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1. TorchSurv: A Lightweight Package for Deep Survival Analysis

Author

Monod, Mélodie, Krusche, Peter, Cao, Qian, Sahiner, Berkman, Petrick, Nicholas, Ohlssen, David, and Coroller, Thibaud

Subjects
Computer Science - Machine Learning
Abstract

TorchSurv is a Python package that serves as a companion tool to perform deep survival modeling within the PyTorch environment. Unlike existing libraries that impose specific parametric forms, TorchSurv enables the use of custom PyTorch-based deep survival models. With its lightweight design, minimal input requirements, full PyTorch backend, and freedom from restrictive survival model parameterizations, TorchSurv facilitates efficient deep survival model implementation and is particularly beneficial for high-dimensional and complex input data scenarios., Comment: https://opensource.nibr.com/torchsurv/

Published
2024

2. Estimating fine age structure and time trends in human contact patterns from coarse contact data: the Bayesian rate consistency model

Author

Dan, Shozen, Chen, Yu, Chen, Yining, Monod, Melodie, Jaeger, Veronika K., Bhatt, Samir, Karch, Andre, and Ratmann, Oliver

Subjects
Statistics - Applications
Abstract

Since the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), many contact surveys have been conducted to measure changes in human interactions in the face of the pandemic and non-pharmaceutical interventions. These surveys were typically conducted longitudinally, using protocols that differ from those used in the pre-pandemic era. We present a model-based statistical approach that can reconstruct contact patterns at 1-year resolution even when the age of the contacts is reported coarsely by 5 or 10-year age bands. This innovation is rooted in population-level consistency constraints in how contacts between groups must add up, which prompts us to call the approach presented here the Bayesian rate consistency model. The model incorporates computationally efficient Hilbert Space Gaussian process priors to infer the dynamics in age- and gender-structured social contacts and is designed to adjust for reporting fatigue in longitudinal surveys. We demonstrate on simulations the ability to reconstruct contact patterns by gender and 1-year age interval from coarse data with adequate accuracy and within a fully Bayesian framework to quantify uncertainty. We investigate the patterns of social contact data collected in Germany from April to June 2020 across five longitudinal survey waves. We reconstruct the fine age structure in social contacts during the early stages of the pandemic and demonstrate that social contacts rebounded in a structured, non-homogeneous manner. We also show that by July 2020, social contact intensities remained well below pre-pandemic values despite a considerable easing of non-pharmaceutical interventions. This model-based inference approach is open access, computationally tractable enabling full Bayesian uncertainty quantification, and readily applicable to contemporary survey data as long as the exact age of survey participants is reported., Comment: 39 pages, 16 figures

Published
2022
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3. Longitudinal population-level HIV epidemiologic and genomic surveillance highlights growing gender disparity of HIV transmission in Uganda

Author

Monod, Mélodie, Brizzi, Andrea, Galiwango, Ronald M., Ssekubugu, Robert, Chen, Yu, Xi, Xiaoyue, Kankaka, Edward Nelson, Ssempijja, Victor, Abeler-Dörner, Lucie, Akullian, Adam, Blenkinsop, Alexandra, Bonsall, David, Chang, Larry W., Dan, Shozen, Fraser, Christophe, Golubchik, Tanya, Gray, Ronald H., Hall, Matthew, Jackson, Jade C., Kigozi, Godfrey, Laeyendecker, Oliver, Mills, Lisa A., Quinn, Thomas C., Reynolds, Steven J., Santelli, John, Sewankambo, Nelson K., Spencer, Simon E. F., Ssekasanvu, Joseph, Thomson, Laura, Wawer, Maria J., Serwadda, David, Godfrey-Faussett, Peter, Kagaayi, Joseph, Grabowski, M. Kate, and Ratmann, Oliver

Published
2024
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4. Bayesian models and methods to estimate age-specific infectious disease transmission dynamics : integrating disease surveillance time series, mobility, and vaccination data

Author

Monod, Mélodie, Ratmann, Oliver, and Bhatt, Samir

Abstract

As of 2022, the coronavirus disease 2019 (COVID-19) pandemic is an ongoing global public health issue. To mount efficient public health control programs, it is essential to understand infection patterns involving, for example, the demographics of vulnerable populations or populations driving transmissions and how these vary over time. In this thesis, we make contributions to the use of Bayesian models and methods to capture fine-scale transmission dynamics of infectious diseases, with applications to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). From a statistical point of view, transmission dynamics may be informed by various data, and we make additional contributions by extracting and using novel data types. We aim to push the complexity of the model as much as the stratification of the data and computational power allow us to, and we perform inference on these complex models using appropriate Bayesian methods. The thesis is structured around two parts. In the first part, we build on age-specific renewal models and develop a Bayesian framework for estimating age-specific transmission dynamics in the context of time-varying social contacts using daily, age-specific human mobility, and mortality data. The model is applied to reconstruct and evaluate the resurgence of COVID-19 between March to October 2020 in the United States (US). We identified the population age groups driving SARS-CoV-2 spread across the US through October 29, 2020 and projected the changes in transmission dynamics after school reopening. This work was published in the Science journal. In the second part, we develop and characterise a computationally efficient, non-parametric smoothing prior, a low-rank Gaussian process projected by regularised B-splines, as an approximation to a standard Gaussian process. We embed this prior into a Bayesian hierarchical model to estimate the evolution of age-specific COVID-19 deaths by 1-year age bands across 50 US states from May 2020 to January 2022. We uncover longitudinal trends in the age profile of COVID-19 deaths, identified states with unusually high mortality in older age groups, explored associations with deaths in carehomes, and showed that strong resurgences in deaths during the summer of 2021 are associated with low vaccination coverage. This work was published in the Bayesian Analysis journal.

Published
2023
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5. Estimating the potential to prevent locally acquired HIV infections in a UNAIDS Fast-Track City, Amsterdam

Author

Blenkinsop, Alexandra, Monod, Mélodie, van Sighem, Ard, Pantazis, Nikos, Bezemer, Daniela, de Coul, Eline Op, van de Laar, Thijs, Fraser, Christophe, Prins, Maria, Reiss, Peter, de Bree, Godelieve, and Ratmann, Oliver

Subjects
Quantitative Biology - Populations and Evolution, Statistics - Applications
Abstract

Amsterdam and other UNAIDS Fast-Track cities aim for zero new HIV infections. Utilising molecular and clinical data of the ATHENA observational HIV cohort, our primary aims are to estimate the proportion of undiagnosed HIV infections and the proportion of locally acquired infections in Amsterdam in 2014-2018, both in MSM and heterosexuals and Dutch-born and foreign-born individuals. We located diagnosed HIV infections in Amsterdam using postcode data at time of registration to the cohort, and estimated their date of infection using clinical HIV data. We then inferred the proportion undiagnosed from the estimated times to diagnosis. To determine sources of Amsterdam infections, we used HIV sequences of people living with HIV (PLHIV) within a background of other Dutch and international sequences to phylogenetically reconstruct transmission chains. Frequent late diagnoses indicate that more recent phylogenetically observed chains are increasingly incomplete, and we use a Bayesian model to estimate the actual growth of Amsterdam transmission chains, and the proportion of locally acquired infections. We estimate that 20% [95% CrI 18-22%] of infections acquired among MSM between 2014-2018 were undiagnosed by the start of 2019, and 44% [37-50%] among heterosexuals, with variation by place of birth. The estimated proportion of MSM infections in 2014-2018 that were locally acquired was 68% [61-74%], with no substantial differences by region of birth. In heterosexuals, this was 57% [41-71%] overall, with heterogeneity by place of birth. The data indicate substantial potential to further curb local transmission, in both MSM and heterosexual Amsterdam residents. In 2014-2018 the largest proportion of local transmissions in Amsterdam are estimated to have occurred in foreign-born MSM, who would likely benefit most from intensified interventions.

Published
2022

6. Regularised B-splines projected Gaussian Process priors to estimate time-trends of age-specific COVID-19 deaths related to vaccine roll-out

Author

Monod, Mélodie, Blenkinsop, Alexandra, Brizzi, Andrea, Chen, Yu, Perello, Carlos Cardoso Correia, Jogarah, Vidoushee, Wang, Yuanrong, Flaxman, Seth, Bhatt, Samir, and Ratmann, Oliver

Subjects
Statistics - Applications
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.

Published
2021

7. Genomics and epidemiology of the P.1 SARS-CoV-2 lineage in Manaus, Brazil

Author

Faria, Nuno R, Mellan, Thomas A, Whittaker, Charles, Claro, Ingra M, Candido, Darlan da S, Mishra, Swapnil, Crispim, Myuki AE, Sales, Flavia CS, Hawryluk, Iwona, McCrone, John T, Hulswit, Ruben JG, Franco, Lucas AM, Ramundo, Mariana S, de Jesus, Jaqueline G, Andrade, Pamela S, Coletti, Thais M, Ferreira, Giulia M, Silva, Camila AM, Manuli, Erika R, Pereira, Rafael HM, Peixoto, Pedro S, Kraemer, Moritz UG, Gaburo, Nelson, Camilo, Cecilia da C, Hoeltgebaum, Henrique, Souza, William M, Rocha, Esmenia C, de Souza, Leandro M, de Pinho, Mariana C, Araujo, Leonardo JT, Malta, Frederico SV, de Lima, Aline B, Silva, Joice do P, Zauli, Danielle AG, Ferreira, Alessandro C de S, Schnekenberg, Ricardo P, Laydon, Daniel J, Walker, Patrick GT, Schlüter, Hannah M, Dos Santos, Ana LP, Vidal, Maria S, Del Caro, Valentina S, Filho, Rosinaldo MF, Dos Santos, Helem M, Aguiar, Renato S, Proença-Modena, José L, Nelson, Bruce, Hay, James A, Monod, Mélodie, Miscouridou, Xenia, Coupland, Helen, Sonabend, Raphael, Vollmer, Michaela, Gandy, Axel, Prete, Carlos A, Nascimento, Vitor H, Suchard, Marc A, Bowden, Thomas A, Pond, Sergei LK, Wu, Chieh-Hsi, Ratmann, Oliver, Ferguson, Neil M, Dye, Christopher, Loman, Nick J, Lemey, Philippe, Rambaut, Andrew, Fraiji, Nelson A, Carvalho, Maria do PSS, Pybus, Oliver G, Flaxman, Seth, Bhatt, Samir, and Sabino, Ester C

Subjects
Human Genome, Immunization, Pneumonia & Influenza, Lung, Prevention, Genetics, Vaccine Related, Biotechnology, Pneumonia, Emerging Infectious Diseases, Biodefense, Infectious Diseases, Infection, Good Health and Well Being, Angiotensin-Converting Enzyme 2, Brazil, COVID-19, Communicable Diseases, Emerging, Epidemiological Monitoring, Genome, Viral, Genomics, Humans, Models, Theoretical, Molecular Epidemiology, Mutation, Protein Binding, SARS-CoV-2, Spike Glycoprotein, Coronavirus, Viral Load, General Science & Technology
Abstract

Cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in Manaus, Brazil, resurged in late 2020 despite previously high levels of infection. Genome sequencing of viruses sampled in Manaus between November 2020 and January 2021 revealed the emergence and circulation of a novel SARS-CoV-2 variant of concern. Lineage P.1 acquired 17 mutations, including a trio in the spike protein (K417T, E484K, and N501Y) associated with increased binding to the human ACE2 (angiotensin-converting enzyme 2) receptor. Molecular clock analysis shows that P.1 emergence occurred around mid-November 2020 and was preceded by a period of faster molecular evolution. Using a two-category dynamical model that integrates genomic and mortality data, we estimate that P.1 may be 1.7- to 2.4-fold more transmissible and that previous (non-P.1) infection provides 54 to 79% of the protection against infection with P.1 that it provides against non-P.1 lineages. Enhanced global genomic surveillance of variants of concern, which may exhibit increased transmissibility and/or immune evasion, is critical to accelerate pandemic responsiveness.

Published
2021

8. Spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals

Author

Brizzi, Andrea, Whittaker, Charles, Servo, Luciana M. S., Hawryluk, Iwona, Prete, Jr, Carlos A., de Souza, William M., Aguiar, Renato S., Araujo, Leonardo J. T., Bastos, Leonardo S., Blenkinsop, Alexandra, Buss, Lewis F., Candido, Darlan, Castro, Marcia C., Costa, Silvia F., Croda, Julio, de Souza Santos, Andreza Aruska, Dye, Christopher, Flaxman, Seth, Fonseca, Paula L. C., Geddes, Victor E. V., Gutierrez, Bernardo, Lemey, Philippe, Levin, Anna S., Mellan, Thomas, Bonfim, Diego M., Miscouridou, Xenia, Mishra, Swapnil, Monod, Mélodie, Moreira, Filipe R. R., Nelson, Bruce, Pereira, Rafael H. M., Ranzani, Otavio, Schnekenberg, Ricardo P., Semenova, Elizaveta, Sonabend, Raphael, Souza, Renan P., Xi, Xiaoyue, Sabino, Ester C., Faria, Nuno R., Bhatt, Samir, and Ratmann, Oliver

Published
2022
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9. Author Correction: Spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals

Author

Brizzi, Andrea, Whittaker, Charles, Servo, Luciana M. S., Hawryluk, Iwona, Prete, Jr, Carlos A., de Souza, William M., Aguiar, Renato S., Araujo, Leonardo J. T., Bastos, Leonardo S., Blenkinsop, Alexandra, Buss, Lewis F., Candido, Darlan, Castro, Marcia C., Costa, Silvia F., Croda, Julio, de Souza Santos, Andreza Aruska, Dye, Christopher, Flaxman, Seth, Fonseca, Paula L. C., Geddes, Victor E. V., Gutierrez, Bernardo, Lemey, Philippe, Levin, Anna S., Mellan, Thomas, Bonfim, Diego M., Miscouridou, Xenia, Mishra, Swapnil, Monod, Mélodie, Moreira, Filipe R. R., Nelson, Bruce, Pereira, Rafael H. M., Ranzani, Otavio, Schnekenberg, Ricardo P., Semenova, Elizaveta, Sonabend, Raphael, Souza, Renan P., Xi, Xiaoyue, Sabino, Ester C., Faria, Nuno R., Bhatt, Samir, and Ratmann, Oliver

Published
2022
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10. State-level tracking of COVID-19 in the United States

Author

Unwin, H. Juliette T., Mishra, Swapnil, Bradley, Valerie C., Gandy, Axel, Mellan, Thomas A., Coupland, Helen, Ish-Horowicz, Jonathan, Vollmer, Michaela A. C., Whittaker, Charles, Filippi, Sarah L., Xi, Xiaoyue, Monod, Mélodie, Ratmann, Oliver, Hutchinson, Michael, Valka, Fabian, Zhu, Harrison, Hawryluk, Iwona, Milton, Philip, Ainslie, Kylie E. C., Baguelin, Marc, Boonyasiri, Adhiratha, Brazeau, Nick F., Cattarino, Lorenzo, Cucunuba, Zulma, Cuomo-Dannenburg, Gina, Dorigatti, Ilaria, Eales, Oliver D., Eaton, Jeffrey W., van Elsland, Sabine L., FitzJohn, Richard G., Gaythorpe, Katy A. M., Green, William, Hinsley, Wes, Jeffrey, Benjamin, Knock, Edward, Laydon, Daniel J., Lees, John, Nedjati-Gilani, Gemma, Nouvellet, Pierre, Okell, Lucy, Parag, Kris V., Siveroni, Igor, Thompson, Hayley A., Walker, Patrick, Walters, Caroline E., Watson, Oliver J., Whittles, Lilith K., Ghani, Azra C., Ferguson, Neil M., Riley, Steven, Donnelly, Christl A., Bhatt, Samir, and Flaxman, Seth

Published
2020
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11. Growing gender disparity in HIV infection in Africa: sources and policy implications

Author

Monod, Mélodie, primary, Brizzi, Andrea, additional, Galiwango, Ronald M, additional, Ssekubugu, Robert, additional, Chen, Yu, additional, Xi, Xiaoyue, additional, Kankaka, Edward Nelson, additional, Ssempijja, Victor, additional, Dörner, Lucie Abeler, additional, Akullian, Adam, additional, Blenkinsop, Alexandra, additional, Bonsall, David, additional, Chang, Larry W, additional, Dan, Shozen, additional, Fraser, Christophe, additional, Golubchik, Tanya, additional, Gray, Ronald H, additional, Hall, Matthew, additional, Jackson, Jade C, additional, Kigozi, Godfrey, additional, Laeyendecker, Oliver, additional, Mills, Lisa A., additional, Quinn, Thomas C., additional, Reynolds, Steven J., additional, Santelli, John, additional, Sewankambo, Nelson K., additional, Spencer, Simon EF, additional, Ssekasanvu, Joseph, additional, Thomson, Laura, additional, Wawer, Maria J, additional, Serwadda, David, additional, Godfrey-Faussett, Peter, additional, Kagaayi, Joseph, additional, Grabowski, M Kate, additional, and Ratmann, Oliver, additional

Published
2023
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12. Growing gender disparity in HIV infection in Africa: sources and policy implications

Author

Ratmann, Oliver, primary, Monod, Mélodie, additional, Brizzi, Andrea, additional, Galiwango, Ronald, additional, Ssekubugu, Robert, additional, Chen, Yu, additional, Xi, Xiaoyue, additional, Kankaka, Edward, additional, Ssempijja, Victor, additional, Abeler-Dörner, Lucie, additional, Akullian, Adam, additional, Blenkinsop, Alexandra, additional, Bonsall, David, additional, Chang, Larry, additional, Shozen, Dan, additional, Fraser, Christophe, additional, Golubchik, Tanya, additional, Gray, Ronald, additional, Hall, Matthew, additional, Jackson, Jade, additional, Kigozi, Godfrey, additional, Laeyendecker, Oliver, additional, Mills, Lisa, additional, Quinn, Thomas, additional, Reynolds, Steven, additional, Santelli, John, additional, Sewankambo, Nelson K., additional, Spencer, Simon, additional, Ssekasanvu, Joseph, additional, Thomson, Laura, additional, Wawer, Maria, additional, Serwadda, David, additional, Godfrey-Faussett, Peter, additional, Kagaayi, Kagaayi Joseph, additional, and Grabowski, M Kate M Kate, additional

Published
2023
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13. Regularised B-splines Projected Gaussian Process Priors to Estimate Time-trends in Age-specific COVID-19 Deaths

Author

Monod, Mélodie, Blenkinsop, Alexandra, Brizzi, Andrea, Chen, Yu, Cardoso Correia Perello, Carlos, Jogarah, Vidoushee, Wang, Yuanrong, Flaxman, Seth, Bhatt, Samir, Ratmann, Oliver, Monod, Mélodie, Blenkinsop, Alexandra, Brizzi, Andrea, Chen, Yu, Cardoso Correia Perello, Carlos, Jogarah, Vidoushee, Wang, Yuanrong, Flaxman, Seth, Bhatt, Samir, and Ratmann, Oliver

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 over time and age, a low-rank Gaussian Process (GP) projected by regularised B-splines. We show that this projection defines a 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 B-splines projected GP may perform better than standard B-splines and Bayesian P-splines, and equivalently well as a standard GP at considerably lower runtimes. 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 vaccination rates were significantly associated with the magnitude of resurgences in COVID-19 deaths during the summer 2021. With counterfactual analyses, we quantify the avoided COVID-19 deaths under lower vaccination rates and avoidable COVID-19 deaths under higher vaccination rates. The B-splines projected GP priors that we develop are likely an appealing addition to the arsenal of Bayesian regularising priors.

Published
2023

14. Author response: Estimating the potential to prevent locally acquired HIV infections in a UNAIDS Fast-Track City, Amsterdam

Author

Blenkinsop, Alexandra, primary, Monod, Mélodie, additional, van Sighem, Ard, additional, Pantazis, Nikos, additional, Bezemer, Daniela, additional, Op de Coul, Eline, additional, van de Laar, Thijs, additional, Fraser, Christophe, additional, Prins, Maria, additional, Reiss, Peter, additional, de Bree, Godelieve J, additional, and Ratmann, Oliver, additional

Published
2022
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15. Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe

Author

Flaxman, Seth, Mishra, Swapnil, Gandy, Axel, Unwin, H. Juliette T., Mellan, Thomas A., Coupland, Helen, Whittaker, Charles, Zhu, Harrison, Berah, Tresnia, Eaton, Jeffrey W., Monod, Mélodie, Perez-Guzman, Pablo N., Schmit, Nora, Cilloni, Lucia, Ainslie, Kylie E. C., Baguelin, Marc, Boonyasiri, Adhiratha, Boyd, Olivia, Cattarino, Lorenzo, Cooper, Laura V., Cucunubá, Zulma, Cuomo-Dannenburg, Gina, Dighe, Amy, Djaafara, Bimandra, Dorigatti, Ilaria, van Elsland, Sabine L., FitzJohn, Richard G., Gaythorpe, Katy A. M., Geidelberg, Lily, Grassly, Nicholas C., Green, William D., Hallett, Timothy, Hamlet, Arran, Hinsley, Wes, Jeffrey, Ben, Knock, Edward, Laydon, Daniel J., Nedjati-Gilani, Gemma, Nouvellet, Pierre, Parag, Kris V., Siveroni, Igor, Thompson, Hayley A., Verity, Robert, Volz, Erik, Walters, Caroline E., Wang, Haowei, Wang, Yuanrong, Watson, Oliver J., Winskill, Peter, Xi, Xiaoyue, Walker, Patrick G. T., Ghani, Azra C., Donnelly, Christl A., Riley, Steven, Vollmer, Michaela A. C., Ferguson, Neil M., Okell, Lucy C., Bhatt, Samir, Medical Research Council (MRC), and Wellcome Trust

Subjects
0301 basic medicine, medicine.medical_specialty, General Science & Technology, Population, Pooling, Psychological intervention, law.invention, 03 medical and health sciences, 0302 clinical medicine, law, Case fatality rate, Pandemic, Epidemiology, Imperial College COVID-19 Response Team, Medicine, 030212 general & internal medicine, education, education.field_of_study, Science & Technology, Multidisciplinary, business.industry, Multidisciplinary Sciences, 030104 developmental biology, Transmission (mechanics), Science & Technology - Other Topics, business, Basic reproduction number, Demography
Abstract

Following the detection of the new coronavirus1 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its spread outside of China, Europe has experienced large epidemics of coronavirus disease 2019 (COVID-19). In response, many European countries have implemented non-pharmaceutical interventions, such as the closure of schools and national lockdowns. Here we study the effect of major interventions across 11 European countries for the period from the start of the COVID-19 epidemics in February 2020 until 4 May 2020, when lockdowns started to be lifted. Our model calculates backwards from observed deaths to estimate transmission that occurred several weeks previously, allowing for the time lag between infection and death. We use partial pooling of information between countries, with both individual and shared effects on the time-varying reproduction number (Rt). Pooling allows for more information to be used, helps to overcome idiosyncrasies in the data and enables more-timely estimates. Our model relies on fixed estimates of some epidemiological parameters (such as the infection fatality rate), does not include importation or subnational variation and assumes that changes in Rt are an immediate response to interventions rather than gradual changes in behaviour. Amidst the ongoing pandemic, we rely on death data that are incomplete, show systematic biases in reporting and are subject to future consolidation. We estimate that-for all of the countries we consider here-current interventions have been sufficient to drive Rt below 1 (probability Rt

Published
2020

17. Social contact patterns and implications for infectious disease transmission – a systematic review and meta-analysis of contact surveys

Author

Mousa, Andria, primary, Winskill, Peter, additional, Watson, Oliver John, additional, Ratmann, Oliver, additional, Monod, Mélodie, additional, Ajelli, Marco, additional, Diallo, Aldiouma, additional, Dodd, Peter J, additional, Grijalva, Carlos G, additional, Kiti, Moses Chapa, additional, Krishnan, Anand, additional, Kumar, Rakesh, additional, Kumar, Supriya, additional, Kwok, Kin O, additional, Lanata, Claudio F, additional, de Waroux, Olivier Le Polain, additional, Leung, Kathy, additional, Mahikul, Wiriya, additional, Melegaro, Alessia, additional, Morrow, Carl D, additional, Mossong, Joël, additional, Neal, Eleanor FG, additional, Nokes, D James, additional, Pan-ngum, Wirichada, additional, Potter, Gail E, additional, Russell, Fiona M, additional, Saha, Siddhartha, additional, Sugimoto, Jonathan D, additional, Wei, Wan In, additional, Wood, Robin R, additional, Wu, Joseph, additional, Zhang, Juanjuan, additional, Walker, Patrick, additional, and Whittaker, Charles, additional

Published
2021
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18. Report 46: Factors driving extensive spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals

Author

Brizzi, Andrea, primary, Whittaker, Charles, additional, Servo, Luciana M. S., additional, Hawryluk, Iwona, additional, Prete, Carlos A., additional, de Souza, William M., additional, Aguiar, Renato S., additional, Araujo, Leonardo J. T., additional, Bastos, Leonardo S., additional, Blenkinsop, Alexandra, additional, Buss, Lewis F., additional, Candido, Darlan, additional, Castro, Marcia C., additional, Costa, Silvia F., additional, Croda, Julio, additional, de Souza Santos, Andreza Aruska, additional, Dye, Christopher, additional, Flaxman, Seth, additional, Fonseca, Paula L. C., additional, Geddes, Victor E. V., additional, Gutierrez, Bernardo, additional, Lemey, Philippe, additional, Levin, Anna S., additional, Mellan, Thomas, additional, Bonfim, Diego M., additional, Miscouridou, Xenia, additional, Mishra, Swapnil, additional, Monod, Mélodie, additional, Moreira, Filipe R. R., additional, Nelson, Bruce, additional, Pereira, Rafael H. M., additional, Ranzani, Otavio, additional, Schnekenberg, Ricardo P., additional, Semenova, Elizaveta, additional, Sonnabend, Raphael, additional, Souza, Renan P., additional, Xi, Xiaoyue, additional, Sabino, Ester C., additional, Faria, Nuno R., additional, Bhatt, Samir, additional, and Ratmann, Oliver, additional

Published
2021
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19. Author response: Social contact patterns and implications for infectious disease transmission – a systematic review and meta-analysis of contact surveys

Author

Mousa, Andria, primary, Winskill, Peter, additional, Watson, Oliver John, additional, Ratmann, Oliver, additional, Monod, Mélodie, additional, Ajelli, Marco, additional, Diallo, Aldiouma, additional, Dodd, Peter J, additional, Grijalva, Carlos G, additional, Kiti, Moses Chapa, additional, Krishnan, Anand, additional, Kumar, Rakesh, additional, Kumar, Supriya, additional, Kwok, Kin O, additional, Lanata, Claudio F, additional, de Waroux, Olivier Le Polain, additional, Leung, Kathy, additional, Mahikul, Wiriya, additional, Melegaro, Alessia, additional, Morrow, Carl D, additional, Mossong, Joël, additional, Neal, Eleanor FG, additional, Nokes, D James, additional, Pan-ngum, Wirichada, additional, Potter, Gail E, additional, Russell, Fiona M, additional, Saha, Siddhartha, additional, Sugimoto, Jonathan D, additional, Wei, Wan In, additional, Wood, Robin R, additional, Wu, Joseph, additional, Zhang, Juanjuan, additional, Walker, Patrick, additional, and Whittaker, Charles, additional

Published
2021
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20. Age groups that sustain resurging COVID-19 epidemics in the United States

Author

Monod, Mélodie, Blenkinsop, Alexandra, Xi, Xiaoyue, Hebert, Daniel, Bershan, Sivan, Tietze, Simon, Baguelin, Marc, Bradley, Valerie C, Chen, Yu, Coupland, Helen, Filippi, Sarah, Ish-Horowicz, Jonathan, McManus, Martin, Mellan, Thomas, Gandy, Axel, Hutchinson, Michael, Unwin, H Juliette T, van Elsland, Sabine L, Vollmer, Michaela AC, Weber, Sebastian, Zhu, Harrison, Bezancon, Anne, Ferguson, Neil M, Mishra, Swapnil, Flaxman, Seth, Bhatt, Samir, Ratmann, Oliver, and Imperial College COVID-19 Response Team

Abstract

After initial declines, in mid-2020 a resurgence in transmission of novel coronavirus disease (COVID-19) occurred in the United States and Europe. As efforts to control COVID-19 disease are reintensified, understanding the age demographics driving transmission and how these affect the loosening of interventions is crucial. We analyze aggregated, age-specific mobility trends from more than 10 million individuals in the United States and link these mechanistically to age-specific COVID-19 mortality data. We estimate that as of October 2020, individuals aged 20 to 49 are the only age groups sustaining resurgent SARS-CoV-2 transmission with reproduction numbers well above one and that at least 65 of 100 COVID-19 infections originate from individuals aged 20 to 49 in the United States. Targeting interventions-including transmission-blocking vaccines-to adults aged 20 to 49 is an important consideration in halting resurgent epidemics and preventing COVID-19-attributable deaths.

Published
2021

21. Report 32: Age groups that sustain resurging COVID-19 epidemics in the United States

Author

Monod, Mélodie, primary, Blenkinsop, Alexandra, additional, Xi, Xiaoyue, additional, Hebert, Daniel, additional, Bershan, Sivan, additional, Tietze, Simon, additional, Bradley, Valerie C, additional, Chen, Yu, additional, Coupland, Helen, additional, Filippi, Sarah, additional, Ish-Horowicz, Jonathan, additional, McManus, Martin, additional, Mellan, Thomas, additional, Gandy, Axel, additional, Hutchinson, Michael, additional, T Unwin, H Juliette, additional, C Vollmer, Michaela A, additional, Weber, Sebastian, additional, Zhu, Harrison, additional, Bezancon, Anne, additional, Ferguson, Neil M, additional, Mishra, Swapnil, additional, Flaxman, Seth, additional, Bhatt, Samir, additional, and Ratmann, Oliver, additional

Published
2020
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22. State-level tracking of COVID-19 in the United States

Author

Unwin, H. Juliette T., primary, Mishra, Swapnil, additional, Bradley, Valerie C., additional, Gandy, Axel, additional, Mellan, Thomas A., additional, Coupland, Helen, additional, Ish-Horowicz, Jonathan, additional, Vollmer, Michaela A. C., additional, Whittaker, Charles, additional, Filippi, Sarah L., additional, Xi, Xiaoyue, additional, Monod, Mélodie, additional, Ratmann, Oliver, additional, Hutchinson, Michael, additional, Valka, Fabian, additional, Zhu, Harrison, additional, Hawryluk, Iwona, additional, Milton, Philip, additional, Ainslie, Kylie E. C., additional, Baguelin, Marc, additional, Boonyasiri, Adhiratha, additional, Brazeau, Nick F., additional, Cattarino, Lorenzo, additional, Cucunuba, Zulma, additional, Cuomo-Dannenburg, Gina, additional, Dorigatti, Ilaria, additional, Eales, Oliver D., additional, Eaton, Jeffrey W., additional, van Elsland, Sabine L., additional, FitzJohn, Richard G., additional, Gaythorpe, Katy A. M., additional, Green, William, additional, Hinsley, Wes, additional, Jeffrey, Benjamin, additional, Knock, Edward, additional, Laydon, Daniel J., additional, Lees, John, additional, Nedjati-Gilani, Gemma, additional, Nouvellet, Pierre, additional, Okell, Lucy, additional, Parag, Kris V., additional, Siveroni, Igor, additional, Thompson, Hayley A., additional, Walker, Patrick, additional, Walters, Caroline E., additional, Watson, Oliver J., additional, Whittles, Lilith K., additional, Ghani, Azra C., additional, Ferguson, Neil M., additional, Riley, Steven, additional, Donnelly, Christl A., additional, Bhatt, Samir, additional, and Flaxman, Seth, additional

Published
2020
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23. Subnational analysis of the COVID-19 epidemic in Brazil

Author

Mellan, Thomas A, primary, Hoeltgebaum, Henrique H, additional, Mishra, Swapnil, additional, Whittaker, Charlie, additional, Schnekenberg, Ricardo P, additional, Gandy, Axel, additional, Unwin, H Juliette T, additional, Vollmer, Michaela A C, additional, Coupland, Helen, additional, Hawryluk, Iwona, additional, Faria, Nuno Rodrigues, additional, Vesga, Juan, additional, Zhu, Harrison, additional, Hutchinson, Michael, additional, Ratmann, Oliver, additional, Monod, Mélodie, additional, Ainslie, Kylie E C, additional, Baguelin, Marc, additional, Bhatia, Sangeeta, additional, Boonyasiri, Adhiratha, additional, Brazeau, Nicholas, additional, Charles, Giovanni, additional, Cucunuba, Zulma, additional, Cuomo-Dannenburg, Gina, additional, Dighe, Amy, additional, Eaton, Jeff, additional, Elsland, Sabine L van, additional, Gaythorpe, Katy A M, additional, Green, Will, additional, Knock, Edward, additional, Laydon, Daniel, additional, Lees, John A, additional, Mousa, Andria, additional, Nedjati-Gilani, Gemma, additional, Nouvellet, Pierre, additional, Parag, Kris V, additional, Thompson, Hayley A, additional, Verity, Robert, additional, Walters, Caroline E, additional, Wang, Haowei, additional, Wang, Yuanrong, additional, Watson, Oliver J, additional, Whittles, Lilith, additional, Xi, Xiaoyue, additional, Dorigatti, Ilaria, additional, Walker, Patrick, additional, Ghani, Azra C, additional, Riley, Steven, additional, Ferguson, Neil M, additional, Donnelly, Christl A, additional, Flaxman, Seth, additional, and Bhatt, Samir, additional

Published
2020
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24. Social contact patterns and implications for infectious disease transmission -- a systematic review and meta- analysis of contact surveys.

Author

Mousa, Andria, Winskill, Peter, Watson, Oliver John, Ratmann, Oliver, Monod, Mélodie, Ajelli, Marco, Diallo, Aldiouma, Dodd, Peter J., Grijalva, Carlos G., Kiti, Moses Chapa, Krishnan, Anand, Kumar, Rakesh, Kumar, Supriya, Kwok, Kin O., Lanata, Claudio F., de Waroux, Olivier Le Polain, Leung, Kathy, Mahikul, Wiriya, Melegaro, Alessia, and Morrow, Carl D.

Published
2022
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25. Age and gender profiles of HIV infection burden and viraemia: novel metrics for HIV epidemic control in African populations with high antiretroviral therapy coverage.

Author

Brizzi A, Kagaayi J, Ssekubugu R, Abeler-Dörner L, Blenkinsop A, Bonsall D, Chang LW, Fraser C, Galiwango RM, Kigozi G, Kyle I, Monod M, Nakigozi G, Nalugoda F, Rosen JG, Laeyendecker O, Quinn TC, Grabowski MK, Reynolds SJ, and Ratmann O

Abstract

Introduction: To prioritize and tailor interventions for ending AIDS by 2030 in Africa, it is important to characterize the population groups in which HIV viraemia is concentrating., Methods: We analysed HIV testing and viral load data collected between 2013-2019 from the open, population-based Rakai Community Cohort Study (RCCS) in Uganda, to estimate HIV seroprevalence and population viral suppression over time by gender, one-year age bands and residence in inland and fishing communities. All estimates were standardized to the underlying source population using census data. We then assessed 95-95-95 targets in their ability to identify the populations in which viraemia concentrates., Results: Following the implementation of Universal Test and Treat, the proportion of individuals with viraemia decreased from 4.9% (4.6%-5.3%) in 2013 to 1.9% (1.7%-2.2%) in 2019 in inland communities and from 19.1% (18.0%-20.4%) in 2013 to 4.7% (4.0%-5.5%) in 2019 in fishing communities. Viraemia did not concentrate in the age and gender groups furthest from achieving 95-95-95 targets. Instead, in both inland and fishing communities, women aged 25-29 and men aged 30-34 were the 5-year age groups that contributed most to population-level viraemia in 2019, despite these groups being close to or had already achieved 95-95-95 targets., Conclusions: The 95-95-95 targets provide a useful benchmark for monitoring progress towards HIV epidemic control, but do not contextualize underlying population structures and so may direct interventions towards groups that represent a marginal fraction of the population with viraemia., Competing Interests: MKG, LCW report grants from the National Institutes of Health during the conduct of this study. ABr, MM report an EPSRC PhD studentship during the conduct of this study. OR acknowledges grants from the Bill and Melinda Gates Foundation (OPP1175094 to C.Fraser., OPP1084362 to D. Pillay), the Engineering and Physical Sciences Research Council (EP/X038440/1), and the Moderna Charitable Foundation during the conduct of this study. This arrangement has been reviewed and approved by the Johns Hopkins University in accordance with its conflict-of-interest policies.

Published
2024
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26. Longitudinal population-level HIV epidemiologic and genomic surveillance highlights growing gender disparity of HIV transmission in Uganda.

Author

Monod M, Brizzi A, Galiwango RM, Ssekubugu R, Chen Y, Xi X, Kankaka EN, Ssempijja V, Dörner LA, Akullian A, Blenkinsop A, Bonsall D, Chang LW, Dan S, Fraser C, Golubchik T, Gray RH, Hall M, Jackson JC, Kigozi G, Laeyendecker O, Mills LA, Quinn TC, Reynolds SJ, Santelli J, Sewankambo NK, Spencer SE, Ssekasanvu J, Thomson L, Wawer MJ, Serwadda D, Godfrey-Faussett P, Kagaayi J, Grabowski MK, and Ratmann O

Abstract

HIV incidence in eastern and southern Africa has historically been concentrated among girls and women aged 15-24 years. As new cases decline with HIV interventions, population-level infection dynamics may shift by age and gender. Here, we integrated population-based surveillance of 38,749 participants in the Rakai Community Cohort Study and longitudinal deep sequence viral phylogenetics to assess how HIV incidence and population groups driving transmission have changed from 2003 to 2018 in Uganda. We observed 1,117 individuals in the incidence cohort and 1,978 individuals in the transmission cohort. HIV viral suppression increased more rapidly in women than men, however incidence declined more slowly in women than men. We found that age-specific transmission flows shifted, while HIV transmission to girls and women (aged 15-24 years) from older men declined by about one third, transmission to women (aged 25-34 years) from men that were 0-6 years older increased by half in 2003 to 2018. Based on changes in transmission flows, we estimated that closing the gender gap in viral suppression could have reduced HIV incidence in women by half in 2018. This study suggests that HIV programs to increase HIV suppression in men are critical to reduce incidence in women, close gender gaps in infection burden and improve men's health in Africa.

Published
2023
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27. Estimating the potential to prevent locally acquired HIV infections in a UNAIDS Fast-Track City, Amsterdam.

Author

Blenkinsop A, Monod M, van Sighem A, Pantazis N, Bezemer D, Op de Coul E, van de Laar T, Fraser C, Prins M, Reiss P, de Bree GJ, and Ratmann O

Subjects
Bayes Theorem, Cities epidemiology, Homosexuality, Male, Humans, Male, Phylogeny, Acquired Immunodeficiency Syndrome epidemiology, HIV Infections diagnosis, HIV Infections epidemiology, HIV Infections prevention & control
Abstract

Background: More than 300 cities including the city of Amsterdam in the Netherlands have joined the UNAIDS Fast-Track Cities initiative, committing to accelerate their HIV response and end the AIDS epidemic in cities by 2030. To support this commitment, we aimed to estimate the number and proportion of Amsterdam HIV infections that originated within the city, from Amsterdam residents. We also aimed to estimate the proportion of recent HIV infections during the 5-year period 2014-2018 in Amsterdam that remained undiagnosed., Methods: We located diagnosed HIV infections in Amsterdam using postcode data (PC4) at time of registration in the ATHENA observational HIV cohort, and used HIV sequence data to reconstruct phylogeographically distinct, partially observed Amsterdam transmission chains. Individual-level infection times were estimated from biomarker data, and used to date the phylogenetically observed transmission chains as well as to estimate undiagnosed proportions among recent infections. A Bayesian Negative Binomial branching process model was used to estimate the number, size, and growth of the unobserved Amsterdam transmission chains from the partially observed phylogenetic data., Results: Between 1 January 2014 and 1 May 2019, there were 846 HIV diagnoses in Amsterdam residents, of whom 516 (61%) were estimated to have been infected in 2014-2018. The rate of new Amsterdam diagnoses since 2014 (104 per 100,000) remained higher than the national rates excluding Amsterdam (24 per 100,000), and in this sense Amsterdam remained a HIV hotspot in the Netherlands. An estimated 14% [12-16%] of infections in Amsterdan MSM in 2014-2018 remained undiagnosed by 1 May 2019, and 41% [35-48%] in Amsterdam heterosexuals, with variation by region of birth. An estimated 67% [60-74%] of Amsterdam MSM infections in 2014-2018 had an Amsterdam resident as source, and 56% [41-70%] in Amsterdam heterosexuals, with heterogeneity by region of birth. Of the locally acquired infections, an estimated 43% [37-49%] were in foreign-born MSM, 41% [35-47%] in Dutch-born MSM, 10% [6-18%] in foreign-born heterosexuals, and 5% [2-9%] in Dutch-born heterosexuals. We estimate the majority of Amsterdam MSM infections in 2014-2018 originated in transmission chains that pre-existed by 2014., Conclusions: This combined phylogenetic, epidemiologic, and modelling analysis in the UNAIDS Fast-Track City Amsterdam indicates that there remains considerable potential to prevent HIV infections among Amsterdam residents through city-level interventions. The burden of locally acquired infection remains concentrated in MSM, and both Dutch-born and foreign-born MSM would likely benefit most from intensified city-level interventions., Funding: This study received funding as part of the H-TEAM initiative from Aidsfonds (project number P29701). The H-TEAM initiative is being supported by Aidsfonds (grant number: 2013169, P29701, P60803), Stichting Amsterdam Dinner Foundation, Bristol-Myers Squibb International Corp. (study number: AI424-541), Gilead Sciences Europe Ltd (grant number: PA-HIV-PREP-16-0024), Gilead Sciences (protocol numbers: CO-NL-276-4222, CO-US-276-1712, CO-NL-985-6195), and M.A.C AIDS Fund., Competing Interests: AB, MM, DB, EO, Tv, CF, OR No competing interests declared, Av Funding for managing the ATHENA cohort is supported by a grant from the Dutch Ministry of Health, Welfare and Sport through the Centre for Infectious Disease Control of the National Institute for Public Health and the Environment. Received grants unrelated to this study from European Centre for Disease Prevention and Control paid to author's institution, NP Received grants unrelated to this study from ECDC and Gilead Sciences Hellas, paid to author's institution. Received honoraria for presentations unrelated to this study from Gilead Sciences Hellas, MP Received unrestricted research grants and speaker/ advisory fees from Gilead Sciences, Abbvie and MSD; all of which were paid to author's institute and were unrelated to this study, PR Has received grants unrelated to this study from Gilead Sciences, ViiV Healthcare and Merck, paid to author's institution. Received Honoraria for lecture from Merck paid to institution. Received Honoraria from Gilead Sciences, ViiV Healthcare and Merck, paid to institution, Gd Received honoraria to her Institution for scientific advisory board participations for Gilead Sciences and speaker fees from Gilead Sciences (2019), Takeda (2018-2022) and ExeVir (2020-current), (© 2022, Blenkinsop et al.)

Published
2022
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28. Report 46: Factors driving extensive spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals.

Author

Brizzi A, Whittaker C, Servo LMS, Hawryluk I, Prete CA Jr, de Souza WM, Aguiar RS, Araujo LJT, Bastos LS, Blenkinsop A, Buss LF, Candido D, Castro MC, Costa SF, Croda J, de Souza Santos AA, Dye C, Flaxman S, Fonseca PLC, Geddes VEV, Gutierrez B, Lemey P, Levin AS, Mellan T, Bonfim DM, Miscouridou X, Mishra S, Monod M, Moreira FRR, Nelson B, Pereira RHM, Ranzani O, Schnekenberg RP, Semenova E, Sonnabend R, Souza RP, Xi X, Sabino EC, Faria NR, Bhatt S, and Ratmann O

Abstract

The SARS-CoV-2 Gamma variant spread rapidly across Brazil, causing substantial infection and death waves. We use individual-level patient records following hospitalisation with suspected or confirmed COVID-19 to document the extensive shocks in hospital fatality rates that followed Gamma's spread across 14 state capitals, and in which more than half of hospitalised patients died over sustained time periods. We show that extensive fluctuations in COVID-19 in-hospital fatality rates also existed prior to Gamma's detection, and were largely transient after Gamma's detection, subsiding with hospital demand. Using a Bayesian fatality rate model, we find that the geographic and temporal fluctuations in Brazil's COVID-19 in-hospital fatality rates are primarily associated with geographic inequities and shortages in healthcare capacity. We project that approximately half of Brazil's COVID-19 deaths in hospitals could have been avoided without pre-pandemic geographic inequities and without pandemic healthcare pressure. Our results suggest that investments in healthcare resources, healthcare optimization, and pandemic preparedness are critical to minimize population wide mortality and morbidity caused by highly transmissible and deadly pathogens such as SARS-CoV-2, especially in low- and middle-income countries., Note: The following manuscript has appeared as 'Report 46 - Factors driving extensive spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals' at https://spiral.imperial.ac.uk:8443/handle/10044/1/91875 ., One Sentence Summary: COVID-19 in-hospital fatality rates fluctuate dramatically in Brazil, and these fluctuations are primarily associated with geographic inequities and shortages in healthcare capacity.

Published
2021
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29. Social Contact Patterns and Implications for Infectious Disease Transmission: A Systematic Review and Meta-Analysis of Contact Surveys.

Author

Mousa A, Winskill P, Watson OJ, Ratmann O, Monod M, Ajelli M, Diallo A, Dodd PJ, Grijalva CG, Kiti MC, Krishnan A, Kumar R, Kumar S, Kwok KO, Lanata CF, Le Polain de Waroux O, Leung K, Mahikul W, Melegaro A, Morrow CD, Mossong J, Neal EF, Nokes DJ, Pan-Ngum W, Potter GE, Russell FM, Saha S, Sugimoto JD, Wei WI, Wood RR, Wu JT, Zhang J, Walker PG, and Whittaker C

Abstract

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, but low-income settings were 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., Funding: This work is primarily being funded by joint Centre funding from the UK Medical Research Council and DFID (MR/R015600/1).

Published
2021
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30. Age groups that sustain resurging COVID-19 epidemics in the United States.

Author

Monod M, Blenkinsop A, Xi X, Hebert D, Bershan S, Tietze S, Baguelin M, Bradley VC, Chen Y, Coupland H, Filippi S, Ish-Horowicz J, McManus M, Mellan T, Gandy A, Hutchinson M, Unwin HJT, van Elsland SL, Vollmer MAC, Weber S, Zhu H, Bezancon A, Ferguson NM, Mishra S, Flaxman S, Bhatt S, and Ratmann O

Subjects
Adolescent, Adult, Age Factors, Basic Reproduction Number, COVID-19 mortality, COVID-19 prevention & control, COVID-19 Vaccines, Cell Phone, Child, Child, Preschool, Communicable Disease Control, Humans, Infant, Middle Aged, Models, Theoretical, Pandemics prevention & control, Schools, United States epidemiology, Young Adult, COVID-19 epidemiology, COVID-19 transmission, Epidemics prevention & control
Abstract

After initial declines, in mid-2020 a resurgence in transmission of novel coronavirus disease (COVID-19) occurred in the United States and Europe. As efforts to control COVID-19 disease are reintensified, understanding the age demographics driving transmission and how these affect the loosening of interventions is crucial. We analyze aggregated, age-specific mobility trends from more than 10 million individuals in the United States and link these mechanistically to age-specific COVID-19 mortality data. We estimate that as of October 2020, individuals aged 20 to 49 are the only age groups sustaining resurgent SARS-CoV-2 transmission with reproduction numbers well above one and that at least 65 of 100 COVID-19 infections originate from individuals aged 20 to 49 in the United States. Targeting interventions-including transmission-blocking vaccines-to adults aged 20 to 49 is an important consideration in halting resurgent epidemics and preventing COVID-19-attributable deaths., (Copyright © 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

Published
2021
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