Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 20 de 57
Filter
1.
Commun Med (Lond) ; 2: 54, 2022.
Article in English | MEDLINE | ID: covidwho-1947549

ABSTRACT

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.

3.
Lancet Child Adolesc Health ; 6(4): 249-259, 2022 04.
Article in English | MEDLINE | ID: covidwho-1927002

ABSTRACT

BACKGROUND: In the 6 months following our estimates from March 1, 2020, to April 30, 2021, the proliferation of new coronavirus variants, updated mortality data, and disparities in vaccine access increased the amount of children experiencing COVID-19-associated orphanhood. To inform responses, we aimed to model the increases in numbers of children affected by COVID-19-associated orphanhood and caregiver death, as well as the cumulative orphanhood age-group distribution and circumstance (maternal or paternal orphanhood). METHODS: We used updated excess mortality and fertility data to model increases in minimum estimates of COVID-19-associated orphanhood and caregiver deaths from our original study period of March 1, 2020-April 30, 2021, to include the new period of May 1-Oct 31, 2021, for 21 countries. Orphanhood was defined as the death of one or both parents; primary caregiver loss included parental death or the death of one or both custodial grandparents; and secondary caregiver loss included co-residing grandparents or kin. We used logistic regression and further incorporated a fixed effect for western European countries into our previous model to avoid over-predicting caregiver loss in that region. For the entire 20-month period, we grouped children by age (0-4 years, 5-9 years, and 10-17 years) and maternal or paternal orphanhood, using fertility contributions, and we modelled global and regional extrapolations of numbers of orphans. 95% credible intervals (CrIs) are given for all estimates. FINDINGS: The number of children affected by COVID-19-associated orphanhood and caregiver death is estimated to have increased by 90·0% (95% CrI 89·7-90·4) from April 30 to Oct 31, 2021, from 2 737 300 (95% CrI 1 976 100-2 987 000) to 5 200 300 (3 619 400-5 731 400). Between March 1, 2020, and Oct 31, 2021, 491 300 (95% CrI 485 100-497 900) children aged 0-4 years, 736 800 (726 900-746 500) children aged 5-9 years, and 2 146 700 (2 120 900-2 174 200) children aged 10-17 years are estimated to have experienced COVID-19-associated orphanhood. Globally, 76·5% (95% CrI 76·3-76·7) of children were paternal orphans, whereas 23·5% (23·3-23·7) were maternal orphans. In each age group and region, the prevalence of paternal orphanhood exceeded that of maternal orphanhood. INTERPRETATION: Our findings show that numbers of children affected by COVID-19-associated orphanhood and caregiver death almost doubled in 6 months compared with the amount after the first 14 months of the pandemic. Over the entire 20-month period, 5·0 million COVID-19 deaths meant that 5·2 million children lost a parent or caregiver. Our data on children's ages and circumstances should support pandemic response planning for children globally. FUNDING: UK Research and Innovation (Global Challenges Research Fund, Engineering and Physical Sciences Research Council, and Medical Research Council), Oak Foundation, UK National Institute for Health Research, US National Institutes of Health, and Imperial College London.


Subject(s)
COVID-19/mortality , Caregivers/supply & distribution , Child, Orphaned/statistics & numerical data , Adolescent , Adult , Child , Female , Humans , Male , Models, Statistical
4.
Proc Natl Acad Sci U S A ; 119(23): e2119266119, 2022 06 07.
Article in English | MEDLINE | ID: covidwho-1873628

ABSTRACT

The effectiveness of mask wearing at controlling severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission has been unclear. While masks are known to substantially reduce disease transmission in healthcare settings [D. K. Chu et al., Lancet 395, 1973­1987 (2020); J. Howard et al., Proc. Natl. Acad. Sci. U.S.A. 118, e2014564118 (2021); Y. Cheng et al., Science eabg6296 (2021)], studies in community settings report inconsistent results [H. M. Ollila et al., medRxiv (2020); J. Brainard et al., Eurosurveillance 25, 2000725 (2020); T. Jefferson et al., Cochrane Database Syst. Rev. 11, CD006207 (2020)]. Most such studies focus on how masks impact transmission, by analyzing how effective government mask mandates are. However, we find that widespread voluntary mask wearing, and other data limitations, make mandate effectiveness a poor proxy for mask-wearing effectiveness. We directly analyze the effect of mask wearing on SARS-CoV-2 transmission, drawing on several datasets covering 92 regions on six continents, including the largest survey of wearing behavior (n= 20 million) [F. Kreuter et al., https://gisumd.github.io/COVID-19-API-Documentation (2020)]. Using a Bayesian hierarchical model, we estimate the effect of mask wearing on transmission, by linking reported wearing levels to reported cases in each region, while adjusting for mobility and nonpharmaceutical interventions (NPIs), such as bans on large gatherings. Our estimates imply that the mean observed level of mask wearing corresponds to a 19% decrease in the reproduction number R. We also assess the robustness of our results in 60 tests spanning 20 sensitivity analyses. In light of these results, policy makers can effectively reduce transmission by intervening to increase mask wearing.


Subject(s)
COVID-19 , Masks , COVID-19/epidemiology , COVID-19/prevention & control , Humans , Public Policy , Surveys and Questionnaires
5.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-337633

ABSTRACT

Covid-19 has caused more than 1 million deaths in the US, including at least 1,433 deaths among children and young people (CYP) aged 0-19 years. Deaths among US CYP are rare in general, and so we argue here that the mortality burden of Covid-19 in CYP is best understood in the context of all other causes of CYP death. Using publicly available data from the National Center for Health Statistics, and comparing to mortality in 2019, the immediate pre-pandemic period, we find that Covid-19 is a leading cause of death in CYP aged 0-19 years in the US, ranking #9 among all causes of deaths, #5 in disease related causes of deaths (excluding accidents, assault and suicide), and #1 in deaths caused by infectious / respiratory diseases. Due to the impact of mitigations such as social distancing and our comparison of a single disease (Covid-19) to groups of causes such as deaths from pneumonia and influenza, these rankings are likely conservative lower bounds. Our findings underscore the importance of continued vaccination campaigns for CYP over 5 years of age in the US and for effective Covid-19 vaccines for under 5 year olds.

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.
Lancet Infect Dis ; 22(7): 967-976, 2022 07.
Article in English | MEDLINE | ID: covidwho-1799640

ABSTRACT

BACKGROUND: Estimates of the severity of the SARS-CoV-2 omicron variant (B.1.1.529) are crucial to assess the public health impact associated with its rapid global dissemination. We estimated the risk of SARS-CoV-2-related hospitalisations after infection with omicron compared with the delta variant (B.1.617.2) in Denmark, a country with high mRNA vaccination coverage and extensive free-of-charge PCR testing capacity. METHODS: In this observational cohort study, we included all RT-PCR-confirmed cases of SARS-CoV-2 infection in Denmark, with samples taken between Nov 21 (date of first omicron-positive sample) and Dec 19, 2021. Individuals were identified in the national COVID-19 surveillance system database, which included results of a variant-specific RT-PCR that detected omicron cases, and data on SARS-CoV-2-related hospitalisations (primary outcome of the study). We calculated the risk ratio (RR) of hospitalisation after infection with omicron compared with delta, overall and stratified by vaccination status, in a Poisson regression model with robust SEs, adjusted a priori for reinfection status, sex, age, region, comorbidities, and time period. FINDINGS: Between Nov 21 and Dec 19, 2021, among the 188 980 individuals with SARS-CoV-2 infection, 38 669 (20·5%) had the omicron variant. SARS-CoV-2-related hospitalisations and omicron cases increased during the study period. Overall, 124 313 (65·8%) of 188 980 individuals were vaccinated, and vaccination was associated with a lower risk of hospitalisation (adjusted RR 0·24, 95% CI 0·22-0·26) compared with cases with no doses or only one dose of vaccine. Compared with delta infection, omicron infection was associated with an adjusted RR of hospitalisation of 0·64 (95% CI 0·56-0·75; 222 [0·6%] of 38 669 omicron cases admitted to hospital vs 2213 [1·5%] of 150 311 delta cases). For a similar comparison by vaccination status, the RR of hospitalisation was 0·57 (0·44-0·75) among cases with no or only one dose of vaccine, 0·71 (0·60-0·86) among those who received two doses, and 0·50 (0·32-0·76) among those who received three doses. INTERPRETATION: We found a significantly lower risk of hospitalisation with omicron infection compared with delta infection among both vaccinated and unvaccinated individuals, suggesting an inherent reduced severity of omicron. Our results could guide modelling of the effect of the ongoing global omicron wave and thus health-care system preparedness. FUNDING: None.


Subject(s)
COVID-19 , Hepatitis D , COVID-19/epidemiology , Cohort Studies , Denmark/epidemiology , Hospitalization , Humans , SARS-CoV-2/genetics
8.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-332946

ABSTRACT

Several vaccines candidates are in development against Middle East respiratory syndrome–related coronavirus (MERS-CoV), which remains a major public health concern. Using individual-level data on the 2013-2014 Kingdom of Saudi Arabia epidemic, we employ counterfactual analysis on inferred transmission trees (“who-infected-whom”) to assess potential vaccine impact. We investigate the conditions under which prophylactic “proactive” campaigns would outperform “reactive” campaigns (i.e. vaccinating either before or in response to the next outbreak), focussing on healthcare workers. Spatial scale is crucial: if vaccinating healthcare workers in response to outbreaks at their hospital only, proactive campaigns perform better, unless efficacy has waned significantly. However, campaigns that react at regional or national level consistently outperform proactive campaigns. Measures targeting the animal reservoir reduce transmission linearly, albeit with wide uncertainty. Substantial reduction of MERS-CoV morbidity and mortality is possible when vaccinating healthcare workers, underlining the need for at-risk countries to stockpile vaccines when available.

9.
Sci Data ; 9(1): 145, 2022 04 01.
Article in English | MEDLINE | ID: covidwho-1773990

ABSTRACT

During the second half of 2020, many European governments responded to the resurging transmission of SARS-CoV-2 with wide-ranging non-pharmaceutical interventions (NPIs). These efforts were often highly targeted at the regional level and included fine-grained NPIs. This paper describes a new dataset designed for the accurate recording of NPIs in Europe's second wave to allow precise modelling of NPI effectiveness. The dataset includes interventions from 114 regions in 7 European countries during the period from the 1st August 2020 to the 9th January 2021. The paper includes NPI definitions tailored to the second wave following an exploratory data collection. Each entry has been extensively validated by semi-independent double entry, comparison with existing datasets, and, when necessary, discussion with local epidemiologists. The dataset has considerable potential for use in disentangling the effectiveness of NPIs and comparing the impact of interventions across different phases of the pandemic.


Subject(s)
COVID-19/therapy , COVID-19/epidemiology , COVID-19/psychology , Europe , Humans , Psychosocial Intervention , SARS-CoV-2
10.
Lancet ; 399(10332): 1303-1312, 2022 04 02.
Article in English | MEDLINE | ID: covidwho-1740323

ABSTRACT

BACKGROUND: The omicron variant (B.1.1.529) of SARS-CoV-2 has demonstrated partial vaccine escape and high transmissibility, with early studies indicating lower severity of infection than that of the delta variant (B.1.617.2). We aimed to better characterise omicron severity relative to delta by assessing the relative risk of hospital attendance, hospital admission, or death in a large national cohort. METHODS: Individual-level data on laboratory-confirmed COVID-19 cases resident in England between Nov 29, 2021, and Jan 9, 2022, were linked to routine datasets on vaccination status, hospital attendance and admission, and mortality. The relative risk of hospital attendance or admission within 14 days, or death within 28 days after confirmed infection, was estimated using proportional hazards regression. Analyses were stratified by test date, 10-year age band, ethnicity, residential region, and vaccination status, and were further adjusted for sex, index of multiple deprivation decile, evidence of a previous infection, and year of age within each age band. A secondary analysis estimated variant-specific and vaccine-specific vaccine effectiveness and the intrinsic relative severity of omicron infection compared with delta (ie, the relative risk in unvaccinated cases). FINDINGS: The adjusted hazard ratio (HR) of hospital attendance (not necessarily resulting in admission) with omicron compared with delta was 0·56 (95% CI 0·54-0·58); for hospital admission and death, HR estimates were 0·41 (0·39-0·43) and 0·31 (0·26-0·37), respectively. Omicron versus delta HR estimates varied with age for all endpoints examined. The adjusted HR for hospital admission was 1·10 (0·85-1·42) in those younger than 10 years, decreasing to 0·25 (0·21-0·30) in 60-69-year-olds, and then increasing to 0·47 (0·40-0·56) in those aged at least 80 years. For both variants, past infection gave some protection against death both in vaccinated (HR 0·47 [0·32-0·68]) and unvaccinated (0·18 [0·06-0·57]) cases. In vaccinated cases, past infection offered no additional protection against hospital admission beyond that provided by vaccination (HR 0·96 [0·88-1·04]); however, for unvaccinated cases, past infection gave moderate protection (HR 0·55 [0·48-0·63]). Omicron versus delta HR estimates were lower for hospital admission (0·30 [0·28-0·32]) in unvaccinated cases than the corresponding HR estimated for all cases in the primary analysis. Booster vaccination with an mRNA vaccine was highly protective against hospitalisation and death in omicron cases (HR for hospital admission 8-11 weeks post-booster vs unvaccinated: 0·22 [0·20-0·24]), with the protection afforded after a booster not being affected by the vaccine used for doses 1 and 2. INTERPRETATION: The risk of severe outcomes following SARS-CoV-2 infection is substantially lower for omicron than for delta, with higher reductions for more severe endpoints and significant variation with age. Underlying the observed risks is a larger reduction in intrinsic severity (in unvaccinated individuals) counterbalanced by a reduction in vaccine effectiveness. Documented previous SARS-CoV-2 infection offered some protection against hospitalisation and high protection against death in unvaccinated individuals, but only offered additional protection in vaccinated individuals for the death endpoint. Booster vaccination with mRNA vaccines maintains over 70% protection against hospitalisation and death in breakthrough confirmed omicron infections. FUNDING: Medical Research Council, UK Research and Innovation, Department of Health and Social Care, National Institute for Health Research, Community Jameel, and Engineering and Physical Sciences Research Council.


Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/epidemiology , COVID-19/prevention & control , Cohort Studies , England/epidemiology , Hospitalization , Humans , Vaccines, Synthetic
11.
EuropePMC;
Preprint in English | EuropePMC | ID: ppcovidwho-327766

ABSTRACT

Five years of sustained indoor residual spraying (IRS) of insecticide from 2014 to 2019, first using a carbamate followed by an organophosphate, was associated with a marked reduction in the burden of malaria in five districts of Uganda. We assessed malaria burden over an additional 21 months, corresponding to a change in IRS formulations using clothianidin with and without deltamethrin and the start of the COVID-19 pandemic. We document an unprecedented resurgence in malaria burden: in years 4-5 of sustained IRS cases were 84% lower than the pre-IRS period, in year 6 this increased to a 43% reduction, and in the first 9 months of year 7, cases were 39% higher than pre-IRS levels. The timing of this resurgence corresponded to a change of active ingredient to clothianidin, a new IRS active ingredient. Further research is needed to determine mechanisms leading to this resurgence.

12.
SSRN;
Preprint in English | SSRN | ID: ppcovidwho-326260

ABSTRACT

Background: The Omicron variant (B.1.1.529) of SARS-CoV-2 has demonstrated partial vaccine escape and high transmissibility, with early studies indicating lower severity of infection compared with Delta (B.1.617.2). We sought to better characterise Omicron severity relative to Delta by assessing the relative risk of hospital attendance, hospital admission or death in a large national cohort. Methods: Individual-level data on laboratory-confirmed COVID-19 cases resident in England between 22 November 2021 and 9 January 2022 were linked to routine datasets on vaccination status, hospitalisation and mortality. The relative risk of attendance at hospital within 14 days, or death within 28 days following confirmed infection, was estimated using proportional hazards regression. Analyses were stratified by test date, 10-year age band, ethnicity, region and vaccination status and further adjusted for sex, index of multiple deprivation decile, evidence of a prior infection and year of age within each age band. A secondary analysis estimated variant- and vaccine-specific vaccine effectiveness and the intrinsic relative severity of Omicron infection compared with Delta;i.e. the relative risk in unvaccinated cases. Findings: We found that the adjusted hazard ratio (HR) of hospital attendance (not necessarily resulting in admission) with Omicron compared with Delta was 0.56 (95%CI: 0.54-0.58);for hospital admission and death the estimates were 0.41 (95%CI: 0.39-0.43) and 0.31 (95%CI: 0.26-0.37), respectively. Omicron vs Delta HR estimates varied with age for all endpoints examined: the adjusted HR for hospital admission was 1.07 (95%CI: 0.83-1.38) in <10 year-olds, falling to 0.25 (95%CI: 0.21-0.30) in 60-69 year-olds, and rising to 0.48 (95%CI: 0.40-0.57) in ≥80 year-olds. For both variants, past infection gave some protection against death both in vaccinated (HR: 0.45 [95%CI: 0.30-0.68]) and unvaccinated (0.14 [95%CI: 0.04-0.45]) cases. In vaccinated cases, past infection offered no additional protection against hospital admission beyond that provided by vaccination (HR: 0.99 [95%CI: 0.9-1.08]), whilst for unvaccinated cases moderate protection remained (HR: 0.53 [95%CI: 0.46-0.61]). Estimation of variant-specific vaccine effectiveness gave lower Omicron vs Delta HR estimates for hospital admission (0.29 [95%CI: 0.28-0.31]) in unvaccinated cases than estimated for all cases in the primary analysis. Booster vaccination with an mRNA vaccine was highly protective against hospitalisation and death in Omicron cases (HR for hospital admission 8-11 weeks post booster, compared with unvaccinated: 0.22 [95%CI: 0.19-0.24]), with the protection afforded after a booster not being significantly affected by the vaccine used for doses 1 and 2. Interpretation: The risk of severe outcomes following SARS-CoV-2 infection is substantially lower for Omicron compared with Delta cases, with higher reductions for more severe endpoints and significant variation with age. The (low) risk of hospital admission in children <10 years of age did not differ significantly by variant, while 60-69 year-olds had an approximately 75% reduced risk of hospital admission with Omicron compared with Delta. Underlying the observed HRs is a larger reduction in intrinsic severity (in unvaccinated individuals) counterbalanced by a reduction in vaccine effectiveness. A documented previous SARS-CoV-2 infection offered some protection against hospitalisation and high protection against death in unvac

13.
EuropePMC;
Preprint in English | EuropePMC | ID: ppcovidwho-326223

ABSTRACT

The COVID-19 pandemic has caused severe public health consequences in the United States. In this study, we use a hierarchical Bayesian model to estimate the age-specific COVID-19 attributable deaths over time in the United States. The model is specified by a novel non-parametric spatial approach, a low-rank Gaussian Process (GP) projected by regularised B-splines. We show that this projection defines a new GP with attractive smoothness and computational efficiency properties, derive its kernel function, and discuss the penalty terms induced by the projected GP. Simulation analyses and benchmark results show that the spatial approach performs better than standard B-splines and Bayesian P-splines and equivalently well as a standard GP, for considerably lower runtimes. The B-splines projected GP priors that we develop are likely an appealing addition to the arsenal of Bayesian regularising priors. We apply the model to weekly, age-stratified COVID-19 attributable deaths reported by the US Centers for Disease Control, which are subject to censoring and reporting biases. Using the B-splines projected GP, we can estimate longitudinal trends in COVID-19 associated deaths across the US by 1-year age bands. These estimates are instrumental to calculate age-specific mortality rates, describe variation in age-specific deaths across the US, and for fitting epidemic models. Here, we couple the model with age-specific vaccination rates to show that lower vaccination rates in younger adults aged 18-64 are associated with significantly stronger resurgences in COVID-19 deaths, especially in Florida and Texas. These results underscore the critical importance of medically able individuals of all ages to be vaccinated against COVID-19 in order to limit fatal outcomes.

14.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-323423

ABSTRACT

Background: Hospitals in England have undergone considerable change to address the surge in demand imposed by the COVID-19 epidemic. The impact of this on emergency department (ED) attendances is unknown, especially for non-COVID-19 related emergencies. Methods We calibrated auto-regressive integrated moving average time-series models of ED attendances to Imperial College Healthcare NHS Trust (ICHNT) using historic (2015–2019) data. Forecasted trends were compared to present year ICHNT data for the period between March 12 (when England implemented the first COVID-19 public health measure) and May 31. We compared ICHTN trends with publicly available regional and national data. Lastly, we compared emergency admissions and in-hospital mortality at ICHNT during the present year to a historic 5-year average. Results ED attendances at ICHNT decreased by 35%, in keeping with the trend for ED attendances across all England regions, which fell by approximately 50%. For ICHNT, the decrease in attendances was mainly amongst those aged < 65 years and those arriving by their own means (e.g. personal or public transport). Increasing distance from postcode of residence to hospital was a significant predictor of reduced attendances. Non-COVID related emergency admissions to hospital after March 12 fell by 48%;there was an indication of a non-significant increase in non-COVID-19 crude mortality risk (RR 1.13, 95%CI 0.94–1.37, p = 0.19). Conclusions Our study finds strong evidence that emergency healthcare seeking has drastically changed across the population in England. At ICHNT, we find that a larger proportion arrived by ambulance and that hospitalisation outcomes of non-COVID patients did not differ from previous years. The extent to which these findings relate to ED avoidance behaviours compared to having sought alternative emergency health services outside of hospital remains unknown. National analyses and strategies to streamline emergency services in England going forward are urgently needed.

15.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-305031

ABSTRACT

Background : The COVID-19 epidemic was declared a Global Pandemic by WHO on 11 March 2020. By 24 March 2020, over 440,000 cases and almost 20,000 deaths had been reported worldwide. In response to the fast-growing epidemic, which began in the Chinese city of Wuhan, Hubei, China imposed strict social distancing in Wuhan on 23 January 2020 followed closely by similar measures in other provinces. These interventions have impacted economic productivity in China, and the ability of the Chinese economy to resume without restarting the epidemic was not clear. Methods : Using daily reported cases from mainland China and Hong Kong SAR, we estimated transmissibility over time and compared it to daily within-city movement, as a proxy for economic activity. Results : Initially, within-city movement and transmission were very strongly correlated in the five mainland provinces most affected by the epidemic and Beijing. However, that correlation decreased rapidly after the initial sharp fall in transmissibility. In general, towards the end of the study period, the correlation was no longer apparent, despite substantial increases in within-city movement. A similar analysis for Hong Kong shows that intermediate levels of local activity were maintained while avoiding a large outbreak. At the very end of the study period, when China began to experience the re-introduction of a small number of cases from Europe and the United States, there is an apparent up-tick in transmission. Conclusions: Although these results do not preclude future substantial increases in incidence, they suggest that after very intense social distancing (which resulted in containment), China successfully exited its lockdown to some degree. Elsewhere, movement data are being used as proxies for economic activity to assess the impact of interventions. The results presented here illustrate how the eventual decorrelation between transmission and movement is likely a key feature of successful COVID-19 exit strategies.

16.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-317320

ABSTRACT

The COVID-19 pandemic has caused severe public health consequences in the United States. The United States began a vaccination campaign at the end of 2020 targeting primarily elderly residents before extending access to younger individuals. With both COVID-19 infection fatality ratios and vaccine uptake being heterogeneous across ages, an important consideration is whether the age contribution to deaths shifted over time towards younger age groups. In this study, we use a Bayesian non-parametric spatial approach to estimate the age-specific contribution to COVID-19 attributable deaths over time. The proposed spatial approach is a low-rank Gaussian Process projected by regularised B-splines. Simulation analyses and benchmark results show that the spatial approach performs better than a standard B-splines approach and equivalently well as a standard Gaussian Process, for considerably lower runtimes. We find that COVID-19 has been especially deadly in the United States. The mortality rates among individuals aged 85+ ranged from 1\% to 5\% across the US states. Since the beginning of the vaccination campaign, the number of weekly deaths reduced in every US state with a faster decrease among individuals aged 75+ than individuals aged 0-74. Simultaneously to this reduction, the contribution of individuals age 75+ to deaths decreased, with important disparities in the timing and rapidity of this decrease across the country.

17.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-317173

ABSTRACT

The SARS-CoV-2 B.1.617.2 (Delta) variant was first identified in the state of Maharashtra in late 2020 and has spread throughout India, displacing the B.1.1.7 (Alpha) variant and other pre-existing lineages. Mathematical modelling indicates that the growth advantage is most likely explained by a combination of increased transmissibility and immune evasion. Indeed in vitro, the delta variant is less sensitive to neutralising antibodies in sera from recovered individuals, with higher replication efficiency as compared to the Alpha variant. In an analysis of vaccine breakthrough in over 100 healthcare workers across three centres in India, the Delta variant not only dominates vaccine-breakthrough infections with higher respiratory viral loads compared to non-delta infections (Ct value of 16.5 versus 19), but also generates greater transmission between HCW as compared to B.1.1.7 or B.1.617.1 (p=0.02). In vitro, the Delta variant shows 8 fold approximately reduced sensitivity to vaccine-elicited antibodies compared to wild type Wuhan-1 bearing D614G. Serum neutralising titres against the SARS-CoV-2 Delta variant were significantly lower in participants vaccinated with ChadOx-1 as compared to BNT162b2 (GMT 3372 versus 654, p<0001). These combined epidemiological and in vitro data indicate that the dominance of the Delta variant in India has been most likely driven by a combination of evasion of neutralising antibodies in previously infected individuals and increased virus infectivity. Whilst severe disease in fully vaccinated HCW was rare, breakthrough transmission clusters in hospitals associated with the Delta variant are concerning and indicate that infection control measures need continue in the post-vaccination era.

18.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-317127

ABSTRACT

Renewal processes are a popular approach used in modelling infectious disease outbreaks. In a renewal process, previous infections give rise to future infections. However, while this formulation seems sensible, its application to infectious disease can be difficult to justify from first principles. It has been shown from the seminal work of Bellman and Harris that the renewal equation arises as the expectation of an age-dependent branching process. In this paper we provide a detailed derivation of the original Bellman Harris process. We introduce generalisations, that allow for time-varying reproduction numbers and the accounting of exogenous events, such as importations. We show how inference on the renewal equation is easy to accomplish within a Bayesian hierarchical framework. Using off the shelf MCMC packages, we fit to South Korea COVID-19 case data to estimate reproduction numbers and importations. Our derivation provides the mathematical fundamentals and assumptions underpinning the use of the renewal equation for modelling outbreaks.

19.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-316844

ABSTRACT

Simulating the spread of infectious diseases in human communities is critical for predicting the trajectory of an epidemic and verifying various policies to control the devastating impacts of the outbreak. Many existing simulators are based on compartment models that divide people into a few subsets and simulate the dynamics among those subsets using hypothesized differential equations. However, these models lack the requisite granularity to study the effect of intelligent policies that influence every individual in a particular way. In this work, we introduce a simulator software capable of modeling a population structure and controlling the disease's propagation at an individualistic level. In order to estimate the confidence of the conclusions drawn from the simulator, we employ a comprehensive probabilistic approach where the entire population is constructed as a hierarchical random variable. This approach makes the inferred conclusions more robust against sampling artifacts and gives confidence bounds for decisions based on the simulation results. To showcase potential applications, the simulator parameters are set based on the formal statistics of the COVID-19 pandemic, and the outcome of a wide range of control measures is investigated. Furthermore, the simulator is used as the environment of a reinforcement learning problem to find the optimal policies to control the pandemic. The obtained experimental results indicate the simulator's adaptability and capacity in making sound predictions and a successful policy derivation example based on real-world data. As an exemplary application, our results show that the proposed policy discovery method can lead to control measures that produce significantly fewer infected individuals in the population and protect the health system against saturation.

20.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-312148

ABSTRACT

Model selection is a fundamental part of the applied Bayesian statistical methodology. Metrics such as the Akaike Information Criterion are commonly used in practice to select models but do not incorporate the uncertainty of the models' parameters and can give misleading choices. One approach that uses the full posterior distribution is to compute the ratio of two models' normalising constants, known as the Bayes factor. Often in realistic problems, this involves the integration of analytically intractable, high-dimensional distributions, and therefore requires the use of stochastic methods such as thermodynamic integration (TI). In this paper we apply a variation of the TI method, referred to as referenced TI, which computes a single model's normalising constant in an efficient way by using a judiciously chosen reference density. The advantages of the approach and theoretical considerations are set out, along with explicit pedagogical 1 and 2D examples. Benchmarking is presented with comparable methods and we find favourable convergence performance. The approach is shown to be useful in practice when applied to a real problem - to perform model selection for a semi-mechanistic hierarchical Bayesian model of COVID-19 transmission in South Korea involving the integration of a 200D density.

SELECTION OF CITATIONS
SEARCH DETAIL