Intensity and frequency of extreme novel epidemics.

Observational knowledge of the epidemic intensity, defined as the number of deaths divided by global population and epidemic duration, and of the rate of emergence of infectious disease outbreaks is necessary to test theory and models and to inform public health risk assessment by quantifying the probability of extreme pandemics such as COVID-19. Despite its significance, assembling and analyzing a comprehensive global historical record spanning a variety of diseases remains an unexplored task. A global dataset of historical epidemics from 1600 to present is here compiled and examined using novel statistical methods to estimate the yearly probability of occurrence of extreme epidemics. Historical observations covering four orders of magnitude of epidemic intensity follow a common probability distribution with a slowly decaying power-law tail (generalized Pareto distribution, asymptotic exponent = -0.71). The yearly number of epidemics varies ninefold and shows systematic trends. Yearly occurrence probabilities of extreme epidemics, Py, vary widely: Py of an event with the intensity of the "Spanish influenza" (1918 to 1920) varies between 0.27 and 1.9% from 1600 to present, while its mean recurrence time today is 400 y (95% CI: 332 to 489 y). The slow decay of probability with epidemic intensity implies that extreme epidemics are relatively likely, a property previously undetected due to short observational records and stationary analysis methods. Using recent estimates of the rate of increase in disease emergence from zoonotic reservoirs associated with environmental change, we estimate that the yearly probability of occurrence of extreme epidemics can increase up to threefold in the coming decades.

An advocate for Africa.

With rigorous science and good-humored braggadocio, Tulio de Oliveira champions coronavirus research from the Global South.

Intensive care medicine and the intensivist: from 1850 to 2021 / A medicina intensiva e o intensivista: de 1850 a 2021

Intensive Care Medicine gained prominence in 2020 and 2021 due to the COVID-19 pandemic. It is a recent medical specialty, which many physicians and the public know little about. This article makes a historical perspective, from the emergence of the first areas for observation of critically ill patients in the nineteenth century to the present, to the impact of the pandemic and its consequences (AU)

A Medicina Intensiva ganhou destaque no anos de 2020 e 2021 devido à pandemia por COVID-19. Trata-se de uma especialidade recente, e ainda pouco conhecida por muitos médicos e pelo público. Este artigo faz uma perspectiva histórica, desde o surgimento das primeiras áreas para observação de pacientes graves no século XIX, até o pre-sente, com o impacto da pandemia, e as perspectivas futuras (AU)

Persuading US White evangelicals to vaccinate for COVID-19: Testing message effectiveness in fall 2020 and spring 2021.

The development of COVID-19 vaccines was an important breakthrough for ending the pandemic. However, people refusing to get vaccinated diminish the level of community protection afforded to others. In the United States, White evangelicals have proven to be a particularly difficult group to convince to get vaccinated. Here we investigate whether this group can be persuaded to get vaccinated. To do this, we leverage data from two survey experiments, one fielded prior to approval of COVID-19 vaccines (study 1) and one fielded after approval (study 2). In both experiments, respondents were randomly assigned to treatment messages to promote COVID-19 vaccination. In study 1, we find that a message that emphasizes community interest and reciprocity with an invocation of embarrassment for choosing not to vaccinate is the most effective at increasing uptake intentions, while values-consistent messaging appears to be ineffective. In contrast, in study 2 we observe that this message is no longer effective and that most messages produce little change in vaccine intent. This inconsistency may be explained by the characteristics of White evangelicals who remain unvaccinated vis à vis those who got vaccinated. These results demonstrate the importance of retesting messages over time, the apparent limitations of values-targeted messaging, and document the need to consider heterogeneity even within well-defined populations. This work also cautions against drawing broad conclusions from studies carried out at a single point in time during the COVID-19 pandemic.

Rapid incidence estimation from SARS-CoV-2 genomes reveals decreased case detection in Europe during summer 2020.

By October 2021, 230 million SARS-CoV-2 diagnoses have been reported. Yet, a considerable proportion of cases remains undetected. Here, we propose GInPipe, a method that rapidly reconstructs SARS-CoV-2 incidence profiles solely from publicly available, time-stamped viral genomes. We validate GInPipe against simulated outbreaks and elaborate phylodynamic analyses. Using available sequence data, we reconstruct incidence histories for Denmark, Scotland, Switzerland, and Victoria (Australia) and demonstrate, how to use the method to investigate the effects of changing testing policies on case ascertainment. Specifically, we find that under-reporting was highest during summer 2020 in Europe, coinciding with more liberal testing policies at times of low testing capacities. Due to the increased use of real-time sequencing, it is envisaged that GInPipe can complement established surveillance tools to monitor the SARS-CoV-2 pandemic. In post-pandemic times, when diagnostic efforts are decreasing, GInPipe may facilitate the detection of hidden infection dynamics.

Phylogenetic reconstruction of the initial stages of the spread of the SARS-CoV-2 virus in the Eurasian and American continents by analyzing genomic data.

Samples from complete genomes of SARS-CoV-2 isolated during the first wave (December 2019-July 2020) of the global COVID-19 pandemic from 21 countries (Asia, Europe, Middle East and America) around the world, were analyzed using the phylogenetic method with molecular clock dating. Results showed that the first cases of COVID-19 in the human population appeared in the period between July and November 2019 in China. The spread of the virus into other countries of the world began in the autumn of 2019. In mid-February 2020, the virus appeared in all the countries we analyzed. During this time, the global population of SARS-CoV-2 was characterized by low levels of the genetic polymorphism, making it difficult to accurately assess the pathways of infection. The rate of evolution of the coding region of the SARS-CoV-2 genome equal to 7.3 × 10-4 (5.95 × 10-4-8.68 × 10-4) nucleotide substitutions per site per year is comparable to those of other human RNA viruses (Measles morbillivirus, Rubella virus, Enterovirus C). SARS-CoV-2 was separated from its known close relative, the bat coronavirus RaTG13 of the genus Betacoronavirus, approximately 15-43 years ago (the end of the 20th century).

One Health Investigation of SARS-CoV-2 Infection and Seropositivity among Pets in Households with Confirmed Human COVID-19 Cases-Utah and Wisconsin, 2020.

Approximately 67% of U.S. households have pets. Limited data are available on SARS-CoV-2 in pets. We assessed SARS-CoV-2 infection in pets during a COVID-19 household transmission investigation. Pets from households with ≥1 person with laboratory-confirmed COVID-19 were eligible for inclusion from April-May 2020. We enrolled 37 dogs and 19 cats from 34 households. All oropharyngeal, nasal, and rectal swabs tested negative by rRT-PCR; one dog's fur swabs (2%) tested positive by rRT-PCR at the first sampling. Among 47 pets with serological results, eight (17%) pets (four dogs, four cats) from 6/30 (20%) households had detectable SARS-CoV-2 neutralizing antibodies. In households with a seropositive pet, the proportion of people with laboratory-confirmed COVID-19 was greater (median 79%; range: 40-100%) compared to households with no seropositive pet (median 37%; range: 13-100%) (p = 0.01). Thirty-three pets with serologic results had frequent daily contact (≥1 h) with the index patient before the person's COVID-19 diagnosis. Of these 33 pets, 14 (42%) had decreased contact with the index patient after diagnosis and none were seropositive; of the 19 (58%) pets with continued contact, four (21%) were seropositive. Seropositive pets likely acquired infection after contact with people with COVID-19. People with COVID-19 should restrict contact with pets and other animals.

High Rate of Mutational Events in SARS-CoV-2 Genomes across Brazilian Geographical Regions, February 2020 to June 2021.

Brazil was considered one of the emerging epicenters of the coronavirus pandemic in 2021, experiencing over 3000 daily deaths caused by the virus at the peak of the second wave. In total, the country had more than 20.8 million confirmed cases of COVID-19, including over 582,764 fatalities. A set of emerging variants arose in the country, some of them posing new challenges for COVID-19 control. The goal of this study was to describe mutational events across samples from Brazilian SARS-CoV-2 sequences publicly obtainable on Global Initiative on Sharing Avian Influenza Data-EpiCoV (GISAID-EpiCoV) platform and to generate indexes of new mutations by each genome. A total of 16,953 SARS-CoV-2 genomes were obtained, which were not proportionally representative of the five Brazilian geographical regions. A comparative sequence analysis was conducted to identify common mutations located at 42 positions of the genome (38 were in coding regions, whereas two were in 5' and two in 3' UTR). Moreover, 11 were synonymous variants, 27 were missense variants, and more than 44.4% were located in the spike gene. Across the total of single nucleotide variations (SNVs) identified, 32 were found in genomes obtained from all five Brazilian regions. While a high genomic diversity has been reported in Europe given the large number of sequenced genomes, Africa has demonstrated high potential for new variants. In South America, Brazil, and Chile, rates have been similar to those found in South Africa and India, providing enough "space" for new mutations to arise. Genomic surveillance is the central key to identifying the emerging variants of SARS-CoV-2 in Brazil and has shown that the country is one of the "hotspots" in the generation of new variants.

Differential mortality of infectious disease in Italian polities: COVID-19, past plague epidemics, and currently endemic respiratory disease.

Coronavirus disease 2019 (COVID-19) has harshly impacted Italy since its arrival in February 2020. In particular, provinces in Italy's Central and Northern macroregions have dealt with disproportionately greater case prevalence and mortality rates than those in the South. In this paper, we compare the morbidity and mortality dynamics of 16th and 17th century Plague outbreaks with those of the ongoing COVID-19 pandemic across Italian regions. We also include data on infectious respiratory diseases which are presently endemic to Italy in order to analyze the regional differences between epidemic and endemic disease. A Growth Curve Analysis allowed for the estimation of time-related intercepts and slopes across the 16th and 17th centuries. Those statistical parameters were later incorporated as criterion variables in multiple General Linear Models. These statistical examinations determined that the Northern macroregion had a higher intercept than the Southern macroregion. This indicated that provinces located in Northern Italy had historically experienced higher plague mortalities than Southern polities. The analyses also revealed that this geographical differential in morbidity and mortality persists to this day, as the Northern macroregion has experienced a substantially higher COVID-19 mortality than the Southern macroregion. These results are consistent with previously published analyses. The only other stable and significant predictor of epidemic disease mortality was foreign urban potential, a measure of the degree of interconnectedness between 16th and 17th century Italian cities. Foreign urban potential was negatively associated with plague slope and positively associated with plague intercept, COVID-19 mortality, GDP per capita, and immigration per capita. Its substantial contribution in predicting both past and present outcomes provides a temporal continuity not seen in any other measure tested here. Overall, this study provides compelling evidence that temporally stable geographical factors, impacting both historical and current foreign pathogen spread above and beyond other hypothesized predictors, underlie the disproportionate impact COVID-19 has had throughout Central and Northern Italian provinces.

The dominant strain of SARS-CoV-2 is a mosaicism.

COVID-19 is seriously threatening human health all over the world. A comprehensive understanding of the genetic mechanisms driving the rapid evolution of its pathogen (SARS-CoV-2) is the key to controlling this pandemic. In this study, by comparing the entire genome sequences of SARS-CoV-2 isolates from Asia, Europe and America, and analyzing their phylogenetic histories, we found a lineage derived from a recombination event that likely occurred before March 2020. More importantly, the recombinant offspring has become the dominant strain responsible for more than one-third of the global cases in the pandemic. These results indicated that the recombination might have played a key role in the pandemic of the virus.

SARS-CoV-2: lessons from both the history of medicine and from the biological behavior of other well-known viruses.

SARS-CoV-2 is the etiological agent of the current pandemic worldwide and its associated disease COVID-19. In this review, we have analyzed SARS-CoV-2 characteristics and those ones of other well-known RNA viruses viz. HIV, HCV and Influenza viruses, collecting their historical data, clinical manifestations and pathogenetic mechanisms. The aim of the work is obtaining useful insights and lessons for a better understanding of SARS-CoV-2. These pathogens present a distinct mode of transmission, as SARS-CoV-2 and Influenza viruses are airborne, whereas HIV and HCV are bloodborne. However, these viruses exhibit some potential similar clinical manifestations and pathogenetic mechanisms and their understanding may contribute to establishing preventive measures and new therapies against SARS-CoV-2.

Racial and Ethnic Disparities in Multisystem Inflammatory Syndrome in Children in the United States, March 2020 to February 2021.

BACKGROUND: The incidence of multisystem inflammatory syndrome in children (MIS-C) varies by race and ethnicity. This study assessed whether disparities in MIS-C in the United States by race and ethnicity exceed known disparities in coronavirus disease 2019 (COVID-19) incidence. METHODS: We compared the distribution of race and ethnicity among patients with MIS-C (<21 years of age, termed children) with onset March 2020 to February 2021 to that of children with COVID-19 and in the general population. Analysis was restricted to 369 counties with high completeness of race and ethnicity reporting for MIS-C and COVID-19. For each racial and ethnic group, observed numbers of patients with MIS-C were compared with expected numbers (observed/expected ratio) in children with COVID-19 and in the general population within these counties. RESULTS: Compared with children in the general population, MIS-C was more frequent among Hispanic (139% of expected) and non-Hispanic Black children (183%) and less frequent among non-Hispanic White (64%) and non-Hispanic Asian children (48%). Compared with children with COVID-19, MIS-C was more frequent in non-Hispanic Black children (207% of expected) and less frequent in non-Hispanic White children (68%); however, frequency was not different among Hispanic (102%) and non-Hispanic Asian (74%) children. CONCLUSIONS: Disparities in MIS-C by race and ethnicity exist, even after controlling for COVID-19 disparities and geographic variations. The high proportion of MIS-C among Hispanic children and low proportion among non-Hispanic Asian children align with COVID-19 rates, while the high proportion among non-Hispanic Black children and low proportion among non-Hispanic White children are not explainable by COVID-19 rates.

A Centenary Tale of Two Pandemics: The 1918 Influenza Pandemic and COVID-19, Part II.

Both the 1918 influenza pandemic and the 2019‒2021 COVID-19 pandemic are among the most disastrous infectious disease emergences of modern times. In addition to similarities in their clinical, pathological, and epidemiological features, the two pandemics, separated by more than a century, were each met with essentially the same, or very similar, public health responses, and elicited research efforts to control them with vaccines, therapeutics, and other medical approaches. Both pandemics had lasting, if at times invisible, psychosocial effects related to loss and hardship. In considering these two deadly pandemics, we ask: what lessons have we learned over the span of a century, and how are we applying those lessons to the challenges of COVID-19?

Epidemiological and co-infection characteristics of common human coronaviruses in Shanghai, 2015-2020: a retrospective observational study.

The coronavirus disease (COVID-19) pandemic is a major challenge worldwide. However, the epidemic potential of common human coronaviruses (HCoVs) remains unclear. This study aimed to determine the epidemiological and co-infection characteristics of common HCoVs in individuals with influenza-like illness (ILI) and severe acute respiratory infection (SARI). This retrospective, observational, multicentre study used data collected from patients admitted to nine sentinel hospitals with ILI and SARI from January 2015 through December 2020 in Shanghai, China. We prospectively tested patients for a total of 22 respiratory pathogens using multi-real-time polymerase chain reaction. Of the 4541 patients tested, 40.37% (1833/4541) tested positive for respiratory pathogens and 3.59% (163/4541) tested positive for common HCoVs. HCoV infection was more common in the non-endemic season for respiratory pathogens (odds ratio: 2.33, 95% confidence interval: 1.64-3.31). HCoV-OC43 (41.72%, 68/163) was the most common type of HCoV detected. The co-infection rate was 31.29% (51/163) among 163 HCoV-positive cases, with HCoV-229E (53.13%, 17/32), the HCoV type that was most frequently associated with co-infection. Respiratory pathogens responsible for co-infections with HCoVs included parainfluenza virus, rhinovirus/enterovirus, influenza A virus, and adenovirus. Furthermore, we identified one patient co-infected with HCoV-OC43 and HCoV-NL63/HKU1. The prevalence of common HCoVs remains low in ILI/SARI cases, in Shanghai. However, the seasonal pattern of HCoVs may be opposite to that of other respiratory pathogens. Moreover, HCoVs are likely to co-exist with specific respiratory pathogens. The potential role of co-infections with HCoVs and other pathogenic microorganisms in infection and pathogenesis of ILI and SARI warrants further study.

Tracking Pandemic Severity Using Data on the Age Structure of Mortality: Lessons From the 1918 Influenza Pandemic in Michigan.

Objectives. To test whether distortions in the age structure of mortality during the 1918 influenza pandemic in Michigan tracked the severity of the pandemic. Methods. We calculated monthly excess deaths during the period of 1918 to 1920 by using monthly data on all-cause deaths for the period of 1912 to 1920 in Michigan. Next, we measured distortions in the age distribution of deaths by using the Kuiper goodness-of-fit test statistic comparing the monthly distribution of deaths by age in 1918 to 1920 with the baseline distribution for the corresponding month for 1912 to 1917. Results. Monthly distortions in the age distribution of deaths were correlated with excess deaths for the period of 1918 to 1920 in Michigan (r = 0.83; P < .001). Conclusions. Distortions in the age distribution of deaths tracked variations in the severity of the 1918 influenza pandemic. Public Health Implications. It may be possible to track the severity of pandemic activity with age-at-death data by identifying distortions in the age distribution of deaths. Public health authorities should explore the application of this approach to tracking the COVID-19 pandemic in the absence of complete data coverage or accurate cause-of-death data.

Dating first cases of COVID-19.

Questions persist as to the origin of the COVID-19 pandemic. Evidence is building that its origin as a zoonotic spillover occurred prior to the officially accepted timing of early December, 2019. Here we provide novel methods to date the origin of COVID-19 cases. We show that six countries had exceptionally early cases, unlikely to represent part of their main case series. The model suggests a likely timing of the first case of COVID-19 in China as November 17 (95% CI October 4). Origination dates are discussed for the first five countries outside China and each continent. Results infer that SARS-CoV-2 emerged in China in early October to mid-November, and by January, had spread globally. This suggests an earlier and more rapid timeline of spread. Our study provides new approaches for estimating dates of the arrival of infectious diseases based on small samples that can be applied to many epidemiological situations.