Tracking the onset date of the community spread of SARS-CoV-2 in western countries

Profile, performance, and perception of pharmacist preparedness for the COVID-19 pandemic

INTRODUCTION

The lack of human resources for disease prevention and control is evident in times of health crisis, such as the COVID-19 pandemic. In public health emergencies, the capacity for adequate assistance and guaranteed access to pharmacological treatment are fundamental and contribute to impact reduction. We aimed to analyze the profile, performance, and characteristics related to the self-perception of preparedness among pharmacists who responded to the COVID-19 pandemic in Brazil.

METHOD

A cross-sectional study was conducted in two stages: content validation of a questionnaire and its application to a representative sample of pharmacists in Rio de Janeiro. The snowball technique was used to recruit participants. A logistic regression model was adjusted to determine the effects of the factors on the probability of a pharmacist feeling prepared to act during the pandemic.

RESULTS

Six experts approved and validated the questionnaire, and 376 pharmacists were included in the study, 60.6 % of whom were in places specially designated by health authorities to diagnose and treat COVID-19. Professionals participated in various activities related to pandemic demands, including medication management and population guidance. Postgraduate degrees increased the odds of participants feeling prepared to act during the pandemic. Furthermore, pharmacists who worked in reference facilities were more likely to feel ready than those who worked in other places. Professionals who knew treatment guidelines were almost three times more likely to feel prepared than the ones without the knowledge of treatment guidelines. Training or guidance on how to act during the pandemic increased pharmacists' odds of feeling prepared by 2.58 times.

CONCLUSION

Pharmacists actuated from diagnosis to treatment and participated in the health activities required during the pandemic. Factors contributing to the self-perception of preparedness were identified. Such factors can be targets for interventions to promote the preparedness of the workforce for future health emergencies.

Complexity of the COVID-19 pandemic in Maringá

While extensive literature exists on the COVID-19 pandemic at regional and national levels, understanding its dynamics and consequences at the city level remains limited. This study investigates the pandemic in Maringá, a medium-sized city in Brazil's South Region, using data obtained by actively monitoring the disease from March 2020 to June 2022. Despite prompt and robust interventions, COVID-19 cases increased exponentially during the early spread of COVID-19, with a reproduction number lower than that observed during the initial outbreak in Wuhan. Our research demonstrates the remarkable impact of non-pharmaceutical interventions on both mobility and pandemic indicators, particularly during the onset and the most severe phases of the emergency. However, our results suggest that the city's measures were primarily reactive rather than proactive. Maringá faced six waves of cases, with the third and fourth waves being the deadliest, responsible for over two-thirds of all deaths and overwhelming the local healthcare system. Excess mortality during this period exceeded deaths attributed to COVID-19, indicating that the burdened healthcare system may have contributed to increased mortality from other causes. By the end of the fourth wave, nearly three-quarters of the city's population had received two vaccine doses, significantly decreasing deaths despite the surge caused by the Omicron variant. Finally, we compare these findings with the national context and other similarly sized cities, highlighting substantial heterogeneities in the spread and impact of the disease.

Utilizing prospective space-time scan statistics to discover the dynamics of coronavirus disease 2019 clusters in the State of São Paulo, Brazil

Background:

The number of deaths and people infected with coronavirus disease 2019 (COVID-19) in Brazil has steadily increased in the first few months of the pandemic. Despite the underreporting of coronavirus cases by government agencies across the country, São Paulo has the highest rate among all Brazilian states.

Methods:

To identify the highest-risk municipalities during the initial outbreak, we utilized daily confirmed case data from official reports between February 25 and May 5, 2020, which were aggregated to the municipality level. A prospective space-time scan statistic was conducted to detect active clusters in three different time periods.

Results:

Our findings suggest that approximately 4.6 times more municipalities belong to a significant space-time cluster with a relative risk (RR) > 1 on May 5, 2020.

Conclusions:

Our study demonstrated the applicability of the space-time scan statistic for the detection of emerging clusters of COVID-19. In particular, we identified the clusters and RR of municipalities in the initial months of the pandemic, explaining the spatiotemporal patterns of COVID-19 transmission in the state of São Paulo. These results can be used to improve disease monitoring and facilitate targeted interventions.

The starting dates of COVID-19 multiple waves

The severe acute respiratory syndrome of coronavirus 2 spread globally very quickly, causing great concern at the international level due to the severity of the associated respiratory disease, the so-called COVID-19. Considering Rio de Janeiro city (Brazil) as an example, the first diagnosis of this disease occurred in March 2020, but the exact moment when the local spread of the virus started is uncertain as the Brazilian epidemiological surveillance system was not widely prepared to detect suspected cases of COVID-19 at that time. Improvements in this surveillance system occurred over the pandemic, but due to the complex nature of the disease transmission process, specifying the exact moment of emergence of new community contagion outbreaks is a complicated task. This work aims to propose a general methodology to determine possible start dates for the multiple community outbreaks of COVID-19, using for this purpose a parametric statistical approach that combines surveillance data, nonlinear regression, and information criteria to obtain a statistical model capable of describing the multiple waves of contagion observed. The dynamics of COVID-19 in the city of Rio de Janeiro is taken as a case study, and the results suggest that the original strain of the virus was already circulating in Rio de Janeiro city as early as late February 2020, probably being massively disseminated in the population during the carnival festivities.

Retrospective surveillance of severe acute respiratory syndrome coronavirus 2 in pets from Brazil

Background and Aim:

The emerging concerns regarding the new Coronavirus’s ability to cause infection in pets has led to animal testing and worrisome findings reported all over the world in domesticated and wild animals. This study aimed to investigate severe acute respiratory syndrome coronavirus (SARS-CoV)-2 by quantitative reverse transcription-polymerase chain reaction in dog and cat samples with the clinical presentation for respiratory or gastrointestinal disease in Brazil.

Materials and Methods:

One hundred and twenty-five samples were collected from 12 states of Brazil that originated from the gastrointestinal, upper respiratory tract, and other sites, including some pools of samples from before the onset of the pandemic including blood and/or urine samples. They were tested for RT-PCR detection of respiratory or gastrointestinal pathogens through Respiratory or Diarrhea RT-PCR Panels in the TECSA (Tecnologia em Saninade Animal - Animal Health Technology) Veterinary Medicine Laboratory. This work was conducted in compliance with ethical standards.

Results:

Seven different microorganisms that can cause respiratory and/or gastrointestinal clinical signs were detected in cats (Feline Coronavirus [FCoV], Feline Parvovirus, Feline Leukemia Virus, Feline Calicivirus, Mycoplasma felis, Campylobacter spp., and Cryptosporidium spp.) and three in dogs (canine distemper virus, Cryptosporidium spp., and Babesia spp.).

Conclusion:

Although the samples corresponded to the beginning of coronavirus disease-19 spread in Brazil and clinically correlated with the expected viral replication sites, none of the animals tested positive for SARS-CoV-2; reassuringly, four cats tested positive or FCoV none of them were positive for SARS-CoV2. The epidemiological surveillance of SARS-CoV-2 in pets is considered a one health issue, important for monitoring the disease evolution, spread and minimizing the animal-human health impacts, and directing Public Health Policies.

Main aspects and prophylatic measures of COVID-19 in Brazil

From the first case of COVID-19 in Brazil, the country became the third in the world in number of cases and deaths. Despite the measures implemented by the government, the number of infected and killed by COVID-19 continues to increase and the country faces several other problems that include social and political aspects, making it difficult to contain the pandemic. The present study aimed to address the general characteristics of SARS-Cov-2, as well as to point out the main socio-epidemiological aspects in Brazil, and the treatment of COVID 19. A literature review was carried out to search for articles in PubMed, Scielo and Google databases. Scholar until October 6, 2020. Patients with COVID-19 may be asymptomatic, but among symptomatic patients the severity of the disease is related to age and pre-existing medical conditions. The lungs are the organs most affected by the virus and, for this reason, respiratory manifestations such as cough, shortness of breath, sputum production, sore throat and nasal congestion are the symptoms most associated with COVID-19 The transmission of SARS-COV-2 between humans occur mainly through respiratory droplets, but they can also occur through contact with contaminated surfaces. Vaccine tests were carried out approved by the World Health Organization (WHO). Brazil stands out in second world position, with five approved vaccines, Pfizer-BioNTech, Oxford-AstraZeneca, /CoronaVac (Sinovac), Janssen /Covishiel

National population prevalence of antibodies to SARS-CoV-2 in Scotland during the first and second waves of the COVID-19 pandemic

Objectives

Studies that measure the prevalence of antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (‘seroprevalence’) are essential to understand population exposure to SARS-CoV-2 among symptomatic and asymptomatic individuals. We aimed to measure seroprevalence in the Scottish population over the course of the COVID-19 pandemic – from before the first recorded case in Scotland through to the second pandemic wave.

Study design

The study design of this study is serial cross sectional.

Methods

We tested 41,477 residual samples retrieved from primary and antenatal care settings across Scotland for SARS-CoV-2 antibodies over a 12-month period from December 2019-December 2020 (before rollout of COVID-19 vaccination). Five-weekly rolling seroprevalence estimates were adjusted for the sensitivity and specificity of the assays and weighted to reference populations. Temporal trends in seroprevalence estimates and weekly SARS-CoV-2 notifications were compared.

Results

Five-weekly rolling seroprevalence rates were 0% until the end of March, when they increased contemporaneously with the first pandemic wave. Seroprevalence rates remained stable through the summer (range: 3%–5%) during a period of social restrictions, after which they increased concurrently with the second wave, reaching 9.6% (95% confidence interval [CI]: 8.4%–10.8%) in the week beginning 28th December in 2020. Seroprevalence rates were lower in rural vs. urban areas (adjusted odds ratio [AOR]: 0.70, 95% CI: 0.61–0.79) and among individuals aged 20–39 years and 60 years and older (AOR: 0.74, 95% CI: 0.64–0.86; AOR: 0.80, 95% CI: 0.69–0.91, respectively) relative to those aged 0–19 years.

Conclusions

After two waves of the COVID-19 pandemic, less than one in ten individuals in the Scottish population had antibodies to SARS-CoV-2. Seroprevalence may underestimate the true population exposure as a result of waning antibodies among individuals who were infected early in the first wave.

Percepção do medo de ser contaminado pelo novo coronavírus

RESUMO Objetivo: Avaliar a prevalência e os fatores associados à percepção do medo de ser contaminado pelo novo coronavírus. Métodos: Estudo transversal realizado em Passo Fundo, Rio Grande do Sul, com indivíduos de ambos os sexos e 18 ou mais anos de idade. Coleta on-line de dados sociodemográficos, de saúde, de comportamento e de conhecimento acerca do vírus. Análise estatística descritiva e cálculo de prevalência e de razões de prevalência (RP) brutas e ajustadas. Resultados: Amostrados 920 participantes, com 64% de prevalência de medo de contaminação, sendo maior em indivíduos que trabalham (RP = 1,10; IC95 1,02-1,20), com idosos no domicílio (RP = 1,18; IC95 1,17-1,19), percepção negativa da saúde (RP = 1,15; IC95 1,02-1,31), avaliação de elevado risco de contaminação (RP = 1,30; IC95 1,23-1,38), com no mínimo um dos principais sinais/sintomas na semana anterior (RP = 1,12; IC95 1,11-1,13), que realizam maior número de medidas preventivas (RP = 1,27; IC95 1,15-1,40), vacinados contra a gripe (RP = 1,08; IC95 1,07-1,10) e que sabem que pertencem ao grupo de risco (RP = 1,17; IC95 1,14-1,19). Menor probabilidade do desfecho observada em idosos (RP = 0,74; IC95 0,60-0,91), profissionais ou estudantes da saúde (RP = 0,82; IC95 0,81-0,83) e em não fumantes (RP = 0,86; IC95 0,79-0,94). Conclusões: Observou-se elevada proporção de medo entre os participantes, especialmente entre aqueles que se percebem sob maior risco. Considerando o importante papel do medo na saúde mental das pessoas, os achados indicam a importância de intensificar ações educativas e informativas, visando ampliar o esclarecimento da população e reduzir os impactos da pandemia nesse aspecto.

COVID-19 mortality in the UK Biobank cohort: revisiting and evaluating risk factors

Most studies of severe/fatal COVID-19 risk have used routine/hospitalisation data without detailed pre-morbid characterisation. Using the community-based UK Biobank cohort, we investigate risk factors for COVID-19 mortality in comparison with non-COVID-19 mortality. We investigated demographic, social (education, income, housing, employment), lifestyle (smoking, drinking, body mass index), biological (lipids, cystatin C, vitamin D), medical (comorbidities, medications) and environmental (air pollution) data from UK Biobank (N = 473,550) in relation to 459 COVID-19 and 2626 non-COVID-19 deaths to 21 September 2020. We used univariate, multivariable and penalised regression models. Age (OR = 2.76 [2.18-3.49] per S.D. [8.1 years], p = 2.6 × 10-17), male sex (OR = 1.47 [1.26-1.73], p = 1.3 × 10-6) and Black versus White ethnicity (OR = 1.21 [1.12-1.29], p = 3.0 × 10-7) were independently associated with and jointly explanatory of (area under receiver operating characteristic curve, AUC = 0.79) increased risk of COVID-19 mortality. In multivariable regression, alongside demographic covariates, being a healthcare worker, current smoker, having cardiovascular disease, hypertension, diabetes, autoimmune disease, and oral steroid use at enrolment were independently associated with COVID-19 mortality. Penalised regression models selected income, cardiovascular disease, hypertension, diabetes, cystatin C, and oral steroid use as jointly contributing to COVID-19 mortality risk; Black ethnicity, hypertension and oral steroid use contributed to COVID-19 but not non-COVID-19 mortality. Age, male sex and Black ethnicity, as well as comorbidities and oral steroid use at enrolment were associated with increased risk of COVID-19 death. Our results suggest that previously reported associations of COVID-19 mortality with body mass index, low vitamin D, air pollutants, renin-angiotensin-aldosterone system inhibitors may be explained by the aforementioned factors.

Death trends based on autopsy data compared to the beginning of the coronavirus pandemic in Brazil

The novel Coronavirus disease (COVID-19) is responsible for thousands of deaths worldwide, especially in Brazil, currently one of the leading countries in number of infections and deaths. The beginning of the COVID-19 epidemic in Brazil is uncertain due to the low number of tests done in the country. The excess number of deaths can suggest the beginning of the pandemic in this context. In this article, we used an autoregressive integrated moving average (ARIMA) model to investigate possible excesses in the number of deaths processed by the São Paulo Autopsy Service according to different causes of deaths: all-cause, cardiovascular, and pulmonary causes. We calculated the expected number of deaths using data from 2019 to 2020 (n=17,011), and investigated different seasonal patterns using harmonic dynamic regression with Fourier terms with residuals modeled by an ARIMA method. We did not find any abnormalities in the predicted number of deaths and the real values in the first months of 2020. We found an increase in the number of deaths only by March 20, 2020, right after the first COVID-19 confirmed case in the city of São Paulo, which occurred on March 16, 2020.

Evolutionary Dynamics and Dissemination Pattern of the SARS-CoV-2 Lineage B.1.1.33 During the Early Pandemic Phase in Brazil

A previous study demonstrates that most of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) Brazilian strains fell in three local clades that were introduced from Europe around late February 2020. Here we investigated in more detail the origin of the major and most widely disseminated SARS-CoV-2 Brazilian lineage B.1.1.33. We recovered 190 whole viral genomes collected from 13 Brazilian states from February 29 to April 31, 2020 and combined them with other B.1.1 genomes collected globally. Our genomic survey confirms that lineage B.1.1.33 is responsible for a variable fraction of the community viral transmissions in Brazilian states, ranging from 2% of all SARS-CoV-2 genomes from Pernambuco to 80% of those from Rio de Janeiro. We detected a moderate prevalence (5-18%) of lineage B.1.1.33 in some South American countries and a very low prevalence (<1%) in North America, Europe, and Oceania. Our study reveals that lineage B.1.1.33 evolved from an ancestral clade, here designated B.1.1.33-like, that carries one of the two B.1.1.33 synapomorphic mutations. The B.1.1.33-like lineage may have been introduced from Europe or arose in Brazil in early February 2020 and a few weeks later gave origin to the lineage B.1.1.33. These SARS-CoV-2 lineages probably circulated during February 2020 and reached all Brazilian regions and multiple countries around the world by mid-March, before the implementation of air travel restrictions in Brazil. Our phylodynamic analysis also indicates that public health interventions were partially effective to control the expansion of lineage B.1.1.33 in Rio de Janeiro because its median effective reproductive number (R e ) was drastically reduced by about 66% during March 2020, but failed to bring it to below one. Continuous genomic surveillance of lineage B.1.1.33 might provide valuable information about epidemic dynamics and the effectiveness of public health interventions in some Brazilian states.

The Interiorization of COVID-19 in the cities of Pernambuco State, Northeast of Brazil

Abstract Objectives: to analyze how the disseminationof COVID-19 occurred in the cities of Pernambuco State, Northeast in Brazil. Methods: descriptive, exploratory and quantitative study whose units of analysis were the 184 cities and Fernando de Noronha Archipelago which constitutes the state of Pernambuco. Geoprocessing techniques used QGis 3.14.16 and were presented in figures. Results: the first city to register a case of COVID-19 was Recife, in 129 days there were already confirmed cases of the disease in all the cities in the state and including Fernando de Noronha Archipelago. Only 117 cities informed the patients’ sexin public reports since the first case and only 88 cities mentioned the patients ’ age. Conclusion: there was a fast spread of COVID-19 in the state of Pernambuco, showing the inability of the Health Surveillance services to control the transmission, especially in smalltowns.

Analysis of Genomic Characteristics and Transmission Routes of Patients With Confirmed SARS-CoV-2 in Southern California During the Early Stage of the US COVID-19 Pandemic

Importance

In late December 2019, an outbreak of a novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in Wuhan, China. Data on the routes of transmission to Los Angeles, California, the US West Coast epicenter for coronavirus disease 2019 (COVID-19), and subsequent community spread are limited.

Objective

To determine the transmission routes of SARS-CoV-2 to Southern California and elucidate local community spread within the Los Angeles metropolitan area.

Design, Setting, and Participants

This case series included 192 consecutive patients with reverse transcription-polymerase chain reaction (RT-PCR) test results positive for SARS-CoV-2 who were evaluated at Cedars-Sinai Medical Center in Los Angeles, California, from March 22 to April 15, 2020. Data analysis was performed from April to May 2020.

Main Outcomes and Measures

SARS-CoV-2 viral genomes were sequenced. Los Angeles isolates were compared with genomes from global subsampling and from New York, New York; Washington state; and China to determine potential sources of viral dissemination. Demographic data and outcomes were collected.

Results

The cohort included 192 patients (median [interquartile range] age, 59.5 [43-75] years; 110 [57.3%] men). The genetic characterization of SARS-CoV-2 isolates in the Los Angeles population pinpointed community transmission of 13 patients within a 3.81 km2 radius. Variation landscapes of this case series also revealed a cluster of 10 patients that contained 5 residents at a skilled nursing facility, 1 resident of a nearby skilled nursing facility, 3 health care workers, and a family member of a resident of one of the skilled nursing facilities. Person-to-person transmission was detected in a cluster of 5 patients who shared the same single-nucleotide variation in their SARS-CoV-2 genomes. High viral genomic diversity was identified: 20 Los Angeles isolates (15.0%) resembled SARS-CoV-2 genomes from Asia, while 109 Los Angeles isolates (82.0%) were similar to isolates originating from Europe. Analysis of other common respiratory viral pathogens did not reveal coinfection in the cohort.

Conclusions and Relevance

These findings highlight the precision of detecting person-to-person transmission and accurate contact tracing directly through SARS-CoV-2 genome isolation and sequencing. Development and application of phylogenetic analyses from the Los Angeles population established connections between COVID-19 clusters locally and throughout the US.

City size and the spreading of COVID-19 in Brazil

The current outbreak of the coronavirus disease 2019 (COVID-19) is an unprecedented example of how fast an infectious disease can spread around the globe (especially in urban areas) and the enormous impact it causes on public health and socio-economic activities. Despite the recent surge of investigations about different aspects of the COVID-19 pandemic, we still know little about the effects of city size on the propagation of this disease in urban areas. Here we investigate how the number of cases and deaths by COVID-19 scale with the population of Brazilian cities. Our results indicate small towns are proportionally more affected by COVID-19 during the initial spread of the disease, such that the cumulative numbers of cases and deaths per capita initially decrease with population size. However, during the long-term course of the pandemic, this urban advantage vanishes and large cities start to exhibit higher incidence of cases and deaths, such that every 1% rise in population is associated with a 0.14% increase in the number of fatalities per capita after about four months since the first two daily deaths. We argue that these patterns may be related to the existence of proportionally more health infrastructure in the largest cities and a lower proportion of older adults in large urban areas. We also find the initial growth rate of cases and deaths to be higher in large cities; however, these growth rates tend to decrease in large cities and to increase in small ones over time.

An optimal predictive control strategy for COVID-19 (SARS-CoV-2) social distancing policies in Brazil

This paper formulates a Model Predictive Control (MPC) policy to mitigate the COVID-19 contagion in Brazil, designed as optimal On-Off social isolation strategy. The proposed optimization algorithm is able to determine the time and duration of social distancing policies in the country. The achieved results are based on data from the period between March and May of 2020, regarding the cumulative number of infections and deaths due to the SARS-CoV-2 virus. This dataset is assumably largely sub-notified due to the absence of mass testing in Brazil. Thus, the MPC is based on a SIR model which is identified using an uncertainty-weighted Least-Squares criterion. Furthermore, this model includes an additional dynamic variable that mimics the response of the population to the social distancing policies determined by the government, which affect the COVID-19 transmission rate. The proposed control method is set within a mixed-logical formalism, since the decision variable is forcefully binary (existence or the absence of social distance policy). A dwell-time constraint is included to avoid too frequent shifts between these two inputs. The achieved simulation results illustrate how such optimal control method would operate in practice, pointing out that no social distancing should be relaxed before mid August 2020. If relaxations are necessary, they should not be performed before this date and should be in small periods, no longer than 25 days. This paradigm would proceed roughly until January/2021. The results also indicate a possible second peak of infections, which has a forecast to the beginning of October. This peak can be reduced if the periods of days with relaxed social isolation measures are shortened.