First Wave Of Infection Research Articles

Public perceptions of multiple risks during the COVID-19 pandemic in Italy and Sweden

Knowing how people perceive multiple risks is essential to the management and promotion of public health and safety. Here we present a dataset based on a survey (N = 4,154) of public risk perception in Italy and Sweden during the COVID-19 pandemic. Both countries were heavily affected by the first wave of infections in Spring 2020, but their governmental responses were very different. As such, the dataset offers unique opportunities to investigate the role of governmental responses in shaping public risk perception. In addition to epidemics, the survey considered indirect effects of COVID-19 (domestic violence, economic crises), as well as global (climate change) and local (wildfires, floods, droughts, earthquakes, terror attacks) threats. The survey examines perceived likelihoods and impacts, individual and authorities’ preparedness and knowledge, and socio-demographic indicators. Hence, the resulting dataset has the potential to enable a plethora of analyses on social, cultural and institutional factors influencing the way in which people perceive risk.

Genomic epidemiology of superspreading events in Austria reveals mutational dynamics and transmission properties of SARS-CoV-2.

Superspreading events shaped the coronavirus disease 2019 (COVID-19) pandemic, and their rapid identification and containment are essential for disease control. Here, we provide a national-scale analysis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) superspreading during the first wave of infections in Austria, a country that played a major role in initial virus transmissions in Europe. Capitalizing on Austria's well-developed epidemiological surveillance system, we identified major SARS-CoV-2 clusters during the first wave of infections and performed deep whole-genome sequencing of more than 500 virus samples. Phylogenetic-epidemiological analysis enabled the reconstruction of superspreading events and charts a map of tourism-related viral spread originating from Austria in spring 2020. Moreover, we exploited epidemiologically well-defined clusters to quantify SARS-CoV-2 mutational dynamics, including the observation of low-frequency mutations that progressed to fixation within the infection chain. Time-resolved virus sequencing unveiled viral mutation dynamics within individuals with COVID-19, and epidemiologically validated infector-infectee pairs enabled us to determine an average transmission bottleneck size of 103 SARS-CoV-2 particles. In conclusion, this study illustrates the power of combining epidemiological analysis with deep viral genome sequencing to unravel the spread of SARS-CoV-2 and to gain fundamental insights into mutational dynamics and transmission properties.

Second Wave of COVID-19 Global Pandemic and Athletes' Confinement: Recommendations to Better Manage and Optimize the Modified Lifestyle.

Coronavirus 2019 (COVID-19) is an infectious viral disease that has spread globally, resulting in the ongoing pandemic. Currently, there is no vaccine or specific treatment for COVID-19. Preventive measures to reduce the chances of contagion consist mainly of confinement, avoiding crowded places, social distancing, masks, and applying strict personal hygiene as recommended by the World Health Organization (WHO). After the first wave of infection in many countries, the potential effects of relaxing containment and physical distancing control measures suggest that as a result of these measures, a second wave of COVID-19 appears probable in these countries. In sport, the period of self-isolation, and quarantine, for COVID-19 affects the physical preparation of athletes as well as their mental health and quality of life to an even greater extent (i.e., nutrition, sleep, healthy lifestyle), and thus, relevant and practical recommendations are needed to help alleviate these physical and mental health concerns. Our review aims to summarize the physiological and psychological effects of detraining associated with athletes’ confinement during the proposed second wave of COVID-19. This article also proposes answers to questions that concern the advantages and disadvantages of different types of social media platforms, the importance of nutrition, and the effects of sleep disturbance on the health and modified lifestyle of athletes during this worldwide pandemic. Thus, this review provides some general guidelines to better manage their modified lifestyle and optimally maintain their physical and mental fitness with respect to measures taken during this restrictive proposed second wave of the COVID-19 confinement period.

EMERGENCE OF SECOND WAVE OF SARS-COV-2 INFECTIONS DURING THE ONGOING COVID-19 PANDEMIC: A MINI REVIEW

The COVID-19 outbreak originated from Wuhan, China has spread over the world, causing a “Global Pandemic”. We analyzed daily confirmed cases and deaths from different countries to understand the progression of the ongoing pandemic in different parts around the world. The data indicated that the pandemic is in different stages in different countries, where they are either at the end of the second wave or middle or early phase of it or still in the middle of the first wave of infection, and they can be divided into four groups. Type 1 countries such as UK, France, Spain, and the Netherlands are currently witnessing the second wave of infection with an exponential increase in daily cases. Countries such as Australia, United States, Japan, and Poland are currently in the declining stage of second-wave, grouped as Type 2 countries. Type 3 countries such as Germany, Italy, Belgium, and Russia are recently seeing the second wave with slowly rising of confirmed cases. Type 4 countries including India, Brazil, Argentina, and Mexico are currently fighting against the first wave of COVID-19. These countries have a chance to learn from the countries which have overcome the second wave successfully. To be ahead of the epidemic curve and preventing it, countries need to make future plans on family, hospital, and community levels. Isolation of the highly vulnerable elderly people and young children, preventing social or public gathering, following the guidelines of COVID-19 prevention including wearing face masks regularly can save countries from devastating effects of the second wave of pandemic COVID-19.

Descripción de la Pandemia por COVID-19 en las Parroquias Samborondón, Daule y Durán

In Ecuador, the highest number of daily infections due to SARS-CoV-2 occurred in Guayaquil between April 4th and May 3th. The objective of this study is to perform a descriptive analysis of the quantitative PCR tests in real-time in Samborondón, Daule, and Durán during the months of April to August in the UEESBiolab laboratory. The results according to gender indicated that men register a greater number of positive cases compared to the female gender. People with an age within the Economically Active Population (EAP) were the ones who attended the test the most and who were positive in 13.9%. Additionally, for positive results, it was found that there is no statistically significant difference between groups for variables gender, age, canton, and parish. Finally, an increase in positive patients is observed in rural areas during this first wave of infection, with the rural population of Samborondón with the highest number of infections.

Modelling SARS-CoV-2 Disease Progression in Australia and New Zealand: An Agent-Based Approach to Support Public Health Decision-Making

Background: For countries with strong border control and an epidemic that is not yet advanced, there is an opportunity to eliminate community transmission of SARS-CoV-2. We show how public health policies and their effects can be modelled to estimate the likely progression of SARS-COV-2 under i) strict physical distancing policies implemented in New Zealand and Australia on the 26 th and 28 th March, 2020 respectively, and ii) from September 1st, 2020 in Victoria, Australia as this state planned its exit from a significant second wave of infections. Methods: We developed a dynamic, public health policy model using an agent-based framework that simulated key aspects of both country’s populations, disease, spatial and behavioural dynamics, as well as the mechanism and effect of public health policy responses on the transmission of SARS-CoV-2. We demonstrate the model’s development and application through the first wave of infections in New Zealand, and first and second wave of infections experienced in Australia. Findings: Under maintained strong physical distancing, we originally estimated a median elimination date of July 12th for Australia (95% SI: June 5th to August 28th) and June 3rd for New Zealand (95% SI May 4th to June 27th). We estimated a 90% probability of elimination was achievable in Australia on August 17th (95% SI: August 8th – August 30th) and on June 14th (95% SI: June 17th – June 29th) in New Zealand. However, under our scenario of decaying adherence to physical distancing from implementation to 60 days post restrictions, we predicted a resurgence in SARS-CoV-2 infections (i.e., a second wave) was likely in Australia and possibly in New Zealand. At 100 days, the probability of elimination was reduced to 10% in Australia and 68% in New Zealand. Having demonstrated the utility of our model above, the subsequent adaptation of the model in Victoria, Australia estimated that a threshold of less than 5 new cases per day over 14 days (from a peak of ~500 in August) could be achieved on or around the 17th of October. This would enable Victoria to move to, and sustain, lower levels of restrictions to movement and trade than had been possible under its strict lockdown policy. Interpretation: The findings suggest that during Australia and NZ’s first wave of infections, elimination of community transmission of SARS-CoV-2 in both countries through effective implementation and maintenance of public health interventions was possible. Subsequently, the structure and function of the agent-based policy model developed to analyse the effect of policies during wave 1 has been instrumental in supporting decision-making among public health authorities during Australia’s current second wave of infections.Funding Statement: MS is funded by a NHMRC Fellowship (APP1136250), JT is funded by an ARC DECRA Fellowship (DE180101411).Declaration of Interests: None to declare.

Association of time to diagnosis with socioeconomic position and geographical accessibility to healthcare among symptomatic COVID-19 patients: A retrospective study in Hong Kong.

Early diagnosis is important to control COVID-19 outbreaks. This study aimed to assess how individual and area socioeconomic position and geographical accessibility to healthcare services were associated with the time to diagnosis among symptomatic COVID-19 patients in Hong Kong. Multivariable generalized linear regression was used to estimate the associations while adjusting for sociodemographic characteristics and case classification. This study found living in public rental housing and living in an area with low education were associated with longer time to diagnosis in the first wave of infections. Specifically, the risk of delayed diagnosis for public rental housing residents was mitigated by the higher density of public clinics/hospitals but was slightly increased by the higher density of private medical practitioners nearby. No such relations were found in the second wave of infections when the surveillance measures were enhanced. Given the grave impact of pandemics around the world, our findings call on taking inequalities into account when public health policies are being devised.

A State of (Greater) Exception? Funerals, Custom and the “War on COVID” in Rural South Africa

ABSTRACT In the analysis of the implementation of the lockdown restrictions in South Africa, a great deal has been made of the unequal ways in which middle-class suburban communities, with access to large homes and biomedical support, have experienced the state of exception in comparison to the poor and unemployed in townships and shack areas. What has been less visible so far is the picture that is beginning to emerge from the rural areas and more marginal provinces. In this paper, we argue that when those experiences are carefully analysed, we begin to see that the former homelands were treated as a kind of “third country,” a country where custom and tradition posed particular threats and required specialised control and management. Using Giorgio Agamben’s notion of a state of exception to frame the discussion, the aim of this paper is to lift the veil from the state’s “war on COVID” in these rural areas during the first wave of infection (April to July 2020) and explore the frightening implications of suspended customary rights to cultural dignity, circular migration and social reproduction in these areas. The empirical focus of the paper is on changing funeral practices and burial rites, and how these were impacted by the COVID lockdown restrictions in the rural Eastern Cape Province, with special reference to rural municipalities in the former Transkei.

Characteristics and outcomes of patients with COVID-19 at a district general hospital in Surrey, UK

This retrospective cohort study aims to define the clinical findings and outcomes of every patient admitted to a district general hospital in Surrey with COVID-19 in March 2020, providing a snapshot of the first wave of infection in the UK. This study is the first detailed insight into the impact of frailty markers on patient outcomes and provides the infection rate among healthcare workers. Data were obtained from medical records. Outcome measures were level of oxygen therapy, discharge and death. Patients were followed up until 21 April 2020. 108 patients were included. 34 (31%) died in hospital or were discharged for palliative care. 43% of patients aged over 65 died. The commonest comorbidities were hypertension (49; 45%) and diabetes (25; 23%). Patients who died were older (mean difference ±SEM, 13.76±3.12 years; p<0.0001) with a higher NEWS2 score (median 6, IQR 2.5-7.5 vs median 2, IQR 2-6) and worse renal function (median differences: urea 2.7 mmol/L, p<0.01; creatinine 4 μmol/L, p<0.05; eGFR 14 mL/min, p<0.05) on admission compared with survivors. Frailty markers were identified as risk factors for death. Clinical Frailty Scale (CFS) was higher in patients over 65 who died than in survivors (median 5, IQR 4-6 vs 3.5, IQR 2-5; p<0.01). Troponin and creatine kinase levels were higher in patients who died than in those who recovered (p<0.0001). Lymphopenia was common (median 0.8, IQR 0.6-1.2; p<0.005). Every patient with heart failure died (8). 26 (24%) were treated with continuous positive airway pressure (CPAP; median 3 days, IQR 2-7.3) and 9 (8%) were intubated (median 14 days, IQR 7-21). All patients who died after discharge (4; 6%) were care home residents. 276 of 699 hospital staff tested were positive for COVID-19. This study identifies older patients with frailty as being particularly vulnerable and reinforces government policy to protect this group at all costs.

Complete Genome Sequences of SARS-CoV-2 Strains Detected in Malaysia.

We sequenced four severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes from Malaysia during the second wave of infection and found unique mutations which suggest local evolution. Circulating Malaysian strains represent introductions from different countries, particularly during the first wave of infection. Genome sequencing is important for understanding local epidemiology.

Estimating required ‘lockdown’ cycles before immunity to SARS-CoV-2: model-based analyses of susceptible population sizes, ‘S0’, in seven European countries, including the UK and Ireland

Background: Following stringent social distancing measures, some European countries are beginning to report a slowed or negative rate of growth of daily case numbers testing positive for the novel coronavirus. The notion that the first wave of infection is close to its peak begs the question of whether future peaks or ‘second waves’ are likely. We sought to determine the current size of the effective (i.e. susceptible) population for seven European countries—to estimate immunity levels following this first wave. Methods: We used Bayesian model inversion to estimate epidemic parameters from the reported case and death rates from seven countries using data from late January 2020 to April 5th 2020. Two distinct generative model types were employed: first a continuous time dynamical-systems implementation of a Susceptible-Exposed-Infectious-Recovered (SEIR) model, and second a partially observable Markov Decision Process or hidden Markov model (HMM) implementation of an SEIR model. Both models parameterise the size of the initial susceptible population (‘S0’), as well as epidemic parameters. Results: Both models recapitulated the dynamics of transmissions and disease as given by case and death rates. Crucially, maximum a posteriori estimates of S0 for each country indicated effective population sizes of below 20% (of total population size), under both the continuous time and HMM models. Using a Bayesian weighted average across all seven countries and both models, we estimated that 6.4% of the total population would be immune. From the two models, the maximum percentage of the effective population was estimated at 19.6% of the total population for the UK, 16.7% for Ireland, 11.4% for Italy, 12.8% for Spain, 18.8% for France, 4.7% for Germany and 12.9% for Switzerland. Conclusion: Our results indicate that after the current wave, a large proportion of the total population will remain without immunity.

Stochastic modeling of influenza spread dynamics with recurrences.

We present results of a study of a simple, stochastic, agent-based model of influenza A infection, simulating its dynamics over the course of one flu season. Building on an early work of Bartlett, we define a model with a limited number of parameters and rates that have clear epidemiological interpretation and can be constrained by data. We demonstrate the occurrence of recurrent behavior in the infected number [more than one peak in a season], which is observed in data, in our simulations for populations consisting of cohorts with strong intra- and weak inter-cohort transmissibility. We examine the dependence of the results on epidemiological and population characteristics by investigating their dependence on a range of parameter values. Finally, we study infection with two strains of influenza, inspired by observations, and show a counter-intuitive result for the effect of inoculation against the strain that leads to the first wave of infection.

RETRACTED: COVID-19 admissions calculators: General population and paediatric cohort

The world is in the grip of pandemic COVID-19 (SARS-CoV-2). Children appear to be only mildly affected but for those countries that are still preparing for their first wave of infections, it is salutary to have some estimates with which to plan for eventual contingencies. These assessments would include acute hospital admission requirements, intensive care admissions and deaths per given population. It is also useful to have an estimate of how many paediatric admissions to expect per given population. However it is only very recently that paediatric epidemiological data has become available. This paper will create an interactive spreadsheet model to estimate population and paediatric admissions for a given population, with the author's country, Malta, as a worked example for both.

First-wave COVID-19 transmissibility and severity in China outside Hubei after control measures, and second-wave scenario planning: a modelling impact assessment

BackgroundAs of March 18, 2020, 13 415 confirmed cases and 120 deaths related to coronavirus disease 2019 (COVID-19) in mainland China, outside Hubei province—the epicentre of the outbreak—had been reported. Since late January, massive public health interventions have been implemented nationwide to contain the outbreak. We provide an impact assessment of the transmissibility and severity of COVID-19 during the first wave in mainland Chinese locations outside Hubei.MethodsWe estimated the instantaneous reproduction number (Rt) of COVID-19 in Beijing, Shanghai, Shenzhen, Wenzhou, and the ten Chinese provinces that had the highest number of confirmed COVID-19 cases; and the confirmed case-fatality risk (cCFR) in Beijing, Shanghai, Shenzhen, and Wenzhou, and all 31 Chinese provinces. We used a susceptible–infectious–recovered model to show the potential effects of relaxing containment measures after the first wave of infection, in anticipation of a possible second wave.FindingsIn all selected cities and provinces, the Rt decreased substantially since Jan 23, when control measures were implemented, and have since remained below 1. The cCFR outside Hubei was 0·98% (95% CI 0·82–1·16), which was almost five times lower than that in Hubei (5·91%, 5·73–6·09). Relaxing the interventions (resulting in Rt >1) when the epidemic size was still small would increase the cumulative case count exponentially as a function of relaxation duration, even if aggressive interventions could subsequently push disease prevalence back to the baseline level.InterpretationThe first wave of COVID-19 outside of Hubei has abated because of aggressive non-pharmaceutical interventions. However, given the substantial risk of viral reintroduction, particularly from overseas importation, close monitoring of Rt and cCFR is needed to inform strategies against a potential second wave to achieve an optimal balance between health and economic protection.FundingHealth and Medical Research Fund, Hong Kong, China.

A dynamical framework for modeling fear of infection and frustration with social distancing in COVID-19 spread.

We introduce a novel modeling framework for incorporating fear of infection and frustration with social distancing into disease dynamics. We show that the resulting SEIR behavior-perception model has three principal modes of qualitative behavior-no outbreak, controlled outbreak, and uncontrolled outbreak. We also demonstrate that the model can produce transient and sustained waves of infection consistent with secondary outbreaks. We fit the model to cumulative COVID-19 case and mortality data from several regions. Our analysis suggests that regions which experience a significant decline after the first wave of infection, such as Canada and Israel, are more likely to contain secondary waves of infection, whereas regions which only achieve moderate success in mitigating the disease's spread initially, such as the United States, are likely to experience substantial secondary waves or uncontrolled outbreaks.

The First Wave of COVID-19 Pandemic: Experiences from Bangladesh

The ongoing pandemic COVID-19 is caused by Severe Acute Respiratory Coronavirus-2 (SARS-CoV-2), has wreaked havoc globally by affecting millions of lives. Although different countries found the implementation of emergency measures useful to combat the viral pandemic (first wave), many countries are now experiencing the resurgence of COVID-19 even after following strict containment guidelines (second wave). Country-specific lessons learned from the first wave of infection appeared to be useful in the successful battle of possible second wave outbreak. In this article, we examined the situation in Bangladesh during the first wave COVID-19 outbreak and discussed the demographic, political, economic, social and environmental influences on the mitigation strategies employed by the country to combat the pandemic. We also tried to explore the preparedness and precautionary measures taken by responsible authorities, choice of strategies implemented and effectiveness of response from government and relevant agencies. Finally, we discussed the possible strategies that might help Bangladesh survive a second wave outbreak based on the experiences from the first wave of the ongoing pandemic.

Basic Demographic Parameters Help Predict Outcomes in Patients Hospitalized With COVID-19 During the First Wave of Infection in West Texas.

The severity of COVID-19 ranges from asymptomatic subclinical infections to severe acute respiratory failure requiring mechanical ventilation. Patients admitted to the hospital have increased mortality rates and patients requiring intensive care have significantly increased mortality rates. Multiple factors influence these outcomes. This study used simple demographic information available on admission to evaluate possible associations between these variables and outcomes, including mortality and length of stay. Clinical outcomes in 63 patients admitted to a tertiary care hospital in West Texas were reviewed. Older patients, patients admitted from nursing homes, and patients admitted to medical intensive care units had increased mortality. Unadjusted analysis indicated that males had increased mortality. Adjusted analysis indicated that males spent nearly 5 days longer in the hospital than females. In summary, age, chronic illness requiring nursing home placement, and acute severe illness requiring intensive care unit admission identify patients with worse prognoses. In addition, males will likely have a longer length of hospital stay.

The Impact of Corona Populism: Empirical Evidence from Austria and Theory

I study the impact of corona populism – politics aimed at denying or downplaying the danger posed by COVID-19 – on the evolution of the pandemic using regional data from Austria. The right-wing FPÖ made a corona populist turn at the end of the first wave of infections. Using panel regression analysis, I show that the vote share of the FPÖ at the last national parliamentary elections is a strong predictor for the number of COVID-19 deaths per capita after the FPÖ switched their policy stance, while there is no correlation before the policy switch. Interestingly, I do not find a statistically significant correlation between the FPÖ vote share and the reported number of infections. I hypothesize that this can be traced back to a self-selection bias in testing, which causes a higher dark figure in FPÖ strongholds. To explore this hypothesis, I extend the classical SIRD model to incorporate conditional quarantine, and heterogeneous mixing of two groups of agents who react differently to the pandemic. Such a model can explain the nontrivial empirics: if mixing is sufficiently homophilic, an increase in the share of “corona sceptics” can cause an increase in the number of deaths without increasing the number of reported infections. I finally discuss the non-trivial implications of the interplay between group sizes, behavioral differences and the degree of homophily on public health outcomes within the theoretical model.

Computational analysis of the receptor binding specificity of novel influenza A/H7N9 viruses

BackgroundInfluenza viruses are undergoing continuous and rapid evolution. The fatal influenza A/H7N9 has drawn attention since the first wave of infections in March 2013, and raised more grave concerns with its increased potential to spread among humans. Experimental studies have revealed several host and virulence markers, indicating differential host binding preferences which can help estimate the potential of causing a pandemic. Here we systematically investigate the sequence pattern and structural characteristics of novel influenza A/H7N9 using computational approaches.ResultsThe sequence analysis highlighted mutations in protein functional domains of influenza viruses. Molecular docking and molecular dynamics simulation revealed that the hemagglutinin (HA) of A/Taiwan/1/2017(H7N9) strain enhanced the binding with both avian and human receptor analogs, compared with the previous A/Shanghai/02/2013(H7N9) strain. The Molecular Mechanics - Poisson Boltzmann Surface Area (MM-PBSA) calculation revealed the change of residue-ligand interaction energy and detected the residues with conspicuous binding preference.ConclusionThe results are novel and specific to the emerging influenza A/Taiwan/1/2017(H7N9) strain compared with A/Shanghai/02/2013(H7N9). Its enhanced ability to bind human receptor analogs, which are abundant in the human upper respiratory tract, may be responsible for the recent outbreak. Residues showing binding preference were detected, which could facilitate monitoring the circulating influenza viruses.

A Survey and Assessment Report of Hiv/Aids Awareness of in North-Eastern Nigeria

Prevention is better than Cure. The effect of Human Immunodeficiency Virus/Acquired Immune deficiency syndrome (HIV/AIDS) global epidemic continue to emerge decades after the first wave of infection. One key aspect of controlling the epidemic is by enlightening the general public on the epidemic. That is on how it can be contracted and controlled. Since the start of the epidemic many measures have been taken by government and non-governmental organizations to control the epidemic but still it continued to infect and kill many people. The measures taken includes manufacturing antiretroviral drugs and therapy, using of condoms and enlightment among others. Nigeria consist of thirty-six (36) states and the federal capital territory (FCT) Abuja, and these are grouped in to six geopolitical zones. North-Eastern Nigeria consist of six states (6) namely Adamawa, Bauchi, Borno, Gombe, Taraba and Yobe states with a total population of about twenty-five million (25m), most of the people live in the rural areas where level of education is low, level of poverty is high and culture and tradition may contribute to the spread of the epidemic. Using secondary data from Federal Ministry of Health, National Bureau of Statistics (NBS), and National Agency for the Control of Aids (NACA), State Agency for the Control of Aids (SACA) and other Non- governmental organizations, the study will find out are the people of North-Eastern Nigeria aware of HIV/AIDS? Statistical methods and techniques are used in analyzing the data.