt of 1·10 (1·06–1·12) before the start of the school closures to 0·73 (0·68–0·77) after school closures. Among respondents to the surveys, 74·5%, 97·5%, and 98·8% reported wearing masks when going out, and 61·3%, 90·2%, and 85·1% reported avoiding crowded places in surveys 1 (n=1008), 2 (n=1000), and 3 (n=1005), respectively.
Our study shows that non-pharmaceutical interventions (including border restrictions, quarantine and isolation, distancing, and changes in population behaviour) were associated with reduced transmission of COVID-19 in Hong Kong, and are also likely to have substantially reduced influenza transmission in early February, 2020.
Health and Medical Research Fund, Hong Kong.
Gionata Fiorino, Matteo Colombo, Carmela Natale, Elena Azzolini, Michele Lagioia,
Verbeek JH, Rajamaki B, Ijaz S, Sauni R, Toomey E, Blackwood B, Tikka C, Ruotsalainen JH, Kilinc Balci
In epidemics of highly infectious diseases, such as Ebola, severe acute respiratory syndrome (SARS), or coronavirus (COVID‐19), healthcare workers (HCW) are at much greater risk of infection than the general population, due to their contact with patients' contaminated body fluids. Personal protective equipment (PPE) can reduce the risk by covering exposed body parts. It is unclear which type of PPE protects best, what is the best way to put PPE on (i.e. donning) or to remove PPE (i.e. doffing), and how to train HCWs to use PPE as instructed.
To evaluate which type of full‐body PPE and which method of donning or doffing PPE have the least risk of contamination or infection for HCW, and which training methods increase compliance with PPE protocols.
We searched CENTRAL, MEDLINE, Embase and CINAHL to 20 March 2020.
We included all controlled studies that evaluated the effect of full‐body PPE used by HCW exposed to highly infectious diseases, on the risk of infection, contamination, or noncompliance with protocols. We also included studies that compared the effect of various ways of donning or doffing PPE, and the effects of training on the same outcomes.
Data collection and analysis
Two review authors independently selected studies, extracted data and assessed the risk of bias in included trials. We conducted random‐effects meta‐analyses were appropriate.
Earlier versions of this review were published in 2016 and 2019. In this update, we included 24 studies with 2278 participants, of which 14 were randomised controlled trials (RCT), one was a quasi‐RCT and nine had a non‐randomised design.
Eight studies compared types of PPE. Six studies evaluated adapted PPE. Eight studies compared donning and doffing processes and three studies evaluated types of training. Eighteen studies used simulated exposure with fluorescent markers or harmless microbes. In simulation studies, median contamination rates were 25% for the intervention and 67% for the control groups.
Evidence for all outcomes is of very low certainty unless otherwise stated because it is based on one or two studies, the indirectness of the evidence in simulation studies and because of risk of bias.
Types of PPE
The use of a powered, air‐purifying respirator with coverall may protect against the risk of contamination better than a N95 mask and gown (risk ratio (RR) 0.27, 95% confidence interval (CI) 0.17 to 0.43) but was more difficult to don (non‐compliance: RR 7.5, 95% CI 1.81 to 31.1). In one RCT (59 participants), people with a long gown had less contamination than those with a coverall, and coveralls were more difficult to doff (low‐certainty evidence). Gowns may protect better against contamination than aprons (small patches: mean difference (MD) −10.28, 95% CI −14.77 to −5.79). PPE made of more breathable material may lead to a similar number of spots on the trunk (MD 1.60, 95% CI −0.15 to 3.35) compared to more water‐repellent material but may have greater user satisfaction (MD −0.46, 95% CI −0.84 to −0.08, scale of 1 to 5).
Modified PPE versus standard PPE
The following modifications to PPE design may lead to less contamination compared to standard PPE: sealed gown and glove combination (RR 0.27, 95% CI 0.09 to 0.78), a better fitting gown around the neck, wrists and hands (RR 0.08, 95% CI 0.01 to 0.55), a better cover of the gown‐wrist interface (RR 0.45, 95% CI 0.26 to 0.78, low‐certainty evidence), added tabs to grab to facilitate doffing of masks (RR 0.33, 95% CI 0.14 to 0.80) or gloves (RR 0.22, 95% CI 0.15 to 0.31).
Donning and doffing
Using Centers for Disease Control and Prevention (CDC) recommendations for doffing may lead to less contamination compared to no guidance (small patches: MD −5.44, 95% CI −7.43 to −3.45). One‐step removal of gloves and gown may lead to less bacterial contamination (RR 0.20, 95% CI 0.05 to 0.77) but not to less fluorescent contamination (RR 0.98, 95% CI 0.75 to 1.28) than separate removal. Double‐gloving may lead to less viral or bacterial contamination compared to single gloving (RR 0.34, 95% CI 0.17 to 0.66) but not to less fluorescent contamination (RR 0.98, 95% CI 0.75 to 1.28). Additional spoken instruction may lead to fewer errors in doffing (MD −0.9, 95% CI −1.4 to −0.4) and to fewer contamination spots (MD −5, 95% CI −8.08 to −1.92). Extra sanitation of gloves before doffing with quaternary ammonium or bleach may decrease contamination, but not alcohol‐based hand rub.
The use of additional computer simulation may lead to fewer errors in doffing (MD −1.2, 95% CI −1.6 to −0.7). A video lecture on donning PPE may lead to better skills scores (MD 30.70, 95% CI 20.14 to 41.26) than a traditional lecture. Face‐to‐face instruction may reduce noncompliance with doffing guidance more (odds ratio 0.45, 95% CI 0.21 to 0.98) than providing folders or videos only.
We found low‐ to very low‐certainty evidence that covering more parts of the body leads to better protection but usually comes at the cost of more difficult donning or doffing and less user comfort, and may therefore even lead to more contamination. More breathable types of PPE may lead to similar contamination but may have greater user satisfaction. Modifications to PPE design, such as tabs to grab, may decrease the risk of contamination. For donning and doffing procedures, following CDC doffing guidance, a one‐step glove and gown removal, double‐gloving, spoken instructions during doffing, and using glove disinfection may reduce contamination and increase compliance. Face‐to‐face training in PPE use may reduce errors more than folder‐based training.
We still need RCTs of training with long‐term follow‐up. We need simulation studies with more participants to find out which combinations of PPE and which doffing procedure protects best. Consensus on simulation of exposure and assessment of outcome is urgently needed. We also need more real‐life evidence. Therefore, the use of PPE of HCW exposed to highly infectious diseases should be registered and the HCW should be prospectively followed for their risk of infection.
Stephen M. Kissler, Christine Tedijanto, Edward Goldstein, Yonatan H. Grad, Marc Lipsitch
It is urgent to understand the future of severe acute respiratory syndrome–coronavirus 2 (SARS-CoV-2) transmission. We used estimates of seasonality, immunity, and cross-immunity for betacoronaviruses OC43 and HKU1 from time series data from the USA to inform a model of SARS-CoV-2 transmission. We projected that recurrent wintertime outbreaks of SARS-CoV-2 will probably occur after the initial, most severe pandemic wave. Absent other interventions, a key metric for the success of social distancing is whether critical care capacities are exceeded. To avoid this, prolonged or intermittent social distancing may be necessary into 2022. Additional interventions, including expanded critical care capacity and an effective therapeutic, would improve the success of intermittent distancing and hasten the acquisition of herd immunity. Longitudinal serological studies are urgently needed to determine the extent and duration of immunity to SARS-CoV-2. Even in the event of apparent elimination, SARS-CoV-2 surveillance should be maintained since a resurgence in contagion could be possible as late as 2024.
D.F. Gudbjartsson, A. Helgason, H. Jonsson, O.T. Magnusson, P. Melsted, G.L. Norddahl, J. Saemundsdottir, A. Sigurdsson, P. Sulem, A.B. Agustsdottir,
B. Eiriksdottir, R. Fridriksdottir, E.E. Gardarsdottir, G. Georgsson, O.S. Gretarsdottir, K.R. Gudmundsson, T.R. Gunnarsdottir, A. Gylfason, H. Holm, B.O. Jensson,
A. Jonasdottir, F. Jonsson, K.S. Josefsdottir, T. Kristjansson, D.N. Magnusdottir, L. le Roux, G. Sigmundsdottir, G. Sveinbjornsson, K.E. Sveinsdottir, M. Sveinsdottir,
E.A. Thorarensen, B. Thorbjornsson, A. Löve, G. Masson, I. Jonsdottir, A.D. Möller, T. Gudnason, K.G. Kristinsson, U. Thorsteinsdottir, and K. Stefansson
During the current worldwide pandemic, coronavirus disease 2019 (Covid-19) was
first diagnosed in Iceland at the end of February. However, data are limited on how
SARS-CoV-2, the virus that causes Covid-19, enters and spreads in a population.
We targeted testing to persons living in Iceland who were at high risk for infection
(mainly those who were symptomatic, had recently traveled to high-risk countries,
or had contact with infected persons). We also carried out population screening us-
ing two strategies: issuing an open invitation to 10,797 persons and sending random
invitations to 2283 persons. We sequenced SARS-CoV-2 from 643 samples.
As of April 4, a total of 1221 of 9199 persons (13.3%) who were recruited for tar-
geted testing had positive results for infection with SARS-CoV-2. Of those tested
in the general population, 87 (0.8%) in the open-invitation screening and 13 (0.6%)
in the random-population screening tested positive for the virus. In total, 6% of the
population was screened. Most persons in the targeted-testing group who received
positive tests early in the study had recently traveled internationally, in contrast to
those who tested positive later in the study. Children under 10 years of age were less
likely to receive a positive result than were persons 10 years of age or older, with
percentages of 6.7% and 13.7%, respectively, for targeted testing; in the population
screening, no child under 10 years of age had a positive result, as compared with
0.8% of those 10 years of age or older. Fewer females than males received positive
results both in targeted testing (11.0% vs. 16.7%) and in population screening (0.6%
vs. 0.9%). The haplotypes of the sequenced SARS-CoV-2 viruses were diverse and
changed over time. The percentage of infected participants that was determined
through population screening remained stable for the 20-day duration of screening.
In a population-based study in Iceland, children under 10 years of age and females
had a lower incidence of SARS-CoV-2 infection than adolescents or adults and males.
The proportion of infected persons identified through population screening did not
change substantially during the screening period, which was consistent with a
beneficial effect of containment efforts. (Funded by deCODE Genetics–Amgen.)
James M. Sanders, Marguerite L. Monogue, Tomasz Z. Jodlowski, James B. Cutrell
K. Barroa, A. Malone b, A. Mokedea, C. Chevancec
David M. Hartley, Eli N. Perencevich
Tom McEnery, Ciara Gough, Richard W Costello
Marzia Lazzerini, Egidio Barbi, Andrea Apicella, Federico Marchetti, Fabio Cardinale, Gianluca Trobia
Erin P. Fraher, Patricia Pittman, Bianca K. Frogner, Joanne Spetz, Jean Moore, Angela J. Beck, David Armstrong, Peter I. Buerhaus
David M. Studdert, L.L.B., Sc.D., and Mark A. Hall, J.D.
Benjamin F. Maier, Dirk Brockmann
The recent outbreak of COVID-19 in Mainland China was characterized by a distinctive subexponential increase of confirmed cases during the early phase of the epidemic, contrasting an initial exponential growth expected for an unconstrained outbreak. We show that this effect can be explained as a direct consequence of containment policies that effectively deplete the susceptible population. To this end, we introduce a parsimonious model that captures both, quarantine of symptomatic infected individuals as well as population-wide isolation practices in response to containment policies or behavioral changes and show that the model captures the observed growth behavior accurately. The insights provided here may aid the careful implementation of containment strategies for ongoing secondary outbreaks of COVID-19 or similar future outbreaks of other emergent infectious diseases.
Kathy Leung, Joseph T Wu, Di Liu, Gabriel M Leung
As of March 18, 2020, 13 415 confirmed cases and 120 deaths related to coronavirus disease 2019 (COVID-19) in mainland China, outside Hubei province—the epicentre of the outbreak—had been reported. Since late January, massive public health interventions have been implemented nationwide to contain the outbreak. We provide an impact assessment of the transmissibility and severity of COVID-19 during the first wave in mainland Chinese locations outside Hubei.
We estimated the instantaneous reproduction number (Rt) of COVID-19 in Beijing, Shanghai, Shenzhen, Wenzhou, and the ten Chinese provinces that had the highest number of confirmed COVID-19 cases; and the confirmed case-fatality risk (cCFR) in Beijing, Shanghai, Shenzhen, and Wenzhou, and all 31 Chinese provinces. We used a susceptible–infectious–recovered model to show the potential effects of relaxing containment measures after the first wave of infection, in anticipation of a possible second wave.
In all selected cities and provinces, the Rt decreased substantially since Jan 23, when control measures were implemented, and have since remained below 1. The cCFR outside Hubei was 0·98% (95% CI 0·82–1·16), which was almost five times lower than that in Hubei (5·91%, 5·73–6·09). Relaxing the interventions (resulting in Rt >1) when the epidemic size was still small would increase the cumulative case count exponentially as a function of relaxation duration, even if aggressive interventions could subsequently push disease prevalence back to the baseline level.
The first wave of COVID-19 outside of Hubei has abated because of aggressive non-pharmaceutical interventions. However, given the substantial risk of viral reintroduction, particularly from overseas importation, close monitoring of Rt and cCFR is needed to inform strategies against a potential second wave to achieve an optimal balance between health and economic protection.
Health and Medical Research Fund, Hong Kong, China.
Boccia, Ricciardi, Ioannidis
Joon-Young Song, Jin-Gu Yun, Ji-Yun Noh, Hee-Jin Cheong, Woo-Joo Kim
Russell M Viner, Simon J Russell, Helen Croker, Jessica Packer, Joseph Ward, Claire Stansfield, Oliver Mytton, Chris Bonell, Robert Booy
In response to the coronavirus disease 2019 (COVID-19) pandemic, 107 countries had implemented national school
closures by March 18, 2020. It is unknown whether school measures are effective in coronavirus outbreaks (eg, due to
severe acute respiratory syndrome [SARS], Middle East respiratory syndrome, or COVID-19). We undertook a
systematic review by searching three electronic databases to identify what is known about the effectiveness of school
closures and other school social distancing practices during coronavirus outbreaks. We included 16 of 616 identified
articles. School closures were deployed rapidly across mainland China and Hong Kong for COVID-19. However, there
are no data on the relative contribution of school closures to transmission control. Data from the SARS outbreak in
mainland China, Hong Kong, and Singapore suggest that school closures did not contribute to the control of the
epidemic. Modelling studies of SARS produced conflicting results. Recent modelling studies of COVID-19 predict
that school closures alone would prevent only 2–4% of deaths, much less than other social distancing interventions.
Policy makers need to be aware of the equivocal evidence when considering school closures for COVID-19, and that
combinations of social distancing measures should be considered. Other less disruptive social distancing interventions
in schools require further consideration if restrictive social distancing policies are implemented for long periods.
From the end of February, the SARS-CoV-2 epidemic in Spain has been following the footsteps of that in Italy very closely. We have analyzed the trends of incident cases, deaths, and intensive care unit admissions (ICU) in both countries before and after their respective national lockdowns using an interrupted time-series design. Data was analyzed with quasi-Poisson regression using an interaction model to estimate the change in trends. After the first lockdown, incidence trends were considerably reduced in both countries. However, although the slopes have been flattened for all outcomes, the trends kept rising. During the second lockdown, implementing more restrictive measures for mobility, it has been a change in the trend slopes for both countries in daily incident cases and ICUs. This improvement indicates that the efforts overtaken are being successful in flattening the epidemic curve, and reinforcing the belief that we must hold on.
Annoor Awadasseid, Yanling Wu, Yoshimasa Tanaka, Wen Zhang
Coronavirus (CoV) has been one of the major pandemic threats to human health in the last two decades.
The human coronavirus was first identified in 1960s. CoVs 229E, NL63, OC43, HKU1, SARS-CoV, and
MERS-CoV have caused numerous disasters or human deaths worldwide. Recently, an outbreak of the
previously unknown deadly CoV disease 2019 (COVID-19) caused by Severe Acute Respiratory
Syndrome CoV 2 (SARS-CoV-2, early named 2019-nCoV) occurred in Wuhan, China, and it had caused
81238 cases of confirmed infection, including 3250 deaths until March 19, 2020. Its risks and pandemic
potential have brought global consideration. We summarized epidemiology, virological characteristics,
clinical symptoms, diagnostic methods, clinical treatments, and prevention methods for COVID-19 to
present a reference for the future wave of probable CoV outbreaks.
Stefania Boccia, Walter Ricciardi, John P. A. Ioannidis
European Medicines Agency
Simiao Chen, Zongjiu Zhang, Juntao Yang, Jian Wang, Xiaohui Zhai, Till Bärnighausen, Chen Wang
Fangcang shelter hospitals are a novel public health concept. They were implemented for the first time in China in
February, 2020, to tackle the coronavirus disease 2019 (COVID-19) outbreak. The Fangcang shelter hospitals in China
were large-scale, temporary hospitals, rapidly built by converting existing public venues, such as stadiums and
exhibition centres, into health-care facilities. They served to isolate patients with mild to moderate COVID-19 from
their families and communities, while providing medical care, disease monitoring, food, shelter, and social activities.
We document the development of Fangcang shelter hospitals during the COVID-19 outbreak in China and explain
their three key characteristics (rapid construction, massive scale, and low cost) and five essential functions (isolation,
triage, basic medical care, frequent monitoring and rapid referral, and essential living and social engagement).
Fangcang shelter hospitals could be powerful components of national responses to the COVID-19 pandemic, as well as
future epidemics and public health emergencies.
Michael Klompas, Charles A. Morris, Julia Sinclair, Madelyn Pearson, Erica S. Shenoy,
Rene Niehus, Pablo M De Salazar, Aimee R Taylor, Marc Lipsitch
The incidence of coronavirus disease 2019 (COVID-19) in Wuhan, China, has been estimated using imported
case counts of international travellers, generally under the assumptions that all cases of the disease in travellers have
been ascertained and that infection prevalence in travellers and residents is the same. However, findings indicate
variation among locations in the capacity for detection of imported cases. Singapore has had very strong epidemiological
surveillance and contact tracing capacity during previous infectious disease outbreaks and has consistently shown high
sensitivity of case-detection during the COVID-19 outbreak.
We used a Bayesian modelling approach to estimate the relative capacity for detection of imported cases of
COVID-19 for 194 locations (excluding China) compared with that for Singapore. We also built a simple mathematical
model of the point prevalence of infection in visitors to an epicentre relative to that in residents.
The weighted global ability to detect Wuhan-to-location imported cases of COVID-19 was estimated to be 38%
(95% highest posterior density interval [HPDI] 22–64) of Singapore’s capacity. This value is equivalent to 2·8 (95% HPDI
1·5–4·4) times the current number of imported and reported cases that could have been detected if all locations had had
the same detection capacity as Singapore. Using the second component of the Global Health Security index to stratify
likely case-detection capacities, the ability to detect imported cases relative to Singapore was 40% (95% HPDI 22–67)
among locations with high surveillance capacity, 37% (18–68) among locations with medium surveillance capacity, and
11% (0–42) among locations with low surveillance capacity. Treating all travellers as if they were residents (rather than
accounting for the brief stay of some of these travellers in Wuhan) contributed modestly to underestimation of prevalence.
Interpretation Estimates of case counts in Wuhan based on assumptions of 100% detection in travellers could have
been underestimated by several fold. Furthermore, severity estimates will be inflated several fold since they also rely
on case count estimates. Finally, our model supports evidence that underdetected cases of COVID-19 have probably
spread in most locations around the world, with greatest risk in locations of low detection capacity and high
connectivity to the epicentre of the outbreak.
US National Institute of General Medical Sciences, and Fellowship Foundation Ramon Areces
Tim Baker, Carl Otto Schell, Dan Brun Petersen, Hendry Sawe, Karima Khalid, Samson Mndolo, Jamie Rylance, Daniel F McAuley, Nobhojit Roy, John Marshall,
Lee Wallis, Elizabeth Molyneux
Harvey V. Fineberg
Gavin Yamey, Marco Schäferhoff, Richard Hatchett, Muhammad Pate, Feng Zhao, Kaci Kennedy McDade
Derek C. Angus
Boris Bibkov, Alexander Bibkov
The manuscript highlights available data on gap in public awareness about recent clinical and scientific facts about COVID-19, insufficient community knowledge about symptoms and preventive measures during COVID-19 and previous MERS-CoV epidemic, and lack of monitoring the community perception and adherence to preventive measures. We also summarize literature evidence about reluctance to change social behavior and disregard recommendations for social distancing among persons who percept to having low risk of infection or complications, and briefly describe destructive psychological response and misleading communications.
Our analysis could be translated into important policy changes in two directions:
(1) to communicate recent scientific discoveries about COVID-19 pathophysiology to better prepare public opinion to longer period of extraordinary measures;
(2) to implement sociological feedback on knowledge, attitudes and practices among general public and some vulnerable social groups.
Mirco Nacoti, Andrea Ciocca, Angelo Giupponi, Pietro Brambillasca, Federico Lussana, Michele Pisano, Giuseppe Goisis, Daniele Bonacina, Francesco Fazzi, Richard Naspro, Luca Longhi, Maurizio Cereda, Carlo Montaguti
In a pandemic, patient-centered care is inadequate and must be replaced by community-centered care. Solutions for Covid-19 are required for the entire population, not only for hospitals. The catastrophe unfolding in wealthy Lombardy could happen anywhere. Clinicians at a hospital at the epicenter call for a long-term plan for the next pandemic.
Kensaku Kakimoto, Hajime Kamiya, Takuya Yamagishi, Tamano Matsui, Motoi Suzuki, Takaji Wakita
Giacomo Grasselli, Antonio Pesenti, Maurizio Cecconi
Adam J Kucharski, Timothy W Russell, Charlie Diamond, Yang Liu, John Edmunds, Sebastian Funk, Rosalind M Eggo
Background An outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to 95333 confirmed cases as of March 5, 2020. Understanding the early transmission dynamics of the infection and evaluating the effectiveness of control measures is crucial for assessing the potential for sustained transmission to occur in new areas. Combining a mathematical model of severe SARS-CoV-2 transmission with four datasets from within and outside Wuhan, we estimated how transmission in Wuhan varied between December, 2019, and February, 2020. We used these estimates to assess the potential for sustained human-to-human transmission to occur in locations outside Wuhan if cases were introduced.
Methods We combined a stochastic transmission model with data on cases of coronavirus disease 2019 (COVID-19) in Wuhan and international cases that originated in Wuhan to estimate how transmission had varied over time during January, 2020, and February, 2020. Based on these estimates, we then calculated the probability that newly introduced cases might generate outbreaks in other areas. To estimate the early dynamics of transmission in Wuhan, we fitted a stochastic transmission dynamic model to multiple publicly available datasets on cases in Wuhan and internationally exported cases from Wuhan. The four datasets we fitted to were: daily number of new internationally exported cases (or lack thereof), by date of onset, as of Jan 26, 2020; daily number of new cases in Wuhan with no market exposure, by date of onset, between Dec 1, 2019, and Jan 1, 2020; daily number of new cases in China, by date of onset, between Dec 29, 2019, and Jan 23, 2020; and proportion of infected passengers on evacuation flights between Jan 29, 2020, and Feb 4, 2020. We used an additional two datasets for comparison with model outputs: daily number of new exported cases from Wuhan (or lack thereof) in countries with high connectivity to Wuhan (ie, top 20 most at-risk countries), by date of confirmation, as of Feb 10, 2020; and data on new confirmed cases reported in Wuhan between Jan 16, 2020, and Feb 11, 2020.
We estimated that the median daily reproduction number (Rt) in Wuhan declined from 2·35 (95% CI 1·15–4·77) 1 week before travel restrictions were introduced on Jan 23, 2020, to 1·05 (0·41–2·39) 1 week after. Based on our estimates of Rt, assuming SARS-like variation, we calculated that in locations with similar transmission potential to Wuhan in early January, once there are at least four independently introduced cases, there is a more than 50% chance the infection will establish within that population.
Our results show that COVID-19 transmission probably declined in Wuhan during late January, 2020, coinciding with the introduction of travel control measures. As more cases arrive in international locations with similar transmission potential to Wuhan before these control measures, it is likely many chains of transmission will fail to establish initially, but might lead to new outbreaks eventually.
Funding Wellcome Trust, Health Data Research UK, Bill & Melinda Gates Foundation, and National Institute for Health Research.
SIMIT (Società Italiana Malattie Infettive e Tropicali)
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