Coronavirus Epidemic Research Articles

Predictors of COVID-19 epidemics in countries of the World Health Organization African Region

Countries of the World Health Organization (WHO) African Region have experienced a wide range of coronavirus disease 2019 (COVID-19) epidemics. This study aimed to identify predictors of the timing of the first COVID-19 case and the per capita mortality in WHO African Region countries during the first and second pandemic waves and to test for associations with the preparedness of health systems and government pandemic responses. Using a region-wide, country-based observational study, we found that the first case was detected earlier in countries with more urban populations, higher international connectivity and greater COVID-19 test capacity but later in island nations. Predictors of a high first wave per capita mortality rate included a more urban population, higher pre-pandemic international connectivity and a higher prevalence of HIV. Countries rated as better prepared and having more resilient health systems were worst affected by the disease, the imposition of restrictions or both, making any benefit of more stringent countermeasures difficult to detect. Predictors for the second wave were similar to the first. Second wave per capita mortality could be predicted from that of the first wave. The COVID-19 pandemic highlights unanticipated vulnerabilities to infectious disease in Africa that should be taken into account in future pandemic preparedness planning.

Association Between What People Learned About COVID-19 Using Web Searches and Their Behavior Toward Public Health Guidelines: Empirical Infodemiology Study.

BackgroundThe use of the internet and web-based platforms to obtain public health information and manage health-related issues has become widespread in this digital age. The practice is so pervasive that the first reaction to obtaining health information is to “Google it.” As SARS-CoV-2 broke out in Wuhan, China, in December 2019 and quickly spread worldwide, people flocked to the internet to learn about the novel coronavirus and the disease, COVID-19. Lagging responses by governments and public health agencies to prioritize the dissemination of information about the coronavirus outbreak through the internet and the World Wide Web and to build trust gave room for others to quickly populate social media, online blogs, news outlets, and websites with misinformation and conspiracy theories about the COVID-19 pandemic, resulting in people’s deviant behaviors toward public health safety measures.ObjectiveThe goals of this study were to determine what people learned about the COVID-19 pandemic through web searches, examine any association between what people learned about COVID-19 and behavior toward public health guidelines, and analyze the impact of misinformation and conspiracy theories about the COVID-19 pandemic on people’s behavior toward public health measures.MethodsThis infodemiology study used Google Trends’ worldwide search index, covering the first 6 months after the SARS-CoV-2 outbreak (January 1 to June 30, 2020) when the public scrambled for information about the pandemic. Data analysis employed statistical trends, correlation and regression, principal component analysis (PCA), and predictive models.ResultsThe PCA identified two latent variables comprising past coronavirus epidemics (pastCoVepidemics: keywords that address previous epidemics) and the ongoing COVID-19 pandemic (presCoVpandemic: keywords that explain the ongoing pandemic). Both principal components were used significantly to learn about SARS-CoV-2 and COVID-19 and explained 88.78% of the variability. Three principal components fuelled misinformation about COVID-19: misinformation (keywords “biological weapon,” “virus hoax,” “common cold,” “COVID-19 hoax,” and “China virus”), conspiracy theory 1 (ConspTheory1; keyword “5G” or “@5G”), and conspiracy theory 2 (ConspTheory2; keyword “ingest bleach”). These principal components explained 84.85% of the variability. The principal components represent two measurements of public health safety guidelines—public health measures 1 (PubHealthMes1; keywords “social distancing,” “wash hands,” “isolation,” and “quarantine”) and public health measures 2 (PubHealthMes2; keyword “wear mask”)—which explained 84.7% of the variability. Based on the PCA results and the log-linear and predictive models, ConspTheory1 (keyword “@5G”) was identified as a predictor of people’s behavior toward public health measures (PubHealthMes2). Although correlations of misinformation (keywords “COVID-19,” “hoax,” “virus hoax,” “common cold,” and more) and ConspTheory2 (keyword “ingest bleach”) with PubHealthMes1 (keywords “social distancing,” “hand wash,” “isolation,” and more) were r=0.83 and r=–0.11, respectively, neither was statistically significant (P=.27 and P=.13, respectively).ConclusionsSeveral studies focused on the impacts of social media and related platforms on the spreading of misinformation and conspiracy theories. This study provides the first empirical evidence to the mainly anecdotal discourse on the use of web searches to learn about SARS-CoV-2 and COVID-19.

Role of Religious Coping and Moral Intelligence in Predicting Students' Psychological Hardiness during the Coronavirus Epidemic

Role of Religious Coping and Moral Intelligence in Predicting Students' Psychological Hardiness during the Coronavirus Epidemic

Comparative analysis of transmissibility and case fatality ratio of SARS, MERS and COVID-19 via a mathematical modeling approach

Coronavirus epidemics emerged in the 1960s and the world has witnessed seven coronavirus outbreaks since then. Four of the coronaviruses instigate human influenza while the rest: Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV), the Middle East Respiratory Syndrome Coronavirus (MERS-CoV) and Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) trigger severe respiratory disorders (SARS, MERS and COVID-19 respectively). The etiology of SARS, MERS and COVID-19 are similar but their epidemiology, in terms of incubation period, infectivity, case fatality ratio and the serial interval differ. In an attempt to compare the infectivity and case fatality ratio of the diseases, a mathematical model was considered for each disease. The key epidemiological quantity, the basic reproduction number, was derived for each model to examine the transmission potential of each disease. The mortality rates for the diseases were also investigated by considering the global report of COVID-19 as of October 1 2020 together with the history of SARS and MERS. Results from the computations showed that COVID-19 had the highest transmission potential and at the same time the lowest case fatality ratio. It was also revealed that COVID-19 would have wrecked more havocs had its case fatality ratio was as high as that of MERS.

Elevated Neopterin Levels Predict Fatal Outcome in SARS-CoV-2-Infected Patients.

HighlightsInnate immune activation during Covid-19 infection is associated with pernicious clinical outcome.BackgroundCoronavirus disease 2019 (Covid-19) is a worldwide threat that has already caused more than 3 000 000 deaths. It is characterized by different patterns of disease evolution depending on host factors among which old-age and pre-existing comorbidities play a detrimental role. Previous coronavirus epidemics, notably SARS-CoV, were associated with increased serum neopterin levels, which can be interpreted as a sign of acute innate immunity in response to viral infection. Here we hypothesize that neopterin may serve as a biomarker of SARS-CoV-2 viral infection and Covid-19 disease severity.MethodsWe measured neopterin blood levels by ELISA. Seric concentration was quantified from 256 healthy donors and 374 Covid-19 patients at hospital admission. Enrolled Covid-19 patients were all symptomatic and displayed a large spectrum of comorbidities. Patients were followed until disease resolution or death.ResultsSevere and critically ill SARS-CoV-2 infected patients were characterized by a profound exacerbation of immune activation characterized by elevated neopterin blood levels. Systemic neopterin levels above 19nM stratified healthy individuals from Covid-19 patients with 87% specificity and 100% sensitivity. Moreover, systemic neopterin levels above 53nM differentiated non-survivors from survivors with 64% specificity and 100% sensitivity.ConclusionWe propose that neopterin concentration measured at arrival to hospital is a hallmark of severe Covid-19 and identifies a high-risk population of pernicious clinical outcome with a need for special medical care.

Understanding the Impacts of Novel Coronavirus Outbreaks on People Who Use Drugs: A Systematic Review to Inform Practice and Drug Policy Responses to COVID-19.

People who use drugs (PWUD) experience many social and health harms and are considered at greater risk of acquiring COVID-19. Little research has examined the impact of coronaviruses either on PWUD, or on services targeted to PWUD. We report the findings of a systematic review of empirical evidence from studies which have examined the impact of coronaviruses (Severe Acute Respiratory Syndrome (SARS-CoV-1) and Middle Eastern Respiratory Syndrome (MERS-CoV) and COVID-19) on PWUD or on service responses to them. Five databases were searched (MEDLINE, PsycINFO, CINAHL, ASSIA and EMBASE) as well as COVID-19 specific databases. Inclusion criteria were studies reporting any impact of SARS, MERS or COVID-19 or any service responses to those, published between January 2000 and October 2020. Weight of Evidence judgements and quality assessment were undertaken. In total, 27 primary studies were included and grouped by seven main themes: treatment/recovery services; emergency medical settings; low-threshold services; prison setting, PWUD/substance use disorder (SUD) diagnosis; people with SUD and HIV; ‘Sexual minority’ men. Overall, research in the area was scant, and of average/poor quality. More robust research is required to inform on-going and future responses to coronavirus epidemics for PWUD.

What COVID-19 has taught the world

Background: A novel coronavirus (SARS-CoV-2) has captured global recognition in a short period of time by dramatically impacting people's everyday lives and emerged as a public health emergency. Undoubtedly, it shows that lessons learned from past coronavirus epidemics such as the Middle East Respiratory Syndrome (MERS) and the Serious Acute Respiratory Syndrome (SARS) were not adequate and thus left us ill-prepared to deal with the challenges presently raised by the COVID-19 pandemic. Methods: COVID-19 adds to the list of previous outbreaks of infectious disease epidemics that try to remind us that we live in an ecosystem where the relationship between human and animal life, and the environment must be respected in order to survive and prosper. Rapid urbanization and our forestland invasion have created a new interface between humans and wildlife, and have exposed humans to unfamiliar species, frequently involving unfamiliar organisms and exotic wildlife. Findings: Every pandemic is nature’s way of reminding us that the interrelationship between all forms of existence needs to be recognized. To limit new infectious outbreaks, the transdisciplinary ‘One Health’ solution incorporating ‘Health in All Policy’ involving all stakeholders especially environmental health and social sciences is being advocated . Conclusion: Savings and investments should be made by everyone to meet the unexpected. Stigmatization and prejudice among individuals in the world should be discouraged. Special attention should be paid to the elderly, as their immune system is weak. Health and safety precautions such as physical distancing and health hygiene etiquettes should be considered as part of life. Global experience teaches that containment steps and active tracing of contacts are effective to minimize the economic burden of disease and enhance knowledge of disease processes, health issues, disease emergence, and re-emergence. These lessons will help us to battle future pandemics.

A database resource and online analysis tools for coronaviruses on a historical and global scale.

The recent outbreak of COVID-19 caused by a new zoonotic origin coronavirus (SARS-CoV-2 or 2019-nCoV) has sound the alarm for the potential spread of epidemic coronavirus crossing species. With the urgent needs to assist disease control and to provide invaluable scientific information, we developed the coronavirus database (CoVdb), an online genomic, proteomic and evolutionary analysis platform. CoVdb has brought together genomes of more than 5000 coronavirus strains, which were collected from 1941 to 2020, in more than 60 countries and in hosts belonging to more than 30 species, ranging from fish to human. CoVdb presents comprehensive genomic information, such as gene function, subcellular localization, topology and protein structure. To facilitate coronavirus research, CoVdb also provides flexible search approaches and online tools to view and analyze protein structure, to perform multiple alignments, to automatically build phylogenetic trees and to carry on evolutionary analyses. CoVdb can be accessed freely at http://covdb.popgenetics.net. Hopefully, it will accelerate the progress to develop medicines or vaccines to control the pandemic of COVID-19.

Effectiveness of Internet Attachment-Based Compassion Therapy on Rumination and Fear of Coronavirus Disease in Elderly Women during Coronavirus Epidemics

Background and Objective: Based on the available data, the elderly people are the most vulnerable population during the coronavirus (COVID-19) epidemic since they both suffer from the disease and have to tolerate the quarantine that has been imposed to control the outbreak of the virus. Rumination is one of the most important variables during the COVID-19 epidemic due to the fact that people experience traumatic problems. The present study aimed to investigate the effect of Internet Attachment-based Compassion Therapy on rumination and fear of COVID-19 in elderly women during the epidemic. Materials and Methods: This was a quasi-experimental study with a pretest, posttest design, and a control group with a one-month follow-up. The statistical population included older women at Hamedan city, Iran, in 2020. The participants included 32 individuals who were randomly assigned into two groups of experiment (n=16) and control (n=16). The experiment group received eight sessions of Internet-based compassion treatment, and the control group did not receive any intervention. The data were collected using the Ruminative Response Scale to measure the fear of COVID-19 disease. The collected data were analyzed using SPSS software (Version 25) through one-way repeated measures analysis of variance and Bonferroni test, in two levels of descriptive (mean and standard deviation) and inferential statistics. Results: The analysis of obtained results in the post-test showed a significant decrease in rumination and fear of COVID-19 in the elderly women in the experiment group, compared to the control group during the pandemic. This result was consistent after a one-month follow-up (P<0.01). Conclusions: According to the results, it is recommended that health professionals and therapists use the Internet attachment-based compassion therapy approach along with other training and therapeutic approaches to decrease rumination and fear of coronavirus disease in the elderly women during the coronavirus epidemic.

Prediction of Health Anxiety Based on Spiritual Well-being and Cognitive Emotion Regulation Strategies During COVID-19 in Iranian Individuals

Background: Epidemic coronavirus disease 2019 (COVID-19) and quarantine implementation have had various effects on the psychological aspects of society. One of the psychological effects of COVID-19 is the fear of getting the disease. Objectives: The present study aimed to predict health anxiety based on spiritual well-being and cognitive emotion regulation strategies during COVID-19 in Iranian individuals. Methods: The present descriptive-correlational study was conducted on the statistical population of all 19-to-79-year-old individuals participating in the study online. A total of 545 subjects were selected by the convenience sampling method. These participants completed short-form health anxiety questionnaires, spiritual well-being scales, and short-form emotion regulation strategies online. The data were analyzed by the Pearson correlation coefficient and stepwise regression analysis using SPSS software (version 23). Results: The results showed that health anxiety had a significant negative relationship with spiritual well-being (r = -0.339**) and adaptive cognitive emotion regulation strategies (r = -0.308**). Furthermore, health anxiety had a significant positive relationship with maladaptive cognitive emotion regulation strategies (r = 0.390**). Overall, the aforementioned three variables explained 26.1% of changes in health anxiety. Conclusions: The results of the present study showed the impacts of spiritual well-being and cognitive emotion regulation strategies on health anxiety. Therefore, it is recommended that training based on spiritual teachings and emotion regulation strategies reduces health anxiety during the outbreak of COVID-19.

An Emerging Trend of Slow Tourism: Perceptions of Hungarian Citizens

Besides slow food, slow city, slow fashion, education, and marketing - slow tourism is one of the several different slow movements. Several trends justify the importance and the reasons for the existence of slow tourism: the aging society, the growing power of women in making travel decisions. Slow tourism was born as a possibility for those, who would like to live their life in a different way even during their travels: giving respect to the environment and to the people, too. In case of slow tourism culture, traditions, gastronomy is in the center. Sustainability is also a priority, meanwhile, the well-being and interests of the inhabitants of the destination are also taken into account. Instead of mass tourism products authentic, not standardized experiences are in the supply. The research aimed to investigate the attitudes and perceptions of respondents towards different slow tourism elements. The study is based on quantitative data from an online survey conducted with 386 Hungarian respondents in the framework of omnibus research. To reveal the perceptions and attitude of the respondents towards slow elements multidimensional scaling model and principal component methods were applied. Based on the results it can be concluded, that the local elements of a journey are important for the respondents, meanwhile, the personalized services, the spirituality of the destination, and the sustainable approach do not matter. Only a small proportion of respondents avoids crowded destinations, so traveling to hidden places is not a favorite holiday option for the majority of Hungarians. However, the coronavirus epidemics can strengthen the demand for this tourism product, since expectedly there will be more tourists, who want to avoid crowded places during their holiday. Service providers can also benefit from the results of the research, and concentrate on the elements that proved to be important for Hungarian travelers.

Coronavirus epidemics are part of human history

Coronavirus epidemics are part of human history

An ancient viral epidemic involving host coronavirus interacting genes more than 20,000 years ago in East Asia

The current severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has emphasized the vulnerability of human populations to novel viral pressures, despite the vast array of epidemiological and biomedical tools now available. Notably, modern human genomes contain evolutionary information tracing back tens of thousands of years, which may help identify the viruses that have impacted our ancestors—pointing to which viruses have future pandemic potential. Here, we apply evolutionary analyses to human genomic datasets to recover selection events involving tens of human genes that interact with coronaviruses, including SARS-CoV-2, that likely started more than 20,000 years ago. These adaptive events were limited to the population ancestral to East Asian populations. Multiple lines of functional evidence support an ancient viral selective pressure, and East Asia is the geographical origin of several modern coronavirus epidemics. An arms race with an ancient coronavirus, or with a different virus that happened to use similar interactions as coronaviruses with human hosts, may thus have taken place in ancestral East Asian populations. By learning more about our ancient viral foes, our study highlights the promise of evolutionary information to better predict the pandemics of the future. Importantly, adaptation to ancient viral epidemics in specific human populations does not necessarily imply any difference in genetic susceptibility between different human populations, and the current evidence points toward an overwhelming impact of socioeconomic factors in the case of coronavirus disease 2019 (COVID-19).

Epidemic spreading in an expanded parameter space: the supercritical scaling laws and subcritical metastable phases

While the mathematical laws of uncontrolled epidemic spreading are well known, the statistical physics of coronavirus epidemics with containment measures is currently lacking. The modelling of available data of the first wave of the Covid-19 pandemic in 2020 over 230 days, in different countries representative of different containment policies is relevant to quantify the efficiency of these policies to face the containment of any successive wave. At this aim we have built a 3D phase diagram tracking the simultaneous evolution and the interplay of the doubling time, T d, and the reproductive number, R t measured using the methodological definition used by the Robert Koch Institute. In this expanded parameter space three different main phases, supercritical, critical and subcritical are identified. Moreover, we have found that in the supercritical regime with R t > 1 the doubling time is smaller than 40 days. In this phase we have established the power law relation between T d and (R t − 1)−ν with the exponent ν depending on the definition of reproductive number. In the subcritical regime where R t < 1 and T d > 100 days, we have identified arrested metastable phases where T d is nearly constant.

Guidelines for Mountain Rescue During the COVID-19 Pandemic: Official Guidelines of the International Commission for Alpine Rescue.

Roy, Steven, Inigo Soteras, Alison Sheets, Richard Price, Kazue Oshiro, Simon Rauch, Don McPhalen, Maria Antonia Nerin, Giacomo Strapazzon, Myron Allen, Alistair Read, and Peter Paal. Guidelines for mountain rescue during the COVID-19 pandemic: official guidelines of the International Commission for Alpine Rescue. High Alt Med Biol. 22: 128–141, 2021.Background: In mountain rescue, uncertainty exists on the best practice to prevent coronavirus disease 2019 (COVID-19) transmission. The aim of this work was to provide a state-of-the-art overview of the challenges caused by the COVID-19 pandemic in mountain rescue.Methods: Original articles or reviews, published until December 27, 2020 in Cochrane COVID-19 Study Register, EMBASE, PubMed, and Google Scholar were included. Articles were limited to English, French, German, or Spanish with the article topic COVID-19 or other epidemics, addressing transmission, transport, rescue, or cardiopulmonary resuscitation.Results: The literature search yielded 6,190 articles. A total of 952 were duplicates and 5,238 were unique results. After exclusion of duplicates and studies that were not relevant to this work, 249 articles were considered for this work. Finally, 72 articles and other sources were included.Conclusions: Recommendations are provided for protection of the rescuer (including screening, personal protective equipment [PPE], and vaccination), protection of the patient (including general masking if low risk, specific PPE if high risk), equipment hygiene (including disinfection after every mission), use of single-use products, training and medical measures under COVID-19 precautions, and psychological wellbeing of rescuers during the COVID-19 pandemic. Adapted COVID-19 precautions for low-and-medium-income countries are also discussed.

The ecological dynamics of the coronavirus epidemics during transmission from outside sources when R 0 is successfully managed below one.

Since COVID-19 spread globally in early 2020 and was declared a pandemic by the World Health Organization (WHO) in March, many countries are managing the local epidemics effectively through intervention measures that limit transmission. The challenges of immigration of new infections into regions and asymptomatic infections remain. Standard deterministic compartmental models are inappropriate for sub- or peri-critical epidemics (reproductive number close to or less than one), so individual-based models are often used by simulating transmission from an infected person to others. However, to be realistic, these models require a large number of parameters, each with its own set of uncertainties and lack of analytic tractability. Here, we apply stochastic age-structured Leslie theory with a long history in ecological research to provide some new insights to epidemic dynamics fuelled by external imports. We model the dynamics of an epidemic when R0 is below one, representing COVID-19 transmission following the successful application of intervention measures, and the transmission dynamics expected when infections migrate into a region. The model framework allows more rapid prediction of the shape and size of an epidemic to improve scaling of the response. During an epidemic when the numbers of infected individuals are rapidly changing, this will help clarify the situation of the pandemic and guide faster and more effective intervention.

Differential impact of non-pharmaceutical public health interventions on COVID-19 epidemics in the United States

BackgroundThe widespread pandemic of novel coronavirus disease 2019 (COVID-19) poses an unprecedented global health crisis. In the United States (US), different state governments have adopted various combinations of non-pharmaceutical public health interventions (NPIs), such as non-essential business closures and gathering bans, to mitigate the epidemic from February to April, 2020. Quantitative assessment on the effectiveness of NPIs is greatly needed to assist in guiding individualized decision making for adjustment of interventions in the US and around the world. However, the impacts of these approaches remain uncertain.MethodsBased on the reported cases, the effective reproduction number (Rt) of COVID-19 epidemic for 50 states in the US was estimated. Measurements on the effectiveness of nine different NPIs were conducted by assessing risk ratios (RRs) between Rt and NPIs through a generalized linear model (GLM).ResultsDifferent NPIs were found to have led to different levels of reduction in Rt. Stay-at-home contributed approximately 51% (95% CI 46–57%), wearing (face) masks 29% (15–42%), gathering ban (more than 10 people) 19% (14–24%), non-essential business closure 16% (10–21%), declaration of emergency 13% (8–17%), interstate travel restriction 11% (5–16%), school closure 10% (7–14%), initial business closure 10% (6–14%), and gathering ban (more than 50 people) 7% (2–11%).ConclusionsThis retrospective assessment of NPIs on Rt has shown that NPIs played critical roles on epidemic control in the US in the past several months. The quantitative results could guide individualized decision making for future adjustment of NPIs in the US and other countries for COVID-19 and other similar infectious diseases.

A retrospective analysis of 12,400 SARS-CoV-2 RNA tests in patients with COVID-19 in Wuhan.

The outbreak and widely spread of coronavirus disease 2019 (COVID-19) has become a global public health concern. COVID-19 has caused an unprecedented and profound impact on the whole world, and the prevention and control of COVID-19 is a global public health challenge remains to be solved. The retrospective analysis of the large scale tests of SARS-CoV-2 RNA may indicate some important information of this pandemic. We selected 12400 SARS-CoV-2 tests detected in Wuhan in the first semester of 2020 and made a systematic analysis of them, in order to find some beneficial clue for the consistent prevention and control of COVID-19.SARS-CoV-2 RNA was detected in suspected COVID-19 patients with real-time fluorescence quantitative PCR (RT-qPCR). The patients’ features including gender, age, type of specimen, source of patients, and the dynamic changes of the clinical symptoms were recorded and statistically analyzed. Quantitative and qualitive statistical analysis were carried out after laboratory detection.The positive rate of SARS-CoV-2 was 33.02% in 12,400 suspected patients’ specimens in Wuhan at the first months of COVID-19 epidemics. SARS-CoV-2 RT-qPCR test of nasopharyngeal swabs might produce 4.79% (594/12400) presumptive results. The positive rate of SARS-CoV-2 RNA was significantly different between gender, age, type of specimen, source of patients, respectively (P < .05). The median window period from the occurrence of clinical symptom or close contact with COVID-19 patient to the first detection of positive PCR was 2 days (interquartile range, 1–4 days). The median interval time from the first SARS-CoV-2 positive to the turning negative was 14 days (interquartile range, 8–19.25 days).This study reveals the comprehensive characteristics of the SARS-CoV-2 RNA detection from multiple perspectives, and it provides important clues and may also supply useful suggestions for future work of the prevention and treatment of COVID-19.

A transdisciplinary approach to disease ecology: Emerging coronaviruses

Humankind is currently facing the effects of an unparalleled pandemic that has impacted healthcare, social, and economic systems worldwide. Numerous studies have been published since the SARS-CoV-2 outbreak began in Wuhan, China. Most have focused on virology, epidemiology, pathogenesis, and therapeutic medicine, having been centered by reactive strategies to control the pandemic. Meanwhile, publications addressing the ecological, evolutionary, and anthropogenic drivers of virus emergence, and potential strategies to prevent future outbreaks have been sparse. Here, we highlight the necessity of complementary and transdisciplinary insight and methodologies from an integrated perspective to study emergent diseases. It is paramount to situate the consistently associated factors to understand the complexity of the current pandemic. Disease ecology can examine information to recognize the causes of emergence while appraising the role of interactions among pathogens, domestic animals, wildlife, and humans, integratively. Here we draw on a variety of disciplines and perspectives, from evolutionary biology, biogeography, ecology, molecular epidemiology and integrative health, to address the emergence of coronaviruses, with particular emphasis on SARS-CoV-2. We describe the process of the surfacing of zoonotic diseases, highlighting the interactions among wildlife, domestic animals, and humans, as well as the genetic, evolutionary, ecological, and anthropogenic processes that favor coronavirus epidemics and epizootics. We discuss specific results related to coronavirus investigations conducted in Mexico based on disease ecology methodologies. Finally, we describe alternative approaches for understanding and preventing future outbreaks and we suggest strategies to entice integrative and transdisciplinary research within the One Health/Ecohealth paradigm.

Prevention and control measures significantly curbed the SARS-CoV-2 and influenza epidemics in China

At the end of 2019, an outbreak of pneumonia took place caused by a new coronavirus (SARS-CoV-2 virus), named coronavirus disease 2019 (COVID-19). A series of strict prevention and control measures were then implemented to reduce the spread of the epidemic. Influenza, another respiratory tract virus, may also respond to these measures. To assess the impact of these measures, we used the total number of passengers movement in mainland China from 2018 to 2020 and daily number of railway passenger flow during the 2020 Spring Festival travel rush to reflect the population movement and to analyze newly and cumulatively confirmed COVID-19 and influenza cases. We found that implementing the series of measures against COVID-19 mitigated both COVID-19 and influenza epidemics in China. Prevention and control measures for COVID-19 might be used to control respiratory tract infections to reduce the national health economic burden caused by these pathogens.