What Is Required to Prevent a Second Major Outbreak of SARS-CoV-2 upon Lifting Quarantine in Wuhan City, China

Novel Mutations in the Non-Structure Protein 2 of SARS-CoV-2

Introduction

Mutation in the genome of SARS-CoV-2 may play a role in immune evasion, pathogenicity, and speed of its transmission. Our investigation aimed to evaluate the mutations that exist in the NSP2.

Materials and Method

RNA was extracted from nasopharyngeal swabs from 100 COVID-19 patients. RT-PCR was performed on all samples using NSP2-specific primers. Following gel electrophoresis, the bands were cut, purified, and sequenced using the Sanger method. After sequencing, 90 sequences could be used for further analysis. Bioinformatics analysis was conducted to investigate the effect of mutations on protein structure, stability, prediction of homology models, and phylogeny tree.

Results

The patients' mean age was 51.08. The results revealed that 8 of the 17 NSP2 mutations (R207C, T224I, G262V, T265I, K337D, N348S, G392D, and I431M) were missense. One deletion was also found in NSP2. Among NSP2 missense mutations studied, K337D and G392D increased structural stability while the others decreased it. The homology-designed models demonstrated that the homologies were comparable to the sequences of the Wuhan-HU-1 virus.

Conclusion

Our study suggested that the mutations K337D and G392D modulate the stability of NSP2, and tracking viral evolution should be implemented and vaccine development updated.

Implementing Silica Nanoparticles in the Study of the Airborne Transmission of SARS-CoV-2

Aerosol transmission constitutes one of the major transmission routes of the SARS-CoV-2 pathogen. Due to the pathogen's properties, research on its airborne transmission has some limitations. This paper focuses on silica nanoparticles (SiO2) of 40 and 200 nm sizes as the physicochemical markers of a single SARS-CoV-2 particle enabling experiments on the transmission of bioaerosols in public spaces. Mixtures of a determined silica concentration were sprayed on as an aerosol, whose particles, sedimented on dedicated matrices, were examined by scanning electron microscopy (SEM) and transmission electron microscopy (TEM). Since it was not possible to quantitatively identify the markers based on the obtained images, the filters exposed with the AirSampler aspirator were analyzed based on inductively coupled plasma optical emission spectroscopy (ICP-OES). The ICP-OES method enabled us to determine the concentration of silica after extracting the marker from the filter, and consequently to estimate the number of markers. The developed procedure opens up the possibility of the quantitative estimation of the spread of the coronavirus, for example in studies on the aerosol transmission of the pathogen in an open environment where biological markers-surrogates included-cannot be used.

Environmental risks of disposable face masks during the pandemic of COVID-19: Challenges and management

Since the COVID-19 outbreak in early 2020, face mask (FM) has been recognized as an effective measure to reduce the infection, increasing its consumption across the world. However, the large amount of at-home FM usage changed traditional medical waste management practices, lack of improper management. Currently, few studies estimate FM consumption at a global scale, not to say a comprehensive investigation on the environmental risks of FM from a life cycle perspective. Therefore, global FM consumption and its associated environmental risks are clarified in the present study. Our result shows that 449.5 billion FMs were consumed from January 2020 to March 2021, with an average of 59.4 FMs per person worldwide. This review also provides a basis to understand the environmental risk of randomly disposed of FM and highlights the urgent requirement for the attention of FMs waste management to prevent pollution in the near future.

What Is the Impact of Early and Subsequent Epidemic Characteristics on the Pre-delta COVID-19 Epidemic Size in the United States?

It is still uncertain how the epidemic characteristics of COVID-19 in its early phase and subsequent waves contributed to the pre-delta epidemic size in the United States. We identified the early and subsequent characteristics of the COVID-19 epidemic and the correlation between these characteristics and the pre-delta epidemic size. Most (96.1% (49/51)) of the states entered a fast-growing phase before the accumulative number of cases reached (30). The days required for the number of confirmed cases to increase from 30 to 100 was 5.6 (5.1−6.1) days. As of 31 March 2021, all 51 states experienced at least 2 waves of COVID-19 outbreaks, 23.5% (12/51) experienced 3 waves, and 15.7% (8/51) experienced 4 waves, the epidemic size of COVID-19 was 19,275−3,669,048 cases across the states. The pre-delta epidemic size was significantly correlated with the duration from 30 to 100 cases (p = 0.003, r = −0.405), the growth rate of the fast-growing phase (p = 0.012, r = 0.351), and the peak cases in the subsequent waves (K1 (p < 0.001, r = 0.794), K2 (p < 0.001, r = 0.595), K3 (p < 0.001, r = 0.977), and K4 (p = 0.002, r = 0.905)). We observed that both early and subsequent epidemic characteristics contribute to the pre-delta epidemic size of COVID-19. This identification is important to the prediction of the emerging viral infectious diseases in the primary stage.

Early and Subsequent Epidemic Characteristics of COVID-19 and Their Impact on the Epidemic Size in Ethiopia

In Ethiopia, multiple waves of the COVID-19 epidemic have been observed. So far, no studies have investigated the characteristics of the waves of epidemic waves in the country. Identifying the epidemic trend in Ethiopia will inform future prevention and control of COVID-19. This study aims to identify the early indicators and the characteristics of multiple waves of the COVID-19 epidemics and their impact on the overall epidemic size in Ethiopia. We employed the Jointpoint software to identify key epidemic characteristics in the early phase of the COVID-19 epidemic and a simple logistic growth model to identify epidemic characteristics of its subsequent waves. Among the first 100 reported cases in Ethiopia, we identified a slow-growing phase (0.37 [CI: 0.10-0.78] cases/day), which was followed by a fast-growing phase (1.18 [0.50-2.00] cases/day). The average turning point from slow to fast-growing phase was at 18 days after first reported. We identified two subsequent waves of COVID-19 in Ethiopia during 03/2020-04/2021. We estimated the number of COVID-19 cases that occurred during the second wave (157,064 cases) was >2 times more than the first (60,016 cases). The second wave's duration was longer than the first (116 vs. 96 days). As of April 30th, 2021, the overall epidemic size in Ethiopia was 794/100,000, ranging from 1,669/100,000 in the Harari region to 40/100,000 in the Somali region. The epidemic size was significantly and positively correlated with the day of the phase turning point (r = 0.750, P = 0.008), the estimated number of cases in wave one (r = 0.854, P < 0.001), and wave two (r = 0.880, P < 0.001). The second wave of COVID-19 in Ethiopia is far greater, and its duration is longer than the first. Early phase turning point and case numbers in the subsequent waves predict its overall epidemic size.

Evaluating the Impact of SARS-CoV-2 Variants on the COVID-19 Epidemic and Social Restoration in the United States: A Mathematical Modelling Study

Background: Multiple SARS-CoV-2 variants are still rampant across the United States (US). We aimed to evaluate the impact of vaccination scale-up and potential reduction in the vaccination effectiveness on the COVID-19 epidemic and social restoration in the US. Methods: We extended a published compartmental model and calibrated the model to the latest US COVID-19 data. We estimated the vaccine effectiveness against the variant and evaluated the impact of a potential reduction in vaccine effectiveness on the epidemics. We explored the epidemic trends under different levels of social restoration. Results: We estimated the overall existing vaccine effectiveness against the variant as 88.5% (95% CI: 87.4-89.5%) with the vaccination coverage of 70% by the end of August, 2021. With this vaccine effectiveness and coverage, there would be 498,972 (109,998-885,947) cumulative infections and 15,443 (3,828-27,057) deaths nationwide over the next 12 months, of which 95.0% infections and 93.3% deaths were caused by the variant. Complete social restoration at 60, 65, 70% vaccination coverage would increase cumulative infections to 1.6 (0.2-2.9) million 0.7 (0.1-1.2) million, and 511,159 (110,578-911,740), respectively. At same time it would increase cumulative deaths to 39,040 (5,509-72,570), 19,562 (3,873-35,250), 15,739 (3,841-27,638), respectively. However, if the vaccine effectiveness were reduced to 75%, 50% or 25% due to new SARS-CoV-2 variants, there would be 667,075 (130,682-1,203,468), 1.7 (0.2-3.2) million, 19.0 (5.3-32.7) million new infections and 19,249 (4,281-34,217), 42,265 (5,081-79,448), 426,860 (117,229-736,490) cumulative deaths to occur over the next 12 months. Further, social restoration at a lower vaccination coverage would lead to even greater secondary outbreaks. Conclusion: Current COVID-19 vaccines remain effective against the SARS-CoV-2 variant, and 70% vaccination coverage would be sufficient to restore social activities to a pre-pandemic level. Further reduction in vaccine effectiveness against SARS-CoV-2 variants would result in a potential surge of the epidemic. Multiple measures, including public health interventions, vaccination scale-up and development of a new vaccine booster, should be integrated to counter the new challenges of new SARS-CoV-2 variants.

The coronavirus global pandemic and its impacts on society

The aim of the study is to assess the impact of various nationalities, cultures, and religions on the spread of the coronavirus in the human environment. Particular attention was paid to compliance with legal and ethical standards during a pandemic. Different cultures, nationalities, and religions have a significant influence on the development and spread of the coronavirus in the world. During the COVID-19 pandemic, due to the tightening of legal standards, it is necessary to ensure: protection of patient confidentiality; of freedom of the expression; accesses to critical information; the opportunities to belong to social organizations and civil society; the accesses to professionals healthcare; ensure equal rights for women and guarantee the right to water and sanitation; continuity of humanitarian aid and targeted economic aid. Travel locks and bans should comply with legal standards; the right to education should be strictly respected. Artificial intelligence can be used in the fight against the crown.

Response of Saudi Population to Strict Preventive Measures against COVID-19

The Saudi ministry of health (MOH) started the preventive measures very early on before having a single case of COVID-19. There were very few studies regarding the awareness and adherence to the preventive measures against COVID-19 among the Saudi population in the literature. Objectives: The study aims to examine the awareness and commitment to the strict Saudi government preventive measures against COVID-19. Methods: A cross-sectional online survey targeted Saudi and non-Saudi populations aged 18+ in March–April 2020. The online questionnaire was designed to explore the participant’s sociodemographic data, washing hygiene habits, the general level of awareness regarding COVID-19, and the extent to which they adhere to the government’s strict instructions. Results: Out of the 2958 participants in the survey, 23% washed their hands for between 20 and 30 s, 59.6% washed their hands after shaking hands with other people, 67.9% washed their hands after use of other’s utilities, 65.9% had appropriately followed the MOH recommended guidelines for home quarantine and social distancing. People in different age groups differed significantly on their practiced hygienic practices score p < 0.001. Respondents’ educational level had converged considerably and positively on their clean proper prevention practices score, f(2838.3) = 15.70. Conclusion: The majority of the participants adhere to the strict government instructions regarding COVID-19 as they have to obey the law. Health sector employees measured significantly greater hygienic preventive measures and precautions in comparison to other sectors. More public health efforts should increase hygienic best practice scores to achieve the best outcome.

Risk and Protective Factors for the Mental Wellbeing of Deployed Healthcare Workers During the COVID-19 Pandemic in China: A Qualitative Study

Background: Though many literatures documented burnout and occupational hazard among healthcare workers and frontliners during pandemic, not many adopted a systemic approach to look at the resilience among this population. Another under-studied population was the large numbers of global healthcare workers who have been deployed to tackle the crisis of COVID-19 pandemic in the less resourceful regions. We investigated both the mental wellbeing risk and protective factors of a deployed healthcare workers (DHWs) team in Wuhan, the epicenter of the virus outbreak during 2020. Method: A consensual qualitative research approach was adopted with 25 DHWs from H province through semi-structured interviews after 3 months of deployment period. Results: Inductive-Deductive thematic coding with self-reflexivity revealed multi-layered risk and protective factors for DHWs at the COVID-19 frontline. Intensive working schedule and high-risk environment, compounded by unfamiliar work setting and colleagues; local culture adaptation; isolation from usual social circle, strained the DHWs. Meanwhile, reciprocal relationships and "familial relatedness" with patients and colleagues; organizational support to the DHWs and their immediate families back home, formed crucial wellbeing resources in sustaining the DHWs. The dynamic and dialectical relationships between risk and protective factors embedded in multiple layers of relational contexts could be mapped into a socio-ecological framework. Conclusion: Our multidisciplinary study highlights the unique social connectedness between patient-DHWs; within DHWs team; between deploying hospital and DHWs; and between DHWs and the local partners. We recommend five organizational strategies as mental health promotion and capacity building for DHWs to build a resilient network and prevent burnout at the disaster frontline.

Investigating the relationship between reopening the economy and implementing control measures during the COVID-19 pandemic

Objectives

The COVID-19 pandemic has resulted in an enormous burden on population health and the economy around the world. Although most cities in the United States have reopened their economies from previous lockdowns, it was not clear how the magnitude of different control measures—such as face mask use and social distancing—may affect the timing of reopening the economy for a local region. This study aimed to investigate the relationship between reopening dates and control measures and identify the conditions under which a city can be reopened safely.

Study design

This was a mathematical modeling study.

Methods

We developed a dynamic compartment model to capture the transmission dynamics of COVID-19 in New York City. We estimated model parameters from local COVID-19 data. We conducted three sets of policy simulations to investigate how different reopening dates and magnitudes of control measures would affect the COVID-19 epidemic.

Results

The model estimated that maintaining social contact at 80% of the prepandemic level and a 50% face mask usage would prevent a major surge of COVID-19 after reopening. If social distancing were completely relaxed after reopening, face mask usage would need to be maintained at nearly 80% to prevent a major surge.

Conclusions

Adherence to social distancing and increased face mask usage are keys to prevent a major surge after a city reopens its economy. The findings from our study can help policymakers identify the conditions under which a city can be reopened safely.

A Retrospective Analysis of the COVID-19 Infodemic in Saudi Arabia

COVID-19 has had broad disruptive effects on economies, healthcare systems, governments, societies, and individuals. Uncertainty concerning the scale of this crisis has given rise to countless rumors, hoaxes, and misinformation. Much of this type of conversation and misinformation about the pandemic now occurs online and in particular on social media platforms like Twitter. This study analysis incorporated a data-driven approach to map the contours of misinformation and contextualize the COVID-19 pandemic with regards to socio-religious-political information. This work consists of a combined system bridging quantitative and qualitative methodologies to assess how information-exchanging behaviors can be used to minimize the effects of emergent misinformation. The study revealed that the social media platforms detected the most significant source of rumors in transmitting information rapidly in the community. It showed that WhatsApp users made up about 46% of the source of rumors in online platforms, while, through Twitter, it demonstrated a declining trend of rumors by 41%. Moreover, the results indicate the second-most common type of misinformation was provided by pharmaceutical companies; however, a prevalent type of misinformation spreading in the world during this pandemic has to do with the biological war. In this combined retrospective analysis of the study, social media with varying approaches in public discourse contributes to efficient public health responses.

How to Reduce the Transmission Risk of COVID-19 More Effectively in New York City: An Age-Structured Model Study

Background: In face of the continuing worldwide COVID-19 epidemic, how to reduce the transmission risk of COVID-19 more effectively is still a major public health challenge that needs to be addressed urgently. Objective: This study aimed to develop an age-structured compartment model to evaluate the impact of all diagnosed and all hospitalized on the epidemic trend of COVID-19, and explore innovative and effective releasing strategies for different age groups to prevent the second wave of COVID-19. Methods: Based on three types of COVID-19 data in New York City (NYC), we calibrated the model and estimated the unknown parameters using the Markov Chain Monte Carlo (MCMC) method. Results: Compared with the current practice in NYC, we estimated that if all infected people were diagnosed from March 26, April 5 to April 15, 2020, respectively, then the number of new infections on April 22 was reduced by 98.02, 93.88, and 74.08%. If all confirmed cases were hospitalized from March 26, April 5, and April 15, 2020, respectively, then as of June 7, 2020, the total number of deaths in NYC was reduced by 67.24, 63.43, and 51.79%. When only the 0-17 age group in NYC was released from June 8, if the contact rate in this age group remained below 61% of the pre-pandemic level, then a second wave of COVID-19 could be prevented in NYC. When both the 0-17 and 18-44 age groups in NYC were released from June 8, if the contact rates in these two age groups maintained below 36% of the pre-pandemic level, then a second wave of COVID-19 could be prevented in NYC. Conclusions: If all infected people were diagnosed in time, the daily number of new infections could be significantly reduced in NYC. If all confirmed cases were hospitalized in time, the total number of deaths could be significantly reduced in NYC. Keeping a social distance and relaxing lockdown restrictions for people between the ages of 0 and 44 could not lead to a second wave of COVID-19 in NYC.

A dossier on COVID-19 chronicle

The dissemination of the 2019 novel coronavirus (2019-nCoV) is presenting the planet with a new health emergency response or threat to health. The virus emerged in bats and was disseminated to humans in December 2019 via still unknown intermediate species in Wuhan, China. It is disseminated by inhalation or breaks out with infected droplets and the incubation period is between 2 and 14 days. The symptoms usually include high body temperature, cough, sore throat, dyspnea, low energy or tiredness, and weakness. The condition is moderate in most people; but in the elderly and those with comorbidities, it advances to pneumonia, acute respiratory distress syndrome (ARDS), and multiple organ failure. Popular research work includes normal/low WBC with upraised C-reactive protein (CRP). Treatment is generally supportive and requires home seclusion of suspected persons and rigorous infection control methods at hospitals. The Covid-19 has lower fatality than SARS and MERS. Among the proposed therapeutic regimen, hydroxychloroquine, chloroquine, remdisevir, azithromycin, toclizumab, and cromostat mesylate have shown promising results, and the limited benefit was seen with lopinavir-ritonavir treatment in hospitalized adult patients with severe COVID-19. Early development of the SARS-CoV-2 vaccine started based on the full-length genome analysis of severe acute respiratory syndrome coronavirus. Several subunit vaccines, peptides, nucleic acids, plant-derived, and recombinant vaccines are under pipeline. Research work, development of new medicines and vaccines, and efforts to reduce disease morbidity and mortality must be encouraged to improve our position in the fight against this disease and to protect human life.

Projected COVID-19 epidemic in the United States in the context of the effectiveness of a potential vaccine and implications for social distancing and face mask use

BACKGROUND

Multiple candidates of COVID-19 vaccines have entered Phase III clinical trials in the United States (US). There is growing optimism that social distancing restrictions and face mask requirements could be eased with widespread vaccine adoption soon.

METHODS

We developed a dynamic compartmental model of COVID-19 transmission for the four most severely affected states (New York, Texas, Florida, and California). We evaluated the vaccine effectiveness and coverage required to suppress the COVID-19 epidemic in scenarios when social contact was to return to pre-pandemic levels and face mask use was reduced. Daily and cumulative COVID-19 infection and death cases from 26th January to 15th September 2020 were obtained from the Johns Hopkins University Coronavirus resource center and used for model calibration.

RESULTS

Without a vaccine (scenario 1), the spread of COVID-19 could be suppressed in these states by maintaining strict social distancing measures and face mask use levels. But relaxing social distancing restrictions to the pre-pandemic level without changing the current face mask use would lead to a new COVID-19 outbreak, resulting in 0.8-4 million infections and 15,000-240,000 deaths across these four states over the next 12 months. Under this circumstance, introducing a vaccine (scenario 2) would partially offset this negative impact even if the vaccine effectiveness and coverage are relatively low. However, if face mask use is reduced by 50% (scenario 3), a vaccine that is only 50% effective (weak vaccine) would require coverage of 55-94% to suppress the epidemic in these states. A vaccine that is 80% effective (moderate vaccine) would only require 32-57% coverage to suppress the epidemic. In contrast, if face mask usage stops completely (scenario 4), a weak vaccine would not suppress the epidemic, and further major outbreaks would occur. A moderate vaccine with coverage of 48-78% or a strong vaccine (100% effective) with coverage of 33-58% would be required to suppress the epidemic. Delaying vaccination rollout for 1-2 months would not substantially alter the epidemic trend if the current non-pharmaceutical interventions are maintained.

CONCLUSIONS

The degree to which the US population can relax social distancing restrictions and face mask use will depend greatly on the effectiveness and coverage of a potential COVID-19 vaccine if future epidemics are to be prevented. Only a highly effective vaccine will enable the US population to return to life as it was before the pandemic.

Effects of New York's Executive Order on Face Mask Use on COVID-19 Infections and Mortality: A Modeling Study

There is growing evidence on the effect of face mask use in controlling the spread of COVID-19. However, few studies have examined the effect of local face mask policies on the pandemic. In this study, we developed a dynamic compartmental model of COVID-19 transmission in New York City (NYC), which was the epicenter of the COVID-19 pandemic in the USA. We used data on daily and cumulative COVID-19 infections and deaths from the NYC Department of Health and Mental Hygiene to calibrate and validate our model. We then used the model to assess the effect of the executive order on face mask use on infections and deaths due to COVID-19 in NYC. Our results showed that the executive order on face mask use was estimated to avert 99,517 (95% CIs 72,723-126,312) COVID-19 infections and 7978 (5692-10,265) deaths in NYC. If the executive order was implemented 1 week earlier (on April 10), the averted infections and deaths would be 111,475 (81,593-141,356) and 9017 (6446-11,589), respectively. If the executive order was implemented 2 weeks earlier (on April 3 when the Centers for Disease Control and Prevention recommended face mask use), the averted infections and deaths would be 128,598 (94,373-162,824) and 10,515 (7540-13,489), respectively. Our study provides public health practitioners and policymakers with evidence on the importance of implementing face mask policies in local areas as early as possible to control the spread of COVID-19 and reduce mortality.

Community evidence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission through air

BACKGROUND

Nine COVID-19 (Corona Virus Disease, 2019) cases were observed in one community in Guangzhou. All the cases lived in three vertically aligned units of one building sharing the same piping system, which provided one unique opportunity to examine the transmission mode of SARS-CoV-2.

METHODS

We interviewed the cases on the history of travelling and close contact with the index patients. Respiratory samples from all the cases were collected for viral phylogenetic analyses. A simulation experiment in the building and a parallel control experiment in a similar building were then conducted to investigate the possibility of transmission through air.

RESULTS

Index patients living in Apartment 15-b had a travelling history in Wuhan, and four cases who lived in Apartment 25-b and 27-b were subsequently diagnosed. Phylogenetic analyses showed that virus of all the patients were from the same strain of the virus. No close contacts between the index cases and other families indicated that the transmission might not occur through droplet and close contacts. Airflow detection and simulation experiment revealed that flushing the toilets could increase the speed of airflow in the pipes and transmitted the airflow from Apartment 15-b to 25-b and 27-b. Reduced exhaust flow rates in the infected building might have contributed to the outbreak.

CONCLUSIONS

The outbreak of COVID-19 in this community could be largely explained by the transmission through air, and future efforts to prevent the infection should take the possibility of transmission through air into consideration. A disconnected drain pipe and exhaust pipe for toilet should be considered in the architectural design to help prevent possible virus spreading through the air.

Risk of Secondary Infection Waves of COVID-19 in an Insular Region: The Case of the Balearic Islands, Spain

The Spanish government declared the lockdown on March 14th, 2020 to tackle the fast-spreading of COVID-19. As a consequence, the Balearic Islands remained almost fully isolated due to the closing of airports and ports, these isolation measures and the home-based confinement have led to a low prevalence of COVID-19 in this region. We propose a compartmental model for the spread of COVID-19 including five compartments (Susceptible, Exposed, Presymptomatic Infective, Diseased, and Recovered), and the mobility between municipalities. The model parameters are calibrated with the temporal series of confirmed cases provided by the Spanish Ministry of Health. After calibration, the proposed model captures the trend of the official confirmed cases before and after the lockdown. We show that the estimated number of cases depends strongly on the initial dates of the local outbreak onset and the number of imported cases before the lockdown. Our estimations indicate that the population has not reached the level of herd immunization necessary to prevent future outbreaks. While the low prevalence, in comparison to mainland Spain, has prevented the saturation of the health system, this low prevalence translates into low immunization rates, therefore facilitating the propagation of new outbreaks that could lead to secondary waves of COVID-19 in the region. These findings warn about scenarios regarding after-lockdown-policies and the risk of second outbreaks, emphasize the need for widespread testing, and could potentially be extrapolated to other insular and continental regions.

Monitoring Crop Growth During the Period of the Rapid Spread of COVID-19 in China by Remote Sensing

The status of crop growth under the influence of COVID-19 is an important information for evaluating the current food security in China. This article used the cloud computing platform of Google Earth Engine, to access and analyze Sentinel-2, MODIS, and other multisource remote sensing data in the last five years to monitor the growth of crops in China, especially in Hubei province, during the period of the rapid spread of COVID-19 (i.e., from late January to mid-March 2020), and compared with the growth over the same period under similar climate conditions in the past four years. We further analyzed the indirect effects of COVID-19 on crop growth. The results showed that: the area of the crops with better growth (51%) was much more than that with worse growth (22%); the crops with better and worse growth were mainly distributed in the North China Plain (the main planting areas of winter wheat in China) and the South China regions (such as Guangxi, Guangdong province), respectively. The area of the crops with a similar growth occupied 27%. In Hubei province, the area of the crops with better growth (61%) was also more than that with worse growth (27%). It was found that there was no obvious effect from COVID-19 on the overall growth of crops in China during the period from late January to mid-March 2020 and the growth of crops was much better than that during the same period in previous years. The findings in this study are helpful in evaluating the impact of the COVID-19 on China's agriculture, which are conducive to serve the relevant agricultural policy formulation and to ensure food security.

Correlation of COVID-19 Pandemic with Healthcare System Response and Prevention Measures in Saudi Arabia

BACKGROUND

The Saudi government has taken the decision to prevent the entrance of about 2.5 million international pilgrims seeking to perform hajj in order to protect the world from a catastrophic widespread of disease. Moreover, health systems in Saudi Arabia are offering free testing for residents whether Saudi and non-Saudi.

OBJECTIVE

This study aimed to evaluate the spread of COVID-19 associated with preventive measures taken in Saudi Arabia and to develop a detailed COVID-19 prevention strategy as a framework for the Saudi Arabia community.

METHODOLOGY

Population size and age distributions among the country of Saudi Arabia were taken from the 2020 World Population Prospects. Contact patterns were measured using the Saudi Arabia Ministry of Health Statistical Annual Report.

CONCLUSIONS

Our study demonstrates that performing screening tests as early as possible to facilitate the rapid detection of infected cases, fast treatment, and instant isolation for suspected cases is the most definitive rejoinder for public health. Moreover, our study revealed the significance of performing preventive measures in reducing infection and death rates around Saudi Arabia by 27%, while in other countries, it reduced the death rate ranging from 10-73%. This study provides an achievable strategy for prevention and early detection of COVID-19 spread.

Early characteristics of the COVID-19 outbreak predict the subsequent epidemic scope

OBJECTIVES

The mostly-resolved first wave of the COVID-19 epidemic in China provided a unique opportunity to investigate how the initial characteristics of the COVID-19 outbreak predict its subsequent magnitude.

METHODS

We collected publicly available COVID-19 epidemiological data from 436 Chinese cities from 16th January-15th March 2020. Based on 45 cities that reported >100 confirmed cases, we examined the correlation between early-stage epidemic characteristics and subsequent epidemic magnitude.

RESULTS

We identified a transition point from a slow- to a fast-growing phase for COVID-19 at 5.5 (95% CI, 4.6-6.4) days after the first report, and 30 confirmed cases marked a critical threshold for this transition. The average time for the number of confirmed cases to increase from 30 to 100 (time from 30-to-100) was 6.6 (5.3-7.9) days, and the average case-fatality rate in the first 100 confirmed cases (CFR-100) was 0.8% (0.2-1.4%). The subsequent epidemic size per million population was significantly associated with both of these indicators. We predicted a ranking of epidemic size in the cities based on these two indicators and found it highly correlated with the actual classification of epidemic size.

CONCLUSIONS

Early epidemic characteristics are important indicators for the size of the entire epidemic.

Can self-imposed prevention measures mitigate the COVID-19 epidemic?

Yuming Guo and colleagues discuss the research by Teslya et al that highlights the importance of personal preventative measures in avoiding a second wave of the COVID-19 epidemic.

COVID-19: test, trace and isolate-new epidemiological data

In the absence of an efficient drug treatment or a vaccine, the control of the COVID‐19 pandemic relies on classic infection control measures. Since these means are socially disruptive and come with substantial economic loss for societies, a better knowledge of the epidemiology of the new coronavirus epidemic is crucial to achieve control at a sustainable cost and within tolerable restrictions of civil rights.