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1.
Nat Commun ; 13(1): 7003, 2022 Nov 16.
Article in English | MEDLINE | ID: covidwho-2116500

ABSTRACT

Genomic sequencing is essential to track the evolution and spread of SARS-CoV-2, optimize molecular tests, treatments, vaccines, and guide public health responses. To investigate the global SARS-CoV-2 genomic surveillance, we used sequences shared via GISAID to estimate the impact of sequencing intensity and turnaround times on variant detection in 189 countries. In the first two years of the pandemic, 78% of high-income countries sequenced >0.5% of their COVID-19 cases, while 42% of low- and middle-income countries reached that mark. Around 25% of the genomes from high income countries were submitted within 21 days, a pattern observed in 5% of the genomes from low- and middle-income countries. We found that sequencing around 0.5% of the cases, with a turnaround time <21 days, could provide a benchmark for SARS-CoV-2 genomic surveillance. Socioeconomic inequalities undermine the global pandemic preparedness, and efforts must be made to support low- and middle-income countries improve their local sequencing capacity.


Subject(s)
COVID-19 , SARS-CoV-2 , Humans , SARS-CoV-2/genetics , Genome, Viral/genetics , COVID-19/epidemiology , Pandemics , Genomics
2.
PLoS Med ; 19(11): e1004132, 2022 Nov.
Article in English | MEDLINE | ID: covidwho-2117868

ABSTRACT

Dr Amitabh Suthar and Dr Christopher Dye give their perspective on infection, immunity and surveillance of COVID-19.


Subject(s)
COVID-19 , Humans
3.
Elife ; 112022 09 22.
Article in English | MEDLINE | ID: covidwho-2040360

ABSTRACT

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.


Subject(s)
COVID-19 , Antibodies, Viral , Blood Donors , Brazil/epidemiology , COVID-19/epidemiology , Cross-Sectional Studies , Female , Humans , Immunoglobulin G , Male , SARS-CoV-2 , Seroepidemiologic Studies
4.
Vaccines (Basel) ; 10(9)2022 Aug 31.
Article in English | MEDLINE | ID: covidwho-2006269

ABSTRACT

SARS-CoV-2 serologic surveys estimate the proportion of the population with antibodies against historical variants, which nears 100% in many settings. New approaches are required to fully exploit serosurvey data. Using a SARS-CoV-2 anti-Spike (S) protein chemiluminescent microparticle assay, we attained a semi-quantitative measurement of population IgG titers in serial cross-sectional monthly samples of blood donations across seven Brazilian state capitals (March 2021-November 2021). Using an ecological analysis, we assessed the contributions of prior attack rate and vaccination to antibody titer. We compared anti-S titer across the seven cities during the growth phase of the Delta variant and used this to predict the resulting age-standardized incidence of severe COVID-19 cases. We tested ~780 samples per month, per location. Seroprevalence rose to >95% across all seven capitals by November 2021. Driven by vaccination, mean antibody titer increased 16-fold over the study, with the greatest increases occurring in cities with the highest prior attack rates. Mean anti-S IgG was strongly correlated (adjusted R2 = 0.89) with the number of severe cases caused by Delta. Semi-quantitative anti-S antibody titers are informative about prior exposure and vaccination coverage and may also indicate the potential impact of future SARS-CoV-2 variants.

6.
Nat Med ; 28(7): 1476-1485, 2022 07.
Article in English | MEDLINE | ID: covidwho-1830084

ABSTRACT

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Gamma variant of concern has spread rapidly across Brazil since late 2020, causing substantial infection and death waves. Here we used individual-level patient records after hospitalization with suspected or confirmed coronavirus disease 2019 (COVID-19) between 20 January 2020 and 26 July 2021 to document temporary, sweeping shocks in hospital fatality rates that followed the spread of Gamma across 14 state capitals, during which typically more than half of hospitalized patients aged 70 years and older died. We show that such extensive shocks in COVID-19 in-hospital fatality rates also existed before the detection of Gamma. Using a Bayesian fatality rate model, we found that the geographic and temporal fluctuations in Brazil's COVID-19 in-hospital fatality rates were primarily associated with geographic inequities and shortages in healthcare capacity. We estimate that approximately half of the COVID-19 deaths in hospitals in the 14 cities 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.


Subject(s)
COVID-19 , Aged , Aged, 80 and over , Bayes Theorem , Brazil/epidemiology , COVID-19/epidemiology , Hospitals , Humans , SARS-CoV-2
7.
BMJ ; 377: o867, 2022 04 27.
Article in English | MEDLINE | ID: covidwho-1816745
8.
Nat Microbiol ; 7(4): 467-468, 2022 04.
Article in English | MEDLINE | ID: covidwho-1795752
9.
BMC Infect Dis ; 22(1): 127, 2022 Feb 05.
Article in English | MEDLINE | ID: covidwho-1690956

ABSTRACT

BACKGROUND: The city of Manaus, north Brazil, was stricken by a second epidemic wave of SARS-CoV-2 despite high seroprevalence estimates, coinciding with the emergence of the Gamma (P.1) variant. Reinfections were postulated as a partial explanation for the second surge. However, accurate calculation of reinfection rates is difficult when stringent criteria as two time-separated RT-PCR tests and/or genome sequencing are required. To estimate the proportion of reinfections caused by Gamma during the second wave in Manaus and the protection conferred by previous infection, we identified anti-SARS-CoV-2 antibody boosting in repeat blood donors as a mean to infer reinfection. METHODS: We tested serial blood samples from unvaccinated repeat blood donors in Manaus for the presence of anti-SARS-CoV-2 IgG antibodies using two assays that display waning in early convalescence, enabling the detection of reinfection-induced boosting. Donors were required to have three or more donations, being at least one during each epidemic wave. We propose a strict serological definition of reinfection (reactivity boosting following waning like a V-shaped curve in both assays or three spaced boostings), probable (two separate boosting events) and possible (reinfection detected by only one assay) reinfections. The serial samples were used to divide donors into six groups defined based on the inferred sequence of infection and reinfection with non-Gamma and Gamma variants. RESULTS: From 3655 repeat blood donors, 238 met all inclusion criteria, and 223 had enough residual sample volume to perform both serological assays. We found 13.6% (95% CI 7.0-24.5%) of all presumed Gamma infections that were observed in 2021 were reinfections. If we also include cases of probable or possible reinfections, these percentages increase respectively to 22.7% (95% CI 14.3-34.2%) and 39.3% (95% CI 29.5-50.0%). Previous infection conferred a protection against reinfection of 85.3% (95% CI 71.3-92.7%), decreasing to respectively 72.5% (95% CI 54.7-83.6%) and 39.5% (95% CI 14.1-57.8%) if probable and possible reinfections are included. CONCLUSIONS: Reinfection by Gamma is common and may play a significant role in epidemics where Gamma is prevalent, highlighting the continued threat variants of concern pose even to settings previously hit by substantial epidemics.


Subject(s)
COVID-19 , SARS-CoV-2 , Blood Donors , Brazil/epidemiology , Humans , Reinfection , Seroepidemiologic Studies
10.
Nat Rev Phys ; 2(6): 279-281, 2020.
Article in English | MEDLINE | ID: covidwho-1684119

ABSTRACT

As the COVID-19 pandemic continues, mathematical epidemiologists share their views on what models reveal about how the disease has spread, the current state of play and what work still needs to be done.

12.
Lancet Microbe ; 2(10): e527-e535, 2021 10.
Article in English | MEDLINE | ID: covidwho-1307293

ABSTRACT

BACKGROUND: Mutations accrued by SARS-CoV-2 lineage P.1-first detected in Brazil in early January, 2021-include amino acid changes in the receptor-binding domain of the viral spike protein that also are reported in other variants of concern, including B.1.1.7 and B.1.351. We aimed to investigate whether isolates of wild-type P.1 lineage SARS-CoV-2 can escape from neutralising antibodies generated by a polyclonal immune response. METHODS: We did an immunological study to assess the neutralising effects of antibodies on lineage P.1 and lineage B isolates of SARS-CoV-2, using plasma samples from patients previously infected with or vaccinated against SARS-CoV-2. Two specimens (P.1/28 and P.1/30) containing SARS-CoV-2 lineage P.1 (as confirmed by viral genome sequencing) were obtained from nasopharyngeal and bronchoalveolar lavage samples collected from patients in Manaus, Brazil, and compared against an isolate of SARS-CoV-2 lineage B (SARS.CoV2/SP02.2020) recovered from a patient in Brazil in February, 2020. Isolates were incubated with plasma samples from 21 blood donors who had previously had COVID-19 and from a total of 53 recipients of the chemically inactivated SARS-CoV-2 vaccine CoronaVac: 18 individuals after receipt of a single dose and an additional 20 individuals (38 in total) after receipt of two doses (collected 17-38 days after the most recent dose); and 15 individuals who received two doses during the phase 3 trial of the vaccine (collected 134-230 days after the second dose). Antibody neutralisation of P.1/28, P.1/30, and B isolates by plasma samples were compared in terms of median virus neutralisation titre (VNT50, defined as the reciprocal value of the sample dilution that showed 50% protection against cytopathic effects). FINDINGS: In terms of VNT50, plasma from individuals previously infected with SARS-CoV-2 had an 8·6 times lower neutralising capacity against the P.1 isolates (median VNT50 30 [IQR <20-45] for P.1/28 and 30 [<20-40] for P.1/30) than against the lineage B isolate (260 [160-400]), with a binominal model showing significant reductions in lineage P.1 isolates compared with the lineage B isolate (p≤0·0001). Efficient neutralisation of P.1 isolates was not seen with plasma samples collected from individuals vaccinated with a first dose of CoronaVac 20-23 days earlier (VNT50s below the limit of detection [<20] for most plasma samples), a second dose 17-38 days earlier (median VNT50 24 [IQR <20-25] for P.1/28 and 28 [<20-25] for P.1/30), or a second dose 134-260 days earlier (all VNT50s below limit of detection). Median VNT50s against the lineage B isolate were 20 (IQR 20-30) after a first dose of CoronaVac 20-23 days earlier, 75 (<20-263) after a second dose 17-38 days earlier, and 20 (<20-30) after a second dose 134-260 days earlier. In plasma collected 17-38 days after a second dose of CoronaVac, neutralising capacity against both P.1 isolates was significantly decreased (p=0·0051 for P.1/28 and p=0·0336 for P.1/30) compared with that against the lineage B isolate. All data were corroborated by results obtained through plaque reduction neutralisation tests. INTERPRETATION: SARS-CoV-2 lineage P.1 might escape neutralisation by antibodies generated in response to polyclonal stimulation against previously circulating variants of SARS-CoV-2. Continuous genomic surveillance of SARS-CoV-2 combined with antibody neutralisation assays could help to guide national immunisation programmes. FUNDING: São Paulo Research Foundation, Brazilian Ministry of Science, Technology and Innovation and Funding Authority for Studies, Medical Research Council, National Council for Scientific and Technological Development, National Institutes of Health. TRANSLATION: For the Portuguese translation of the abstract see Supplementary Materials section.


Subject(s)
COVID-19 , SARS-CoV-2 , Antibodies, Neutralizing , Antibodies, Viral , Brazil/epidemiology , COVID-19/prevention & control , COVID-19 Vaccines , Humans , SARS-CoV-2/genetics , United States , Vaccination
13.
Science ; 371(6535): 1184, 2021 03 19.
Article in English | MEDLINE | ID: covidwho-1142990
15.
PLoS One ; 16(1): e0241190, 2021.
Article in English | MEDLINE | ID: covidwho-1013205

ABSTRACT

Multiple national and international trends and drivers are radically changing what biological security means for the United Kingdom (UK). New technologies present novel opportunities and challenges, and globalisation has created new pathways and increased the speed, volume and routes by which organisms can spread. The UK Biological Security Strategy (2018) acknowledges the importance of research on biological security in the UK. Given the breadth of potential research, a targeted agenda identifying the questions most critical to effective and coordinated progress in different disciplines of biological security is required. We used expert elicitation to generate 80 policy-relevant research questions considered by participants to have the greatest impact on UK biological security. Drawing on a collaboratively-developed set of 450 questions, proposed by 41 experts from academia, industry and the UK government (consulting 168 additional experts) we subdivided the final 80 questions into six categories: bioengineering; communication and behaviour; disease threats (including pandemics); governance and policy; invasive alien species; and securing biological materials and securing against misuse. Initially, the questions were ranked through a voting process and then reduced and refined to 80 during a one-day workshop with 35 participants from a variety of disciplines. Consistently emerging themes included: the nature of current and potential biological security threats, the efficacy of existing management actions, and the most appropriate future options. The resulting questions offer a research agenda for biological security in the UK that can assist the targeting of research resources and inform the implementation of the UK Biological Security Strategy. These questions include research that could aid with the mitigation of Covid-19, and preparation for the next pandemic. We hope that our structured and rigorous approach to creating a biological security research agenda will be replicated in other countries and regions. The world, not just the UK, is in need of a thoughtful approach to directing biological security research to tackle the emerging issues.


Subject(s)
Pandemics/prevention & control , Security Measures/trends , Bioterrorism/prevention & control , COVID-19/prevention & control , Clinical Governance/trends , Communication , Disease Transmission, Infectious/prevention & control , Disease Transmission, Infectious/statistics & numerical data , Humans , Pandemics/statistics & numerical data , Policy , SARS-CoV-2/pathogenicity , Security Measures/statistics & numerical data , Surveys and Questionnaires , United Kingdom/epidemiology
16.
R Soc Open Sci ; 7(11): 201726, 2020 Nov.
Article in English | MEDLINE | ID: covidwho-991020

ABSTRACT

The number of COVID-19 deaths reported from European countries has varied more than 100-fold. In terms of coronavirus transmission, the relatively low death rates in some countries could be due to low intrinsic (e.g. low population density) or imposed contact rates (e.g. non-pharmaceutical interventions) among individuals, or because fewer people were exposed or susceptible to infection (e.g. smaller populations). Here, we develop a flexible empirical model (skew-logistic) to distinguish among these possibilities. We find that countries reporting fewer deaths did not generally have intrinsically lower rates of transmission and epidemic growth, and flatter epidemic curves. Rather, countries with fewer deaths locked down earlier, had shorter epidemics that peaked sooner and smaller populations. Consequently, as lockdowns were eased, we expected, and duly observed, a resurgence of COVID-19 across Europe.

17.
Science ; 371(6526): 288-292, 2021 01 15.
Article in English | MEDLINE | ID: covidwho-965798

ABSTRACT

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spread rapidly in Manaus, the capital of Amazonas state in northern Brazil. The attack rate there is an estimate of the final size of the largely unmitigated epidemic that occurred in Manaus. We use a convenience sample of blood donors to show that by June 2020, 1 month after the epidemic peak in Manaus, 44% of the population had detectable immunoglobulin G (IgG) antibodies. Correcting for cases without a detectable antibody response and for antibody waning, we estimate a 66% attack rate in June, rising to 76% in October. This is higher than in São Paulo, in southeastern Brazil, where the estimated attack rate in October was 29%. These results confirm that when poorly controlled, COVID-19 can infect a large proportion of the population, causing high mortality.


Subject(s)
Antibodies, Viral/blood , COVID-19/epidemiology , Epidemics , Immunoglobulin G/blood , SARS-CoV-2/isolation & purification , Adolescent , Adult , Aged , Blood Donors , Brazil/epidemiology , COVID-19/blood , COVID-19/mortality , Epidemiological Monitoring , Female , Humans , Male , Middle Aged , SARS-CoV-2/immunology , Seroepidemiologic Studies , Young Adult
18.
Nat Med ; 26(12): 1829-1834, 2020 12.
Article in English | MEDLINE | ID: covidwho-834900

ABSTRACT

The coronavirus disease 2019 (COVID-19) pandemic is straining public health systems worldwide, and major non-pharmaceutical interventions have been implemented to slow its spread1-4. During the initial phase of the outbreak, dissemination of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was primarily determined by human mobility from Wuhan, China5,6. Yet empirical evidence on the effect of key geographic factors on local epidemic transmission is lacking7. In this study, we analyzed highly resolved spatial variables in cities, together with case count data, to investigate the role of climate, urbanization and variation in interventions. We show that the degree to which cases of COVID-19 are compressed into a short period of time (peakedness of the epidemic) is strongly shaped by population aggregation and heterogeneity, such that epidemics in crowded cities are more spread over time, and crowded cities have larger total attack rates than less populated cities. Observed differences in the peakedness of epidemics are consistent with a meta-population model of COVID-19 that explicitly accounts for spatial hierarchies. We paired our estimates with globally comprehensive data on human mobility and predict that crowded cities worldwide could experience more prolonged epidemics.


Subject(s)
COVID-19/epidemiology , COVID-19/etiology , Crowding , Pandemics , China/epidemiology , Cities/epidemiology , Contact Tracing , Demography/standards , Demography/statistics & numerical data , Disease Outbreaks , Forecasting/methods , Geography , Human Activities/statistics & numerical data , Humans , Physical Distancing , Population Density , Public Policy/trends , SARS-CoV-2/physiology , Travel/statistics & numerical data
19.
Science ; 368(6491): 638-642, 2020 05 08.
Article in English | MEDLINE | ID: covidwho-20742

ABSTRACT

Responding to an outbreak of a novel coronavirus [agent of coronavirus disease 2019 (COVID-19)] in December 2019, China banned travel to and from Wuhan city on 23 January 2020 and implemented a national emergency response. We investigated the spread and control of COVID-19 using a data set that included case reports, human movement, and public health interventions. The Wuhan shutdown was associated with the delayed arrival of COVID-19 in other cities by 2.91 days. Cities that implemented control measures preemptively reported fewer cases on average (13.0) in the first week of their outbreaks compared with cities that started control later (20.6). Suspending intracity public transport, closing entertainment venues, and banning public gatherings were associated with reductions in case incidence. The national emergency response appears to have delayed the growth and limited the size of the COVID-19 epidemic in China, averting hundreds of thousands of cases by 19 February (day 50).


Subject(s)
Betacoronavirus , Coronavirus Infections/prevention & control , Coronavirus Infections/transmission , Pandemics/prevention & control , Pneumonia, Viral/prevention & control , Pneumonia, Viral/transmission , Travel , COVID-19 , China/epidemiology , Communicable Disease Control , Coronavirus Infections/epidemiology , Epidemics , Humans , Incidence , Models, Statistical , Pneumonia, Viral/epidemiology , Public Health Practice , Regression Analysis , SARS-CoV-2
20.
Science ; 368(6490): 493-497, 2020 05 01.
Article in English | MEDLINE | ID: covidwho-18400

ABSTRACT

The ongoing coronavirus disease 2019 (COVID-19) outbreak expanded rapidly throughout China. Major behavioral, clinical, and state interventions were undertaken to mitigate the epidemic and prevent the persistence of the virus in human populations in China and worldwide. It remains unclear how these unprecedented interventions, including travel restrictions, affected COVID-19 spread in China. We used real-time mobility data from Wuhan and detailed case data including travel history to elucidate the role of case importation in transmission in cities across China and to ascertain the impact of control measures. Early on, the spatial distribution of COVID-19 cases in China was explained well by human mobility data. After the implementation of control measures, this correlation dropped and growth rates became negative in most locations, although shifts in the demographics of reported cases were still indicative of local chains of transmission outside of Wuhan. This study shows that the drastic control measures implemented in China substantially mitigated the spread of COVID-19.


Subject(s)
Coronavirus Infections/epidemiology , Pneumonia, Viral/epidemiology , Travel/statistics & numerical data , Age Distribution , Betacoronavirus , COVID-19 , China , Coronavirus Infections/prevention & control , Coronavirus Infections/transmission , Epidemiological Monitoring , Humans , Linear Models , Pandemics/prevention & control , Pneumonia, Viral/prevention & control , Pneumonia, Viral/transmission , SARS-CoV-2 , Sex Distribution , Spatial Analysis
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