Publications
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de Souza WM, de Lima STS, Simões Mello LM, et al., 2023, Spatiotemporal dynamics and recurrence of chikungunya virus in Brazil: an epidemiological study, The Lancet Microbe, Vol: 4, Pages: e319-e329, ISSN: 2666-5247
BACKGROUND: Chikungunya virus (CHIKV) is an Aedes mosquito-borne virus that has caused large epidemics linked to acute, chronic, and severe clinical outcomes. Currently, Brazil has the highest number of chikungunya cases in the Americas. We aimed to investigate the spatiotemporal dynamics and recurrence pattern of chikungunya in Brazil since its introduction in 2013. METHODS: In this epidemiological study, we used CHIKV genomic sequencing data, CHIKV vector information, and aggregate clinical data on chikungunya cases from Brazil. The genomic data comprised 241 Brazilian CHIKV genome sequences from GenBank (n=180) and the 2022 CHIKV outbreak in Ceará state (n=61). The vector data (Breteau index and House index) were obtained from the Brazilian Ministry of Health for all 184 municipalities in Ceará state and 116 municipalities in Tocantins state in 2022. Epidemiological data on laboratory-confirmed cases of chikungunya between 2013 and 2022 were obtained from the Brazilian Ministry of Health and Laboratory of Public Health of Ceará. We assessed the spatiotemporal dynamics of chikungunya in Brazil via time series, mapping, age-sex distribution, cumulative case-fatality, linear correlation, logistic regression, and phylogenetic analyses. FINDINGS: Between March 3, 2013, and June 4, 2022, 253 545 laboratory-confirmed chikungunya cases were reported in 3316 (59·5%) of 5570 municipalities, mainly distributed in seven epidemic waves from 2016 to 2022. To date, Ceará in the northeast has been the most affected state, with 77 418 cases during the two largest epidemic waves in 2016 and 2017 and the third wave in 2022. From 2016 to 2022 in Ceará, the odds of being CHIKV-positive were higher in females than in males (odds ratio 0·87, 95% CI 0·85-0·89, p<0·0001), and the cumulative case-fatality ratio was 1·3 deaths per 1000 cases. Chikungunya recurrences in the states of Ceará
Hemilembolo MC, Niama AC, Campillo JT, et al., 2023, Excess Mortality Associated with Loiasis: Confirmation by a New Retrospective Cohort Study Conducted in the Republic of Congo, Open Forum Infectious Diseases, Vol: 10
Background. Loiasis (Loa loa filariasis) is considered a benign disease and is currently not included in the World Health Organization’s (WHO’s) list of Neglected Tropical Diseases, despite mounting evidence suggesting significant disease burden in endemic areas. We conducted a retrospective cohort study to assess the mortality associated with L. loa microfilaremia in the Southwestern Republic of Congo. Methods. The cohort included 3329 individuals from 53 villages screened for loiasis in 2004. We compared mortality rates in 2021 for individuals initially diagnosed as with or without L. loa microfilariae 17 years earlier. Data were analyzed at the community level to calculate crude mortality rates. Survival models were used to estimate the effect of L. loa microfilaremia on mortality in the population. Results. At baseline, prevalence of microfilaremia was 16.2%. During 17.62 years of cohort follow-up, 751 deaths were recorded, representing a crude mortality rate of 15.36 (95% CI, 14.28–16.50) per 1000 person-years. Median survival time was 58.5 (95% CI, 49.7–67.3) years and 39.2 (95% CI, 32.6–45.8) years for amicrofilaremic and microfilaremic indiviudals, respectively. Conclusions. A significant reduction in life expectancy was associated with L. loa microfilaremia, confirming previous observations from Cameroon. This adds to the evidence that loiasis is not a benign disease and deserves to be included in the WHO’s list of Neglected Tropical Diseases.
Whittaker C, Hamlet A, Sherrard-Smith E, et al., 2023, Seasonal dynamics of Anopheles stephensi and its implications for mosquito detection and emergent malaria control in the Horn of Africa, Proceedings of the National Academy of Sciences of USA, Vol: 120, Pages: 1-9, ISSN: 0027-8424
Invasion of the malaria vector Anopheles stephensi across the Horn of Africa threatens control efforts across the continent, particularly in urban settings where the vector is able to proliferate. Malaria transmission is primarily determined by the abundance of dominant vectors, which often varies seasonally with rainfall. However, it remains unclear how An. stephensi abundance changes throughout the year, despite this being a crucial input to surveillance and control activities. We collate longitudinal catch data from across its endemic range to better understand the vector's seasonal dynamics and explore the implications of this seasonality for malaria surveillance and control across the Horn of Africa. Our analyses reveal pronounced variation in seasonal dynamics, the timing and nature of which are poorly predicted by rainfall patterns. Instead, they are associated with temperature and patterns of land use; frequently differing between rural and urban settings. Our results show that timing entomological surveys to coincide with rainy periods is unlikely to improve the likelihood of detecting An. stephensi. Integrating these results into a malaria transmission model, we show that timing indoor residual spraying campaigns to coincide with peak rainfall offers little improvement in reducing disease burden compared to starting in a random month. Our results suggest that unlike other malaria vectors in Africa, rainfall may be a poor guide to predicting the timing of peaks in An. stephensi-driven malaria transmission. This highlights the urgent need for longitudinal entomological monitoring of the vector in its new environments given recent invasion and potential spread across the continent.
de Menezes MT, Moreira FRR, Whittaker C, et al., 2023, Dynamics of early establishment of SARS-CoV-2 VOC Omicron lineages in Minas Gerais, Brazil, Viruses, Vol: 15, Pages: 1-13, ISSN: 1999-4915
Brazil is one of the nations most affected by Coronavirus disease 2019 (COVID-19). The introduction and establishment of new virus variants can be related to an increase in cases and fatalities. The emergence of Omicron, the most modified SARS-CoV-2 variant, caused alarm for the public health of Brazil. In this study, we examined the effects of the Omicron introduction in Minas Gerais (MG), the second-most populous state of Brazil. A total of 430 Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) samples from November 2021 to June 2022 from Belo Horizonte (BH) city were sequenced. These newly sequenced genomes comprise 72% of all previously available SARS-CoV-2 genomes for the city. Evolutionary analysis of novel viral genomes reveals that a great diversity of Omicron sublineages have circulated in BH, a pattern in-keeping with observations across Brazil more generally. Bayesian phylogeographic reconstructions indicate that this diversity is a product of a large number of international and national importations. As observed previously, São Paulo state is shown as a significant hub for viral spread throughout the country, contributing to around 70% of all viral Omicron introductions detected in MG.
Penn M, Laydon D, penn J, et al., 2023, The uncertainty of infectious disease outbreaks is underestimated
<jats:title>Abstract</jats:title> <jats:p>Uncertainty can be classified as either aleatoric (intrinsic randomness) or epistemic (imperfect knowledge of parameters). The majority of frameworks assessing infectious disease risk consider only epistemic uncertainty. We only ever observe a single epidemic, and therefore cannot empirically determine aleatoric uncertainty. Here, for the first time, we characterise both epistemic and aleatoric uncertainty using a time-varying general branching processes. Our framework explicitly decomposes aleatoric variance into mechanistic components, quantifying the contribution to uncertainty produced by each factor in the epidemic process, and how these contributions vary over time. The aleatoric variance of an outbreak is itself a renewal equation where past variance affects future variance. Perhaps surprisingly, superspreading is not necessary for substantial uncertainty, and profound variation in outbreak size can occur even without overdispersion in the offspring distribution (i.e. the distribution of the number of secondary infections an infected person produces). Crucially, aleatoric forecasting uncertainty grows dynamically and rapidly, and so forecasting using only epistemic uncertainty is a significant underestimate. Therefore, failure to account for aleatoric uncertainty will ensure that policymakers are misled about the substantially higher true extent of potential risk. We demonstrate our method, and the extent to which potential risk is underestimated, using two historical examples: firstly the 2003 Hong Kong severe acute respiratory syndrome (SARS) outbreak, and secondly the early 2020 UK COVID-19 epidemic. Our framework provides analytical tools to estimate epidemic uncertainty with limited data, to provide reasonable worst-case scenarios and assess both epistemic and aleatoric uncertainty in forecasting, and to retrospectively assess an epidemic and thereby provide a baseline risk estimate for f
Brito AF, Semonva E, Dudas G, et al., 2022, Global disparities in SARS-CoV-2 genomic surveillance, Nature Communications, Vol: 13, Pages: 1-13, ISSN: 2041-1723
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 (TAT) on variant detection in 189 countries. In two years of pandemic, 78% of high income countries (HICs) sequenced >0.5% of their COVID-19 cases, while 42% of low (LICs) and middle income countries (MICs) reached that mark. Around 25% of the genomes from HICs were submitted within 21 days, a pattern observed in 5% of the genomes from LICs and MICs. We found that sequencing around 0.5% of the cases, with a TAT <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 LICs and MICs improve their local sequencing capacity.
Morgenstern C, Laydon D, Whittaker C, et al., 2022, The interaction of transmission intensity, mortality, and the economy: a retrospective analysis of the COVID-19 pandemic
<jats:title>Abstract</jats:title> <jats:p>The COVID-19 pandemic has caused over 6.4 million registered deaths to date, and has had a profound impact on economic activity. Here, we study the interaction of transmission, mortality, and the economy during the SARS-CoV-2 pandemic from January 2020 to December 2022 across 25 European countries. We adopt a Bayesian vector autoregressive model with both fixed and random effects. We find that increases in disease transmission intensity decreases Gross domestic product (GDP) and increases daily excess deaths, with a longer lasting impact on excess deaths in comparison to GDP, which recovers more rapidly. Broadly, our results reinforce the intuitive phenomenon that significant economic activity arises from diverse person-to-person interactions. We report on the effectiveness of non-pharmaceutical interventions (NPIs) on transmission intensity, excess deaths and changes in GDP, and resulting implications for policy makers. Our results highlight a complex cost-benefit trade off from individual NPIs. For example, banning international travel increases GDP however reduces excess deaths. We consider country random effects and their associations with excess changes in GDP and excess deaths. For example, more developed countries in Europe typically had more cautious approaches to the COVID-19 pandemic, prioritising healthcare and excess deaths over economic performance. Long term economic impairments are not fully captured by our model, as well as long term disease effects (Long Covid). Our results highlight that the impact of disease on a country is complex and multifaceted, and simple heuristic conclusions to extract the best outcome from the economy and disease burden are challenging.</jats:p>
Whittaker C, Chesnais CB, Pion SDS, et al., 2022, Factors associated with variation in single-dose albendazole pharmacokinetics: A systematic review and modelling analysis, PLOS NEGLECTED TROPICAL DISEASES, Vol: 16, ISSN: 1935-2735
Prete CA, Buss LF, Whittaker C, et al., 2022, SARS-CoV-2 antibody dynamics in blood donors and COVID-19 epidemiology in eight Brazilian state capitals: A serial cross-sectional study, eLife, Vol: 11, ISSN: 2050-084X
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 Me
Buss L, Prete CA, Whittaker C, et al., 2022, Predicting SARS-CoV-2 variant spread in a completely seropositive population using semi-quantitative antibody measurements in blood donors, Vaccines, Vol: 10, Pages: 1-11, ISSN: 2076-393X
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.
Dixon-Zegeye M, Winskill P, Harrison W, et al., 2022, Global force-of-infection trends for human taenia solium taeniasis/cysticercosis, eLife, Vol: 11, ISSN: 2050-084X
Infection by Taenia solium poses a major burden across endemic countries. The World Health Organization (WHO) 2021–2030 Neglected Tropical Diseases roadmap has proposed that 30% of endemic countries achieve intensified T. solium control in hyperendemic areas by 2030. Understanding geographical variation in age-prevalence profiles and force-of-infection (FoI) estimates will inform intervention designs across settings. Human taeniasis (HTT) and human cysticercosis (HCC) age-prevalence data from 16 studies in Latin America, Africa and Asia were extracted through a systematic review. Catalytic models, incorporating diagnostic performance uncertainty, were fitted to the data using Bayesian methods, to estimate rates of antibody (Ab)-seroconversion, infection acquisition and Ab-seroreversion or infection loss. HCC FoI and Ab-seroreversion rates were also estimated across 23 departments in Colombia from 28,100 individuals. Across settings, there was extensive variation in all-ages seroprevalence. Evidence for Ab seroreversion or infection loss was found in most settings for both HTT and HCC and for HCC Ab seroreversion in Colombia. The average duration until humans became Ab-seropositive/infected decreased as all-age (sero)prevalence increased. There was no clear relationship between the average duration humans remain Ab-seropositive and all-age seroprevalence. Marked geographical heterogeneity in T. solium transmission rates indicate the need for setting43 specific intervention strategies to achieve the WHO goals.
Brizzi A, Whittaker C, Servo LMS, et al., 2022, Author correction: spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals, Nature Medicine, Vol: 28, Pages: 1509-1509, ISSN: 1078-8956
Correction to: Nature Medicine https://doi.org/10.1038/s41591-022-01807-1, published online 10 May 2022.
Whittaker C, Watson O, Alvarez-Moreno C, et al., 2022, Understanding the Potential Impact of Different Drug Properties On SARS-CoV-2 Transmission and Disease Burden: A Modelling Analysis, Clinical Infectious Diseases, Vol: 75, Pages: e224-e233, ISSN: 1058-4838
BackgroundThe 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.MethodsUsing a mathematical model of 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.ResultsThe 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 hospitalisation) could have much greater benefits, particularly in resource-poor settings facing large epidemics.ConclusionsAdvances in the treatment of COVID-19 to date have been focussed on hospitalised-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.
Whittaker C, Chesnais CB, Pion SDS, et al., 2022, Factors associated with variation in single-dose albendazole pharmacokinetics: A systematic review and modelling analysis
<jats:title>Abstract</jats:title><jats:sec><jats:title>Background</jats:title><jats:p>Albendazole is an orally administered anti-parasitic medication with widespread usage in a variety of both programmatic and clinical contexts. Previous work has shown the drug to be characterised by significant inter-individual pharmacokinetic variation. This variation is thought to have important consequences for treatment success, but current understanding of the factors associated with this variation remains incomplete.</jats:p></jats:sec><jats:sec><jats:title>Methodology/Principal Findings</jats:title><jats:p>We carried out a systematic review to identify references containing temporally disaggregated data on the blood concentration of albendazole and/or (its pharmacologically-active metabolite) albendazole sulfoxide following a single oral dose. These data were then integrated into a mathematical modelling framework to infer key pharmacokinetic parameters and relate them to characteristics of the populations being treated. These characteristics included age, weight, sex, dosage, infection status, and whether patients had received a fatty meal prior to treatment or other drugs alongside albendazole. Our results highlight a number of factors systematically associated with albendazole pharmacokinetic variation including age, existing parasitic infection and receipt of a fatty meal. These factors impact different aspects of the drug’s pharmacokinetic profile. Whilst age is significantly associated with albendazole sulfoxide half-life, receipt of a fatty meal prior to treatment was associated with increased albendazole bioavailability (and by extension, peak blood concentration and total drug exposure following the dose). Parasitic infection (particularly echinococcosis and neurocysticercosis) was associated with altered pharmacokinetic parameters, with infected populations displaying distinct characteris
Okell L, Brazeau NF, Verity R, et al., 2022, Estimating the COVID-19 infection fatality ratio accounting for seroreversion using statistical modelling, Communications Medicine, Vol: 2, Pages: 1-13, ISSN: 2730-664X
Background: The infection fatality ratio (IFR) is a key statistic for estimating the burden of coronavirus disease 2019 (COVID-19) and has been continuously debated throughout the COVID-19 pandemic. The age-specific IFR can be quantified using antibody surveys to estimate total infections, but requires consideration of delay-distributions from time from infection to seroconversion, time to death, and time to seroreversion (i.e. antibody waning) alongside serologic test sensitivity and specificity. Previous IFR estimates have not fully propagated uncertainty or accounted for these potential biases, particularly seroreversion. Methods: We built a Bayesian statistical model that incorporates these factors and applied this model to simulated data and 10 serologic studies from different countries. Results: We demonstrate that seroreversion becomes a crucial factor as time accrues but is less important during first-wave, short-term dynamics. We additionally show that disaggregating surveys by regions with higher versus lower disease burden can inform serologic test specificity estimates. The overall IFR in each setting was estimated at 0.49 -2.53%.Conclusion: We developed a robust statistical framework to account for full uncertainties in the parameters determining IFR. We provide code for others to apply these methods to further datasets and future epidemics.
Brizzi A, Whittaker C, Servo LMS, et al., 2022, Spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals, Nature Medicine, Vol: 28, ISSN: 1078-8956
The SARS-CoV-2 Gamma variant of concern spread rapidly across Brazil since late 2020, causing substantial infection and death waves. We use individual-level patient records following hospitalisation with suspected or confirmed COVID-19 between 20 January 2020 and 26 July 2021 to document temporary, sweeping shocks in hospital fatality rates that followed Gamma’s spread across 14 state capitals, during which typically more than half of hospitalised patients aged 70 and over died. We show that such extensive shocks in COVID-19 in-hospital fatality rates also existed prior to detection of Gamma. Using a Bayesian fatality rate model, we find 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.
Whittaker C, Winskill P, Sinka M, et al., 2022, A novel statistical framework for exploring the population dynamics and seasonality of mosquito populations, Proceedings of the Royal Society B: Biological Sciences, Vol: 289, Pages: 1-10, ISSN: 0962-8452
Understanding the temporal dynamics of mosquito populations underlying vector-borne disease transmission is key to optimizing control strategies. Many questions remain surrounding the drivers of these dynamics and how they vary between species—questions rarely answerable from individual entomological studies (that typically focus on a single location or species). We develop a novel statistical framework enabling identification and classification of time series with similar temporal properties, and use this framework to systematically explore variation in population dynamics and seasonality in anopheline mosquito time series catch data spanning seven species, 40 years and 117 locations across mainland India. Our analyses reveal pronounced variation in dynamics across locations and between species in the extent of seasonality and timing of seasonal peaks. However, we show that these diverse dynamics can be clustered into four ‘dynamical archetypes’, each characterized by distinct temporal properties and associated with a largely unique set of environmental factors. Our results highlight that a range of environmental factors including rainfall, temperature, proximity to static water bodies and patterns of land use (particularly urbanicity) shape the dynamics and seasonality of mosquito populations, and provide a generically applicable framework to better identify and understand patterns of seasonal variation in vectors relevant to public health.
Prete CA, Buss LF, Buccheri R, et al., 2022, Reinfection by the SARS-CoV-2 Gamma variant in blood donors in Manaus, Brazil, BMC Infectious Diseases, Vol: 22, ISSN: 1471-2334
BackgroundThe 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.MethodsWe 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.ResultsFrom 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.
Brito AF, Semenova E, Dudas G, et al., 2021, Global disparities in SARS-CoV-2 genomic surveillance.
Genomic sequencing provides critical information to track the evolution and spread of SARS-CoV-2, optimize molecular tests, treatments and vaccines, and guide public health responses. To investigate the spatiotemporal heterogeneity in the global SARS-CoV-2 genomic surveillance, we estimated the impact of sequencing intensity and turnaround times (TAT) on variant detection in 167 countries. Most countries submit genomes >21 days after sample collection, and 77% of low and middle income countries sequenced <0.5% of their cases. We found that sequencing at least 0.5% of the cases, with a TAT <21 days, could be a benchmark for SARS-CoV-2 genomic surveillance efforts. Socioeconomic inequalities substantially impact our ability to quickly detect SARS-CoV-2 variants, and undermine the global pandemic preparedness.
McCabe R, Kont MD, Watson O, et al., 2021, Communicating uncertainty in epidemic models, Epidemics: the journal of infectious disease dynamics, Vol: 37, Pages: 1-6, ISSN: 1755-4365
While mathematical models of disease transmission are widely used to inform public health decision-makers globally, the uncertainty inherent in results are often poorly communicated. We outline some potential sources of uncertainty in epidemic models, present traditional methods used to illustrate uncertainty and discuss alternative presentation formats used by modelling groups throughout the COVID-19 pandemic. Then, by drawing on the experience of our own recent modelling, we seek to contribute to the ongoing discussion of how to improve upon traditional methods used to visualise uncertainty by providing a suggestion of how this can be presented in a clear and simple manner.
Mousa A, Winskill P, Watson OJ, et al., 2021, Social contact patterns and implications for infectious disease transmission - a systematic review and meta-analysis of contact surveys, ELIFE, Vol: 10, ISSN: 2050-084X
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Mousa A, Winskill P, Watson OJ, et al., 2021, Social contact patterns and implications for infectious disease transmission: a systematic review and meta-analysis of contact surveys, eLife, Vol: 10, ISSN: 2050-084X
Background: Transmission of respiratory pathogens such as SARS-CoV-2 depends on patterns of contact and mixing across populations. Understanding this is crucial to predict pathogen spread and the effectiveness of control efforts. Most analyses of contact patterns to date have focussed on high-income settings.Methods: Here, we conduct a systematic review and individual-participant meta-analysis of surveys carried out in low- and middle-income countries and compare patterns of contact in these settings to surveys previously carried out in high-income countries. Using individual-level data from 28,503 participants and 413,069 contacts across 27 surveys we explored how contact characteristics (number, location, duration and whether physical) vary across income settings.Results: Contact rates declined with age in high- and upper-middle-income settings, but not in low-income settings, where adults aged 65+ made similar numbers of contacts as younger individuals and mixed with all age-groups. Across all settings, increasing household size was a key determinant of contact frequency and characteristics, with low-income settings characterised by the largest, most intergenerational households. A higher proportion of contacts were made at home in low-income settings, and work/school contacts were more frequent in high-income strata. We also observed contrasting effects of gender across income-strata on the frequency, duration and type of contacts individuals made.Conclusions: These differences in contact patterns between settings have material consequences for both spread of respiratory pathogens, as well as the effectiveness of different non-pharmaceutical interventions.
Dhar MS, Marwal R, Radhakrishnan VS, et al., 2021, Genomic characterization and epidemiology of an emerging SARS-CoV-2 variant in Delhi, India, SCIENCE, Vol: 374, Pages: 995-+, ISSN: 0036-8075
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- Citations: 122
Whittaker C, Walker PGT, Alhaffar M, et al., 2021, Under-reporting of deaths limits our understanding of true burden of covid-19, BMJ-BRITISH MEDICAL JOURNAL, Vol: 375, ISSN: 0959-535X
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- Citations: 35
Brizzi A, Whittaker C, Servo LMS, et al., 2021, Factors driving extensive spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals
The SARS‐CoV‐2 Gamma variant spread rapidly across Brazil, causing substantial infection and death wa ves. 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 pe riods. 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 d emand. Using a Bayesian fatality rate model, we find that the geo‐graphic and temporal fluctuations in Brazil’s COVID‐19 in‐hospital fatality rates are primarily associated with geo‐graphic inequities and shortages in healthcare c apacity. 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 trans‐missible and deadly pathogens such as SARS‐CoV‐2, especially in low‐ and middle‐income countries.
Whittaker C, Ratmann O, Dye C, et al., 2021, Altered demographic profile of hospitalizations during the second COVID-19 wave in Amazonas, Brazil, The Lancet Regional Health - Americas, Vol: 2, ISSN: 2667-193X
Mlcochova P, Kemp SA, Dhar MS, et al., 2021, SARS-CoV-2 B.1.617.2 Delta variant replication and immune evasion, NATURE, Vol: 599, Pages: 114-+, ISSN: 0028-0836
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- Citations: 479
Mishra S, Scott JA, Laydon DJ, et al., 2021, Comparing the responses of the UK, Sweden and Denmark to COVID-19 using counterfactual modelling, SCIENTIFIC REPORTS, Vol: 11, Pages: 1-9, ISSN: 2045-2322
The UK and Sweden have among the worst per-capita COVID-19 mortality in Europe. Sweden stands out for its greater reliance on voluntary, rather than mandatory, control measures. We explore how the timing and effectiveness of control measures in the UK, Sweden and Denmark shaped COVID-19 mortality in each country, using a counterfactual assessment: what would the impact have been, had each country adopted the others’ policies? Using a Bayesian semi-mechanistic model without prior assumptions on the mechanism or effectiveness of interventions, we estimate the time-varying reproduction number for the UK, Sweden and Denmark from daily mortality data. We use two approaches to evaluate counterfactuals which transpose the transmission profile from one country onto another, in each country’s first wave from 13th March (when stringent interventions began) until 1st July 2020. UK mortality would have approximately doubled had Swedish policy been adopted, while Swedish mortality would have more than halved had Sweden adopted UK or Danish strategies. Danish policies were most effective, although differences between the UK and Denmark were significant for one counterfactual approach only. Our analysis shows that small changes in the timing or effectiveness of interventions have disproportionately large effects on total mortality within a rapidly growing epidemic.
Okell L, Whittaker C, Ghani A, et al., 2021, Global patterns of submicroscopic Plasmodium falciparum malaria infection: insights from a systematic review and meta-analysis of population surveys, The Lancet Microbe, Vol: 2, Pages: e366-e374, ISSN: 2666-5247
Background: Adoption of molecular techniques to detect Plasmodium falciparum infection has revealed many previously undetected (by microscopy) yet transmissible low-density infections. The proportion of these infections is typically highest in low transmission settings, but drivers of submicroscopic infection remain unclear. Here, we update a previously conducted systematic review of asexual P. falciparum prevalence by microscopy and polymerase chain reaction (PCR) in the same population. We conduct a meta-analysis to explore potential drivers of submicroscopic infection and identify the locations where submicroscopic infections are most common. Methods: PubMed and Web of Science databases were searched up to 11th October 2020 for cross-sectional studies reporting data on asexual P.falciparum prevalence by both microscopy and PCR. Surveys of pregnant women, where participants had been chosen based on symptoms/treatment or that did not involve a population from a defined location were excluded. Both the number of individuals tested and positive by microscopy and PCR for P. falciparum infection were extracted from each reference. Bayesian regression modelling was used to explore determinants of the size of the submicroscopic reservoir including geography, seasonality, age, methodology and current/historical patterns of transmission.Findings: A total of 166 references containing 551 cross-sectional survey microscopy/PCR prevalence pairs were included. Our results highlight that submicroscopic infections predominate in low transmission settings across all settings, but also reveal marked geographical variation, with the proportion of infections that are submicroscopic being highest in South American surveys and lowest in West African studies. Whilst current transmission levels partly explain these results, we find that historical transmission intensity also represents a crucial determinant of the size of the submicroscopic reservoir, as does the demographic structure of
Mishra S, Mindermann S, Sharma M, et al., 2021, Changing composition of SARS-CoV-2 lineages and rise of Delta variant in England, ECLINICALMEDICINE, Vol: 39
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