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BackgroundArboviruses cause both seasonal epidemics (e.g. dengue viruses, DENV) and emerging outbreaks (e.g. chikungunya and Zika viruses, CHIKV and ZIKV) with a significant impact on global health. These viruses share mosquito vector species, often infecting the same host population within overlapping geographic regions. Thus, comparative analyses of their evolutionary and epidemiological dynamics across spatial and temporal scales could reveal convergent transmission trends.Methodology/Principal FindingsFocusing on Mexico as a case study, we generated CHIKV, DENV-1 and DENV-2 genomes from an epidemiological surveillance-derived historical sample collection, and analysed them together with longitudinally-collected genome and epidemiological data from the Americas. Arboviruses endemically circulating within the country were found to be introduced multiple times from lineages predominantly sampled from the Caribbean and Central America. For CHIKV, at least thirteen introductions were inferred over a year, with six of these leading to persistent transmission chains. For both DENV-1 and DENV-2, at least seven introductions were inferred over a decade.Conclusions/SignificanceOur results suggest that CHIKV, DENV-1 and DENV-2 in Mexico share similar evolutionary and epidemiological trajectories. The southwest region of the country was determined to be the most likely location for viral introductions from abroad, with a subsequent spread into the Pacific coast towards the north of Mexico. The virus diffusion patterns observed across the country are likely driven by multiple factors, including mobility linked to human migration from Central towards North America. Considering Mexico‘s economic role and geographic positioning displaying a high human mobility across borders, our results prompt the need to better understand the role of anthropogenic factors in the transmission dynamics of arboviruses, particularly linked to land-based human migration.AUTHOR SUMMARYMexico is endemic to several mosquito-borne viruses relevant to global health, and ranks within the top five countries in the Americas that report the highest case numbers. Our study provides a general overview of arbovirus introduction, spread and establishment patterns in North and Central America, and should be of interest to both local health and global authorities. Moreover, it sets to explore the paradigm of convergence at different scales in independent virus populations, represented by comparable epidemiological and evolutionary trends in arboviruses sharing ecological niches. Our results represent important advances in the study of mosquito-borne viruses listed as a threat to global health, specifically applied to key countries within the developing world

Zoonotic viruses that originate in wildlife harm global human health and economic prosperity1. Understanding virus transmission at the human-animal-environment interface is a key component of pandemic risk-reduction2,3. Zoonotic disease emergence is highest in biodiverse, tropical forests undergoing intensive land-use change4,5. Phylodynamic analyses of virus genomes can powerfully test epidemiological hypotheses, but are rarely applied to viruses of animals inhabiting these habitats. Brazil’s densely-populated Atlantic Forest and Cerrado region experienced in 2016–2021 an explosive human outbreak of sylvatic yellow fever, caused by repeated virus spillover from wild neotropical primates6. Here we use yellow fever virus (YFV) genome sequences and epidemiological data from neotropical primates, humans, and mosquito vectors to identify the environmental, demographic, and climatic factors determining zoonotic virus spread. Using portable sequencing approaches we generated 498 YFV genomes, resulting in a well-sampled dataset of zoonotic virus genomes sampled from wild mammals. YFV dispersal velocity was slower at higher elevation, in colder regions, and further away from main roads. Virus lineage dispersal was more frequent through wetter areas, areas with high neotropical primate density and through landscapes covered by mosaic vegetation. Higher temperatures were associated with higher virus effective population sizes, and peaks of transmission in warmer, wetter seasons were associated with higher virus evolutionary rates. Our study demonstrates how zoonotic disease transmission is linked to land-use and climate, underscoring the need for One-Health approaches to reducing the rate of zoonotic spillover.

SummaryIn many regions of the world, the Alpha, Beta and Gamma SARS-CoV-2 Variants of Concern (VOCs) co-circulated during 2020-21 and fueled waves of infections. During 2021, these variants were almost completely displaced by the Delta variant, causing a third wave of infections worldwide. This phenomenon of global viral lineage displacement was observed again in late 2021, when the Omicron variant disseminated globally. In this study, we use phylogenetic and phylogeographic methods to reconstruct the dispersal patterns of SARS-CoV-2 VOCs worldwide. We find that the source-sink dynamics of SARS-CoV-2 varied substantially by VOC, and identify countries that acted as global hubs of variant dissemination, while other countries became regional contributors to the export of specific variants. We demonstrate a declining role of presumed origin countries of VOCs to their global dispersal: we estimate that India contributed 80 countries had received introductions of Omicron BA.1 100 days after its inferred date of emergence, compared to just over 25 countries for the Alpha variant. This increased speed of global dissemination was associated with a rebound in air travel volume prior to Omicron emergence in addition to the higher transmissibility of Omicron relative to Alpha. Our study highlights the importance of global and regional hubs in VOC dispersal, and the speed at which highly transmissible variants disseminate through these hubs, even before their detection and characterization through genomic surveillance.HighlightsGlobal phylogenetic analysis reveals relationship between air travel and speed of dispersal of SARS-CoV-2 variants of concern (VOCs)Omicron VOC spread to 5x more countries within 100 days of its emergence compared to all other VOCsOnward transmission and dissemination of VOCs Delta and Omicron was primarily from secondary hubs rather than initial country of detection during a time of increased global air travelAnalysis highlights highly connected countries identified as major global and regional exporters of VOCs

Background The public health impact of the coronavirus disease 2019 (COVID-19) pandemic has motivated a rapid search for potential therapeutics, with some key successes. However, the potential impact of different treatments, and consequently research and procurement priorities, have not been clear. Methods Using a mathematical model of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission, COVID-19 disease and clinical care, we explore the public-health impact of different potential therapeutics, under a range of scenarios varying healthcare capacity, epidemic trajectories; and drug efficacy in the absence of supportive care. Results The impact of drugs like dexamethasone (delivered to the most critically-ill in hospital and whose therapeutic benefit is expected to depend on the availability of supportive care such as oxygen and mechanical ventilation) is likely to be limited in settings where healthcare capacity is lowest or where uncontrolled epidemics result in hospitals being overwhelmed. As such, it may avert 22% of deaths in high-income countries but only 8% in low-income countries (assuming R = 1.35). Therapeutics for different patient populations (those not in hospital, early in the course of infection) and types of benefit (reducing disease severity or infectiousness, preventing hospitalization) could have much greater benefits, particularly in resource-poor settings facing large epidemics. Conclusions Advances in the treatment of COVID-19 to date have been focused on hospitalized-patients and predicated on an assumption of adequate access to supportive care. Therapeutics delivered earlier in the course of infection that reduce the need for healthcare or reduce infectiousness could have significant impact, and research into their efficacy and means of delivery should be a priority.

Background:The COVID-19 situation in Brazil is complex due to large differences in the shape and size of regional epidemics. Understanding these patterns is crucial to understand future outbreaks of SARS-CoV-2 or other respiratory pathogens in the country.Methods:We tested 97,950 blood donation samples for IgG antibodies from March 2020 to March 2021 in 8 of Brazil’s most populous cities. Residential postal codes were used to obtain representative samples. Weekly age- and sex-specific seroprevalence were estimated by correcting the crude seroprevalence by test sensitivity, specificity, and antibody waning.Results:The inferred attack rate of SARS-CoV-2 in December 2020, before the Gamma variant of concern (VOC) was dominant, ranged from 19.3% (95% credible interval [CrI] 17.5–21.2%) in Curitiba to 75.0% (95% CrI 70.8–80.3%) in Manaus. Seroprevalence was consistently smaller in women and donors older than 55 years. The age-specific infection fatality rate (IFR) differed between cities and consistently increased with age. The infection hospitalisation rate increased significantly during the Gamma-dominated second wave in Manaus, suggesting increased morbidity of the Gamma VOC compared to previous variants circulating in Manaus. The higher disease penetrance associated with the health system’s collapse increased the overall IFR by a minimum factor of 2.91 (95% CrI 2.43–3.53).Conclusions:These results highlight the utility of blood donor serosurveillance to track epidemic maturity and demonstrate demographic and spatial heterogeneity in SARS-CoV-2 spread.Funding:This work was supported by Itaú Unibanco ‘Todos pela Saude’ program; FAPESP (grants 18/14389-0, 2019/21585-0); Wellcome Trust and Royal Society Sir Henry Dale Fellowship 204311/Z/16/Z; the Gates Foundation (INV- 034540 and INV-034652); REDS-IV-P (grant HHSN268201100007I); the UK Medical Research Council (MR/S0195/1, MR/V038109/1); CAPES; CNPq (304714/2018-6); Fundação Faculdade de Medicina; Programa Inova Fiocruz-CE/Funcap - Edital 01/2020 Number: FIO-0167-00065.01.00/20 SPU N°06531047/2020; JBS – Fazer o bem faz bem.

Insect-specific viruses (ISVs) are viruses that replicate exclusively in arthropod cells. Many ISVs have been studied in mosquitoes as many of them act as vectors for human etiological agents, such as arboviruses.

We documented 4 cases of severe acute respiratory syndrome coronavirus 2 reinfection by non-variant of concern strains among healthcare workers in Campinas, Brazil. We isolated infectious particles from nasopharyngeal secretions during both infection episodes. Improved and continued protection measures are necessary to mitigate the risk for reinfection among healthcare workers.

Chikungunya virus (CHIKV) is an Aedes mosquito-borne virus that has caused explosive epidemics linked to acute, chronic, and severe clinical outcomes. Since 2014, Brazil has had the highest number of chikungunya fever (CHIKF) cases in the Americas. Here, we report and contextualize the spatiotemporal dynamic of CHIKF in Brazil and combine genomic, epidemiological, and vector analyses to investigate CHIKF recurrence in several Brazilian states. From 2013 to 2022, CHIKV caused seven epidemic waves across Brazil, affecting 59.5% (3,316 of 5,570) of the country’s municipalities. To date, Ceará State in the northeast has been the most affected, with 81,274 cases during the two largest epidemic waves in 2016 and 2017, and the ongoing third wave in 2022. The 2022 CHIKF recurrence was associated with a new introduction of an East/Central/South African strain. Also, the CHIKV recurrences in Ceará, Tocantins, and Pernambuco States were limited to municipalities with few or no prior reported cases in the previous epidemic waves, suggesting that spatial heterogeneity of CHIKV spread and population immunity may explain the recurrence pattern in the country. In addition, the population density metrics of main CHIKV vector in Brazil, Ae. aegypti, were not correlated spatially with locations of CHIKF recurrence in Ceará and Tocantins States. Also, we show that CHIKF disproportionally affected females, and we estimated the case-fatality ratio in Ceará at ∼1.3 deaths per 1,000 cases. These findings more comprehensively describe CHIKV epidemics in Brazil and contribute to understanding CHIKF recurrence in urban settings. Overall, this information may help guide public health policy to mitigate and reduce the burden of urban arboviruses.

The emergence and global dissemination of Severe Acute Respiratory Syndrome virus 2 (SARS-CoV-2) variants of concern (VOCs) have been described as the main factor driving the Coronavirus Disease 2019 pandemic. In Brazil, the Gamma variant dominated the epidemiological scenario during the first period of 2021. Many Brazilian regions detected the Delta variant after its first description and documented its spread. To monitor the introduction and spread of VOC Delta, we performed Polymerase Chain Reaction (PCR) genotyping and genome sequencing in ten regional sentinel units from June to October 2021 in the State of Minas Gerais (MG). We documented the introduction and spread of Delta, comprising 70 per cent of the cases 8 weeks later. Comparing the viral loads of the Gamma and Delta dominance periods, we provide additional evidence that the latter is more transmissible. The spread and dominance of Delta did not culminate in the increase in cases and deaths, suggesting that the vaccination may have restrained the epidemic growth. Analysis of 224 novel Delta genomes revealed that Rio de Janeiro state was the primary source for disseminating this variant in the state of MG. We present the establishment of Delta, providing evidence of its enhanced transmissibility and showing that this variant shift did not aggravate the epidemiological scenario in a high immunity setting.

Monkeypox virus (MPXV), a zoonotic virus endemic to the African continent, has been reported in 33 non-endemic countries since May 2022. We report an almost complete genome of the first confirmed case of MPXV in Brazil. Shotgun metagenomic sequencing was completed in 18 hours, from DNA extraction to consensus sequence generation.

Unmitigated spread in Brazil Despite an extensive network of primary care availability, Brazil has suffered profoundly during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. Using daily data from state health offices, Castro et al. analyzed the pattern of spread of COVID-19 cases and deaths in the country from February to October 2020. Clusters of deaths before cases became apparent indicated unmitigated spread. SARS-CoV-2 circulated undetected in Brazil for more than a month as it spread north from Sã o Paulo. In Manaus, transmission reached unprecedented levels after a momentary respite in mid-2020. Faria et al. tracked the evolution of a new, more aggressive lineage called P.1, which has 17 mutations, including three (K417T, E484K, and N501Y) in the spike protein. After a period of accelerated evolution, this variant emerged in Brazil during November 2020. Coupled with the emergence of P.1, disease spread was accelerated by stark local inequalities and political upheaval, which compromised a prompt federal response. Science , abh1558 and abh2644, this issue p. 821 and p. 815

Background Immunity after dengue virus (DENV) infection has been suggested to cross-protect from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and mortality. Methods We tested whether serologically proven prior DENV infection diagnosed in September–October 2019, before the coronavirus disease 2019 (COVID-19) pandemic, reduced the risk of SARS-CoV-2 infection and clinically apparent COVID-19 over the next 13 months in a population-based cohort in Amazonian Brazil. Mixed-effects multiple logistic regression analysis was used to identify predictors of infection and disease, adjusting for potential individual and household-level confounders. Virus genomes from 14 local SARS-CoV-2 isolates were obtained using whole-genome sequencing. Results Anti-DENV immunoglobulin G (IgG) was found in 37.0% of 1285 cohort participants (95% confidence interval [CI]: 34.3% to 39.7%) in 2019, with 10.4 (95% CI: 6.7–15.5) seroconversion events per 100 person-years during the follow-up. In 2020, 35.2% of the participants (95% CI: 32.6% to 37.8%) had anti-SARS-CoV-2 IgG and 57.1% of the 448 SARS-CoV-2 seropositives (95% CI: 52.4% to 61.8%) reported clinical manifestations at the time of infection. Participants aged >60 years were twice more likely to have symptomatic COVID-19 than children under 5 years. Locally circulating SARS-CoV-2 isolates were assigned to the B.1.1.33 lineage. Contrary to the cross-protection hypothesis, prior DENV infection was associated with twice the risk of clinically apparent COVID-19 upon SARS-CoV-2 infection, with P values between .025 and .039 after adjustment for identified confounders. Conclusions Higher risk of clinically apparent COVID-19 among individuals with prior dengue has important public health implications for communities sequentially exposed to DENV and SARS-CoV-2 epidemics.

Currently, there are no evidence-based treatment options for long COVID-19, and it is known that SARS-CoV-2 can persist in part of the infected patients, especially those with immunosuppression. Since there is a robust secretion of SARS-CoV-2-specific highly-neutralizing IgA antibodies in breast milk, and because this immunoglobulin plays an essential role against respiratory virus infection in mucosa cells, being, in addition, more potent in neutralizing SARS-CoV-2 than IgG, here we report the clinical course of an NFκB-deficient patient chronically infected with the SARS-CoV-2 Gamma variant, who, after a non-full effective treatment with plasma infusion, received breast milk from a vaccinated mother by oral route as treatment for COVID-19. After such treatment, the symptoms improved, and the patient was systematically tested negative for SARS-CoV-2. Thus, we hypothesize that IgA and IgG secreted antibodies present in breast milk could be useful to treat persistent SARS-CoV-2 infection in immunodeficient patients.

Eastern equine encephalitis virus (EEEV), Madariaga virus (MADV) and Venezuelan equine encephalitis virus complex (VEEV) are New World mosquito-borne alphaviruses and cause severe neurological disease in human and equine hosts. However, their detection during the acute phase is complicated by non-specific clinical manifestations and lack of available diagnostic tools. To develop and clinically evaluate rRT-PCRs for VEEV complex, MADV and EEEV, primers and probes were designed from publicly available whole-genome sequences. The rRT-PCRs were validated using 15 retrospective serum samples from febrile patients collected during the 2015 and 2017 alphavirus outbreaks in Panama. In addition, the protocol was validated with 150 mosquito pools from 2015, and with 118 samples from prospective disease surveillance from 2021 and 2022. The rRT-PCRs detected VEEV complex RNA in 10 samples (66.7%) from the 2015 and 2017 outbreaks, and in one of these ten samples, both VEEV complex and MADV RNAs were detected. Additionally, VEEV complex RNA was detected in 5 suspected dengue from prospective disease surveillance. The rRT-PCR assays detected VEEV complex RNA in 3 fromCulex(Melanoconion)vomeriferpools, 2 of which yielded VEEV isolates. Untargeted sequencing and phylogenetic analysis identified VEEV ID subtype in seven VEEV complex RNA positive sample. The VEEV complex, MADV and EEEV rRT-PCRs provide accurate detection while yielding significant benefits over currently available molecular methods. Our results suggest that 11.9% of suspected dengue cases in Panama are VEEV infections.

Nigeria has the highest number of AIDS-related deaths in the world. In this study, we characterised the HIV-1 molecular epidemiology by analysing 1442 HIV-1 pol sequences collected 1999–2014 from four geopolitical zones in Nigeria using state-of-the-art maximum-likelihood and Bayesian phylogenetic analyses. The main circulating forms were the circulating recombinant form (CRF) 02_AG (44% of the analysed sequences), CRF43_02G (16%), and subtype G (8%). Twenty-three percent of the sequences represented unique recombinant forms (URFs), whereof 37 (11%) could be grouped into seven potentially novel CRFs. Bayesian phylodynamic analysis suggested that five major Nigerian HIV-1 sub-epidemics were introduced in the 1960s and 1970s, close to the Nigerian Civil War. The analysis also indicated that the number of effective infections decreased in Nigeria after the introduction of free antiretroviral treatment in 2006. Finally, Bayesian phylogeographic analysis suggested gravity-like dynamics in which virus lineages first emerge and expand within large urban centers such as Abuja and Lagos, before migrating towards smaller rural areas. This study provides novel insight into the Nigerian HIV-1 epidemic and may have implications for future HIV-1 prevention strategies in Nigeria and other severely affected countries.

Metagenomic next-generation sequencing (mNGS), the shotgun sequencing of RNA and DNA from clinical samples, has proved useful for broad-spectrum pathogen detection and the genomic surveillance of viral outbreaks. An additional target enrichment step is generally needed for high-sensitivity pathogen identification in low-titre infections, yet available methods using PCR or capture probes can be limited by high cost, narrow scope of detection, lengthy protocols and/or cross-contamination. Here, we developed metagenomic sequencing with spiked primer enrichment (MSSPE), a method for enriching targeted RNA viral sequences while simultaneously retaining metagenomic sensitivity for other pathogens. We evaluated MSSPE for 14 different viruses, yielding a median tenfold enrichment and mean 47% (±16%) increase in the breadth of genome coverage over mNGS alone. Virus detection using MSSPE arboviral or haemorrhagic fever viral panels was comparable in sensitivity to specific PCR, demonstrating 95% accuracy for the detection of Zika, Ebola, dengue, chikungunya and yellow fever viruses in plasma samples from infected patients. Notably, sequences from re-emerging and/or co-infecting viruses that have not been specifically targeted a priori, including Powassan and Usutu, were successfully enriched using MSSPE. MSSPE is simple, low cost, fast and deployable on either benchtop or portable nanopore sequencers, making this method directly applicable for diagnostic laboratory and field use., This study describes a new method that improves the sensitivity of viral detection compared with next-generation sequencing and enables the detection of emerging flaviviruses not specifically targeted a priori. Metagenomic sequencing with spiked primer enrichment is simple, low cost, fast and deployable on either benchtop or portable nanopore sequencers, making it applicable for diagnostic laboratory and field use.

Only two naturally occurring human Sabiá virus (SABV) infections have been reported, and those occurred over 20 years ago.We diagnosed two new cases of SABV infection using metagenomics in patients thought to have severe yellow fever and described new features of histopathological findings.We characterized clinical manifestations, histopathology and analyzed possible nosocomial transmission. Patients presented with hepatitis, bleeding, neurological alterations and died. We traced twenty-nine hospital contacts and evaluated them clinically and by RT-PCR and neutralizing antibodies. Autopsies uncovered unique features on electron microscopy, such as hepatocyte "pinewood knot" lesions. Although previous reports with similar New-World arenavirus had nosocomial transmission, our data did not find any case in contact tracing.Although an apparent by rare, Brazilian mammarenavirus infection is an etiology for acute hemorrhagic fever syndrome. The two fatal cases had peculiar histopathological findings not previously described. The virological diagnosis was possible only by contemporary techniques such as metagenomic assays. We found no subsequent infections when we used serological and molecular tests to evaluate close contacts.

Background Yellow fever (YF) is an arboviral disease which is endemic to Brazil due to a sylvatic transmission cycle maintained by infected mosquito vectors, non-human primate (NHP) hosts, and humans. Despite the existence of an effective vaccine, recent sporadic YF epidemics have underscored concerns about sylvatic vector surveillance, as very little is known about their spatial distribution. Here, we model and map the environmental suitability of YF’s main vectors in Brazil, Haemagogus spp. and Sabethes spp., and use human population and NHP data to identify locations prone to transmission and spillover risk. Methodology/Principal findings We compiled a comprehensive set of occurrence records on Hg. janthinomys, Hg. leucocelaenus, and Sabethes spp. from 1991–2019 using primary and secondary data sources. Linking these data with selected environmental and land-cover variables, we adopted a stacked regression ensemble modelling approach (elastic-net regularized GLM, extreme gradient boosted regression trees, and random forest) to predict the environmental suitability of these species across Brazil at a 1 km x 1 km resolution. We show that while suitability for each species varies spatially, high suitability for all species was predicted in the Southeastern region where recent outbreaks have occurred. By integrating data on NHP host reservoirs and human populations, our risk maps further highlight municipalities within the region that are prone to transmission and spillover. Conclusions/Significance Our maps of sylvatic vector suitability can help elucidate potential locations of sylvatic reservoirs and be used as a tool to help mitigate risk of future YF outbreaks and assist in vector surveillance. Furthermore, at-risk regions identified from our work could help disease control and elucidate gaps in vaccination coverage and NHP host surveillance., Author summary Yellow fever virus (YFV) is an arbovirus transmitted to humans from mosquitoes and can lead to severe disease and death. Recent sporadic outbreaks coupled with low vaccination coverage have highlighted the importance of mosquito surveillance for preventing future outbreaks and potential virus spillover into dense urban areas. Yet, very little is known about the spatial distribution of mosquitoes known to transmit YFV and the factors that contribute to their environmental suitability in Brazil. We compiled an occurrence database of primary and secondary mosquito vectors belonging to Haemagogus and Sabethes species’ collected between 1991–2019 and integrated this data with environmental and land-use data to predict their spatial suitability at 1 km x 1 km resolution. Using this information, we identified suitable regions for their co-existence. We overlaid this information with human population density and locations of non-human primate host reservoirs to identify areas at risk of transmission and spillover. Our study provides high-resolution mapping tools to assist with mosquito and arbovirus surveillance which is especially useful in low-resource settings.

On 26 November, the newly emerged variant Omicron was designated a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant of concern (VOC) (1). Rapid polymerase chain reaction (PCR) test results could improve estimates of the prevalence of Omicron around the world. The widely used Thermo Fisher TaqPath COVID-19 PCR assay was valuable in tracking the spread of the Alpha (B.1.1.7) VOC (2) because a deletion of amino acids 69 and 70 in Alpha’s spike gene (Δ69–70) yields a distinct absent S-gene (S−) despite positive test results. The Delta VOC lacks this deletion and is therefore S-gene positive (S+) on TaqPath PCR tests (3). The Omicron VOC shares the spike Δ69–70 deletion with Alpha, which has dropped to negligible levels worldwide. Therefore, the frequency of S− results can be used as a rapid proxy for the frequency of Omicron cases, provided initial detection of local circulation had been confirmed by sequencing.

The SARS-CoV-2 Gamma variant spread rapidly across Brazil, causing substantial infection and death waves. We use individual-level patient records following hospitalisation with suspected or confirmed COVID-19 to document the extensive shocks in hospital fatality rates that followed Gamma’s spread across 14 state capitals, and in which more than half of hospitalised patients died over sustained time periods. We show that extensive fluctuations in COVID-19 in-hospital fatality rates also existed prior to Gamma’s detection, and were largely transient after Gamma’s detection, subsiding with hospital demand. Using a Bayesian fatality rate model, we find that the geographic and temporal fluctuations in Brazil’s COVID-19 in-hospital fatality rates are primarily associated with geographic inequities and shortages in healthcare capacity. We project that approximately half of Brazil’s COVID-19 deaths in hospitals could have been avoided without pre-pandemic geographic inequities and without pandemic healthcare pressure. Our results suggest that investments in healthcare resources, healthcare optimization, and pandemic preparedness are critical to minimize population wide mortality and morbidity caused by highly transmissible and deadly pathogens such as SARS-CoV-2, especially in low- and middle-income countries., One sentence summary COVID-19 in-hospital fatality rates fluctuate dramatically in Brazil, and these fluctuations are primarily associated with geographic inequities and shortages in healthcare capacity.

BackgroundThe unprecedented public health impact of the COVID-19 pandemic has motivated a rapid search for potential therapeutics, with some key successes. However, the potential impact of different treatments, and consequently research and procurement priorities, have not been clear.Methods and FindingsWe develop a mathematical model of SARS-CoV-2 transmission, COVID-19 disease and clinical care to explore the potential public-health impact of a range of different potential therapeutics, under a range of different scenarios varying: i) healthcare capacity, ii) epidemic trajectories; and iii) drug efficacy in the absence of supportive care. In each case, the outcome of interest was the number of COVID-19 deaths averted in scenarios with the therapeutic compared to scenarios without. We find the impact of drugs like dexamethasone (which are delivered to the most critically-ill in hospital and whose therapeutic benefit is expected to depend on the availability of supportive care such as oxygen and mechanical ventilation) is likely to be limited in settings where healthcare capacity is lowest or where uncontrolled epidemics result in hospitals being overwhelmed. As such, it may avert 22% of deaths in high-income countries but only 8% in low-income countries (assuming R=1.35). Therapeutics for different patient populations (those not in hospital, early in the course of infection) and types of benefit (reducing disease severity or infectiousness, preventing hospitalisation) could have much greater benefits, particularly in resource-poor settings facing large epidemics.ConclusionsThere is a global asymmetry in who is likely to benefit from advances in the treatment of COVID-19 to date, which have been focussed on hospitalised-patients and predicated on an assumption of adequate access to supportive care. Therapeutics that can feasibly be delivered to those earlier in the course of infection that reduce the need for healthcare or reduce infectiousness could have significant impact, and research into their efficacy and means of delivery should be a priority.

Mathematical models can provide insights into the control of pandemic COVID-19, which remains a global priority. The dynamics of directly-transmitted infectious diseases, such as COVID-19, are usually described by compartmental models where individuals are classified as susceptible, infected and removed. These SIR models typically assume homogenous transmission of infection, even in large populations, a simplification that is convenient but inconsistent with observations. Here we use original data on the dynamics of COVID-19 spread in a Brazilian city to investigate the structure of the transmission network. We find that transmission can be described by a network in which each infectious individual has a small number of susceptible contacts, of the order of 2-5, which is independent of total population size. Compared with standard models of homogenous mixing, this scale-free, fractal infection process gives a better description of COVID-19 dynamics through time. In addition, the contact process explains the geographically localized clusters of disease seen in this Brazilian city. Our scale-free model can help refine criteria for physical and social distancing in order to more effectively mitigate the spread of COVID-19. We propose that scale-free COVID-19 dynamics could be a widespread phenomenon, a topic for further investigation.