K. J. Kramer et al.

Single-cell profiling of the antigen-specific response to BNT162b2 SARS-CoV-2 RNA vaccine

Nature communications, June 2022 ; doi.org/10.1038/s41467-022-31142-5


RNA-based vaccines against SARS-CoV-2 have proven critical to limiting COVID-19 disease severity and spread. Cellular mechanisms driving antigen-specific responses to these vaccines, however, remain uncertain. Here we identify and characterize antigen-specific cells and antibody responses to the RNA vaccine BNT162b2 using multiple single-cell technologies for in depth analysis of longitudinal samples from a cohort of healthy participants. Mass cytometry and unbiased machine learning pinpoint an expanding, population of antigen-specific memory CD4+ and CD8+ T cells with characteristics of follicular or peripheral helper cells. B cell receptor sequencing suggest progression from IgM, with apparent cross-reactivity to endemic coronaviruses, to SARS-CoV-2-specific IgA and IgG memory B cells and plasmablasts. Responding lymphocyte populations correlate with eventual SARS-CoV-2 IgG, and a participant lacking these cell populations failed to sustain SARS-CoV-2-specific antibodies and experienced breakthrough infection. These integrated proteomic and genomic platforms identify an antigen-specific cellular basis of RNA vaccine-based immunity.

J.W. Cabore et al.  

COVID-19 in the 47 countries of the WHO African region: a modelling analysis of past trends and future patterns

The Lancet, June 2002; doi.org/10.1016/S2214-109X(22)00233-9


Background COVID-19 has affected the African region in many ways. We aimed to generate robust information on the transmission dynamics of COVID-19 in this region since the beginning of the pandemic and throughout 2022.

MethodsFor each of the 47 countries of the WHO African region, we consolidated COVID-19 data from reported infections and deaths (from WHO statistics); published literature on socioecological, biophysical, and public health interventions; and immunity status and variants of concern, to build a dynamic and comprehensive picture of COVID-19 burden. The model is consolidated through a partially observed Markov decision process, with a Fourier series to produce observed patterns over time based on the SEIRD (denoting susceptible, exposed, infected, recovered, and dead) modelling framework. The model was set up to run weekly, by country, from the date the first infection was reported in each country until Dec 31, 2021. New variants were introduced into the model based on sequenced data reported by countries. The models were then extrapolated until the end of 2022 and included three scenarios based on possible new variants with varying transmissibility, severity, or immunogenicity.

Findings Between Jan 1, 2020, and Dec 31, 2021, our model estimates the number of SARS-CoV-2 infections in the African region to be 505·6 million (95% CI 476·0–536·2), inferring that only 1·4% (one in 71) of SARS-CoV-2 infections in the region were reported. Deaths are estimated at 439 500 (95% CI 344 374–574 785), with 35·3% (one in three) of these reported as COVID-19-related deaths. Although the number of infections were similar between 2020 and 2021, 81% of the deaths were in 2021. 52·3% (95% CI 43·5–95·2) of the region's population is estimated to have some SARS-CoV-2 immunity, given vaccination coverage of 14·7% as of Dec 31, 2021. By the end of 2022, we estimate that infections will remain high, at around 166·2 million (95% CI 157·5–174·9) infections, but deaths will substantially reduce to 22 563 (14 970–38 831).

InterpretationThe African region is estimated to have had a similar number of COVID-19 infections to that of the rest of the world, but with fewer deaths. Our model suggests that the current approach to SARS-CoV-2 testing is missing most infections. These results are consistent with findings from representative seroprevalence studies. There is, therefore, a need for surveillance of hospitalisations, comorbidities, and the emergence of new variants of concern, and scale-up of representative seroprevalence studies, as core response strategies.

L. Zhou et al.

An interpretable deep learning workflow for discovering subvisual abnormalities in CT scans of COVID-19 inpatients and survivors

Nature, May 2022; doi.org/10.1038/s42256-022-00483-7


Tremendous efforts have been made to improve diagnosis and treatment of COVID-19, but knowledge on long-term complications is limited. In particular, a large portion of survivors has respiratory complications, but currently, experienced radiologists and state-of-the-art artificial intelligence systems are not able to detect many abnormalities from follow-up computerized tomography (CT) scans of COVID-19 survivors. Here we propose Deep-LungParenchyma-Enhancing (DLPE), a computer-aided detection (CAD) method for detecting and quantifying pulmonary parenchyma lesions on chest CT. Through proposing a number of deep-learning-based segmentation models and assembling them in an interpretable manner, DLPE removes irrelevant tissues from the perspective of pulmonary parenchyma, and calculates the scan-level optimal window, which considerably enhances parenchyma lesions relative to the lung window. Aided by DLPE, radiologists discovered novel and interpretable lesions from COVID-19 inpatients and survivors, which were previously invisible under the lung window. Based on DLPE, we removed the scan-level bias of CT scans, and then extracted precise radiomics from such novel lesions. We further demonstrated that these radiomics have strong predictive power for key COVID-19 clinical metrics on an inpatient cohort of 1,193 CT scans and for sequelae on a survivor cohort of 219 CT scans. Our work sheds light on the development of interpretable medical artificial intelligence and showcases how artificial intelligence can discover medical findings that are beyond sight.

Cai et al.

Modeling transmission of SARS-CoV-2 Omicron in China

Nature Medicine, May 2022; doi.org/10.1038/s41591-022-01855-7


Having adopted a dynamic zero-COVID strategy to respond to SARS-CoV-2 variants with higher transmissibility since August 2021, China is now considering whether and for how long this policy can remain in place. The debate has thus shifted towards the identification of mitigation strategies for minimizing disruption to the healthcare system in the case of a nationwide epidemic. To this aim, we developed an age-structured stochastic compartmental susceptible-latent-infectious-removed-susceptible (SLIRS) model of SARS-CoV-2 transmission calibrated on the initial growth phase for the 2022 Omicron outbreak in Shanghai, to project COVID-19 burden (i.e., number of cases, patients requiring hospitalization and intensive care, and deaths) under hypothetical mitigation scenarios. The model also considers age-specific vaccine coverage data, vaccine efficacy against different clinical endpoints, waning of immunity, different antiviral therapies, and non-pharmaceutical interventions. We find that the level of immunity induced by the March 2022 vaccination campaign would be insufficient to prevent an Omicron wave that would result in exceeding critical care capacity with a projected intensive care unit peak demand of 15.6-times the existing capacity and causing approximately 1.55 million deaths. However, we also estimate that protecting vulnerable individuals by ensuring accessibility to vaccines and antiviral therapies, and maintaining implementation of non-pharmaceutical interventions could be sufficient to prevent overwhelming the healthcare system, suggesting that these factors should be points of emphasis in future mitigation policies.

M. Poletti

Mapping the epithelial–immune cell interactome upon infection in the gut and the upper airways

Systems biology and applications, May 2022; doi.org/10.1038/s41540-022-00224-x


Increasing evidence points towards the key role of the epithelium in the systemic and over-activated immune response to viral infection, including SARS-CoV-2 infection. Yet, how viral infection alters epithelial–immune cell interactions regulating inflammatory responses, is not well known. Available experimental approaches are insufficient to properly analyse this complex system, and computational predictions and targeted data integration are needed as an alternative approach. In this work, we propose an integrated computational biology framework that models how infection alters intracellular signalling of epithelial cells and how this change impacts the systemic immune response through modified interactions between epithelial cells and local immune cell populations. As a proof-of-concept, we focused on the role of intestinal and upper-airway epithelial infection. To characterise the modified epithelial–immune interactome, we integrated intra- and intercellular networks with single-cell RNA-seq data from SARS-CoV-2 infected human ileal and colonic organoids as well as from infected airway ciliated epithelial cells. This integrated methodology has proven useful to point out specific epithelial–immune interactions driving inflammation during disease response, and propose relevant molecular targets to guide focused experimental analysis.

A. Cicchetti et al.

Analisi dei modelli di risposta al Covid-19 in Italia: Instant Report ALTEMS # 2020-2022. Una fotografia a due anni dal primo caso in Italia

Report Altems 2020-2022, Aprile 2022;

COVID-19 Excess Mortality Collaborators

Estimating excess mortality due to the COVID-19 pandemic: a systematic analysis of COVID-19-related mortality, 2020–21

Lancet, March 2022; doi.org/10.1016/ S0140-6736(21)02796-3



Mortality statistics are fundamental to public health decision making. Mortality varies by time and location, and its measurement is affected by well known biases that have been exacerbated during the COVID-19 pandemic. This paper aims to estimate excess mortality from the COVID-19 pandemic in 191 countries and territories, and 252 subnational units for selected countries, from Jan 1, 2020, to Dec 31, 2021.


All-cause mortality reports were collected for 74 countries and territories and 266 subnational locations (including 31 locations in low-income and middle-income countries) that had reported either weekly or monthly deaths from all causes during the pandemic in 2020 and 2021, and for up to 11 year previously. In addition, we obtained excess mortality data for 12 states in India. Excess mortality over time was calculated as observed mortality, after excluding data from periods affected by late registration and anomalies such as heat waves, minus expected mortality. Six models were used to estimate expected mortality; final estimates of expected mortality were based on an ensemble of these models. Ensemble weights were based on root mean squared errors derived from an out-of-sample predictive validity test. As mortality records are incomplete worldwide, we built a statistical model that predicted the excess mortality rate for locations and periods where all-cause mortality data were not available. We used least absolute shrinkage and selection operator (LASSO) regression as a variable selection mechanism and selected 15 covariates, including both covariates pertaining to the COVID-19 pandemic, such as seroprevalence, and to background population health metrics, such as the Healthcare Access and Quality Index, with direction of effects on excess mortality concordant with a meta-analysis by the US Centers for Disease Control and Prevention. With the selected best model, we ran a prediction process using 100 draws for each covariate and 100 draws of estimated coefficients and residuals, estimated from the regressions run at the draw level using draw-level input data on both excess mortality and covariates. Mean values and 95% uncertainty intervals were then generated at national, regional, and global levels. Out-of-sample predictive validity testing was done on the basis of our final model specification.


Although reported COVID-19 deaths between Jan 1, 2020, and Dec 31, 2021, totalled 5·94 million worldwide, we estimate that 18·2 million (95% uncertainty interval 17·1–19·6) people died worldwide because of the COVID-19 pandemic (as measured by excess mortality) over that period. The global all-age rate of excess mortality due to the COVID-19 pandemic was 120·3 deaths (113·1–129·3) per 100 000 of the population, and excess mortality rate exceeded 300 deaths per 100 000 of the population in 21 countries. The number of excess deaths due to COVID-19 was largest in the regions of south Asia, north Africa and the Middle East, and eastern Europe. At the country level, the highest numbers of cumulative excess deaths due to COVID-19 were estimated in India (4·07 million [3·71–4·36]), the USA (1·13 million [1·08–1·18]), Russia (1·07 million [1·06–1·08]), Mexico (798 000 [741 000–867 000]), Brazil (792 000 [730 000–847 000]), Indonesia (736 000 [594 000–955 000]), and Pakistan (664 000 [498 000–847 000]). Among these countries, the excess mortality rate was highest in Russia (374·6 deaths [369·7–378·4] per 100 000) and Mexico (325·1 [301·6–353·3] per 100 000), and was similar in Brazil (186·9 [172·2–199·8] per 100 000) and the USA (179·3 [170·7–187·5] per 100 000).


The full impact of the pandemic has been much greater than what is indicated by reported deaths due to COVID-19 alone. Strengthening death registration systems around the world, long understood to be crucial to global public health strategy, is necessary for improved monitoring of this pandemic and future pandemics. In addition, further research is warranted to help distinguish the proportion of excess mortality that was directly caused by SARS-CoV-2 infection and the changes in causes of death as an indirect consequence of the pandemic.

Koelle, K.; et al.

The changing epidemiology of SARS-CoV-2

Science, https://www.science.org/doi/epdf/10.1126/science.abm4915

CONTENUTO E COMMENTO: Questa review sull’evoluzione dell’epidemiologia della pandemia di COVID-19 e sulle sfide da essa poste si concentra sui ruoli chiave che i modelli matematici e le analisi quantitative dei dati empirici hanno giocato nel permetterci di affrontare i vari interrogativi che via via ci siamo posti e nel provare a controllare la pandemia. Questi interrogativi, succedutisi nel corso di questi due anni vengono messi in correlazione, in questo lavoro, con le fasi della pandemia, ad esempio all’inizio del 2020 ci siamo chiesti se  SARS-CoV-2 avesse il potenziale di causare una pandemia, oggi invece ci stiamo chiedendo :  SARS-CoV-2 continuerà ancora ad evolversi per sfuggire all’immunità ?? Le domande sul vaccino si sono invece allargate a quelle riguardanti la misura in cui la vaccinazione potrebbe ridurre la trasmissione.Altre questioni analizzate sono  le proporzioni delle diffusioni delle diverse varianti di SARS-CoV-2, o il rischio di reinfezione.

Bartsch S et al.

Maintaining face mask use before and after achieving different COVID-19 vaccination coverage levels: a modelling study

Lancet Publich Health, https://www.sciencedirect.com/science/article/pii/S2468266722000408

CONTENUTO E COMMENTO : Studio di modello matematico confrontante due scenari : cosa sarebbe successo se, in parallelo alla diffusione della campagna vaccinale, a) le mascherine non fossero state o b) fossero state usate.

Tale simulazione mette in evidenza come l’utilizzo delle mascherine fino al raggiungimento di una copertura vaccinale del 70-90% sia conveniente, dal punto di vista economico, in tutti gli scenari esplorati. In particolare, perché il beneficio sia più pronunciato se l’utilizzo delle mascherine viene rinforzato nei mesi invernali e prolungato fino a 2-10 settimane dal raggiungimento della soglia vaccinale. Ovviamente, la comparsa di varianti che riducono l’efficacia dei vaccini non fa che consolidare l’efficace e la convenienza economica delle mascherine.

 Elien Colman et al.

Following the science? Views from scientists on government advisory boards during the COVID-19 pandemic: a qualitative interview study in five European countries

BMJ Global Hearth , https://gh.bmj.com/content/6/9/e006928.long

CONTENUTO: Ventuno scienziati impegnati in ruoli di consulenza governativa provenienti da 5 paesi europei sono stati intervistati tra dicembre 2020 e aprile 2021 per comprendere le loro esperienze, comprese eventuali criticità, anche al fine di facilitare il ruolo degli scienziati in eventuali future emergenze sanitarie. Ne emerge la necessità di una collaborazione interdisciplinare, di migliorare la trasparenza dell’informazione e di favorire il supporto al ruolo degli studiosi in particolare nell’informazione al pubblico.

Musa Abubakar Kana et al.

BMJ Global Hearth

Africa's contribution to the science of the COVID-19/SARS-CoV-2 pandemic

BMJ Global Hearth , https://gh.bmj.com/content/6/3/e004059

CONTENUTO: L’articolo mira a descrivere il ruolo dei Paesi del continente africano nella ricerca su COVID-19/SARS-CoV-2 alla luce della peculiarità dell’epidemiologia dell’infezione in Africa e nella prospettiva di una sempre maggior collaborazione tra ricercatori all’interno del continente e con altri continenti. 

Mary A. Shiraef et al.

COVID Border Accountability Project, a hand-coded global database of border closures introduced during 2020

Scientific Data, https://www.nature.com/articles/s41597-021-01031-5

CONTENUTO: L’articolo descrive il “COVID Border Accountability Project” (COBAP) che fornisce un database delle restrizioni degli accessi nei diversi Paesi del mondo, l’evoluzione di tali misure e aggiornamenti delle misure in essere tramite una mappa disponibile online (https://covidborderaccountability.org/).

Erika Arteaga-Cruz, Juan Cuvi

Thinking outside the modern capitalist logic: health-care systems based in other world views

Lancet Global Health , https://www.thelancet.com/journals/langlo/article/PIIS2214-109X(21)00341-7/fulltext

CONTENUTO: L'America Latina è abitata da circa 800 diversi popoli e nazionalità indigene, l'equivalente del 9-8% della sua popolazione. Il tasso medio di mortalità infantile nei bambini indigeni è del 60% più alto di quello dei bambini non indigeni. Nel 2018, l'Ecuador ha riferito che il 50-6% della sua popolazione indigena vive in povertà, rispetto al 20-9% della popolazione non indigena.2 Tra il 2014 e il 2017, la mortalità materna è stata del 69% più alta negli indigeni che nelle donne mestizo. La malnutrizione cronica colpisce un bambino ecuadoriano su quattro, e il tasso raddoppia nei bambini indigeni.

Queste cifre evidenziano disuguaglianze storiche e strutturali. no alcuni aspetti di questa dominazione.Una delle forme più sottili e, allo stesso tempo, più violente di subordinazione è l'imposizione culturale. Nel campo della salute, questa imposizione è mantenuta attraverso il modello biomedico sviluppato nei paesi ad alto reddito. Ma i popoli indigeni hanno sistemi sanitari propri molto efficienti. Durante la pandemia di COVID-19, e di fronte alle scarse risposte statali, hanno messo in atto azioni concrete per rispondere alla crisi sanitaria: isolandosi volontariamente nelle loro comunità, impedendo l'ingresso di compagnie petrolifere e minerarie nei loro territori, promuovendo lo scambio di cibo tra le regioni a basso contagio e quelle ad alto contagio (per le quali non esistevano disposizioni governative per la sicurezza alimentare), registrando il numero di casi di COVID-19, dando priorità ai rimedi a base di piante, producendo materiale informativo nelle loro lingue,5 e facendo partorire i bambini dagli assistenti tradizionali, tra le altre misure. La pandemia ha anche evidenziato i gravi limiti del modello biomedico egemonico basato su concezioni tecnologiche e pragmatiche dell'assistenza sanitaria.Questa esperienza vissuta riattiva un dibattito in America Latina: la possibilità di costruire altri sistemi sanitari che, pur fungendo da contrappeso al sistema ufficiale, rispondano alle esigenze specifiche dei settori indigeno e rurale.

COMMENTO: questo articolo importante espande e rende concreto il concetto di Salute Globale e illustra non solo le terribili disuguaglianze che esistono nel mondo più povero in termini di salute, ma pone anche la drammatica necessità di ridisegnare i nostri concetti di sistema sanitario, adattato ai bisogni delle popolazioni più fragili. Questo è già in atto in molti Paesi africani ma ovviamente andrebbe allargato a molte altre popolazioni del Sud del mondo.

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