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title	authors	date	data_availability	search term	doi	url	abstract
SARS-CoV-2 infection in health care workers: a retrospective analysis and a model study	Yansen Bai Sr.;Xuan Wang Sr.;Qimin Huang Sr.;Han Wang Sr.;David Gurarie;Martial Ndeffo-Mbah;Fei Fan;Peng Fu;Mary Ann Horn;Shuai Xu;Anirban Mondal;Xiaobing Jiang Sr.;Hongyang Zhao	2020-04-01	confidential	covid-19	https://doi.org/10.1101/2020.03.29.20047159	https://www.medrxiv.org/content/10.1101/2020.03.29.20047159v1	AbstractBackground There had been a preliminary occurrence of human-to-human transmissions between healthcare workers (HCWs), but risk factors in the susceptibility for COVID-19, and infection patterns among HCWs have largely remained unknown. Methods Retrospective data collection on demographics, lifestyles, contact status with infected subjects for 118 HCWs (include 12 COVID-19 HCWs) from a single-center. Sleep quality and working pressure were evaluated by Pittsburgh Sleep Quality Index (PSQI) and The Nurse Stress Index (NSI), respectively. Follow-up duration was from Dec 25, 2019, to Feb 15, 2020. Risk factors and transmission models of COVID-19 among HCWs were analyzed and constructed. Findings A high proportion of COVID-19 HCWs had engaged in night shift-work (75.0% vs. 40.6%) and felt they were working under pressure (66.7% vs. 32.1%) than uninfected HCWs. COVID-19 HCWs had higher total scores of PSQI and NSI than uninfected HCWs. Furthermore, these scores were both positively associated with COVID-19 risk. An individual-based model (IBM) estimated the outbreak duration among HCWs in a non-typical COVID-19 ward at 62-80 days and the basic reproduction number =1.27 [1.06, 1.61]. By reducing the average contact rate per HCW by a 1.35 factor and susceptibility by a 1.40 factor, we can avoid an outbreak of the basic case among HCWs. Interpretation Poor sleep quality and high working pressure were positively associated with high risks of COVID-19. A novel IBM of COVID-19 transmission is suitable for simulating different outbreak patterns in a hospital setting.
How lethal is the novel coronavirus, and how many undetected cases there are? The importance of being tested.	Ugo Bastolla	2020-04-01	upon request	covid-19	https://doi.org/10.1101/2020.03.27.20045062	https://www.medrxiv.org/content/10.1101/2020.03.27.20045062v1	AbstractThere is big concern for estimating the lethality and the extent of undetected infections associated with the novel coronavirus SARS-CoV2 outbreak. While detailed epidemiological models are certainly needed, I suggest here an orthogonal approach based on a minimum number of parameters robustly fitted from the cumulative data easily accessible for all countries at the John Hopkins University database that became the worldwide reference for the pandemics. I show that, after few days from the beginning of the outbreak, the apparent death rate can be extrapolated to infinite time through regularized regression such as rescaled ridge regression. The variation from country to country of these extrapolated death rates appears to depend almost only (r^2=0.91) on the ratio between performed tests and detected cases even when the instantaneous apparent lethality rates are as different as 9% in Italy and 0.4% in Germany. Extrapolating to the limit of infinite number of tests, I obtain a death rate of 0.012+/- 0.012, in agreement with other estimates. The inverse relationship between the extrapolated death rate and the intensity tests allows estimating that more than 50% of cases were undetected in most countries, with more than 90% undetected cases in countries severely hit by the epidemics such as Italy. Finally, I propose to adopt the ratio between the cumulative number of recovered and deceased persons as an indicator that can anticipate the halting of the epidemics.
Risk factors for severe corona virus disease 2019 (COVID-19) patients : a systematic review and meta analysis	Lizhen Xu;mao yaqian;Gang Chen	2020-04-01	upon request	covid-19	https://doi.org/10.1101/2020.03.30.20047415	https://www.medrxiv.org/content/10.1101/2020.03.30.20047415v1	AbstractImportance: With the increasing number of infections for COVID-19, the global health resources are deficient. At present, we don't have specific medicines or vaccines against novel coronavirus pneumonia (NCP) and our assessment of risk factors for patients with severe pneumonia was limited. In order to maximize the use of limited medical resources, we should distinguish between mild and severe patients as early as possible. Objective: To systematically review the evidence of risk factors for severe corona virus disease 2019 (COVID-19) patients. Evidence Review: We conducted a comprehensive search for primary literature in both Chinese and English electronic bibliographic data bases including China National Knowledge Infrastructure (CNKI), Wanfang, Weipu, Chinese Biomedicine Literature Database (CBM-SinoMed), MEDLINE (via PubMed), EMBASE, Cochrane Central Register, and Web of science. The American agency for health research and quality (AHRQ) tool were used for assessing risk of bias. Mata-analysis was undertaken using STATA version 15.0. Results: 20 articles (N=4062 participants) were eligible for this systematic review and meta-analysis. First in this review and meta-analysis, we found that elderly male patients with a high body mass index, high breathing rate and a combination of underlying diseases (such as hypertension, diabetes, cardiovascular disease, and chronic obstructive pulmonary disease) were more likely to develop into critically ill patients. second, compared with ordinary patients, severe patients had more significant symptom such as fever and dyspnea. Besides, the laboratory test results of severe patients had more abnormal than non-severe patients, such as the elevated levels of white-cell counts, liver enzymes, lactate dehydrogenase, creatine kinase, c-reactive protein and procalcitonin, etc, while the decreased levels of lymphocytes and albumin, etc. Interpretation: This is the first systematic review investigating the risk factors for severe corona virus disease 2019 (COVID-19) patients. The findings are presented and discussed by different clinical characteristics. Therefore, our review may provide guidance for clinical decision-making and optimizes resource allocation.
Stochastic Compartmental Modelling of SARS-CoV-2 with Approximate Bayesian Computation	Vedant Chandra	2020-04-01	github	covid-19	https://doi.org/10.1101/2020.03.29.20046862	https://www.medrxiv.org/content/10.1101/2020.03.29.20046862v1	AbstractIn this proof-of-concept study, we model the spread of SARS-CoV-2 in various environments with a stochastic susceptible-infectious-recovered (SIR) compartmental model. We fit this model to the latest epidemic data with an approximate Bayesian computation (ABC) technique. Within this SIR-ABC framework, we extrapolate long-term infection curves for several regions and evaluate their steepness. We propose several applications and extensions of the SIR-ABC technique.
Patterns of the COVID19 epidemic spread around the world: exponential vs power laws	Dominik Wodarz;Natalia L. Komarova	2020-04-01	other	covid-19	https://doi.org/10.1101/2020.03.30.20047274	https://www.medrxiv.org/content/10.1101/2020.03.30.20047274v1	"AbstractWe have analyzed the COVID19 epidemic data of more than 174 countries (excluding China) in the period between January 22 and March 28, 2020. We found that some countries (such as the US, the UK, and Canada) follow an exponential epidemic growth, while others (like Italy and several other European countries) show a power law like growth. At the same time, regardless of the best fitting law, most countries can be shown to follow a trajectory similar to that of Italy, but with varying degrees of delay. We found that countries with ``younger"" epidemics tend to exhibit more exponential like behavior, while countries that are closer behind Italy tend to follow a power law growth. We hypothesize that there is a universal growth pattern of this infection that starts off as exponential and subsequently becomes more power law like. Although it cannot be excluded that this growth pattern is a consequence of social distancing measures, an alternative explanation is that it is an intrinsic epidemic growth law, dictated by a spatially distributed community structure, where the growth in individual highly mixed communities is exponential but the longer term, local geographical spread (in the absence of global mixing) results in a power-law. This is supported by computer simulations of a metapopulation model that gives rise to predictions about the growth dynamics that are consistent with correlations found in the epidemiological data. Therefore, seeing a deviation from straight exponential growth may not be a consequence of working non-pharmaceutical interventions (except for, perhaps, restricting the air travel). Instead, this is a normal course of raging infection spread. On the practical side, this cautions us against overly optimistic interpretations of the countries epidemic development and emphasizes the need to continue improving the compliance with social distancing behavior recommendations."
Guideline-based Chinese herbal medicine treatment plus standard care for severe coronavirus disease 2019 (G-CHAMPS): evidence from China	Yong-an Ye;G-CHAMPS collaborative group	2020-04-01	upon request	covid-19	https://doi.org/10.1101/2020.03.27.20044974	https://www.medrxiv.org/content/10.1101/2020.03.27.20044974v1	AbstractAbstract Objectives: To assess outcomes in patients who have severe coronavirus disease 2019 (COVID-19) and were treated with either China guideline based Chinese herbal medicines (CHMs) plus standard care or standard care alone. Design: A pilot randomized controlled trial. Setting Hubei Provincial Hospital of Integrated Chinese and Western Medicine, Wuhan, China Patients: A total of 42 adults with severe COVID-19. Interventions: Participants in the CHM plus standard care group received CHM and standard care, and the control group received standard care alone. Measurements and Main Results: The primary outcome was the change in the disease severity category of COVID-19 after treatment at 7 days. Among 42 participants who were randomized (mean [SD] age 60.43 years [12.69 years]; 21 [50%] were aged ≥ 65 years; and 35 [83%] women, 42 (100%) had data available for the primary outcome. For the primary outcome, one patient from each group died during treatment; the odds of a shift towards death was lower in the CHM plus group than the standard care alone group (common OR 0.59, 95% CI 0.148 to 2.352 P=.454). Three (2 from the CHM plus group and 1 from the standard care alone group) patients progressed from severe to critical illness. After treatment, mild, moderate, and severe COVID-19 disease accounted for 18% (5) vs 14% (2), 71% (20) vs 64% (9), and 0% (0) vs 7% (1) of the patients treated with CHM plus standard care vs. standard care alone. Conclusions: For the first time, the G-CHAMPS trial provided valuable information for the national guideline-based CHM treatment for hospitalized patients with severe COVID-19. CHM effects in COVID-19 may be clinically important and warrant further consideration and studies.
Clinical observations of low molecular weight heparin in relieving inflammation in COVID-19 patients: A retrospective cohort study	CHEN SHI;CONG WANG;HANXIANG WANG;CHAO YANG;FEI CAI;FANG ZENG;FANG CHENG;YIHUI LIU;TAOTAO ZHOU;BIN DENG;JINPING LI;YU ZHANG	2020-04-01	other	covid-19	https://doi.org/10.1101/2020.03.28.20046144	https://www.medrxiv.org/content/10.1101/2020.03.28.20046144v1	AbstractAbstract: Background On March 11, 2020, the World Health Organization declared its assessment of COVID-19 as a global pandemic. Effective therapeutic drugs are urgently needed to improve the overall prognosis of patients, but currently no such drugs are available. Methods Patients in the study were divided into a heparin and a control group based on whether low molecular weight heparin (LMWH) was used. D-dimer, C-reactive protein (CRP), peripheral blood lymphocyte percentage, interleukin-6, and other indices in 42 patients with novel coronavirus pneumonia were retrospectively analyzed to compare and evaluate the progress of patients before and after LMWH treatment. Results Compared to the control group, D-dimer levels in the heparin group significantly increased before treatment, and there was no significant difference after treatment. There was no significant difference in the change of CRP levels between the two groups of patients before and after LMWH treatment, and levels for both groups were significantly lower after, compared to before, treatment. Compared to the control group, patients in the heparin group had a higher percentage of lymphocytes after treatment and lower levels of interleukin-6; these differences were statistically significant. Conclusions Under conventional antiviral treatment regimens, LMWH can improve hypercoagulability, inhibit IL-6 release, and counteract IL-6 biological activity in patients. LMWH has potential antiviral effects and can help delay or block inflammatory cytokine storms. It can also increase the lymphocytes (LYM%)of patients and has the potential for treatment of COVID-19.
Detection of Air and Surface Contamination by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in Hospital Rooms of Infected Patients	Po Ying Chia;Kristen K Coleman;Yian Kim Tan;Sean Wei Xiang Ong;Marcus Gum;Sok Kiang Lau;Stephanie Sutjipto;Pei Hua Lee;Than The Son;Barnaby E. Young;Donald K. Milton;Gregory C. Gray;Stephan Schuster;Timothy Barkham;Partha Prathim De;Shawn Vasoo;Monica Chan;Brenda Sze Peng Ang;Boon Huan Tan;Yee Sin Leo;Oon-Tek Ng;Michelle Su Yen Wong;Kalisvar Marimuthu	2020-04-01	other	covid-19	https://doi.org/10.1101/2020.03.29.20046557	https://www.medrxiv.org/content/10.1101/2020.03.29.20046557v1	AbstractBackground: Understanding the particle size distribution in the air and patterns of environmental contamination of SARS-CoV-2 is essential for infection prevention policies. Objective: To detect the surface and air contamination by SARS-CoV-2 and study the associated patient-level factors. Design: Cross-sectional study. Setting: Airborne infection isolation rooms (AIIRs) at the National Centre for Infectious Diseases, Singapore. Patients: COVID-19 inpatients with a positive PCR test for SARS-CoV-2 within 72 hours before the environmental sampling. Measurements: Extent of environmental surface contamination in AIIRs of 30 COVID-19 patients by PCR on environmental swabs. The particle size distribution of SARS-CoV-2 in the air was measured using NIOSH air samplers. Results: 245 surface samples were collected from 30 rooms of COVID-19 patients, and air sampling was conducted in 3 rooms. 56.7% of the rooms had at least one environmental surface contaminated, with 18.5% of the toilet seats and toilet flush button being contaminated. High touch surface contamination was shown in ten (66.7%) out of 15 patients in the first week of illness, and three (20%) beyond the first week of illness (p = 0.010). Air sampling of two COVID-19 patients (both day 5 of symptoms) detected SARS-CoV-2 PCR-positive particles of sizes >4 μm and 1-4 μm. In a single subject at day 9 of symptoms, no SARS-CoV-2 PCR-positive particles were detected. Limitations: Viral culture results were not available to assess the viability of the virus contaminating the air and surface. Conclusion: Environmental contamination was detected in rooms with COVID-19 patients in early stages of illness, but was significantly less after day 7 of disease. Under AIIR conditions, SARS-CoV-2 respiratory particles can be detected at sizes 1-4 μm and >4 μm in diameter in the air which warrants further studies.
Understanding COVID-19 spreading through simulation modeling and scenarios comparison: preliminary results.	CESAR BORDEHORE;Miriam Navarro;Zaida Herrador;Eva S. Fonfria	2020-04-01	other	covid-19	https://doi.org/10.1101/2020.03.30.20047043	https://www.medrxiv.org/content/10.1101/2020.03.30.20047043v1	AbstractSince late 2019 the world is facing the rapid spreading of a novel viral disease (SARS-CoV-2) provoked by the coronavirus 2 infection (COVID-19), declared pandemic last 12 March 2020. As of 27 March 2020, there were more than 500,000 confirmed cases and 23,335 deaths worldwide. In those places with a rapid growth in numbers of sick people in need of hospitalization and intensive care, this demand has over-saturate the medical facilities and, in turn, rise the mortality rate. In the absence of a vaccine, classical epidemiological measures such as testing, quarantine and physical distancing are ways to reduce the growing speed of new infections. Thus, these measures should be a priority for all governments in order to minimize the morbidity and mortality associated to this disease. System dynamics is widely used in many fields of the biological sciences to study and explain changing systems. The system dynamics approach can help us understand the rapid spread of an infectious disease such as COVID-19 and also generate scenarios to test the effect of different control measures. The aim of this study is to provide an open model (using STELLA® from Iseesystems) that can be customized to any area/region and by any user, allowing them to evaluate the different behavior of the COVID-19 dynamics under different scenarios. Thus, our intention is not to generate a model to accurately predict the evolution of the disease nor to supplant others more robust -official and non-official- from governments and renowned institutions. We believe that scenarios comparison can be an effective tool to convince the society of the need of a colossal and unprecedented effort to reduce new infections and ultimately, fatalities.
COVID-19, City Lockdown, and Air Pollution: Evidence from China	Guojun He;Yuhang Pan;Takanao Tanaka	2020-04-01	upon request	covid-19	https://doi.org/10.1101/2020.03.29.20046649	https://www.medrxiv.org/content/10.1101/2020.03.29.20046649v1	AbstractThe rapid spread of COVID-19 is a global public health challenge. To prevent the escalation of its transmission, China locked down one-third of its cities and strictly restricted human mobility and economic activities. Using timely and comprehensive air quality data in China, we show that these counter-COVID-19 measures led to remarkable improvement in air quality. Within weeks, the Air Quality Index and PM2.5 concentrations were brought down by 25%. The effects are larger in colder, richer, and more industrialized cities. We estimate that such improvement would avert 24,000 to 36,000 premature deaths from air pollution on a monthly basis.
Early surveillance and public health emergency disposal measures between novel coronavirus disease 2019 and avian influenza in China: a case-comparison study	Tiantian Zhang;Wenming Shi;Ying Wang;Ge Bai;Ruiming Dai;Qian Wang;Li Luo	2020-04-01	other	covid-19	https://doi.org/10.1101/2020.03.29.20046490	https://www.medrxiv.org/content/10.1101/2020.03.29.20046490v1	AbstractBackground: The novel coronavirus disease 2019 (COVID-19) outbreak is spreading rapidly throughout China and the world. Hence, early surveillance and public health emergency disposal are considered crucial to curb this emerging infectious disease. However, studies that investigated the early surveillance and public health emergency disposal for the prevention and control of the COVID-19 outbreak in China are relatively few. We aimed to compare the strengths and weaknesses of early surveillance and public health emergency disposal for prevention and control between COVID-19 and H7N9 avian influenza, which was commended by the international community, in China. Methods: A case-comparison study was conducted using a set of six key time nodes to form a reference framework for evaluating early surveillance and public health emergency disposal between H7N9 avian influenza (2013) in Shanghai, China and COVID-19 in Wuhan, China. Findings: A report to the local Center for Disease Control and Prevention, China, for the first hospitalized patient was sent after 6 and 20 days for H7N9 avian influenza and COVID-19, respectively. In contrast, the pathogen was identified faster in the case of COVID-19 than in the case of H7N9 avian influenza (12 days vs. 31 days). The government response regarding COVID-19 was 10 days later than that regarding avian influenza. The entire process of early surveillance and public health emergency disposal lasted 5 days longer in COVID-19 than in H7N9 avian influenza (46 days vs. 41 days). Conclusions: The identification of the unknown pathogen improved in China between the outbreaks of avian influenza and COVID-19. The longer emergency disposal period in the case of COVID-19 could be attributed to the government's slower response to the epidemic. Improving public health emergency management could lessen the adverse social effects of emerging infectious diseases and public health crisis in the future.
A phased lift of control: a practical strategy to achieve herd immunity against Covid-19 at the country level	Sake J de Vlas;Luc E. Coffeng	2020-04-01	gitlab	covid-19	https://doi.org/10.1101/2020.03.29.20046011	https://www.medrxiv.org/content/10.1101/2020.03.29.20046011v1	AbstractMost countries are affected by the Covid-19 pandemic and experience rapidly increasing numbers of cases and deaths. Many have implemented nationwide stringent control to avoid overburdening the health care system. This paralyzes economic and social activities until the availability of a vaccine, which may take years. We propose an alternative exit strategy to develop herd immunity in a predictable and controllable way: a phased lift of control. This means that successive parts of the country (e.g. provinces) stop stringent control, and Covid-19-related IC admissions are distributed over the country as the whole. Importantly, vulnerable individuals need to be shielded until herd immunity has developed in their area. We explore the characteristics and duration of this strategy using a novel individual-based model for geographically stratified transmission of Covid-19 in a country. The model predicts that individuals will have to experience stringent control for about 14 months on average, but this duration may be significantly shortened by future developments (more IC beds, better drugs). Clearly, the strategy will have a profound impact on individuals and society, and should therefore be considered carefully by various other disciplines (e.g. health systems, ethics, economics) before actual implementation.
Analysis of the Worldwide Corona Virus (COVID-19) Pandemic Trend;A Modelling Study to Predict Its Spread	Muhammad Qasim;Waqas Ahmad;Minami Yoshida;Maree Gould;Muhammad Yasir	2020-04-01	other	covid-19	https://doi.org/10.1101/2020.03.30.20048215	https://www.medrxiv.org/content/10.1101/2020.03.30.20048215v1	AbstractObjective: The Coronavirus (COVID-19) has advanced into 197 countries and territories leaving behind a total of 372,757 confirmed cases and 16231 deaths. Methods: One the basis of WHO situation reports data of COVID-19 along with daily official reports from the Japan, China and the Korea we modeled the spread of COVID19 by using the Successive Approximation Method. We defined the two state of data to find the mean ratio (η) of the present cases count to the sum of previous and present cases. This ratio further predicts the future state of COVID-19 pandemic. Results: The mean ratio (η) of expected cases were found 0.485, while the mean ratio for deaths was found to be 0.49. We calculated worldwide expected lower bound value for confirmed cases 247007 cases with maximum limit of 1667719 cases and minimum deaths count 8660 with upper limit of 117397 deaths in next 30 days. While in the case of Iran, a large increase in the number of deaths are expected in the upcoming 30 days with lower bound value of 1140 deaths and maximum value of 598478 deaths. Interpretation: Iran whole population is on risk.
The COVID-19 infection in Italy: a statistical study of an abnormally severe disease	Giuseppe De Natale;Valerio Ricciardi;Gabriele De Luca;Dario De Natale;Giovanni Di Meglio;Antonio Ferragamo;Vito Marchitelli;Andrea Piccolo;Antonio Scala;Renato Somma;Emanuele Spina;Claudia Troise	2020-04-01	other	covid-19	https://doi.org/10.1101/2020.03.28.20046243	https://www.medrxiv.org/content/10.1101/2020.03.28.20046243v1	AbstractWe statistically investigate the COVID-19 epidemics, which is particularly invasive in Italy. We show that the high apparent mortality (or Case Fatality Ratio, CFR) observed in Italy, as compared with other countries, is likely biased by a strong underestimation of infected cases. To give a more realistic estimate of the mortality of Covid-19, we use the most recent estimates of the IFR (Infection Fatality Ratio) of epidemic, based on CFR for Germany, and furthermore analyse data obtained from the ship Diamond Princess, a good representation of a laboratory case-study from an isolated system in which all the people have been tested. From such analyses we try to derive more realistic estimates of the real extension of the infection, as well as more accurate indicators of how fast the infection propagates. We then try to point out, from the various explanations proposed, the dominant factors causing such an abnormal seriousness of the disease in Italy. Finally, we use the deceased data, the only ones estimated to be reliable enough, to predict the total number of infected people and the interval of time when the infection in Italy could stop.
Predicting Mortality Risk in Patients with COVID-19 Using Artificial Intelligence to Help Medical Decision-Making	Mohammad Pourhomayoun;Mahdi Shakibi	2020-04-01	other	covid-19	https://doi.org/10.1101/2020.03.30.20047308	https://www.medrxiv.org/content/10.1101/2020.03.30.20047308v1	AbstractIn the wake of COVID-19 disease, caused by the SARS-CoV-2 virus, we designed and developed a predictive model based on Artificial Intelligence (AI) and Machine Learning algorithms to determine the health risk and predict the mortality risk of patients with COVID-19. In this study, we used documented data of 117,000 patients world-wide with laboratory-confirmed COVID-19. This study proposes an AI model to help hospitals and medical facilities decide who needs to get attention first, who has higher priority to be hospitalized, triage patients when the system is overwhelmed by overcrowding, and eliminate delays in providing the necessary care. The results demonstrate 93% overall accuracy in predicting the mortality rate. We used several machine learning algorithms including Support Vector Machine (SVM), Artificial Neural Networks, Random Forest, Decision Tree, Logistic Regression, and K-Nearest Neighbor (KNN) to predict the mortality rate in patients with COVID-19. In this study, the most alarming symptoms and features were also identified. Finally, we used a separate dataset of COVID-19 patients to evaluate our developed model accuracy, and used confusion matrix to make an in-depth analysis of our classifiers and calculate the sensitivity and specificity of our model.
THE EMOTIONAL IMPACT OF THE ASRM GUIDELINES ON FERTILITY PATIENTS DURING THE COVID-19 PANDEMIC	Jenna M Turocy;Alex Robles;Daniel Hercz;Mary D'Alton;Eric J Forman;Zev Williams	2020-04-01	upon request	covid-19	https://doi.org/10.1101/2020.03.29.20046631	https://www.medrxiv.org/content/10.1101/2020.03.29.20046631v1	AbstractObjective: To survey fertility patients' agreement with ASRM recommendations during the COVID-19 pandemic and the emotional impact on them. Design: An online survey was sent to current fertility patients Setting: New York City academic fertility practice at the epicenter of the COVID-19 pandemic Patient(s): Fertility patients seen within the last year Intervention(s): None Main Outcome Measure(s): Patient agreement with the ASRM recommendations during the COVID-19 pandemic and the emotional impact rated on a Likert scale Result(s): A total of 518 patients completed the survey for a response rate of 17%. Fifty percent of respondents had a cycle canceled due to the COVID-19 pandemic. Of those who had a cycle cancelled, 85% of respondents found it to be moderately to extremely upsetting with 22% rating it to be equivalent to the loss of a child. There was no difference on the emotional impact based on the type of cycle cancelled. Fifty-five percent of patients agreed that diagnostic procedures such as hysterosalpingograms should be cancelled while 36% of patients agreed all fertility cycles should be cancelled. Patients were slightly more likely to agree with the ASRM guidelines if they have an upcoming cycle cancelled (p = 0.041). Of all respondents 82% would have preferred to have the option to start a treatment cycle in consultation with their doctor. Conclusion(s): Given the severity of the COVID-19 pandemic, the physical, financial and emotional impact of this unprecedented threat cannot be underestimated in our fertility patients. Key Word(s): COVID-19, novel coronavirus, ASRM, mental health, infertility
Demand for hospitalization services for COVID-19 patients in Brazil	Marcia C Castro;Lucas Resende de Carvalho;Taylor Chin;Rebecca Kahn;Giovanny V. A. Franca;Eduardo Marques Macario;Wanderson Kleber de Oliveira	2020-04-01	github	covid-19	https://doi.org/10.1101/2020.03.30.20047662	https://www.medrxiv.org/content/10.1101/2020.03.30.20047662v1	AbstractCOVID-19 is now a pandemic and many of the affected countries face severe shortages of hospital resources. In Brazil, the first case was reported on February 26. As the number of cases grows in the country, there is a concern that the health system may become overwhelmed, resulting in shortages of hospital beds, intensive care unit beds, and mechanical ventilators. The timing of shortage is likely to vary geographically depending on the observed onset and pace of transmission observed, on the availability of resources, and on the actions implemented. Here we consider the daily number of cases reported in municipalities in Brazil to simulate twelve alternative scenarios of the likely timing of shortage, based on parameters consistently reported for China and Italy, on rates of hospital occupancy for other health conditions observed in Brazil in 2019, and on assumptions of allocation of patients in public and private facilities. Results show that hospital services could start to experience shortages of hospital beds, ICU beds, and ventilators in early April, the most critical situation observed for ICU beds. Increasing the allocation of beds for COVID-19 (in lieu of other conditions) or temporarily placing all resources under the administration of the state delays the anticipated start of shortages by a week. This suggests that solutions adopted by the Brazilian government must aim at expanding the available capacity (e.g., makeshift hospitals), and not simply prioritizing the allocation of available resources to COVID-19.
Impact of COVID-19 on psychiatric assessment in emergency and outpatient settings measured using electronic health records	Victor M. Castro;Roy H Perlis	2020-04-01	other	covid-19	https://doi.org/10.1101/2020.03.30.20048207	https://www.medrxiv.org/content/10.1101/2020.03.30.20048207v1	AbstractImportance: As with other traumatic events, pandemics such as coronavirus-19 (COVID-19) may precipitate or exacerbate psychiatric symptoms such as anxiety and depression, while potentially interfering with health systems' capacity to treat such symptoms. Objective: To quantify the impact of increasing COVID-19 infection on extent of psychiatric assessment across 5 Eastern Massachusetts hospitals. Design: In silico cohort using narrative clinical notes generated between 1/2/2020 and 3/25/2020 Setting: Emergency department and outpatient settings from 2 academic medical centers and 3 community hospitals Participants: All individuals age 13 and older presenting to emergency department or outpatient clinics Main Outcome or Measure: Documentation of psychiatric symptoms reflecting depression, anxiety, psychosis, or suicide, and documentation of violence, was drawn from previously-validated term lists. Results: A total of 2,483,159 outpatient and 205,957 emergency department visit notes were analyzed. Instances of notes referencing depression or anxiety decreased 75-81% in outpatient settings with onset of coronavirus in March 2019, and by 44-45% in emergency departments. In adjusted logistic regression, presence of individual psychiatric symptoms in outpatient notes was associated with significant decreases in likelihood of coronavirus testing (for depression, OR=0.636, 95% CI 0.606-0.667). Conversely, presence of violence in an emergency department note was associated with greater likelihood of testing (OR=1.487, 95% CI 1.249-1.761). Conclusions and Relevance: Documentation of psychiatric symptoms in both outpatient and emergency department settings diminished sharply in the context of increasing coronavirus infection in Massachusetts, suggesting that efforts to provide additional resources to manage psychiatric symptoms will be needed. Funding: none.
Perception of emergent epidemic of COVID-2019 / SARS CoV-2 on the Polish Internet	Andrzej Jarynowski;Monika Wojta-Kempa;Vitaly Belik	2020-04-01	github	covid-19	https://doi.org/10.1101/2020.03.29.20046789	https://www.medrxiv.org/content/10.1101/2020.03.29.20046789v1	AbstractProblem: Due to the spread of SARS CoV-2 virus infection and COVID-2019 disease, there is an urgent need to analyze COVID-2019 epidemic perception in Poland. This would enable authorities for preparation of specific actions minimizing public health and economic risks. Methods: We study the perception of COVID-2019 epidemic in Polish society using quantitative analysis of its digital footprints on the Internet (on Twitter, Google, YouTube, Wikipedia and electronic media represented by Event Registry) from January 2020 to 12.03.2020 (before and after official introduction to Poland on 04.03.2020). To this end we utilize data mining, social network analysis, natural language processing techniques. Each examined internet platform was analyzed for representativeness and composition of the target group. Results: We identified three major cluster of the interest before disease introduction on the topic COVID-2019: China- and Italy-related peaks on all platforms, as well as a peak on social media related to the recent special law on combating COVID-2019. Besides, there was a peak in interest on the day of officially confirmed introduction as well as an exponential increase of interest when the Polish government declared war against disease with a massive mitigation program. From sociolingistic perspective, we found that concepts and issues of threat, fear and prevention prevailed before introduction. After introduction, practical concepts about disease and epidemic dominate. Twitter reflected the clear, structural division of the Polish political sphere. We were able to identify potential sources of misinformation as well as key actors (especially early adopters) and influencers. Conclusions: Traditional and social media not only reflect reality, but also create it. Polish authorities, having a reliable analysis of the perception of the problem, could optimally prepare and manage the social dimension of the current epidemic and future ones. Due to filter bubbles observed on Twitter, public information campaigns might have less impact on society than expected. For greater penetration, it might be necessary to diversify information channels to reach as many people as possible which might already be happening. Moreover, it might be necessary to prevent the spread of disinformation, which is now possible due to the special law on combating COVID-2019.
Transmission Dynamics of COVID-19 and Impact on Public Health Policy	B Shayak;Mohit Manoj Sharma;Richard H Rand;Awadhesh Kumar Singh;Anoop Misra	2020-04-01	other	covid-19	https://doi.org/10.1101/2020.03.29.20047035	https://www.medrxiv.org/content/10.1101/2020.03.29.20047035v1	AbstractIn this work we construct a mathematical model for the transmission and spread of coronavirus disease 2019 or COVID-19. Our model features delay terms to account for (a) the time lapse or latency period between contracting the disease and displaying symptoms, and (b) the time lag in testing patients for the virus due to the limited numbers of testing facilities currently available. We find that the delay introduces a significant disparity between the actual and reported time-trajectories of cases in a particular region. Specifically, the reported case histories lag the actual histories by a few days. Hence, to minimize the spread of the disease, lockdowns and similarly drastic social isolation measures need to be imposed some time before the reported figures are approaching their peak values. We then account for the social reality that lockdowns can only be of a limited duration in view of practical considerations. We find that the most effective interval for imposing such a limited-time lockdown is one where the midpoint of the lockdown period coincides with the actual peak of the spread of the disease in the absence of the lockdown. We further show that the true effectivity of imposing a lockdown may be misrepresented and grossly underestimated by the reported case trajectories in the days following the action.
Early behavior of Madrid Covid-19 disease outbreak: A mathematical model	Daniel Garcia-Iglesias;Francisco Javier de Cos Juez	2020-04-01	other	covid-19	https://doi.org/10.1101/2020.03.30.20047019	https://www.medrxiv.org/content/10.1101/2020.03.30.20047019v1	AbstractIntroduction: Madrid Covid-19 disease outbreak started on 28 February 2020 and since then it became the main Covid-19 disease cluster in Spain. On 26 March 2020, a total of 17166 cases were already reported, with 2090 deaths. Globally a R0 index of 2-3 has been reported. We aimed to build an experimental mathematical model that help to analyze the early characteristics of Madrid Covid-19 disese outbreak and to explore the actual R0 index on Madrid Covid-19 outbreak. Material and Methods: A simulated mathematical model was built, based on a SIR epidemiological model and the reported characteristics of Wuhan Covid-19 disease outbreak. Monte Carlo simulations were further done to estimate the R0 value over time in the Madrid Covid-19 disease outbreak. Results: Mean estimated R0 value along the early period is of 2.22 (+/- 1.21 SD). A significant increase of 0.093 (+/- 0.037, p=0.025) in R0 value each day of outbreak is found. Conclussions: Our proposed Mathematical Simulation model may be useful to evaluate early characteristics of this outbreak. The present work is the first reported estimation of R0 value in the Spanish Madrid Covid-19 outbreak, with similar results to the previous reported in the Wuhan outbreak, although it may suggest a slightly increase on R0 along time.
Transmission Dynamics and Control Methodology of COVID-19: a Modeling Study	Hongjun Zhu	2020-04-01	other	covid-19	https://doi.org/10.1101/2020.03.29.20047118	https://www.medrxiv.org/content/10.1101/2020.03.29.20047118v1	AbstractThe coronavirus disease 2019 (COVID-19) has grown up to be a pandemic within a short span of time. To investigate transmission dynamics and then determine control methodology, we took epidemic in Wuhan as a study case. Unfortunately, to our best knowledge, the existing models are based on the common assumption that the total population follows a homogeneous spatial distribution, which is not the case for the prevalence occurred both in the community and in hospital due to the difference in the contact rate. To solve this problem, we propose a novel epidemic model called SEIR-HC, which is a novel epidemic model with two different social circles. Using the model alongside the exclusive optimization algorithm, the spread process of COVID-19 epidemic in Wuhan city is reproduced and then the propagation characteristics and unknown data are estimated. Furthermore, the control measures implemented in Wuhan are assessed and the control methodology of COVID-19 is discussed to provide guidance for limiting the epidemic spread.
Classification of COVID-19 in chest X-ray images using DeTraC deep convolutional neural network	Asmaa Abbas;Mohammed Abdelsamea;Mohamed Gaber	2020-04-01	github	covid-19	https://doi.org/10.1101/2020.03.30.20047456	https://www.medrxiv.org/content/10.1101/2020.03.30.20047456v1	AbstractChest X-ray is the first imaging technique that plays an important role in the diagnosis of COVID-19 disease. Due to the high availability of large-scale annotated image datasets, great success has been achieved using convolutional neural networks (CNNs) for image recognition and classification. However, due to the limited availability of annotated medical images, classification of medical images remains the biggest challenge in medical diagnosis. Thanks to transfer learning, an effective mechanism that can provide a promising solution by transferring knowledge from generic object recognition tasks to domain-specific tasks. In this paper, we validate and adopt our previously developed CNN, called Decompose, Transfer, and Compose (DeTraC), for the classification of COVID-19 chest X-ray images. DeTraC can deal with any irregularities in the image dataset by investigating its class boundaries using a class decomposition mechanism. The experimental results showed the capability of DeTraC in the detection of COVID-19 cases from a comprehensive image dataset collected from several hospitals around the world. A high accuracy of 95.12% (with sensitivity of 97.91%, specificity of 91.87%, and precision of 93.36%) was achieved by DeTraC in the detection of COVID-19 X-ray images from normal, and severe acute respiratory syndrome cases.
Optimal timing for social distancing during an epidemic	Oscar Patterson-Lomba	2020-04-01	other	covid-19	https://doi.org/10.1101/2020.03.30.20048132	https://www.medrxiv.org/content/10.1101/2020.03.30.20048132v1	AbstractSocial distancing is an effective way to contain the spread of a contagious disease, particularly when pharmacological interventions are not available. Conventional wisdom suggests that social distancing measures should be introduced as soon as possible after the beginning of an outbreak. Using a simple epidemiological model we show, however, that there is in fact an optimal time to initiate a temporal social distancing intervention if the goal is to reduce the final epidemic size or flatten the epidemic curve. The optimal timing depends strongly on the effective reproduction number (R0) of the disease, such that as the R0 increases, the optimal time decreases non-linearly. Additionally, if pharmacological interventions (e.g., a vaccine) become available at some point during the epidemic, the sooner these interventions become available the sooner social distancing should be initiated to maximize its effectiveness. Although based on a simple model, we hope that these insights inspire further investigations within the context of more complex and data-driven epidemiological models, and can ultimately help decision makers to improve temporal social distancing policies to mitigate the spread of epidemics.
Assessing the interactions between COVID-19 and influenza in the United States	Casey M Zipfel;Shweta Bansal	2020-04-01	other	covid-19	https://doi.org/10.1101/2020.03.30.20047993	https://www.medrxiv.org/content/10.1101/2020.03.30.20047993v1	AbstractThe 2019-2020 influenza sentinel surveillance data exhibits unexpected trends. Typical influenza seasons have a small herald wave, followed by a decrease due to school closure during holidays, and then a main post-holiday peak that is significantly larger than the pre-holiday wave. During the 2019-2020 influenza season, influenza-like illness data in the United States appears to have a markedly lower main epidemic peak compared to what would be expected based on the pre-holiday peak. We hypothesize that the 2019-2020 influenza season does have a lower than expected burden and that this deflation is due to a behavioral or ecological interaction with COVID-19. We apply an intervention analysis to assess if this influenza season deviates from expectations, then we compare multiple hypothesized drivers of the decrease in influenza in a spatiotemporal regression model. Lastly, we develop a mechanistic metapopulation model, incorporating transmission reduction that scales with COVID-19 risk perception. We find that the 2019-2020 ILI season is smaller and decreases earlier than expected based on prior influenza seasons, and that the increase in COVID-19 risk perception is associated with this decrease. Additionally, we find that a 5% average reduction in transmission is sufficient to reproduce the observed flu dynamics. We propose that precautionary behaviors driven by COVID-19 risk perception or increased isolation driven by undetected COVID-19 spread dampened the influenza season. We suggest that when surveillance for a novel pathogen is limited, surveillance streams of co-circulating infections may provide a signal.
COVID-19 Epidemic in Switzerland: Growth Prediction and Containment Strategy Using Artificial Intelligence and Big Data	Reza S. Abhari;Marcello Marini;Ndaona Chokani	2020-04-01	other	covid-19	https://doi.org/10.1101/2020.03.30.20047472	https://www.medrxiv.org/content/10.1101/2020.03.30.20047472v1	AbstractUsing a previously developed agent-based artificial intelligence simulation platform (EnerPol) coupled with Big Data, the evolution and containment of COVID-19 in Switzerland is examined. The EnerPol platform has been used in a broad range of case studies in different sectors in all of Europe, USA, Japan, South Korea and sub Saharan Africa over the last 10 years. In the present study, the entire Swiss population (8.57 million people), including cross-border commuters, and the entire Swiss public and private transport network that is simulated to assess transmission of the COVID-19 virus. The individual contacts within the population, and possible transmission pathways, are established from a simulation of daily activities that are calibrated with micro-census data. Various governmental interventions with regards to closures and social distancing are also implemented. The epidemiology of the COVID-19 virus is based on publicly available statistical data and adapted to Swiss demographics. The predictions estimate that between 22 February and 11 April 2020, there will be 720 deaths from 83300 COVID-19 cases, and 73300 will have recovered; our preliminary variability in these estimates is about 21% over the aforementioned period. In the absence of governmental intervention, 42.7% of the Swiss population would have been infected by 25 April 2020 compared to our prediction of a 1% infection over this time period, saving thousands of lives. It is argued that future scenarios regarding relaxation of the lockdown should be carefully simulated, as by 19 April 2020, there will still remain a substantial number of infected individuals, who could retrigger a second spread of COVID-19. Through the use of a digital tool, such as Enerpol, to evaluate in a data-driven manner the impacts of various policy scenarios, the most effective measures to mitigate a spread of COVID-19 can be devised while we await the deployment of large-scale vaccination for the population globally. By tailoring the spatio-temporal characteristics of the spread to match the capacity of local healthcare facilities, appropriate logistic needs can be determined, in order not to overwhelm the health care services across the country.
Why is chest CT important for early diagnosis of COVID-19? Prevalence matters	Antonio Esposito;Anna Palmisano;Giulia Maria Scotti;Marco Jacopo Morelli;Davide Vignale;Francesco De Cobelli;Giovanni Tonon;Carlo Tacchetti	2020-04-01	other	covid-19	https://doi.org/10.1101/2020.03.30.20047985	https://www.medrxiv.org/content/10.1101/2020.03.30.20047985v1	AbstractSARS-CoV-2 viral infection is a global pandemic disease (COVID-19). Reaching a swift, reliable diagnosis of COVID-19 in the emergency departments is imperative to direct patients to proper care and to prevent disease dissemination. COVID-19 diagnosis is based on the identification of viral RNA through RT-PCR from oral-nasopharyngeal swabs, which however presents suboptimal sensitivity and may require several hours in overstressed laboratories. These drawbacks have called for an additional, complementary first line approach. CT is the gold standard method for the detection of interstitial pneumonia, a hallmark feature of COVID-19, often present in the asymptomatic stage of the disease. Here, we show that CT scan presents a sensitivity of 95.48% (std.err=0.35%), vastly outperforming RT-PCR. Additionally, as diagnostic accuracy is influenced by disease prevalence, we argue that predictive values provide a more precise measure of CT reliability in the current pandemics. We generated a model showing that CT scan is endowed with a high negative predictive value (> 90%) and positive predictive value (69 - 84%), for the range of prevalence seen in countries with rampant dissemination. We conclude that CT is an expedite and reliable diagnostic tool to support first line triage of suspect COVID-19 patients in areas where the diffusion of the virus is widespread.
How will this continue? Modelling interactions between the COVID-19 pandemic and policy responses	Axel G Rossberg;Robert J. Knell	2020-04-01	github	covid-19	https://doi.org/10.1101/2020.03.30.20047597	https://www.medrxiv.org/content/10.1101/2020.03.30.20047597v1	AbstractMuch of the uncertainty about the progression of the COVID-19 pandemic stems from questions about when and how non-pharmaceutical interventions (NPI) by governments, in particular social distancing measures, are implemented, to what extent the population complies with these measures, and how compliance changes through time. Further uncertainty comes from a lack of knowledge of the potential effects of removing interventions once the epidemic is declining. By combining an epidemiological model of COVID-19 for the United Kingdom with simple sub-models for these societal processes, this study aims to shed light on the conceivable trajectories that the pandemic might follow over the next 1.5 years. We show strong improvements in outcomes if governments review NPI more frequently whereas, in comparison, the stability of compliance has surprisingly small effects on cumulative mortality. Assuming that mortality does considerably increase once a country's hospital capacity is breached, we show that the inherent randomness of societal processes can lead to a wide range of possible outcomes, both in terms of disease dynamics and mortality, even when the principles according to which policy and population operate are identical.. Our model is easily modified to take other aspects of the socio-pandemic interaction into account.
The Institutional and Cultural Context of Cross-National Variation in COVID-19 Outbreaks	Wolfgang Messner	2020-04-01	other	covid-19	https://doi.org/10.1101/2020.03.30.20047589	https://www.medrxiv.org/content/10.1101/2020.03.30.20047589v1	AbstractBackground. The COVID-19 pandemic poses an unprecedented and cascading threat to the health and economic prosperity of the world's population. Objectives. To understand whether the institutional and cultural context influences the COVID-19 outbreak. Methods. At the ecological level, regression coefficients are examined to figure out contextual variables influencing the pandemic's exponential growth rate across 96 countries. Results. While a strong institutional context is negatively associated with the outbreak (B = -0.55 ... -0.64, p < 0.001), the pandemic's growth rate is steeper in countries with a quality education system (B = 0.33, p < 0.001). Countries with an older population are more affected (B = 0.46, p < 0.001). Societies with individualistic (rather than collectivistic) values experience a flatter rate of pathogen proliferation (B = -0.31, p < 0.001), similarly for higher levels of power distance (B = -0.32, p < 0.001). Hedonistic values, that is seeking indulgence and not enduring restraints, are positively related to the outbreak (B = 0.23, p = 0.001). Conclusions. The results emphasize the need for public policy makers to pay close attention to the institutional and cultural context in their respective countries when instigating measures aimed at constricting the pandemic's growth.
Global versus focused isolation during the SARS-CoV-2 pandemic-A cost-effectiveness analysis	Amir Shlomai;Ari Leshno;Ella H Sklan;Moshe Leshno	2020-04-01	other	covid-19	https://doi.org/10.1101/2020.03.30.20047860	https://www.medrxiv.org/content/10.1101/2020.03.30.20047860v1	AbstractBackground: The novel coronavirus (SARS-CoV-2) pandemic is driving many countries to adopt global isolation measures in an attempt to slow-down its spread. These extreme measures are associated with extraordinary economic costs. Objective: To compare the cost-effectiveness of global isolation of the whole population to focused isolation of individuals at high risk of being exposed, augmented by thorough PCR testing. Design: We applied a modified Susceptible, Exposed, Infectious, Removed (SEIR) model to compare two different strategies in controlling the SARS-CoV-2 spread. Data sources and target population: We modeled the dynamics in Israel, a small country with ~ 9 million people. Time horizon: 200 days. Interventions: 1. Global isolation of the whole population (strategy 1) 2. Focused isolation of people at high risk of exposure with extensive PCR testing (strategy 2). Outcome measures: Number of deaths and the cost per one avoided death in strategy 1 vs 2. Results of Base-Case analysis: The number of expected deaths is 389 in strategy 1 versus 432 in strategy 2. The incremental cost-effectiveness ratio (ICER) in case of adhering to global isolation will be $ 102,383,282 to prevent one case of death. Results of sensitivity analysis: The ICER value is between $ 22.5 million to over $280 million per one avoided death. Conclusions: According to our model, global isolation will save ~43 more lives compared to a strategy of focused isolation and extensive screening. This benefit is implicated in tremendous costs that might result in overwhelming economic effects. Limitations: Compartment models do not necessarily fit to countries with heterogeneous populations. In addition, we rely on current published parameters that might not reliably reflect infection dynamics.
Forecasting the CoViD19 Diffusion in Italy and the Related Occupancy of Intensive Care Units	Livio Fenga	2020-04-01	other	covid-19	https://doi.org/10.1101/2020.03.30.20047894	https://www.medrxiv.org/content/10.1101/2020.03.30.20047894v1	AbstractThis paper provides a model based method for the forecast of the total number of currently CoVoD19 positive individuals and of the occupancy of the available Intensive Care Units in Italy. The predictions obtained, for a time horizon of 10 days starting from March 29th, will be provided at a national as well as at a more disaggregate levels, following a criterion based on the magnitude of the phenomenon. While the Regions which have been hit the most by the pandemic have been kept separated, the less affected ones have been aggregated into homogeneous macroareas. Results show that , within the forecast period considered (March 29th April 7th ) , all of the Italian regions will show a decreasing number of CoViD-19 positive people. Same for the number of people who will need to be hospitalized in a Intensive Care Unit (ICU). These estimates are valid under constancy of the Government s current containment policies. In this scenario, Northern Regions will remain the most affected ones and no significant outbreak are foreseen in the southern regions.
Analytical sensitivity and efficiency comparisons of SARS-COV-2 qRT-PCR assays	Chantal B.F. Vogels;Anderson F. Brito;Anne Louise Wyllie;Joseph R Fauver;Isabel M. Ott;Chaney C. Kalinich;Mary E. Petrone;Marie-Louise Landry;Ellen F. Foxman;Nathan D. Grubaugh	2020-04-01	other	covid-19	https://doi.org/10.1101/2020.03.30.20048108	https://www.medrxiv.org/content/10.1101/2020.03.30.20048108v1	"AbstractThe recent spread of severe acute respiratory syndrome coronavirus (SARS-CoV-2) exemplifies the critical need for accurate and rapid diagnostic assays to prompt public health actions. Currently, several quantitative reverse-transcription polymerase chain reaction (qRT-PCR) assays are being used by clinical, research, and public health laboratories for rapid detection of the virus. However, it is currently unclear if results from different tests are comparable. Our goal was to evaluate the primer-probe sets used in four common diagnostic assays available on the World Health Organization (WHO) website. To facilitate this effort, we generated RNA transcripts to create standards and distributed them to other laboratories for internal validation. We then used these RNA transcript standards, full-length SARS-CoV-2 RNA, and RNA-spiked mock samples to determine analytical efficiency and sensitivity of nine primer-probe sets. We show that all primer-probe sets can be used to detect SARS-CoV-2, but there are clear differences in the ability to differentiate between true negatives and positives with low amounts of virus. Adding to this, many primer-probe sets, including the ""N2"" and ""N3"" sets issued by the US Centers for Disease Control and Prevention, have background amplification with SARS-CoV-2-negative nasopharyngeal swabs, which may lead to inconclusive results. Our findings characterize the limitations of commonly used primer-probe sets and can assist other laboratories in selecting appropriate assays for the detection of SARS-CoV-2."
Estimating the risk of COVID-19 death during the course of the outbreak in Korea, February-March, 2020	Eunha Shim;Kenji Mizumoto;Wongyeong Choi;Gerardo Chowell	2020-04-01	other	covid-19	https://doi.org/10.1101/2020.03.30.20048264	https://www.medrxiv.org/content/10.1101/2020.03.30.20048264v1	AbstractBackground: In Korea, a total of 8,799 confirmed cases of COVID-19 including 102 deaths have been recorded as of Mar 21, 2020. The time-delay adjusted case fatality risk of COVID-19 in Korea is yet to be estimated. Methods: We obtained the daily series of confirmed cases and deaths in Korea reported prior to March 21,2020. Using statistical methods, we estimated the time-delay adjusted risk for death from COVID-19 in the city of Daegu, Gyeongsangbuk-do, other regions in Korea, as well as for the entire country. Results: Our model-based crude CFR fitted the observed data well throughout the course of the epidemic except for the very early stage in Gyeongsangbuk-do, partially due to the reporting delay. Our estimates of the risk for death in Gyeongsangbuk-do reached 2.4% (95% CrI: 1.6-3.4%), 1.3% (95% CrI: 1.0-1.6%) in Daegu and 0.7% (95% CrI: 0.3-1.4%) in other regions, whereas the national estimate of the risk for death was estimated at 1.4% (95% CrI: 1.2-1.7%) in Korea. Conclusions: The relatively low CFRs are associated with the early implementation of public health interventions including widespread testing, social distancing, and delayed school openings in Korea. Geographic differences in CFR are likely influenced by clusters of nosocomial transmission.
Early Spread of SARS-Cov-2 in the Icelandic Population	Daniel F Gudbjartsson;Agnar Helgason;Hakon Jonsson;Olafur T Magnusson;Pall Melsted;Gudmundur L Norddahl;Jona Saemundsdottir;Asgeir Sigurdsson;Patrick Sulem;Arna B Agustsdottir;Berglind Eiriksdottir;Run Fridriksdottir;Elisabet E Gardarsdottir;Gudmundur Georgsson;Olafia S Gretarsdottir;Kjartan R Gudmundsson;Thora R Gunnarsdottir;Arnaldur Gylfason;Hilma Holm;Brynjar O Jensson;Aslaug Jonasdottir;Frosti Jonsson;Kamilla S Josefsdottir;Thordur Kristjansson;Droplaug N Magnusdottir;Louise le Roux;Gudrun Sigmundsdottir;Gardar Sveinbjornsson;Kristin E Sveinsdottir;Maney Sveinsdottir;Emil A Thorarensen;Bjarni Thorbjornsson;Arthur Love;Gisli Masson;Ingileif Jonsdottir;Alma Moller;Thorolfur Gudnason;Karl G Kristinsson;Unnur Thorsteinsdottir;Kari Stefansson	2020-03-31	other	covid-19	https://doi.org/10.1101/2020.03.26.20044446	https://www.medrxiv.org/content/10.1101/2020.03.26.20044446v2	AbstractBACKGROUND Limited data exist on how SARS-CoV-2 enters and spreads in the general population. METHODS We used two strategies for SARS-CoV-2 testing: targeted testing of high-risk individuals (n=4,551) and a population screening (n=5,502). We sequenced SARS-CoV-2 from 340 individuals. RESULTS On March 22 2020, 528 had tested positive for SARS-CoV-2 in the targeted testing (11.6%) and 50 in the population screening (0.9%); approximately 0.2% of the Icelandic population. Large fractions of positives had travelled outside Iceland (38.4% and 34.0%). Fewer under 10 years old were positive than those older: 2.8% vs. 12.3% for targeted testing (P=1.6e-9) and 0.0% vs. 1.0% for population screening (P=0.031). Fewer females were positive in the targeted testing than males (9.5% vs. 14.6%, P=6.8e-9). SARS-CoV-2 came from eight clades, seven A clades and one B clade. The clade composition differed between the testing groups and changed with time. In the early targeted testing, 65.0% of clades were A2a1 and A2a2 derived from Italian and Austrian skiing areas, but in the later targeted testing went down to 30.6% and were overtaken by A1a and A2a, the most common clades in the population screening. CONCLUSION SARS-CoV-2 has spread widely in Iceland outside of the high-risk groups. Several strains cause these infections and their relative contribution changed rapidly. Children and females are less vulnerable than adults and males. To contain the pandemic we must increase the scope of the testing.
Efficacy of hydroxychloroquine in patients with COVID-19: results of a randomized clinical trial	Zhaowei Chen;Jijia Hu;Zongwei Zhang;Shan Jiang;Shoumeng Han;Dandan Yan;Ruhong Zhuang;Ben Hu;Zhan Zhang	2020-03-31	other	covid-19	https://doi.org/10.1101/2020.03.22.20040758	https://www.medrxiv.org/content/10.1101/2020.03.22.20040758v2	AbstractAims: Studies have indicated that chloroquine (CQ) shows antagonism against COVID-19 in vitro. However, evidence regarding its effects in patients is limited. This study aims to evaluate the efficacy of hydroxychloroquine (HCQ) in the treatment of patients with COVID-19. Main methods: From February 4 to February 28, 2020, 62 patients suffering from COVID-19 were diagnosed and admitted to Renmin Hospital of Wuhan University. All participants were randomized in a parallel-group trial, 31 patients were assigned to receive an additional 5-day HCQ (400 mg/d) treatment, Time to clinical recovery (TTCR), clinical characteristics, and radiological results were assessed at baseline and 5 days after treatment to evaluate the effect of HCQ. Key findings: For the 62 COVID-19 patients, 46.8% (29 of 62) were male and 53.2% (33 of 62) were female, the mean age was 44.7 (15.3) years. No difference in the age and sex distribution between the control group and the HCQ group. But for TTCR, the body temperature recovery time and the cough remission time were significantly shortened in the HCQ treatment group. Besides, a larger proportion of patients with improved pneumonia in the HCQ treatment group (80.6%, 25 of 32) compared with the control group (54.8%, 17 of 32). Notably, all 4 patients progressed to severe illness that occurred in the control group. However, there were 2 patients with mild adverse reactions in the HCQ treatment group. Significance: Among patients with COVID-19, the use of HCQ could significantly shorten TTCR and promote the absorption of pneumonia.
SARS-CoV-2 infection in 86 healthcare workers in two Dutch hospitals in March 2020	Marjolein Kluytmans;Anton Buiting;Suzan Pas;Robbert Bentvelsen;Wouter van den Bijllaardt;Anne van Oudheusden;Miranda van Rijen;Jaco Verweij;Marion Koopmans;Jan Kluytmans	2020-03-31	upon request	covid-19	https://doi.org/10.1101/2020.03.23.20041913	https://www.medrxiv.org/content/10.1101/2020.03.23.20041913v3	AbstractBackground On February 27, 2020, the first patient with COVID-19 was reported in the Netherlands. During the following weeks, nine healthcare workers (HCWs) were diagnosed with COVID-19 in two Dutch teaching hospitals, eight of whom had no history of travel to China or Northern-Italy. A low-threshold screening regimen was implemented to determine the prevalence and clinical presentation of COVID-19 among HCWs in these two hospitals. Methods HCWs who suffered from fever or respiratory symptoms were voluntarily tested for SARS-CoV-2 by real-time reverse-transcriptase PCR on oropharyngeal samples. Structured interviews were conducted to document symptoms for all HCWs with confirmed COVID-19. Findings Thirteen-hundred fifty-three (14%) of 9,705 HCWs employed were tested, 86 (6%) of whom were infected with SARS-CoV-2. Most HCWs suffered from relatively mild disease and only 46 (53%) reported fever. Seventy-nine (92%) HCWs met a case definition of fever and/or coughing and/or shortness of breath. None of the HCWs identified through the screening reported a travel history to China or Northern Italy, and 3 (3%) reported to have been exposed to an inpatient known with COVID-19 prior to the onset of symptoms. Interpretation Within two weeks after the first Dutch case was detected, a substantial proportion of HCWs with fever or respiratory symptoms were infected with SARS-CoV-2, probably caused by acquisition of the virus in the community during the early phase of local spread. The high prevalence of mild clinical presentations, frequently not including fever, asks for less stringent use of the currently recommended case-definition for suspected COVID-19.
Global, Regional and National Incidence and Case-fatality rates of Novel Coronavirus (COVID-19) across 154 countries and territories: A systematic assessment of cases reported from January to March 16, 2020	Akshaya Srikanth Bhagavathula;Jamal Rahmani;Wafa Ali Aldhaleei;Pavan Kumar;Alessandro Rovetta	2020-03-31	other	covid-19	https://doi.org/10.1101/2020.03.26.20044743	https://www.medrxiv.org/content/10.1101/2020.03.26.20044743v2	AbstractBackground: The 2019 novel coronavirus disease (COVID-19) outbreak turned into a pandemic, with hundreds of thousands of cases reported globally. The number of cases dramatically increased beginning in early March 2020. Aim: We assessed the cumulative change in the incidence and case-fatality rates of COVID-19 at the global, regional, and national levels from January to March 16, 2020, in 154 affected countries and territories globally. Methods: We collected data of COVID-19 cases using the GitHub repository, which provided real-time surveillance information developed by the Center for Systems Science and Engineering (CSSE), Johns Hopkins University (USA). Information such as confirmed COVID-19 cases, deaths, and recoveries reported across all affected countries was collected from January 22 to March 16, 2020. We estimated the change in the incidence rate, case-fatality rate, and recovery rate from January 22 to February 29 and from March 1 to March 16, 2020. Results: From January 22 to March 16, 2020, globally, the number of incident COVID-19 cases increased by 276.2%, and Europe recorded 65,281 new cases from March 1 to 16, 2020. Overall, the case-fatality rate was 3.92%, with a high COVID-19 fatality rate in Italy (7.7%), Iran (5.7%), China (4.2%) and the United Kingdom (3.6%). The estimated percentage change in COVID-19 cases from March 1 to 16, 2020, was highest in Belgium (105.8/100,000 population), followed by Qatar (439/100,000 population) and Portugal (331/100,000 population). The overall recovery rate of COVID-19 was 43%; China (35.5%) had the highest recovery rate, while the United States of America recorded a recovery rate of 0.3%. Conclusion: Overall, all the COVID-19-affected countries showed an upward trend in incidence, with little change in the incidence rate of -0.20% from January to Mid-March. The case-fatality rate was found to be 3.92%, and the recovery rate was observed to be less than half (43%) among COVID-19 patients. Italy, Iran, and Spain had the largest numbers of new cases of COVID-19 from March 1 to 16, 2020.
A single holiday was the turning point of the COVID-19 policy of Israel	Ziv Klausner;Eyal Fattal;Eitan Hirsch;Shmuel C Shapira	2020-03-31	other	covid-19	https://doi.org/10.1101/2020.03.26.20044412	https://www.medrxiv.org/content/10.1101/2020.03.26.20044412v2	AbstractBackground: The impact of COVID-19 has been profound, and the public health challenge seem to be the most serious regarding respiratory viruses since the 1918 H1N1 influenza pandemic. In the absence of effective vaccine or biomedical treatment, the basic rules of public health measures have not changed, namely public distancing. Methods: We analyzed epidemiological investigation reports during the first month of the outbreak in Israel. In addition, we present a deterministic compartment model and simulations of several scenarios emphasizing quarantine and isolation policies given their efficiency. Results: We identify an abrupt change from controlled epidemic regime to an exponential growth (R_0= 2.19) in light of the actual policy-makers decisions and public behavior in Israel. Our analysis show that before the abrupt change, the new cases trend was due to returning citizens infected abroad. The abrupt change followed a holiday in which social distancing was clearly inefficient and many public gatherings were held. We further discuss three different modeled scenarios of quarantine efficiency: high-, medium-, and low-efficiency. Conclusions: Israel early lessons show that there is no allowance to compromise with the directive of social distancing. Even before the onset of the pandemic in Israel, fine-tuned but determined early decisions were taken by policy makers to monitor flight arrivals from Covid-19 affected regions and to limit public gatherings. Our analysis show that one particular holiday has shifted the occurrence curve from controlled regime to exponential growth. Therefore, even a short lapse in public responsiveness can have a dramatic effect.
A model to forecast regional demand for COVID-19 related hospital beds	Johannes Opsahl Ferstad;Angela Jessica Gu;Raymond Ye Lee;Isha Thapa;Andrew Y Shin;Joshua A Salomon;Peter Glynn;Nigam H Shah;Arnold Milstein;Kevin Schulman;David Scheinker	2020-03-31	other	covid-19	https://doi.org/10.1101/2020.03.26.20044842	https://www.medrxiv.org/content/10.1101/2020.03.26.20044842v2	AbstractCOVID-19 threatens to overwhelm hospital facilities throughout the United States. We created an interactive, quantitative model that forecasts demand for COVID-19 related hospitalization based on county-level population characteristics, data from the literature on COVID-19, and data from online repositories. Using this information as well as user inputs, the model estimates a time series of demand for intensive care beds and acute care beds as well as the availability of those beds. The online model is designed to be intuitive and interactive so that local leaders with limited technical or epidemiological expertise may make decisions based on a variety of scenarios. This complements high-level models designed for public consumption and technically sophisticated models designed for use by epidemiologists. The model is actively being used by several academic medical centers and policy makers, and we believe that broader access will continue to aid community and hospital leaders in their response to COVID-19.
Temperature, humidity, and wind speed are associated with lower Covid-19 incidence	Nazrul Islam;Sharmin Shabnam;A Mesut Erzurumluoglu	2020-03-31	upon request	covid-19	https://doi.org/10.1101/2020.03.27.20045658	https://www.medrxiv.org/content/10.1101/2020.03.27.20045658v2	AbstractIn absence of empirical research data, there has been considerable speculative hypothesis on the relationship between climatic factors (such as temperature and humidity) and the incidence of Covid-19. This study analyzed the data from 310 regions across 116 countries that reported confirmed cases of Covid-19 by March 12, 2020, and found that temperature, humidity, and wind speed were inversely associated with the incidence rate of Covid-19 after adjusting for the regional and temporal trend in the incidence of Covid-19, columnar density of ozone, precipitation probability, sea-level air-pressure, and length of daytime.