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The past several decades have seen an alarming spike in communicable disease outbreaks worldwide. Given a confluence of host, virologic, environmental, and human factors, experts agree that the next pandemic could already be on the horizon. In a globalized world, changes in how people use land and interact with their ecosystems—such as rapid deforestation and agricultural expansion—have resulted in humans and animals coming into more frequent and intense contact with one another, increasing opportunities for what is known as "zoonotic disease spillover." In the past few years alone, numerous disease outbreaks have had suspected or confirmed zoonotic origin, including mpox (formerly known as monkeypox), Ebola virus disease, dengue fever, and COVID-19. Experts also recognize the need to prepare for another possible Disease X, a term used to describe a currently unknown pathogen with pandemic potential. To direct resources toward the most high-consequence pathogens, it is paramount that leaders have an accurate concept of pandemic risk—for individual viruses as well as viral families. Several institutions are developing disease rankings at national and global levels, including the Priority Zoonotic Diseases Lists facilitated by the U.S. Centers for Disease Control and Prevention and the Research and Development (R&D) Blueprint created by the World Health Organization. The original SpillOver risk ranking framework (SpillOver 1.0), an open-source webtool launched by researchers at the University of California, Davis One Health Institute, estimated the relative spillover potential of wildlife-origin viruses to humans based on a series of host, viral, and environmental risk factors determined via expert opinion and scientific evidence. Its next iteration, SpillOvers 2.0, has rebranded to better describe the diversity and frequency of virus spillovers to people. The new platform uses a One Health approach, which recognizes the interdependence of human, animal, and environmental health. It will expand to include domestic animal and vector-borne viruses and assess pandemic risk rather than just spillover risk for wildlife viruses.
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A team of researchers analyzed the genomes of more than 2,500 modern humans from 26 worldwide populations, to better understand how humans have adapted to historical coronavirus outbreaks. The team used computational methods to uncover genetic traces of adaptation to coronaviruses, the family of viruses responsible for three major outbreaks in the last 20 years, including the ongoing COVID-19 pandemic. Traces of the outbreak are evident in the genetic makeup of people from that area, they’ve found. A coronavirus epidemic broke out in the East Asia region more than 20,000 years ago, as per their findings. The discovery of a coronavirus outbreak from 20,000 years ago is "like finding fossilized dinosaur footprints instead of finding fossilized bones directly. The work shows that over the course of the epidemic, selection favored certain variants of human genes involved in the virus-cell interactions that could have led to a less severe disease. Studying the “tracks” left by ancient viruses can help researchers better understand how the genomes of different human populations adapted to viruses that have emerged as important drivers of human evolution. The study’s authors say their research could help identify viruses that have caused epidemics in the distant past and may do so in the future. Studies like theirs help researchers compile a list of potentially dangerous viruses and then develop diagnostics, vaccines, and drugs for the event of their return. read the paper at https://www.cell.com/current-biology/fulltext/S0960-9822(21)00794-6 more at https://www.futurity.org/coronavirus-epidemic-viruses-2597742/
We discuss the concept of a participatory digital contact notification approach to assist tracing of contacts who are exposed to confirmed cases of coronavirus disease (COVID-19); The core functionality of our concept is to provide a usable, labor-saving tool for contact tracing by confirmed cases themselves the approach is simple and affordable for countries with limited access to health care resources and advanced technology. The proposed tool serves as a supplemental contract tracing approach to counteract the shortage of health care staff while providing privacy protection for both cases and contacts. - This tool can be deployed on the internet or as a plugin for a smartphone app.
- Confirmed cases with COVID-19 can use this tool to provide contact information (either email addresses or mobile phone numbers) of close contacts.
- The system will then automatically send a message to the contacts informing them of their contact status, what this status means, the actions that should follow (eg, self-quarantine, respiratory hygiene/cough etiquette), and advice for receiving early care if they develop symptoms.
- The name of the sender of the notification message by email or mobile phone can be anonymous or not.
- The message received by the contact contains no disease information but contains a security code for the contact to log on the platform to retrieve the information.
Conclusion The successful application of this tool relies heavily on public social responsibility and credibility, and it remains to be seen if the public would adopt such a tool and what mechanisms are required to prevent misuse. This is a simple tool that does not require complicated computer techniques despite strict user privacy protection design with respect to countries and regions. Additionally, this tool can help avoid coercive surveillance, facilitate the allocation of health resources, and prioritize clinical service for patients with COVID-19. Information obtained from the platform can also increase our understanding of the epidemiology of COVID-19. read this concept paper at https://mhealth.jmir.org/2020/6/e20369
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Despite recent achievements in vaccines, antiviral drugs, and medical infrastructure, the emergence of COVID-19 has posed a serious threat to humans worldwide. Most countries are well connected on a global scale, making it nearly impossible to implement perfect and prompt mitigation strategies for infectious disease outbreaks. In particular, due to the explosive growth of international travel, the complex network of human mobility enabled the rapid spread of COVID-19 globally.
Objective:
South Korea was one of the earliest countries to be affected by COVID-19. In the absence of vaccines and treatments, South Korea has implemented and maintained stringent interventions, such as large-scale epidemiological investigations, rapid diagnosis, social distancing, and prompt clinical classification of severely ill patients with appropriate medical measures. In particular, South Korea has implemented effective airport screenings and quarantine measures. In this study, we aimed to assess the country-specific importation risk of COVID-19 and investigate its impact on the local transmission of COVID-19. Methods: The country-specific importation risk of COVID-19 in South Korea was assessed. We investigated the relationships between country-specific imported cases, passenger numbers, and the severity of country-specific COVID-19 prevalence from January to October 2020. We assessed the country-specific risk by incorporating country-specific information. A renewal mathematical model was employed, considering both imported and local cases of COVID-19 in South Korea. Furthermore, we estimated the basic and effective reproduction numbers.
Results: The risk of importation from China was highest between January and February 2020, while that from North America (the United States and Canada) was high from April to October 2020. The R0 was estimated at 1.87 (95% CI 1.47-2.34), using the rate of α=0.07 for secondary transmission caused by imported cases. The Rt was estimated in South Korea and in both Seoul and Gyeonggi.
Conclusions: A statistical model accounting for imported and locally transmitted cases was employed to estimate R0 and Rt.
Our results indicated that the prompt implementation of airport screening measures (contact tracing with case isolation and quarantine) successfully reduced local transmission caused by imported cases despite passengers arriving from high-risk countries throughout the year. Moreover, various mitigation interventions, including social distancing and travel restrictions within South Korea, have been effectively implemented to reduce the spread of local cases in South Korea. read the paper at https://publichealth.jmir.org/2021/6/e26784/
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In a clinical trial, diagnostic testing of suspected cases e.g RT-PCR for severe acute respiratory SARS-CoV-2, can be triggered by the presence of any COVID-19 associated symptom.
A household survey in the United Kingdom (UK) showed that fever, cough, anosmia, and ageusia were present on the day of testing in only 60% of symptomatic, RT-PCR positive individuals, implying that other less specific signs/symptoms associated with COVID-19 occur in a substantial number of patients.
The signs/symptoms associated with COVID-19 are extensive and overlap with those of other common viral infections.
Diagnostic work-up following any COVID-19 associated symptom will lead to extensive testing, potentially overwhelming laboratory capacity whilst primarily yielding negative results. We aimed to identify optimal symptom combinations to capture most cases using fewer tests with implications for COVID-19 vaccine developers across different resource settings and public health.
Methods
UK and US users of the COVID-19 Symptom Study app who reported new-onset symptoms and an RT-PCR test within seven days of symptom onset were included. Sensitivity, specificity, and number of RT-PCR tests needed to identify one case (test per case [TPC]) were calculated for different symptom combinations.
A multi-objective evolutionary algorithm was applied to generate combinations with optimal trade-offs between sensitivity and specificity.
Interpretation
We confirmed the significance of COVID-19 specific symptoms for triggering RT-PCR and identified additional symptom combinations with optimal trade-offs between sensitivity and specificity that maximize case capture given different resource settings.
read this paper at https://www.journalofinfection.com/article/S0163-4453(21)00079-7/fulltext
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Given the potential for the evolution of SARS-CoV-2 variants that render vaccines less effective (vaccine escape), assisted by waning immunity following vaccination, how can COVID-19 exit strategies be planned while limiting the vaccine escape risk? A key component of any plausible strategy towards the permanent removal of non-pharmaceutical interventions (NPIs) is ensuring low case numbers in the short to medium term using NPIs and vaccination. Read this paper which discusses this mathematically https://www.thelancet.com/journals/laninf/article/PIIS1473-3099(21)00202-4/fulltext
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The COVID-19 pandemic consistently demonstrated a pattern of growing community transmission worldwide, even with the adoption of social distancing measures (lockdown or voluntarily shelter in place) in January and early May 2020. The continuing transmission of the virus despite the policy measures adopted in some countries was an important point of debate and investigation in the scientific community and among authorities. Unexpected forms of transmission (atmospheric) associated with the social distancing policy became the central question for the infectious transmission modeling of SARS-CoV-2 and predictive methods. Daily new COVID-19 cases from January to April 2020 demonstrate varying patterns of SARS-CoV-2 transmission across different geographical regions. China and South Korea successfully and quickly flattened their COVID-19 curve. To understand why this was the case, this paper investigated possible aerosol-forming patterns in the atmosphere and their relationship to the policy measures adopted by select countries.
Objective: The main research objective was to compare the outcomes of policies adopted by countries between January and April 2020. Policies included physical distancing measures that in some cases were associated with mask use and city disinfection. We investigated whether the type of social distancing framework adopted by some countries (ie, without mask use and city disinfection) led to the continual dissemination of SARS-CoV-2 (daily new cases) in the community during the study period.
Methods: We examined the policies used as a preventive framework for virus community transmission in some countries and compared them to the policies adopted by China and South Korea. Countries that used a policy of social distancing by 1-2 m were divided into two groups. The first group consisted of countries that implemented social distancing (1-2 m) only, and the second comprised China and South Korea, which implemented distancing with additional transmission/isolation measures using masks and city disinfection. Global daily case maps from Johns Hopkins University were used to provide time-series data for the analysis.
Results: The results showed that virus transmission was reduced due to policies affecting SARS-CoV-2 propagation over time. Remarkably, China and South Korea obtained substantially better results than other countries at the beginning of the epidemic due to their adoption of social distancing (1-2 m) with the additional use of masks and sanitization (city disinfection). These measures proved to be effective due to the atmosphere carrier potential of SARS-CoV-2 transmission.
Conclusions: Our findings confirm that social distancing by 1-2 m with mask use and city disinfection yields positive outcomes. These strategies should be incorporated into prevention and control policies and be adopted both globally and by individuals as a method to fight the COVID-19 pandemic.
read the study at https://publichealth.jmir.org/2021/4/e20699/
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Communicable diseases including COVID-19 pose a major threat to public health worldwide. To curb the spread of communicable diseases effectively, timely surveillance and prediction of the risk of pandemics are essential. The aim of this study is to analyze free and publicly available data to construct useful travel data records for network statistics other than common descriptive statistics. This study describes analytical findings of time-series plots and spatial-temporal maps to illustrate or visualize pandemic connectedness. We observed similar patterns in the time-series plots of worldwide daily flights from January to early-March of 2019 and 2020. A sharp reduction in the number of daily flights recorded in mid-March 2020 was likely related to large-scale air travel restrictions owing to the COVID-19 pandemic. The levels of connectedness between places are strong indicators of the risk of a pandemic. Since the initial reports of COVID-19 cases worldwide, a high network density and reciprocity in early-March 2020 served as early signals of the COVID-19 pandemic and were associated with the rapid increase in COVID-19 cases in mid-March 2020. The spatial-temporal map of connectedness in Europe on March 13, 2020, shows the highest level of connectedness among European countries, which reflected severe outbreaks of COVID-19 in late March and early April of 2020. The analysis can facilitate early recognition of the risk of a current communicable disease pandemic and newly emerging communicable diseases in the future. read the study at https://publichealth.jmir.org/2021/3/e27317
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National governments worldwide have implemented non-pharmaceutical interventions to control the COVID-19 pandemic and mitigate its effects.
Objective: The aim of this study was to investigate the prediction of future daily national confirmed COVID-19 infection growth—the percentage change in total cumulative cases—across 14 days for 114 countries using non-pharmaceutical intervention metrics and cultural dimension metrics, which are indicative of specific national socio-cultural norms.
Methods: We combined the Oxford COVID-19 Government Response Tracker data set, Hofstede cultural dimensions, and daily reported COVID-19 infection case numbers to train and evaluate five non–time series machine learning models in predicting confirmed infection growth.
We used three validation methods—in-distribution, out-of-distribution, and country-based cross-validation—for the evaluation, each of which was applicable to a different use case of the models.
Results: Our results demonstrate high R2 values between the labels and predictions for the in-distribution method (0.959) and moderate R2 values for the out-of-distribution and country-based cross-validation methods (0.513 and 0.574, respectively) using random forest and adaptive boosting (AdaBoost) regression.
Although these models may be used to predict confirmed infection growth, the differing accuracies obtained from the three tasks suggest a strong influence of the use case.
Conclusions: This study adds to the rapidly growing body of work related to predicting COVID-19 infection rates by introducing an approach that incorporates routinely available data on NPIs and cultural dimensions. Importantly, this study emphasizes the utility of NPIs and cultural dimensions for predicting country-level growth of confirmed infections of COVID-19, which to date have been limited in existing forecasting models. Our findings offer a new direction for the broader inclusion of these types of measures, which are also relevant for other infectious diseases, using non–time series machine learning models. Our experiments also provide insight into validation methods for different applications of the models.
read the entire study at https://www.jmir.org/2021/4/e26628
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Viruses need entry proteins to penetrate the cells where they will replicate. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) version is called the spike or S protein. The S protein, also the target of the current vaccines, is quickly adapting to its new human hosts. It took its first major step in this direction early in 2020, when its amino acid 614 (of 1297) changed from an aspartic acid (D) to a glycine (G). Viruses bearing this D614G mutation transmit among humans more rapidly and now form the majority in circulation. On page 525 of this issue, Zhang et al. (1) use careful structural analyses to reveal how D614G changed the S protein to accelerate the pandemic. The work of Zhang et al. also reveals more about the natural history of the virus. The notable emergence of D614G suggests that the acquisition of a destabilizing furin site was a recent event. The virus could easily lose this site, as it does frequently in cell culture systems, implying that it in some way facilitates human transmission. This is not a conclusion that most students of human coronaviruses would have anticipated, given that SARS-CoV-1, which transmits with reasonable efficiency, lacks this site, whereas the more distantly related MERS coronavirus bears this site and transmits poorly. How the SARS-CoV-2 furin site promotes new human infections remains a key open question in the field. read the entire article at https://science.sciencemag.org/content/372/6541/466
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More than two dozen virologists, epidemiologists, and others responded to STAT's question about what they still most wanted to know. In the 16 months since the SARS-CoV-2 virus burst into the global consciousness, we’ve learned much about this new health threat. People who contract the virus are infectious before they develop symptoms and are most infectious early in their illness. Getting the public to wear masks, even homemade ones, can reduce transmission. Vaccines can be developed, tested, and put into use within months. As they say, where there’s a will, there’s a way. But many key questions about SARS-2 and the disease it causes, Covid-19, continue to bedevil scientists. What accounts for the wide variety of human responses to this virus? How much immunity is enough immunity? How often will reinfections happen and what will they be like? how long will immunity last? How are viral variants going to impact the battle against Covid-19? What is long Covid, who is at risk of developing it, and can it be prevented? What’s the deal with Covid and kids? How big a role do asymptomatically infected people actually play in SARS-2 transmission? What does the future hold for SARS-2, evolutionarily and otherwise? Can we figure out who might become a superspreader? Can we learn more quicker from the study of the genetic sequences of SARS-2 viruses? What is the impact of the nonpharmaceutical interventions? What are the barriers to compliance of proven public health interventions and how can that problem best be addressed? what are yhe differences between SARS-2 and its older cousin, SARS-1 Where did SARS-2 come from? Read more at https://www.statnews.com/2021/04/20/we-know-a-lot-about-covid-19-experts-have-many-more-questions/
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The pandemics of major infectious diseases often cause public health, economic, and social problems. Virtual reality (VR) and augmented reality (AR), as two novel technologies, have been used in many fields for emergency management of disasters. The objective of this paper was to review VR and AR applications in the emergency management of infectious outbreaks with an emphasis on the COVID-19 outbreak. It appears that VR and AR technologies can play a positive role during infectious disease outbreaks. VR and AR have been widely used in the prevention and response phases of emergency management during infectious disease pandemics, such as SARS and Ebola pandemics, especially for educating and training purposes for the public. During the COVID-19 outbreak, these technologies have the potential to be used in various fields, including 1) clinical context (e.g., telehealth, drug discovery, patient assessment, mental health management), 2) entertainment (e.g., video call, meditation, gaming), 3) business and industry (e.g., holding meetings and conferences, marketing), and 4) education (e.g., in schools and universities, for healthcare providers, and VR-based content for improving public health). These technologies can be used in the above-mentioned fields by providing their different features for facilitating the challenges of COVID-19. However, to respond to COVID-19, all applications of VR and AR should be considered as a supportive approach alongside other information technologies. We believe that VR and AR have a substantial potential to impact the emergency management of COVID-19 or any infectious disease pandemics; however, these potentials need to be studied in a more robust manner. read the paper ta https://www.sciencedirect.com/science/article/pii/S2352914821000691
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Pandemic SEIR and SEIRV modelling software and infrastructure for the Corona SARS-COV-2 COVID-19 disease with data from Johns-Hopkins-University CSSE, Robert Koch-Institute and vaccination data from Our World In Data. The SARS-COV-2 pandemic has been affecting our lives for months. The effectiveness of measures against the pandemic can be tested and predicted by using epidemiological models. The Corona SEIR Workbench uses a SEIR model and combines a graphical output of the results with a simple parameter input for the model. Modelled data can be compared country by country with the SARS-COV-2 infection data of the Johns Hopkins University. Additionally, the R₀ values of the Robert Koch Institute can be displayed for Germany. Vaccination data is used from Our World In Data.
The COVID-19 pandemic is the greatest public health crisis of the last 100 years. Countries have responded with various levels of lockdown to save lives and stop health systems from being overwhelmed. At the same time, lockdowns entail large socioeconomic costs. One exit strategy under consideration is a mobile phone app that traces the close contacts of those infected with COVID-19. Recent research has demonstrated the theoretical effectiveness of this solution in different disease settings. However, concerns have been raised about such apps because of the potential privacy implications. This could limit the acceptability of app-based contact tracing in the general population. As the effectiveness of this approach increases strongly with app uptake, it is crucial to understand public support for this intervention. Objective: The objective of this study is to investigate the user acceptability of a contact-tracing app in five countries hit by the pandemic.
Methods: We conducted a largescale, multicountry study (N=5995) to measure public support for the digital contact tracing of COVID-19 infections.
We ran anonymous online surveys in France, Germany, Italy, the United Kingdom, and the United States and measured intentions to use a contact-tracing app across different installation regimes (voluntary installation vs automatic installation by mobile phone providers) and studied how these intentions vary across individuals and countries.
Results: We found strong support for the app under both regimes, in all countries, across all subgroups of the population, and irrespective of regional-level COVID-19 mortality rates.
We investigated the main factors that may hinder or facilitate uptake and found that concerns about cybersecurity and privacy, together with a lack of trust in the government, are the main barriers to adoption.
Conclusions:
Epidemiological evidence shows that app-based contact tracing can suppress the spread of COVID-19 if a high enough proportion of the population uses the app and that it can still reduce the number of infections if uptake is moderate. Our findings show that the willingness to install the app is very high. The available evidence suggests that app-based contact tracing may be a viable approach to control the diffusion of COVID-19. read the study at https://mhealth.jmir.org/2020/8/e19857
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Background: In March 2020, South Africa implemented strict nonpharmaceutical interventions (NPIs) to contain the spread of COVID-19. Over the subsequent 5 months, NPI policies were eased in stages according to a national strategy. COVID-19 spread throughout the country heterogeneously; the case numbers peaked from July to August. A second COVID-19 wave began in late 2020. Data on the impact of NPI policies on social and economic well-being and access to health care are limited.
Objective: We aimed to determine how rural residents in three South African provinces changed their behaviors during the first COVID-19 epidemic wave.
Methods: The South African Population Research Infrastructure Network nodes in the Mpumalanga (Agincourt), KwaZulu-Natal, (Africa Health Research Institute) and Limpopo (Dikgale-Mamabolo-Mothiba) provinces conducted up to 14 rounds of longitudinal telephone surveys among randomly sampled households from rural and periurban surveillance populations every 2-3 weeks. Interviews included questions on the following topics: COVID-19–related knowledge and behaviors, the health and economic impacts of NPIs, and mental health. We analyzed how responses varied based on NPI stringency and household sociodemographics.
Conclusions: South Africans complied with stringent, COVID-19–related NPIs despite the threat of substantial social, economic, and health repercussions. Government-supported social welfare programs appeared to buffer interruptions in income and health care access during local outbreaks. Epidemic control policies must be balanced against the broader well-being of people in resource-limited settings and designed with parallel support systems when such policies threaten peoples’ income and access to basic services.
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COVID-19 Research Resources to develop your own study materials
The Covid-19 Research Implementation and Knowledge Hub of the Global Health Network contains a wide range of resources to guide teams in developing their own study materials and support high-quality, rapid implementation of critical COVID-19 studies in various settings. The Global Health Network is running this crowdsourcing initiative to support a faster implementation of research studies during this pandemic. It slow and unnecessary for each group wanting to set up a study to start from scratch; when there are excellent studies already running. The Hub is being continually updated so its good to bookmark it so you can check it regularly for new resources that could help your research team with your COVID-19 study. Link to the Covid-19 Research Implementation and Knowledge Hub
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When it comes to loosening COVID restrictions all eyes are usually trained on the famous R number. But as epidemiologists Julia Gog and Thomas House recently explained to us, there's also another important factor to consider alongside R. That's the prevalence of COVID-19 in the population: the proportion of people who currently have the disease. Put simply, if prevalence has been so high that the NHS is in crisis, then opening up might stretch it to breaking point, even if R is less than 1, or would remain so. If, on the other hand, prevalence is very low, we might be able to tolerate a higher value of R as it would not immediately lead to many cases. This is true particularly if prevalence has been low for some time. We've illustrated this idea in the schematic plot below. The vertical axis measures prevalence and the horizontal axis measures R. Any point on this plot, such as the one we marked in black right in the middle, corresponds to a situation where we have the value of R that lies directly beneath the point on the horizontal axis, and the value of prevalence that lies directly to the left of the point on the vertical axis read this excellent piece at https://plus.maths.org/content/R-not-all?nl=0
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The Centers for Disease Control and Prevention (CDC) warned in a document published Friday of "repeatedly documented" instances of coronavirus spreading through the air to people more than 6 feet away under certain conditions. The new document explaining the latest understanding of how the virus spreads is part of a shifting emphasis towards airborne transmission of the virus. "Transmission of SARS-CoV-2 from inhalation of virus in the air farther than six feet from an infectious source can occur," the new document says in large letters, while noting it is "less likely than at closer distances." Some experts have been pushing the CDC for months to place a greater emphasis on airborne transmission and the need to improve ventilation, even with something as simple as opening the window in a room. Experts have also long said that outdoors is far safer than indoors. The CDC acknowledged last year that the virus can spread through airborne transmission, but there has since been a growing emphasis on that method of transmission. The agency emphasized that while it is updating its understanding of how the virus spreads, the same methods for keeping safe still apply. Wearing a mask, distancing from others, avoiding crowded indoor areas and allowing adequate ventilation are recommended. read the story at https://thehill.com/policy/healthcare/552406-cdc-warns-virus-can-spread-more-than-six-feet-under-certain-conditions
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The spread of SARS-CoV-2, originating in Wuhan, China, was classified as a pandemic by the World Health Organization on March 11, 2020. The governments of affected countries have implemented various measures to limit the spread of the virus. The starting point of this paper is the different government approaches, in terms of promulgating new legislative regulations to limit the virus diffusion and to contain negative effects on the populations. Objective: This paper aims to study how the spread of SARS-CoV-2 is linked to government policies and to analyze how different policies have produced different results on public health.
Methods: Considering the official data provided by 4 countries (Italy, Germany, Sweden, and Brazil) and from the measures implemented by each government, we built an agent-based model to study the effects that these measures will have over time on different variables such as the total number of COVID-19 cases, intensive care unit (ICU) bed occupancy rates, and recovery and case-fatality rates. The model we implemented provides the possibility of modifying some starting variables, and it was thus possible to study the effects that some policies (eg, keeping the national borders closed or increasing the ICU beds) would have had on the spread of the infection.
Conclusions: In line with what we expected, the obtained results showed that the countries that have taken restrictive measures in terms of limiting the population mobility have managed more successfully than others to contain the spread of COVID-19. Moreover, the model demonstrated that herd immunity cannot be reached even in countries that have relied on a strategy without strict containment measures.
read the study at https://medinform.jmir.org/2021/4/e24192
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Sentinel surveillance of influenza-like illness (ILI) in Egypt started in 2000 at 8 sentinel sites geographically distributed all over the country. In response to the COVID-19 pandemic, SARS-CoV-2 was added to the panel of viral testing by polymerase chain reaction (PCR) for the first 2 patients with ILI seen at one of the sentinel sites. We report the first SARS-CoV-2 and influenza A(H1N1) virus co-infection with mild symptoms detected through routine ILI surveillance in Egypt.
This report aims to describe how the case was identified and the demographic and clinical characteristics and outcomes of the patient.
Conclusions: This case highlights the possible occurrence of SARS-CoV-2/influenza A(H1N1) co-infection in younger and healthy people, who may resolve the infection rapidly. We emphasize the usefulness of the surveillance system for detection of viral causative agents of ILI and recommend broadening of the testing panel, especially if it can guide case management.
read the paper at https://publichealth.jmir.org/2021/4/e27433
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The authors propose that it is a scientific error to use lack of direct evidence of SARS-CoV-2 in some air samples to cast doubt on airborne transmission while overlooking the quality and strength of the overall evidence base. There is consistent, strong evidence that SARS-CoV-2 spreads by airborne transmission. Although other routes can contribute, the authors believe that the airborne route is likely to be dominant. The public health community should act accordingly and without further delay. Summary: If an infectious virus spreads predominantly through large respiratory droplets that fall quickly, the key control measures are reducing direct contact, cleaning surfaces, physical barriers, physical distancing, use of masks within droplet distance, respiratory hygiene, and wearing high-grade protection only for so-called aerosol-generating health-care procedures. Such policies need not distinguish between indoors and outdoors, since a gravity-driven mechanism for transmission would be similar for both settings. But if an infectious virus is mainly airborne, an individual could potentially be infected when they inhale aerosols produced when an infected person exhales, speaks, shouts, sings, sneezes, or coughs. Reducing airborne transmission of virus requires measures to avoid inhalation of infectious aerosols, including ventilation, air filtration, reducing crowding and time spent indoors, use of masks whenever indoors, attention to mask quality and fit, and higher-grade protection for health-care staff and front-line workers. Airborne transmission of respiratory viruses is difficult to demonstrate directly. Mixed findings from studies that seek to detect viable pathogen in air are therefore insufficient grounds for concluding that a pathogen is not airborne if the totality of scientific evidence indicates otherwise. Decades of painstaking research, which did not include capturing live pathogens in the air, showed that diseases once considered to be spread by droplets are airborne. Ten streams of evidence collectively support the hypothesis that SARS-CoV-2 is transmitted primarily by the airborne route.
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Simple in structure but advanced in function, viruses exist in a category that lies between the inert and the living. Slightly ovoid in shape and somewhat blurred at the edges, the black splotches were scattered across a mottled gray background, looking much like a postmodern painting. At a meeting of the Medical Society of Berlin in 1938, Helmut Ruska, a German physician and biologist, was presenting the first images ever seen of virus particles. The splotches were members of the poxvirus family, specifically ectromelia, visualized directly in the lymph fluids of infected mice. Thanks to the invention of the electron microscope, then known as the Übermikroscop, scientists could finally observe—actually see—what was already known to exist: the minuscule and mysterious world of viruses. Ruska’s brother, Ernst, a physicist, had built the first prototype of the instrument while completing his Ph.D., but Helmut saw the device’s potential application to the field of biology. Helmut and his colleagues went on to gather nearly 2,000 black-and-white images by the end of 1939. Their collection included a variety of pathogens known to infect humans and plants, including the variola virus (which causes smallpox) and tobacco mosaic virus (the first virus ever discovered). Just over 80 years later, scientists published the first images of SARS-CoV-2, the novel virus that causes COVID-19. To reveal its iconic spike protein, they used an instrument similar to Ruska’s. The black-and-white images visually confirmed that this was a member of the coronavirus family, enabling scientists around the world to begin drawing upon existing knowledge of such viruses from years of prior research. Scientists were able to directly observe this new virus soon after a cluster of patients in China was diagnosed in late December 2019 with a pneumonia of unknown cause. By March 2020, COVID-19 had been declared a pandemic by the World Health Organization. Events moved far more slowly in previous pandemics. The Black Death pandemic in the mid 1300s killed more than one-third of Europe’s population in four years, without anyone knowing what caused it. By the time of the 1918 flu pandemic, scientists understood the disease’s cause but couldn’t see the virus or test for it. When SARS-CoV-2 emerged, the value of basic science research conducted many decades earlier became quickly evident in the form of innovative tools for virus detection. Researchers can now sequence novel viruses and study their genomes, but even so the electron microscope continues to offer a unique “open” view of such pathogens. There may be more viruses than there are stars in the universe. Basic science research being conducted today will play a critical role in helping us to understand their past, present, and future—and better prepare us for the emergence of still more novel viruses. read the entire essay at https://nautil.us/issue/99/universality/the-vast-viral-world-what-we-know-and-dont-know
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