Estimates of the ongoing need for social distancing and control measures post-"lockdown" from trajectories of COVID-19 cases and mortality

The Impact of Loneliness and Social Isolation on Cognitive Aging: A Narrative Review

Social concepts such as loneliness and social isolation are fairly new factors that have been recently gaining attention as to their involvement in changes in cognitive function and association with dementia. The primary aim of this narrative review was to describe the current understanding of how loneliness and social isolation influence cognitive aging and how they are linked to dementia. Studies have shown that there is an association between loneliness, social isolation, and reduced cognitive function, in older adults, across multiple cognitive domains, as well as a heightened risk of dementia. Numerous changes to underlying neural biomechanisms including cortisol secretion and brain volume alterations (e.g., white/grey matter, hippocampus) may contribute to these relationships. However, due to poor quality research, mixed and inconclusive findings, and issues accurately defining and measuring loneliness and social isolation, more consistent high-quality interventions are needed to determine whether studies addressing loneliness and social isolation can impact longer term risk of dementia. This is especially important given the long-term impact of the COVID-19 pandemic on social isolation in older people is yet to be fully understood.

The value of discharged case fatality rate in estimating the severity and epidemic trend of COVID-19 in China: a novel epidemiological study

Aim

The main objective of this study was to explore the value of the discharged case fatality rate (DCFR) in estimating the severity and epidemic trend of COVID-19 in China.

Subjects and methods

Epidemiological data on COVID-19 in China and Hubei Province were obtained from the National Health Commission of the People's Republic of China from January 20, 2020, to March 31, 2020. The number of daily new confirmed cases, daily confirmed deaths, daily recovered cases, the proportion of daily deaths and total deaths of discharged cases were collected, and the total discharge case fatality rate (tDCFR), daily discharge case fatality rate (dDCFR), and stage-discharge case fatality rate (sDCFR) were calculated. We used the R software (version 3.6.3, R core team) to apply a trimmed exact linear time method to search for changes in the mean and variance of dDCFR in order to estimate the pandemic phase from dDCFR.

Results

The tDCFR of COVID-19 in China was 4.16% until March 31, 2020. According to the pattern of dDCFR, the pandemic was divided into four phases: the transmission phase (from January 20 to February 2), the epidemic phase (from February 3 to February 14), the decline phase (from February 15 to February 22), and the sporadic phase (from February 23 to March 31). The sDCFR for these four phases was 43.18% (CI 39.82-46.54%), 13.23% (CI 12.52-13.94%), 5.86% (CI 5.49-6.22%), and 1.61% (CI 1.50-1.72%), respectively.

Conclusion

DCFR has great value in assessing the severity and epidemic trend of COVID-19.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10389-023-01895-4.

Uncertainty and error in SARS-CoV-2 epidemiological parameters inferred from population-level epidemic models

During the SARS-CoV-2 pandemic, epidemic models have been central to policy-making. Public health responses have been shaped by model-based projections and inferences, especially related to the impact of various non-pharmaceutical interventions. Accompanying this has been increased scrutiny over model performance, model assumptions, and the way that uncertainty is incorporated and presented. Here we consider a population-level model, focusing on how distributions representing host infectiousness and the infection-to-death times are modelled, and particularly on the impact of inferred epidemic characteristics if these distributions are mis-specified. We introduce an SIR-type model with the infected population structured by 'infected age', i.e. the number of days since first being infected, a formulation that enables distributions to be incorporated that are consistent with clinical data. We show that inference based on simpler models without infected age, which implicitly mis-specify these distributions, leads to substantial errors in inferred quantities relevant to policy-making, such as the reproduction number and the impact of interventions. We consider uncertainty quantification via a Bayesian approach, implementing this for both synthetic and real data focusing on UK data in the period 15 Feb-14 Jul 2020, and emphasising circumstances where it is misleading to neglect uncertainty. This manuscript was submitted as part of a theme issue on "Modelling COVID-19 and Preparedness for Future Pandemics".

An improved epidemiological-unscented Kalman filter (hybrid SEIHCRDV-UKF) model for the prediction of COVID-19. Application on real-time data

The prevalence of COVID-19 has been the most serious health challenge of the 21th century to date, concerning national health systems on a daily basis, since December 2019 when it appeared in Wuhan City. Nevertheless, most of the proposed mathematical methodologies aiming to describe the dynamics of an epidemic, rely on deterministic models that are not able to reflect the true nature of its spread. In this paper, we propose a SEIHCRDV model - an extension/improvement of the classic SIR compartmental model - which also takes into consideration the populations of exposed, hospitalized, admitted in intensive care units (ICU), deceased and vaccinated cases, in combination with an unscented Kalman filter (UKF), providing a dynamic estimation of the time dependent system's parameters. The stochastic approach is considered necessary, as both observations and system equations are characterized by uncertainties. Apparently, this new consideration is useful for examining various pandemics more effectively. The reliability of the model is examined on the daily recordings of COVID-19 in France, over a long period of 265 days. Two major waves of infection are observed, starting in January 2021, which signified the start of vaccinations in Europe providing quite encouraging predictive performance, based on the produced NRMSE values. Special emphasis is placed on proving the non-negativity of SEIHCRDV model, achieving a representative basic reproductive number R 0 and demonstrating the existence and stability of disease equilibria according to the formula produced to estimate R 0 . The model outperforms in predictive ability not only deterministic approaches but also state-of-the-art stochastic models that employ Kalman filters. Furthermore, the relevant analysis supports the importance of vaccination, as even a small increase in the dialy vaccination rate could lead to a notable reduction in mortality and hospitalizations.

Development of Social Distancing Phobia Scale and Its Association with Anxiety and Perceived Stress

The aim of the present study is to develop the social distancing phobia scale and is to determine the role of generalized anxiety disorder of the individual in predicting social distancing phobia and perceived stress. The sample of the study consists of 1260 people selected according to the convenience sampling method. Social distancing phobia scale, generalized anxiety disorder, perceived stress scale, and positive negative emotion scale were used in the study. As a result of the analysis, this scale consists of 17 items with three factors including "physiological, emotional, and behavioral response." With its psychometric properties in assessing the three-sub-dimensional construct of the social distancing phobia scale, this scale will help to provide a better understanding of the emotions and psychological or psychiatric disorders during the COVID-19 pandemic. In addition, generalized anxiety disorder was found to significantly predict perceived stress and social distancing phobia.

Evaluation of Vulnerability Factors for Developing Stress and Depression due to COVID-19 Spread and its Associated Lockdown

Background

COVID-19 is a pandemic that has been widespread throughout the world. The disease and the measures employed to contain its spread have a detrimental effect on the mental health of individuals. Countries across the world have applied variable combinations of quarantine and social distancing measures to contain the spread of COVID-19. This project aims at identifying the susceptible groups for the development of depression and stress due to COVID-19-associated containment measures. This evaluation will help in prioritizing efforts to ameliorate the detrimental effects of COVID-19 on psychological health.

Methods

A cross-sectional study was conducted through an online survey that included questions on the demographics and COVID-19 experience. The prevalence of depressive symptoms was evaluated using the PHQ-9 survey, whereas stress levels were detected using the perceived stress scale (PSS). Data regarding demographics as well as exposure to COVID-19, working at home and the financial impact of the pandemic were collected.

Results

Data were collected from 1541 participants from the MENA region. Depressive symptoms were detected in 54.2% of the participants, and the average stress score was 18.4±0.8. Adjusting for demographics and other variables, younger participants were more likely to report depressive symptoms and higher stress scores. Additionally, younger age, female gender, the coexistence of depressive symptoms, negative effects on monthly income, and ability to do work were found to be independent predictors of higher stress scores.

Conclusion

Young individuals are more likely to develop depression symptoms and stress. Thus, there is a need for prompt measures to alleviate COVID-19-associated effects on this group.

Decline of onset-to-diagnosis interval and its impacts on clinical outcome of COVID-19 in China: a nation-wide observational study

Background

To quantitatively assess the impact of the onset-to-diagnosis interval (ODI) on severity and death for coronavirus disease 2019 (COVID-19) patients.

Methods

This retrospective study was conducted based on the data on COVID-19 cases of China over the age of 40 years reported through China’s National Notifiable Infectious Disease Surveillance System from February 5, 2020 to October 8, 2020. The impacts of ODI on severe rate (SR) and case fatality rate (CFR) were evaluated at individual and population levels, which was further disaggregated by sex, age and geographic origin.

Results

As the rapid decline of ODI from around 40 days in early January to < 3 days in early March, both CFR and SR of COVID-19 largely dropped below 5% in China. After adjusting for age, sex, and region, an effect of ODI on SR was observed with the highest OR of 2.95 (95% CI 2.37‒3.66) at Day 10–11 and attributable fraction (AF) of 29.1% (95% CI 22.2‒36.1%) at Day 8–9. However, little effect of ODI on CFR was observed. Moreover, discrepancy of effect magnitude was found, showing a greater effect from ODI on SR among patients of male sex, younger age, and those cases in Wuhan.

Conclusion

The ODI was significantly associated with the severity of COVID-19, highlighting the importance of timely diagnosis, especially for patients who were confirmed to gain increased benefit from early diagnosis to some extent.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-022-07660-4.

Assessment of Knowledge about Traditional Medicine Reveals Overuse as a Potential Risk for Aggravating COVID-19 and Underlying Diseases in Geriatrics and Women’s Health in the Saudi Population

The devastating COVID-19 pandemic has created several gaps in the management of viral infections, leaving biocontainment and supportive measures as the only resorts for control. As such, there has been a dramatic increase in the use of dietary supplementations and herbal medicine for COVID-19. However, serious concerns regarding the efficacy, safety, and recommended doses of these medicines have been raised. In this study, we aimed to assess the population knowledge about alternative medicine administration for COVID-19 and the associated factors. Using a self-administered cross-sectional survey, we analyzed a total of 2042 valid responses. Most of the included participants were females (69.7%), with an overall mean age of 20.8 ± 11.8 years. Most respondents (62.8%) obtained their knowledge from social media while only 16.6% received knowledge from the health care workers. Half of the participants (50.6%) correctly identified all COVID-19 symptoms, where fever (18.5%) and loss of smell and taste (17.1%) were the most frequent answers. On the use of traditional medicines and supplements for COVID-19, 57.8% did not answer, 23.7% admitted regular use, and 18.5% used sometimes. Family members or friends suggested the use of traditional medicines and dietary supplements to 28.0% of the participants while only 14.7% were advised by a nutritionist, physician, pharmacist, nurse, or a health worker. Moreover, seniors and illiterate portions of society had lower knowledge scores and increased utilization of alternative medicine. Marital status, income, and previous COVID-19 were all significant predictors of the awareness and knowledge score. Thus, this study has identified overuse of unregulated medicinal products in the region, which potentially aggravates COVID-19 or other underlying risks of the disease, making clinical management challenging, particularly in geriatrics and women’s health. Regulation of medicinal products and establishment of educational campaigns about the disease have become imperative.

The global transmission of new coronavirus variants

Coronavirus Disease 2019 (COVID-19) has caused tremendous losses to the world. This study addresses the impact and diffusion of the five major new coronavirus variants namely Alpha, Beta, Gamma, Eta, and Delta lineage. The results of this study indicate that Africa and Europe will be affected by new coronavirus variants the most compared with other continents. The comparative analysis indicates that vaccination can contain the spread of the virus in most of the continent, and non-pharmaceutical interventions (NPIs), such as restriction on gatherings and close public transport, will effectively curb the pandemic, especially in densely populated continents. According to our Global Prediction System of COVID-19 Pandemic, the diffusion of delta lineage in the US shows seasonal oscillation characteristics, and the first wave will occur in October 2021, with the record of 323,360, and followed by a small resurgence in April 2022, with the record of 184,196, while the second wave will reach to 232,622 cases in October 2022. Our study will raise the awareness of new coronavirus variants among the public, and will help the governments make appropriate directives to cope with the new coronavirus variants.

A Parametric Multi-Agent Simulation Framework to Emulate Social Isolation During the Pandemic

Many people worldwide have been at home for months and practicing social distancing to mitigate the spread of coronavirus (COVID-19). What may have started as a single case is now in at least 180 countries. Preliminary surveys indicate that the COVID-19 pandemic has caused people to feel more lonely and isolated than they did before. It may be due to the fear of the virus, death of loved ones, and the lock-downs restrictions imposed in some countries. This paper proposes a parametric multi-agent simulation framework to emulate Social Isolation during the pandemic. Using the proposed simulator we mimic real-world area of 144 km2 and population size of 200,000 in order to have near-accurate settings. Various parameters, such as the number of hospitals and capacity, infection rate, recovery, hospitalization, and death, are considered. The simulation is validated on a real-world scale artificial society and is parameterized to a great extent to simulate various settings.

Effect of COVID-19 driven lockdown on social contact pattern in Puducherry, India: A longitudinal study

Objective

This study was undertaken to assess the change in social contact and transmission dynamics among adults in the Puducherry district during the different phases of country-wide lockdown.

Methods

Adults aged 18-69 years in Puducherry were assessed for frequency and duration of contacts in the following time points: prior to lockdown (March 2020), during lockdown, immediate post-lockdown (April, June 2020), and seven months post-lockdown (February 2021). Adjusted incidence rate ratios (aIRR) were obtained using a generalized estimating equation. We also assessed the exponential trajectory of the time-varying reproduction number (R_t) during and after lockdown.

Results

Compared to pre-lockdown phase, frequency of social contacts during 1^st week, 4^th week of lockdown, and immediate post-lockdown were reduced by 89% (aIRR = 0.11; 95% CI: 0.09-0.13), 40% (aIRR = 0.60; 95% CI: 0.52-0.69) and 91% (aIRR = 0.09; 95% CI: 0.07-0.10) respectively. However, the decline was not statistically significant at seven months post-lockdown. Correspondingly, we observed an initial spike in R_t during the lockdown phase followed by a gradual decline during the immediate post-lockdown phase. However, seven months post-lockdown, R_t has increased again.

Conclusion

The study showed high compliance to the lockdown measures in Puducherry during the lockdown and immediate post-lockdown periods. However, as the lockdown measures were relaxed, the contact rate returned to the pre-lockdown state.

Positivity rate: an indicator for the spread of COVID-19

OBJECTIVE

This paper investigates the relationship between the positivity rate and numbers of deaths and intensive care unit (ICU) patients. In addition, it explores the use of the positivity rate as an indicator for the spread of COVID-19.

METHODS

We used COVID-19 datasets for eight countries - Canada, USA, UK, Italy, Belgium, Ireland, Colombia and South Africa - and considered two correlation cases. The first case considers the correlation of the number of confirmed cases with each of deaths and ICU patients. The second case considers the correlation of the positivity rate with each of deaths and ICU patients. When obtaining the correlation, we considered different lagging periods between the date of confirming a case and the date of its ICU admittance or death. We compared the obtained correlation coefficient values for each of the two considered cases to explore whether the positivity rate is a better indicator for the spread of the disease than confirmed cases. For each of the eight considered countries, we obtained the daily reproduction number using each of confirmed cases and positivity rate. The two obtained sets of reproduction number values for each country were statistically compared to investigate whether they are significantly different.

RESULTS

When considering the daily positivity rate instead of the daily number of confirmed cases, the maximum correlation with deaths is increased by 349.9% for the USA (the country with the highest increase) and 4.5% for the UK (the country with the lowest increase), with an average increase of 60.8% considering the eight countries. Considering the daily positivity rate instead of the daily number of confirmed cases caused the maximum correlation with the number of ICU patients to be increased by 74.7% for the USA (the country with the highest increase) and 2.2% for the UK (the country with the lowest increase), with an average increase of 25% over the considered countries. The results for the daily reproduction number obtained using the positivity rate are statistically different from those obtained using daily confirmed cases.

CONCLUSION

The results indicate that positivity rate is a better indicator for the spread of the disease than the number of confirmed cases. Therefore, it is highly advised to use measures based on the positivity rate when indicating the spread of the disease and considering responses accordingly because these measures consider the daily number of tests and confirmed cases.

COVID-19 and loneliness: A rapid systematic review

BACKGROUND

Loneliness is known to be associated with both poorer physical and mental health, being associated with increased mortality. Responses throughout the world to the current COVID-19 pandemic all incorporate varying degrees of social distancing and isolation. There is an imperative to provide a timely review and synthesis of the impact of COVID-19 on loneliness in the general population.

METHODS

PubMed was searched using the key terms 'COVID-19', 'coronavirus', 'SARS-COV2' and 'loneliness'. Fifty-four articles were identified and screened against the inclusion criteria. The inclusion criteria stipulated that the study needed to incorporate a measure of loneliness with participants being drawn from the general adult population. Twenty-four studies met the inclusion criteria.

RESULTS

The key data extracted from the 24 reviewed studies are presented and summarised with a focus on key demographics of participants, the research designs utilised, the measures of loneliness employed and the other variables assessed in the studies. Overall, the findings indicate that loneliness has been a significant issue during the current COVID-19 pandemic and loneliness is positively associated with mental health symptoms. However, there were inconsistencies in the results evident across studies.

CONCLUSION

To our knowledge, this is the first systematic review of research investigating loneliness during the current COVID-19 pandemic in the general adult population. Despite the inconsistencies evident in some of the results across the studies, it is clearly apparent that loneliness is having an impact on the mental health and wellbeing of the general adult population. Furthermore, it is apparent that the current COVID-19 pandemic has had an impact on loneliness in the general adult population and that loneliness is significantly positively associated with mental illness symptomatology. Thus, there is an imperative to address loneliness through public policy and interventions. The limitations of this review are noted and directions given for future research.

Lung Ultrasonography in Ruling Out COVID-19 Among Health Care Workers in Two Italian Emergency Departments: A Multicenter Study

Objective:

The low sensitivity of the real-time reverse transcription-polymerase chain reaction (rRT-PCR) test on the nasopharyngeal swab for SARS-CoV2 virus could cause infections among health care professionals and could be a source of viral spread. The aim of this study was to verify whether lung ultrasonography (LUS) had a negative predictive value (NPV) high enough to rule out coronavirus disease 2019 (COVID-19) in a cohort of health care employees, working in emergency departments (EDs).

Materials and Methods:

A multicenter prospective observational study was conducted in two EDs in Northeast Italy. An adjudication committee established the definitive diagnosis of COVID-19.

Results:

A cohort was enrolled of 155 possible patient cases (two true positives). Twenty-one health care employees presented with suggestive symptoms for COVID-19. The rRT-PCR test was positive in one of the two patients. LUS was suggestive for COVID-19 pneumonia in four patients. The diagnostic accuracy of LUS was 98.7% (95% confidence interval [CI] = 95.4%–99.8%). The NPV was 100% (95% CI = 100%–100%).

Conclusion:

LUS has a high enough NPV for excluding a COVID-19-related pneumonia in a cohort of health care employees who were exposed to the SARS-CoV2 virus.

Human Factors and Ergonomics and the management of existential threats: A work domain analysis of a COVID-19 return from lockdown restrictions system

Following strict "lockdown" restrictions designed to control the spread of the COVID-19 virus, many jurisdictions are now engaged in a process of easing restrictions in an attempt to stimulate economic and social activity while continuing to suppress virus transmission. This is challenging and complex, and in several regions, new outbreaks have emerged. We argue that systems Human Factors and Ergonomics methods can assist in understanding and optimizing the return from lockdown. To demonstrate, we used work domain analysis to develop an abstraction hierarchy model of a generic "return from lockdown restrictions" system. The model was assessed to identify (a) issues preventing a successful return from lockdown; and (b) leverage points that could be exploited to optimize future processes. The findings show that the aim of continuing to suppress virus transmission conflicts with the aims of returning to pre-virus economic and social activity levels. As a result, many functions act against each other, ensuring that the system cannot optimally achieve all three of its primary aims. Potential leverage points include modifying the goals and rules of the system and enhancing communications and feedback. Specifically, it is argued that moderating economic aims and modifying how social and community activities are undertaken will result in longer term suppression of the virus.

An engineering model of the COVID-19 trajectory to predict the success of isolation initiatives

Much media and societal attention is today focused on how to best control the spread of coronavirus (COVID-19). Every day brings us new data, and policy makers are implementing different strategies in different countries to manage the impact of COVID-19. To respond to the first 'wave' of infection, several countries, including the UK, opted for isolation/lockdown initiatives, with different degrees of rigour. Data showed that these initiatives have yielded the expected results in terms of containing the rapid trajectory of the virus. When this article was first prepared (April 2020), the affected societies were wondering when the isolation/lockdown initiatives should be lifted. While detailed epidemiological, economic as well as social studies would be required to answer this question completely, here we employ a simple engineering model. Albeit simple, the model is capable of reproducing the main features of the data reported in the literature concerning the COVID-19 trajectory in different countries, including the increase in cases in countries following the initially successful isolation/lockdown initiatives. Keeping in mind the simplicity of the model, we attempt to draw some conclusions, which seem to suggest that a decrease in the number of infected individuals after the initiation of isolation/lockdown initiatives does not necessarily guarantee that the virus trajectory is under control. Within the limit of this model, it would seem that rigid isolation/lockdown initiatives for the medium term would lead to achieving the desired control over the spread of the virus. This observation seems consistent with the 2020 summer months, during which the COVID-19 trajectory seemed to be almost under control across most European countries. Consistent with the results from our simple model, winter 2020 data show that the virus trajectory was again on the rise. Because the optimal solution will achieve control over the spread of the virus while minimising negative societal impacts due to isolation/lockdown, which include but are not limited to economic and mental health aspects, the engineering model presented here is not sufficient to provide the desired answer. However, the model seems to suggest that to keep the COVID-19 trajectory under control, a series of short-to-medium term isolation measures should be put in place until one or more of the following scenarios is achieved: a cure has been developed and has become accessible to the population at large; a vaccine has been developed, tested and distributed to large portions of the population; a sufficiently large portion of the population has developed resistance to the COVID-19 virus; or the virus itself has become less aggressive. It is somewhat remarkable that an engineering model, despite all its approximations, provides suggestions consistent with advanced epidemiological models developed by several experts in the field. The model proposed here is however not expected to be able to capture the emergence of variants of the virus, which seem to be responsible for significant outbreaks, notably in India, in the spring of 2021, it cannot describe the effectiveness of vaccine strategies, as it does not differentiate among different age groups within the population, nor does it allow us to consider the duration of the immunity achieved after infection or vaccination.

Development of a coronavirus social distance attitudes scale

OBJECTIVE

Our goal was to develop a scale to assess social distance attitudes related to COVID-19.

METHODS

We performed an online national survey of US adults (n = 1,074) to assess social distance attitudes, COVID-19 related beliefs and behaviors, and demographics. We assessed scale structure using confirmatory factor analysis and evaluated internal consistency and validity. We assessed association of scale factors with respondent characteristics.

RESULTS

Confirmatory factor analysis supported a hypothesized two-factor solution. Internal consistency was high for both positive (Alpha = 0.92) and negative (Alpha = 0.91) attitude factors. Analyses supported construct and predictive validity with expected associations between scale factors and perceived norms and behavior (e.g. trips out of the home). We found an interaction suggesting that holding highly negative attitudes reduced the effect of holding positive beliefs. Both attitude factors were related to age, gender, race/ethnicity, and political affiliation. Perceived COVID-19 risk (to others but not for self) and perceived severity were consistently associated with higher positive and lower negative attitudes.

CONCLUSION

This COVID-19 Social Distance Attitude Scale contains positive and negative factors with high internal consistency and construct and predictive validity.

PRACTICE IMPLICATION

A greater understanding and ongoing assessment of COVID-19 social distance attitudes could inform policymakers, researchers, and clinicians who seek to promote protective social distance behaviors.

Estimation of novel coronavirus (COVID-19) reproduction number and case fatality rate: A systematic review and meta-analysis

BACKGROUND AND AIMS

Realizing the transmission potential and the magnitude of the coronavirus disease 2019 (COVID-19) aids public health monitoring, strategies, and preparation. Two fundamental parameters, the basic reproduction number (R 0) and case fatality rate (CFR) of COVID-19, help in this understanding process. The objective of this study was to estimate the R 0 and CFR of COVID-19 and assess whether the parameters vary in different regions of the world.

METHODS

We carried out a systematic review to find the reported estimates of the R 0 and the CFR in articles from international databases between January 1 and August 31, 2020. Random-effect models and Forest plots were implemented to evaluate the mean effect size of R 0 and the CFR. Furthermore, R 0 and CFR of the studies were quantified based on geographic location, the tests/thousand population, and the median population age of the countries where the studies were conducted. To assess statistical heterogeneity among the selected articles, the I 2 statistic and the Cochran's Q test were used.

RESULTS

Forty-five studies involving R 0 and 34 studies involving CFR were included. The pooled estimation of R 0 was 2.69 (95% CI: 2.40, 2.98), and that of the CFR was 2.67 (2.25, 3.13). The CFR in different regions of the world varied significantly, from 2.49 (2.08, 2.94) in Asia to 3.40 (2.81, 4.04) in North America. We observed higher mean CFR values for the countries with lower tests (3.15 vs 2.16) and greater median population age (3.13 vs 2.27). However, R 0 did not vary significantly in different regions of the world.

CONCLUSIONS

An R 0 of 2.69 and a CFR of 2.67 indicate the severity of the COVID-19. Although R 0 and CFR may vary over time, space, and demographics, we recommend considering these figures in control and prevention measures.

EpiCovDA: a mechanistic COVID-19 forecasting model with data assimilation

We introduce a minimalist outbreak forecasting model that combines data-driven parameter estimation with variational data assimilation. By focusing on the fundamental components of nonlinear disease transmission and representing data in a domain where model stochasticity simplifies into a process with independent increments, we design an approach that only requires four core parameters to be estimated. We illustrate this novel methodology on COVID-19 forecasts. Results include case count and deaths predictions for the US and all of its 50 states, the District of Columbia, and Puerto Rico. The method is computationally efficient and is not disease- or location-specific. It may therefore be applied to other outbreaks or other countries, provided case counts and/or deaths data are available.

The Commonly Utilized Natural Products during the COVID-19 Pandemic in Saudi Arabia: A Cross-Sectional Online Survey

OBJECTIVES

The utilization rate of herbal and dietary supplements among the Saudi population is reported to be high. However, the utilization rate and types of herbal and dietary supplements during the COVID-19 pandemic are largely unknown.

METHODS

This was an online questionnaire-based cross-sectional study that used convenience sampling and social media platforms (Telegram®, Twitter®, and WhatsApp®) to disseminate a 12-item questionnaire across the Saudi general public aged 18 years and above. The questionnaire inquired about the sociodemographic characteristics (e.g., age, gender, education, geographical location), presence of chronic health conditions and the use of prescription medications, awareness of the viral nature of COVID-19 infection and its common symptoms, and the commonly utilized herbal and/or dietary supplements.

RESULTS

Sixty-four percent of the 1473 participants reported using herbal and/or dietary supplements for the purpose of boosting their immune system to prevent COVID-19 infection. In addition, 88.2% of the respondents were misinformed about the manifestation of COVID-19 symptoms. Most of the participants were Saudi (91.9%), aged 49 years and younger (83%), female (52%), and healthy (81%). Honey (46%), lemon (45%), ginger (36%), vitamin C (32%), black seed (26%), garlic (26%), and turmeric (19%) were the most commonly used herbal and/or dietary supplements by the participants. Saudi nationals (OR = 1.67, 95% CI: 1.08 to 2.6, p = 0.02), older adults (OR = 1.30, 95% CI:1.10 to 1.55, p = 0.002), and those taking prescription medications had higher odds of using dietary and/or herbal supplements (OR = 3.31, 95% CI: 2.61 to 4.18, p < 0.0001).

CONCLUSION

The utilization rate of herbal and dietary supplements among the Saudi public during the COVID-19 pandemic is high. Future studies should examine the impact of different public awareness campaigns aimed at improving the public knowledge of the risk and benefits associated with the use of different commonly utilized herbal and dietary products identified in this study.

Rashidi T. Facemask and social distancing, pillars of opening up economies

The COVID-19 pandemic has caused severe health and economic impacts globally. Strategies to safely reopen economies, travel and trade are a high priority. Until a reliable vaccine is available, non-pharmaceutical techniques are the only available means of disease control. In this paper, we aim to evaluate the extent to which social distancing (SD) and facemask (FM) use can mitigate the transmission of COVID-19 when restrictions are lifted. We used a microsimulation activity-based model for Sydney Greater Metropolitan Area, to evaluate the power of SD and FM in controlling the pandemic under numerous scenarios. The hypothetical scenarios are designed to picture feasible futures under different assumptions. Assuming that the isolation of infected cases and the quarantining of close contacts are in place, different numerical tests are conducted and a full factorial two-way MANOVA test is used to evaluate the effectiveness of the FM and SD control strategies. The main and interactive effects of the containment strategies are evaluated by the total number of infections, percentage of infections reduction, the time it takes to get the pandemic under control, and the intensity of active cases.

Study on the variation of air pollutant concentration and its formation mechanism during the COVID-19 period in Wuhan

To prevent the spread of COVID-19 (2019 novel coronavirus), from January 23 to April 8 in 2020, the highest Class 1 Response was ordered in Wuhan, requiring all residents to stay at home unless absolutely necessary. This action was implemented to cut down all unnecessary human activities, including industry, agriculture and transportation. Reducing these activities to a very low level during these hard times meant that some unprecedented naturally occurring measures of controlling emissions were executed. Ironically, however, after these measures were implemented, ozone levels increased by 43.9%. Also worthy of note, PM_2.5 decreased 31.7%, which was found by comparing the observation data in Wuhan during the epidemic from 8th Feb. to 8th Apr. in 2020 with the same periods in 2019. Utilizing CMAQ (The Community Multiscale Air Quality modeling system), this article investigated the reason for these phenomena based on four sets of numerical simulations with different schemes of emission reduction. Comparing the four sets of simulations with observation, it was deduced that the emissions should decrease to approximately 20% from the typical industrial output, and 10% from agriculture and transportation sources, attributed to the COVID-19 lockdown in Wuhan. More importantly, through the CMAQ process analysis, this study quantitatively analyzed differences of the physical and chemical processes that were affected by the COVID-19 lockdown. It then examined the differences of the COVID-19 lockdown impact and determined the physical and chemical processes between when the pollution increased and decreased, determining the most affected period of the day. As a result, this paper found that (1) PM_2.5 decreased mainly due to the reduction of emission and the contrary contribution of aerosol processes. The North-East wind was also in favor of the decreasing of PM_2.5. (2) O₃ increased mainly due to the slowing down of chemical consumption processes, which made the concentration change of O₃ pollution higher at about 4 p.m.-7 p.m. of the day, while increasing the concentration of O₃ at night during the COVID-19 lockdown in Wuhan. The higher O₃ concentration in the North-East of the main urban area also contributed to the increasing of O₃ with unfavorable wind direction.

Study on the variation of air pollutant concentration and its formation mechanism during the COVID-19 period in Wuhan

To prevent the spread of COVID-19 (2019 novel coronavirus), from January 23 to April 8 in 2020, the highest Class 1 Response was ordered in Wuhan, requiring all residents to stay at home unless absolutely necessary. This action was implemented to cut down all unnecessary human activities, including industry, agriculture and transportation. Reducing these activities to a very low level during these hard times meant that some unprecedented naturally occurring measures of controlling emissions were executed. Ironically, however, after these measures were implemented, ozone levels increased by 43.9%. Also worthy of note, PM_2.5 decreased 31.7%, which was found by comparing the observation data in Wuhan during the epidemic from 8th Feb. to 8th Apr. in 2020 with the same periods in 2019. Utilizing CMAQ (The Community Multiscale Air Quality modeling system), this article investigated the reason for these phenomena based on four sets of numerical simulations with different schemes of emission reduction. Comparing the four sets of simulations with observation, it was deduced that the emissions should decrease to approximately 20% from the typical industrial output, and 10% from agriculture and transportation sources, attributed to the COVID-19 lockdown in Wuhan. More importantly, through the CMAQ process analysis, this study quantitatively analyzed differences of the physical and chemical processes that were affected by the COVID-19 lockdown. It then examined the differences of the COVID-19 lockdown impact and determined the physical and chemical processes between when the pollution increased and decreased, determining the most affected period of the day. As a result, this paper found that (1) PM_2.5 decreased mainly due to the reduction of emission and the contrary contribution of aerosol processes. The North-East wind was also in favor of the decreasing of PM_2.5. (2) O₃ increased mainly due to the slowing down of chemical consumption processes, which made the concentration change of O₃ pollution higher at about 4 p.m.-7 p.m. of the day, while increasing the concentration of O₃ at night during the COVID-19 lockdown in Wuhan. The higher O₃ concentration in the North-East of the main urban area also contributed to the increasing of O₃ with unfavorable wind direction.

Role of social distancing in tackling COVID-19 during the first wave of pandemic in Nordic region: Evidence from daily deaths, infections and needed hospital resources

OBJECTIVES

To measure the effect of social distancing on reducing daily deaths, infections and hospital resources needed for coronavirus disease 2019 (COVID-19) patients during the first wave of the pandemic in Nordic countries.

METHODS

The observations of social distancing, daily deaths, infections along with the needed hospital resources for COVID-19 patient hospitalizations including the numbers of all hospital beds, beds needed in ICUs and infection wards, nursing staffs needed in ICUs and infection wards were collected from the Institute for Health Metrics and Evaluation (IHME) by the University of Washington. The observations of social distancing were based on the reduction in human contact relative to background levels for each location quantified by cell phone mobility data collected from IHME. The weighted data per 100,000 population gathered in a 40-day period of the first wave of the pandemic in Denmark, Finland, Iceland, Norway and Sweden. Statistical technique of panel data analysis is used to measure the associations between social distancing and COVID-19 indicators in long-run.

RESULTS

Results of dynamic long-run models confirm that a 1% rise in social distancing by reducing human contacts may decline daily deaths, daily infections, all hospital beds needed, beds/nurses needed in ICUs and beds/nurses needed in infection wards due COVID-19 pandemic by 1.13%, 15.26%, 1.10%, 1.17% and 1.89%, respectively. Moreover, results of error correction models verify that if the equilibriums between these series are disrupted by a sudden change in social distancing, the lengths of restoring back to equilibrium are 67, 62, 40, 22 and 49 days for daily deaths, daily infections, all hospital beds needed, nurses/beds needed in ICUs and nurses/beds needed in infection wards, respectively.

CONCLUSION

Proper social distancing was a successful policy for tackling COVID-19 with falling mortality and infection rates as well as the needed hospital resources for patient hospitalizations in Nordic countries. The results alert governments of the need for continuously implementing social distancing policies while using vaccines to prevent national lockdowns and reduce the burden of patient hospitalizations.

Concerns Discussed on Chinese and French Social Media During the COVID-19 Lockdown: Comparative Infodemiology Study Based on Topic Modeling

Background

During the COVID-19 pandemic, numerous countries, including China and France, have implemented lockdown measures that have been effective in controlling the epidemic. However, little is known about the impact of these measures on the population as expressed on social media from different cultural contexts.

Objective

This study aims to assess and compare the evolution of the topics discussed on Chinese and French social media during the COVID-19 lockdown.

Methods

We extracted posts containing COVID-19–related or lockdown-related keywords in the most commonly used microblogging social media platforms (ie, Weibo in China and Twitter in France) from 1 week before lockdown to the lifting of the lockdown. A topic model was applied independently for three periods (prelockdown, early lockdown, and mid to late lockdown) to assess the evolution of the topics discussed on Chinese and French social media.

Results

A total of 6395; 23,422; and 141,643 Chinese Weibo messages, and 34,327; 119,919; and 282,965 French tweets were extracted in the prelockdown, early lockdown, and mid to late lockdown periods, respectively, in China and France. Four categories of topics were discussed in a continuously evolving way in all three periods: epidemic news and everyday life, scientific information, public measures, and solidarity and encouragement. The most represented category over all periods in both countries was epidemic news and everyday life. Scientific information was far more discussed on Weibo than in French tweets. Misinformation circulated through social media in both countries; however, it was more concerned with the virus and epidemic in China, whereas it was more concerned with the lockdown measures in France. Regarding public measures, more criticisms were identified in French tweets than on Weibo. Advantages and data privacy concerns regarding tracing apps were also addressed in French tweets. All these differences were explained by the different uses of social media, the different timelines of the epidemic, and the different cultural contexts in these two countries.

Conclusions

This study is the first to compare the social media content in eastern and western countries during the unprecedented COVID-19 lockdown. Using general COVID-19–related social media data, our results describe common and different public reactions, behaviors, and concerns in China and France, even covering the topics identified in prior studies focusing on specific interests. We believe our study can help characterize country-specific public needs and appropriately address them during an outbreak.

Forecasting Social Distancing impact on COVID-19 in Jakarta using SIRD Model

Coronavirus disease 2019 (COVID-19) is a new emerging disease and a pandemic causing a high number of deaths. It is caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV2) and transmitted via droplets. Several countries including Indonesia had applied social distancing to reduce the disease transmission. In this study, we were using two groups, with social distancing and without social distancing represented by quarantine parameter Q. We predict the peak number in both groups using Susceptible-Infected-Recovered-Deceased (SIRD) model. The aims of this study are to compare the peak number of cases in groups with and without social distancing cases in Jakarta. This study result in a lower peak number and longer days of disease period in group with strict social distancing than in groups without social distancing, the current case number represent quarantine parameter Q 0.4 of SIRD Model. We suggest applying strict social distancing in Jakarta considering the duration, health standard, and other factors affecting COVID-19 cases.

The impact of non-pharmaceutical interventions on SARS-CoV-2 transmission across 130 countries and territories

BACKGROUND

Non-pharmaceutical interventions (NPIs) are used to reduce transmission of SARS coronavirus 2 (SARS-CoV-2) that causes coronavirus disease 2019 (COVID-19). However, empirical evidence of the effectiveness of specific NPIs has been inconsistent. We assessed the effectiveness of NPIs around internal containment and closure, international travel restrictions, economic measures, and health system actions on SARS-CoV-2 transmission in 130 countries and territories.

METHODS

We used panel (longitudinal) regression to estimate the effectiveness of 13 categories of NPIs in reducing SARS-CoV-2 transmission using data from January to June 2020. First, we examined the temporal association between NPIs using hierarchical cluster analyses. We then regressed the time-varying reproduction number (Rt) of COVID-19 against different NPIs. We examined different model specifications to account for the temporal lag between NPIs and changes in Rt, levels of NPI intensity, time-varying changes in NPI effect, and variable selection criteria. Results were interpreted taking into account both the range of model specifications and temporal clustering of NPIs.

RESULTS

There was strong evidence for an association between two NPIs (school closure, internal movement restrictions) and reduced Rt. Another three NPIs (workplace closure, income support, and debt/contract relief) had strong evidence of effectiveness when ignoring their level of intensity, while two NPIs (public events cancellation, restriction on gatherings) had strong evidence of their effectiveness only when evaluating their implementation at maximum capacity (e.g. restrictions on 1000+ people gathering were not effective, restrictions on < 10 people gathering were). Evidence about the effectiveness of the remaining NPIs (stay-at-home requirements, public information campaigns, public transport closure, international travel controls, testing, contact tracing) was inconsistent and inconclusive. We found temporal clustering between many of the NPIs. Effect sizes varied depending on whether or not we included data after peak NPI intensity.

CONCLUSION

Understanding the impact that specific NPIs have had on SARS-CoV-2 transmission is complicated by temporal clustering, time-dependent variation in effects, and differences in NPI intensity. However, the effectiveness of school closure and internal movement restrictions appears robust across different model specifications, with some evidence that other NPIs may also be effective under particular conditions. This provides empirical evidence for the potential effectiveness of many, although not all, actions policy-makers are taking to respond to the COVID-19 pandemic.

The impact of non-pharmaceutical interventions on SARS-CoV-2 transmission across 130 countries and territories

BACKGROUND

Non-pharmaceutical interventions (NPIs) are used to reduce transmission of SARS coronavirus 2 (SARS-CoV-2) that causes coronavirus disease 2019 (COVID-19). However, empirical evidence of the effectiveness of specific NPIs has been inconsistent. We assessed the effectiveness of NPIs around internal containment and closure, international travel restrictions, economic measures, and health system actions on SARS-CoV-2 transmission in 130 countries and territories.

METHODS

We used panel (longitudinal) regression to estimate the effectiveness of 13 categories of NPIs in reducing SARS-CoV-2 transmission using data from January to June 2020. First, we examined the temporal association between NPIs using hierarchical cluster analyses. We then regressed the time-varying reproduction number (R_t) of COVID-19 against different NPIs. We examined different model specifications to account for the temporal lag between NPIs and changes in R_t, levels of NPI intensity, time-varying changes in NPI effect, and variable selection criteria. Results were interpreted taking into account both the range of model specifications and temporal clustering of NPIs.

RESULTS

There was strong evidence for an association between two NPIs (school closure, internal movement restrictions) and reduced R_t. Another three NPIs (workplace closure, income support, and debt/contract relief) had strong evidence of effectiveness when ignoring their level of intensity, while two NPIs (public events cancellation, restriction on gatherings) had strong evidence of their effectiveness only when evaluating their implementation at maximum capacity (e.g. restrictions on 1000+ people gathering were not effective, restrictions on < 10 people gathering were). Evidence about the effectiveness of the remaining NPIs (stay-at-home requirements, public information campaigns, public transport closure, international travel controls, testing, contact tracing) was inconsistent and inconclusive. We found temporal clustering between many of the NPIs. Effect sizes varied depending on whether or not we included data after peak NPI intensity.

CONCLUSION

Understanding the impact that specific NPIs have had on SARS-CoV-2 transmission is complicated by temporal clustering, time-dependent variation in effects, and differences in NPI intensity. However, the effectiveness of school closure and internal movement restrictions appears robust across different model specifications, with some evidence that other NPIs may also be effective under particular conditions. This provides empirical evidence for the potential effectiveness of many, although not all, actions policy-makers are taking to respond to the COVID-19 pandemic.

Codon usage analysis of zoonotic coronaviruses reveals lower adaptation to humans by SARS-CoV-2

Since 2002, the world has witnessed major outbreaks of acute respiratory illness by three zoonotic coronaviruses (CoVs), which differ from each other in pathogenicity. Reasons for the lower pathogenicity of SARS-CoV-2 than the other two zoonotic coronaviruses, SARS-CoV and MERS-CoV, are not well understood. We herein compared the codon usage patterns of the three zoonotic CoVs causing severe acute respiratory syndromes and four human-specific CoVs (NL63, 229E, OC43, and HKU1) causing mild diseases. We found that the seven viruses have different codon usages, with SARS-CoV-2 having the lowest effective number of codons (ENC) among the zoonotic CoVs. Human codon adaptation index (CAI) analysis revealed that the CAI value of SARS-CoV-2 is the lowest among the zoonotic CoVs. The ENC and CAI values of SARS-CoV-2 were more similar to those of the less-pathogenic human-specific CoVs. To further investigate adaptive evolution within SARS-CoV-2, we examined codon usage patterns in 3573 genomes of SARS-CoV-2 collected over the initial 4 months of the pandemic. We showed that the ENC values and the CAI values of SARS-CoV-2 were decreasing over the period. The low ENC and CAI values could be responsible for the lower pathogenicity of SARS-CoV-2. While mutational pressure appears to shape codon adaptation in the overall genomes of SARS-CoV-2 and other zoonotic CoVs, the E gene of SARS-CoV-2, which has the highest codon usage bias, appears to be under strong natural selection. Data from the study contribute to our understanding of the pathogenicity and evolution of SARS-CoV-2 in humans.

COVID-19 pandemic management and the rheumatology patient

We discuss the evidence behind mask use, including evidence for homemade masks, social distancing, and the local coronavirus disease-2019 (COVID-19) epidemics in countries that initially employed more limited public health interventions. Given the absence of data for specific interventions in the rheumatic disease population, we reviewed the evidence available for the general population. The risk of poor outcomes with COVID-19 in patients with rheumatic diseases is a potential concern given the immunosuppression associated with these conditions and disease-modifying anti-rheumatic drug therapy, as well as advancing age and many of the comorbidities present in such patients. Infection prevention is key, for both individual patients and their community. Given the data collected from the general population, we recommend ongoing proper mask use, social distancing, and hand hygiene for patients with rheumatic diseases and encourage providers to counsel these patients in prevention strategies and attempt to dispel abundant misinformation.

Pandemic trials: evidence-based medicine on steroids

Research is the only exit strategy from current coronavirus disease 2019 (COVID-19) restrictions. The second wave of COVID-19 infections currently affecting most of Europe emphasises that COVID-19, the disease caused by infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is likely to require strict control measures impacting on the daily life of most citizens until either a highly effective approach to treatment or effective vaccines are in widespread use [1–3].

Small trials have been largely overlooked in the early part of the COVID-19 pandemic in favour of “mega-trials”. As new therapies are urgently needed, phase 2 “proof of concept” studies are crucial as we move into a new phase of pandemic research.https://bit.ly/3o0K9kl

State-level variation of initial COVID-19 dynamics in the United States

During an epidemic, metrics such as R0, doubling time, and case fatality rates are important in understanding and predicting the course of an epidemic. However, if collected over country or regional scales, these metrics hide important smaller-scale, local dynamics. We examine how commonly used epidemiological metrics differ for each individual state within the United States during the initial COVID-19 outbreak. We found that the detected case number and trajectory of early detected cases differ considerably between states. We then test for correlations with testing protocols, interventions and population characteristics. We find that epidemic dynamics were most strongly associated with non-pharmaceutical government actions during the early phase of the epidemic. In particular, early social distancing restrictions, particularly on restaurant operations, was correlated with increased doubling times. Interestingly, we also found that states with little tolerance for deviance from enforced rules saw faster early epidemic growth. Together with other correlates such as population density, our results highlight the different factors involved in the heterogeneity in the early spread of COVID-19 throughout the United States. Although individual states are clearly not independent, they can serve as small, natural experiments in how different demographic patterns and government responses can impact the course of an epidemic.

Correlation and causality: a COVID-19 conundrum

I read with interest the two contributions by J.D. Chalmers and co-workers to the July issue of the European Respiratory Journal. In a reply to correspondence concerning the inhaled corticosteroid withdrawal controversy in COPD [1], they suggest that A. Agusti succumbs to the fallacy of post hoc, ergo, propter hoc [2], i.e. A occurred, then B occurred: therefore, A caused B. However, as we know, correlation is not causality.

Predictive models depend heavily on the assumptions made in their constructionhttps://bit.ly/2Eex05F

Evidence, rationality, and ignorance: Agnotological issues in COVID-19 science

Two decades ago, Robert Proctor coined the term agnotology to refer to the study of ignorance that stems from scientific research. Amid the coronavirus disease pandemic, the world is witnessing the greatest natural experiment ever, and countries have adopted different response strategies. An evaluation of the effectiveness of different policies will play a valuable role in preparing for future public health emergencies. However, controversial issues such as the timing and pathways of viral emergence, the effectiveness of social distancing and lockdown strategies, and the use of antimalarial drugs as therapy have still not been fully resolved. This serves as a fertile breeding ground for agnotological strategies, whereby scientific studies are deliberately or unintentionally designed to create distractions or draw conclusions that are not supported by research findings. Researchers, public health authorities, and healthcare workers should be equipped to identify such agnotological strategies, distinguish them from scientific fraud, and avoid drawing misleading inferences based on an irrational adherence to hypotheses and a lack of criticism of implausible results.

On the Progression of COVID-19 in Portugal: A Comparative Analysis of Active Cases Using Non-linear Regression

Portugal is often portrayed as a relatively successful case in the control of COVID-19's March 2020 outbreak in Europe due to timely confinement measures, commonly referred to as the "lockdown". As in other European Union member states, by late April, Portugal was preparing the phased loosening of such measures scheduled for the beginning of May. Despite a modest reduction in infection rates by that time, there was insufficient data to reliably forecast imminent scenarios. Using the South Korea data as scaffold, which became a paradigmatic case of recovery following a high number of infected people, we fitted the Portuguese data to biphasic models using non-linear regression and compared the two countries. The models, which yielded a good fit, showed that recovery would be slow, with over 50% active cases months after the lockdown. These findings acted at the time as a warning, showing that a high number of infected individuals, together with an unknown number of asymptomatic carriers, could increase the risk of a slow recovery, if not of new outbreaks. A month later, the models showed more favorable outcomes. However, shortly after, as the effects of leaving the lockdown became evident, the number of infections began rising again, leaving Portugal in a situation of inward and outward travel restrictions and baffling even the most conservative forecasts for the clearing of the pandemic.

A cuckoo COVID coincidence?

We are grateful to A.H. Morice for his reminder of the limits of observational data, and the need for caution in its interpretation. And we accept that it is unlikely to ever be proved conclusively that the dramatic restrictions imposed as countries locked down caused the dramatic changes in epidemic trajectories, even though the epidemiological changes seemed to follow the behavioural changes. However, there is also a large logical leap from observing the Swedish data to inferring that social distancing “measures can only have had a minor effect”.

There are limitations to inferring causality from observational data, but lockdowns have almost certainly saved lives worldwidehttps://bit.ly/2YWAhhl

Is COVID-19 spreading and curing silently: an observation of three family clusters in Bangladesh

Objectives The number of coronavirus disease (COVID-19) cases is increasing in Bangladesh. Many people have suffered from symptoms like COVID-19 during this pandemic, and some people have cured without taking any treatment or taking minor pharmacological and non-pharmacological treatments. However, they might be spreading their infections among their family members and perhaps in the community. It is unsure that individuals with COVID-19-like symptoms are positive with COVID-19, but our concern is, during this pandemic, any types of symptoms such as flu-like symptoms should have been taken seriously. This study was observed in the cases from three families with COVID-19 like symptoms. Case presentation This observational study was done between May 20 and Jun 2, 2020, in Bangladesh. The members of the inspected families shared COVID-19 like symptoms that were lasted for 3-10 days. Conclusions COVID-19 might be spread and cured silently in Bangladesh, which recommends that awareness is needed throughout the country to prevent the spreading of the disease.

Estimates of the ongoing need for social distancing and control measures post-"lockdown" from trajectories of COVID-19 cases and mortality

By 21 May 2020, severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) had caused more than 5 million cases of coronavirus 2019 (COVID-19) across more than 200 countries. Most countries with significant outbreaks have introduced social distancing or “lockdown” measures to reduce viral transmission. So the key question now is when, how and to what extent these measures can be lifted.

Publicly available data on daily numbers of newly confirmed cases and mortality were used to fit regression models estimating trajectories, doubling times and the reproduction number (R₀) of the disease, before and under the control measures. These data ran up to 21 May 2020, and were sufficient for analysis in 89 countries.

The estimates of R₀ before lockdown based on these data were broadly consistent with those previously published: between 2.0 and 3.7 in the countries with the largest number of cases available for analysis (USA, Italy, Spain, France and UK). There was little evidence to suggest that the restrictions had reduced R far below 1 in many places, with France having the most rapid reductions: R₀ 0.76 (95% CI 0.72–0.82) based on cases, and 0.77 (95% CI 0.73–0.80) based on mortality.

Intermittent lockdown has been proposed as a means of controlling the outbreak while allowing periods of increased freedom and economic activity. These data suggest that few countries could have even 1 week per month unrestricted without seeing resurgence of the epidemic. Similarly, restoring 20% of the activity that has been prevented by the lockdowns looks difficult to reconcile with preventing the resurgence of the disease in most countries.

Data from multiple countries show that current restrictions on behaviour barely contain the spread of COVID-19. Resuming 20% of the currently excluded contact between individuals looks sufficient to restart the epidemic's progression in many countries.https://bit.ly/2B4dIOw