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1. 25 Models in the COVID-19 Pandemic

Author

Imai, Natsuko, Baguelin, Marc, Ferguson, Neil M., Sorenson, Robert A., editor, Higgs, Elizabeth S., Editor-in-Chief, Fallah, Mosoka P., Section Editor, Lurie, Nicole, Section Editor, McNay, Laura A., Section Editor, and Smith, Peter G., Section Editor

Published
2024
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2. Branched flows of flexural elastic waves in non-uniform cylindrical shells

Author

Jose, Kevin, Ferguson, Neil, and Bhaskar, Atul

Subjects
Physics - Classical Physics
Abstract

Propagation of elastic waves along the axis of cylindrical shells is of great current interest due to their ubiquitous presence and technological importance. Geometric imperfections and spatial variations of properties are inevitable in such structures. Here we report the existence of branched flows of flexural waves in such waveguides. The location of high amplitude motion, away from the launch location, scales as a power law with respect to the variance and linearly with respect to the correlation length of the spatial variation in the bending stiffness. These scaling laws are then theoretically derived from the ray equations. Numerical integration of the ray equations also exhibit this behaviour-consistent with finite element numerical simulations as well as the theoretically derived scaling. There appears to be a universality for the exponents in the scaling with respect to similar observations in the past for other types of waves, as well as flexural and hence dispersive waves in elastic plates., Comment: 9 pages, 10 figures, supplementary information attached as separate file

Published
2022

3. The interaction of transmission intensity, mortality, and the economy: a retrospective analysis of the COVID-19 pandemic

Author

Morgenstern, Christian, Laydon, Daniel J., Whittaker, Charles, Mishra, Swapnil, Haw, David, Bhatt, Samir, and Ferguson, Neil M.

Subjects
Statistics - Applications, Computer Science - Machine Learning, Quantitative Biology - Populations and Evolution
Abstract

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 Mixed Effects model with auto-regressive terms. 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 and 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.

Published
2022
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4. Retrospective evaluation of real-time estimates of global COVID-19 transmission trends and mortality forecasts.

Author

Bhatia, Sangeeta, Parag, Kris, Wardle, Jack, Nash, Rebecca, Imai, Natsuko, Elsland, Sabine, Lassmann, Britta, Brownstein, John, Herringer, Mark, Sewalk, Kara, Loeb, Sarah, Ramatowski, John, Cuomo-Dannenburg, Gina, Jauneikaite, Elita, Unwin, H, Riley, Steven, Ferguson, Neil, Donnelly, Christl, Cori, Anne, Nouvellet, Pierre, and Desai, Angel

Subjects
Humans, COVID-19, Retrospective Studies, SARS-CoV-2, Epidemics, Time, Forecasting
Abstract

Since 8th March 2020 up to the time of writing, we have been producing near real-time weekly estimates of SARS-CoV-2 transmissibility and forecasts of deaths due to COVID-19 for all countries with evidence of sustained transmission, shared online. We also developed a novel heuristic to combine weekly estimates of transmissibility to produce forecasts over a 4-week horizon. Here we present a retrospective evaluation of the forecasts produced between 8th March to 29th November 2020 for 81 countries. We evaluated the robustness of the forecasts produced in real-time using relative error, coverage probability, and comparisons with null models. During the 39-week period covered by this study, both the short- and medium-term forecasts captured well the epidemic trajectory across different waves of COVID-19 infections with small relative errors over the forecast horizon. The model was well calibrated with 56.3% and 45.6% of the observations lying in the 50% Credible Interval in 1-week and 4-week ahead forecasts respectively. The retrospective evaluation of our models shows that simple transmission models calibrated using routine disease surveillance data can reliably capture the epidemic trajectory in multiple countries. The medium-term forecasts can be used in conjunction with the short-term forecasts of COVID-19 mortality as a useful planning tool as countries continue to relax public health measures.

Published
2023

10. Estimating the health effects of COVID-19-related immunisation disruptions in 112 countries during 2020–30: a modelling study

Author

Hartner, Anna-Maria, Li, Xiang, Echeverria-Londono, Susy, Roth, Jeremy, Abbas, Kaja, Auzenbergs, Megan, de Villiers, Margaret J, Ferrari, Matthew J, Fraser, Keith, Fu, Han, Hallett, Timothy, Hinsley, Wes, Jit, Mark, Karachaliou, Andromachi, Moore, Sean M, Nayagam, Shevanthi, Papadopoulos, Timos, Perkins, T Alex, Portnoy, Allison, Minh, Quan Tran, Vynnycky, Emilia, Winter, Amy K, Burrows, Holly, Chen, Cynthia, Clapham, Hannah E, Deshpande, Aniruddha, Hauryski, Sarah, Huber, John, Jean, Kevin, Kim, Chaelin, Kim, Jong-Hoon, Koh, Jemima, Lopman, Benjamin A, Pitzer, Virginia E, Tam, Yvonne, Lambach, Philipp, Sim, So Yoon, Woodruff, Kim, Ferguson, Neil M, Trotter, Caroline L, and Gaythorpe, Katy A M

Published
2024
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12. Semi-Mechanistic Bayesian Modeling of COVID-19 with Renewal Processes

Author

Bhatt, Samir, Ferguson, Neil, Flaxman, Seth, Gandy, Axel, Mishra, Swapnil, and Scott, James A.

Subjects
Statistics - Applications, Statistics - Methodology
Abstract

We propose a general Bayesian approach to modeling epidemics such as COVID-19. The approach grew out of specific analyses conducted during the pandemic, in particular an analysis concerning the effects of non-pharmaceutical interventions (NPIs) in reducing COVID-19 transmission in 11 European countries. The model parameterizes the time varying reproduction number $R_t$ through a regression framework in which covariates can e.g be governmental interventions or changes in mobility patterns. This allows a joint fit across regions and partial pooling to share strength. This innovation was critical to our timely estimates of the impact of lockdown and other NPIs in the European epidemics, whose validity was borne out by the subsequent course of the epidemic. Our framework provides a fully generative model for latent infections and observations deriving from them, including deaths, cases, hospitalizations, ICU admissions and seroprevalence surveys. One issue surrounding our model's use during the COVID-19 pandemic is the confounded nature of NPIs and mobility. We use our framework to explore this issue. We have open sourced an R package epidemia implementing our approach in Stan. Versions of the model are used by New York State, Tennessee and Scotland to estimate the current situation and make policy decisions.

Published
2020

13. Simulation and Experimental Estimation of the Free Wavenumbers for Helically Grooved Tubes

Author

Bavaresco, Milena Watanabe, Ferguson, Neil, Ibsen, Claus Hessler, Bhaskar, Atul, Ceccarelli, Marco, Series Editor, Agrawal, Sunil K., Advisory Editor, Corves, Burkhard, Advisory Editor, Glazunov, Victor, Advisory Editor, Hernández, Alfonso, Advisory Editor, Huang, Tian, Advisory Editor, Jauregui Correa, Juan Carlos, Advisory Editor, Takeda, Yukio, Advisory Editor, Dimitrovová, Zuzana, editor, Biswas, Paritosh, editor, Gonçalves, Rodrigo, editor, and Silva, Tiago, editor

Published
2023
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15. Estimating the number of infections and the impact of non-pharmaceutical interventions on COVID-19 in European countries: technical description update

Author

Flaxman, Seth, Mishra, Swapnil, Gandy, Axel, Unwin, H Juliette T, Coupland, Helen, Mellan, Thomas A, Zhu, Harrison, Berah, Tresnia, Eaton, Jeffrey W, Guzman, Pablo N P, Schmit, Nora, Callizo, Lucia, Team, Imperial College COVID-19 Response, Whittaker, Charles, Winskill, Peter, Xi, Xiaoyue, Ghani, Azra, Donnelly, Christl A., Riley, Steven, Okell, Lucy C, Vollmer, Michaela A C, Ferguson, Neil M., and Bhatt, Samir

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

Following the emergence of a novel coronavirus (SARS-CoV-2) and its spread outside of China, Europe has experienced large epidemics. In response, many European countries have implemented unprecedented non-pharmaceutical interventions including case isolation, the closure of schools and universities, banning of mass gatherings and/or public events, and most recently, wide-scale social distancing including local and national lockdowns. In this technical update, we extend a semi-mechanistic Bayesian hierarchical model that infers the impact of these interventions and estimates the number of infections over time. Our methods assume that changes in the reproductive number - a measure of transmission - are an immediate response to these interventions being implemented rather than broader gradual changes in behaviour. Our model estimates these changes by calculating backwards from temporal data on observed to estimate the number of infections and rate of transmission that occurred several weeks prior, allowing for a probabilistic time lag between infection and death. In this update we extend our original model [Flaxman, Mishra, Gandy et al 2020, Report #13, Imperial College London] to include (a) population saturation effects, (b) prior uncertainty on the infection fatality ratio, (c) a more balanced prior on intervention effects and (d) partial pooling of the lockdown intervention covariate. We also (e) included another 3 countries (Greece, the Netherlands and Portugal). The model code is available at https://github.com/ImperialCollegeLondon/covid19model/ We are now reporting the results of our updated model online at https://mrc-ide.github.io/covid19estimates/ We estimated parameters jointly for all M=14 countries in a single hierarchical model. Inference is performed in the probabilistic programming language Stan using an adaptive Hamiltonian Monte Carlo (HMC) sampler.

Published
2020

16. 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

21. Risk factors and vectors for SARS-CoV-2 household transmission: a prospective, longitudinal cohort study

Author

Cutajar, Jessica, Quinn, Valerie, Hammett, Sarah, McDermott, Eimèar, Luca, Constanta, Timcang, Kristel, Samuel, Jada, Bremang, Samuel, Evetts, Samuel, Wang, Lulu, Nevin, Sean, Davies, Megan, Tejpal, Chitra, Essoussi, Mohammed, Ketkar, Anjeli V, Miserocchi, Giulia, Catchpole, Harriet, Badhan, Anjna, Dustan, Simon, Day Weber, Isaac J, Marchesin, Federica, Whitfield, Michael G, Poh, John, Kondratiuk, Alexandra, Derqui, Nieves, Koycheva, Aleksandra, Zhou, Jie, Pillay, Timesh D, Crone, Michael A, Hakki, Seran, Fenn, Joe, Kundu, Rhia, Varro, Robert, Conibear, Emily, Madon, Kieran J, Barnett, Jack L, Houston, Hamish, Singanayagam, Anika, Narean, Janakan S, Tolosa-Wright, Mica R, Mosscrop, Lucy, Rosadas, Carolina, Watber, Patricia, Anderson, Charlotte, Parker, Eleanor, Freemont, Paul S, Ferguson, Neil M, Zambon, Maria, McClure, Myra O, Tedder, Richard, Barclay, Wendy S, Dunning, Jake, Taylor, Graham P, and Lalvani, Ajit

Published
2023
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27. Quantifying the effect of delaying the second COVID-19 vaccine dose in England: a mathematical modelling study

Author

Imai, Natsuko, Rawson, Thomas, Knock, Edward S, Sonabend, Raphael, Elmaci, Yasin, Perez-Guzman, Pablo N, Whittles, Lilith K, Kanapram, Divya Thekke, Gaythorpe, Katy A M, Hinsley, Wes, Djaafara, Bimandra A, Wang, Haowei, Fraser, Keith, FitzJohn, Richard G, Hogan, Alexandra B, Doohan, Patrick, Ghani, Azra C, Ferguson, Neil M, Baguelin, Marc, and Cori, Anne

Published
2023
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31. Long-term vaccination strategies to mitigate the impact of SARS-CoV-2 transmission: A modelling study

Author

Hogan, Alexandra B., Wu, Sean L., Toor, Jaspreet, Olivera Mesa, Daniela, Doohan, Patrick, Watson, Oliver J., Winskill, Peter, Charles, Giovanni, Barnsley, Gregory, Riley, Eleanor M., Khoury, David S., Ferguson, Neil M., and Ghani, Azra C.

Subjects
Vaccination -- Health aspects, Medical research -- Health aspects, Medicine, Experimental -- Health aspects, Disease transmission -- Health aspects, Severe acute respiratory syndrome -- Health aspects, Coronaviruses -- Health aspects, Biological sciences
Abstract

Background Vaccines have reduced severe disease and death from Coronavirus Disease 2019 (COVID-19). However, with evidence of waning efficacy coupled with continued evolution of the virus, health programmes need to evaluate the requirement for regular booster doses, considering their impact and cost-effectiveness in the face of ongoing transmission and substantial infection-induced immunity. Methods and findings We developed a combined immunological-transmission model parameterised with data on transmissibility, severity, and vaccine effectiveness. We simulated Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) transmission and vaccine rollout in characteristic global settings with different population age-structures, contact patterns, health system capacities, prior transmission, and vaccine uptake. We quantified the impact of future vaccine booster dose strategies with both ancestral and variant-adapted vaccine products, while considering the potential future emergence of new variants with modified transmission, immune escape, and severity properties. We found that regular boosting of the oldest age group (75+) is an efficient strategy, although large numbers of hospitalisations and deaths could be averted by extending vaccination to younger age groups. In countries with low vaccine coverage and high infection-derived immunity, boosting older at-risk groups was more effective than continuing primary vaccination into younger ages in our model. Our study is limited by uncertainty in key parameters, including the long-term durability of vaccine and infection-induced immunity as well as uncertainty in the future evolution of the virus. Conclusions Our modelling suggests that regular boosting of the high-risk population remains an important tool to reduce morbidity and mortality from current and future SARS-CoV-2 variants. Our results suggest that focusing vaccination in the highest-risk cohorts will be the most efficient (and hence cost-effective) strategy to reduce morbidity and mortality., Author(s): Alexandra B. Hogan 1,2,*, Sean L. Wu 3, Jaspreet Toor 2, Daniela Olivera Mesa 2, Patrick Doohan 2, Oliver J. Watson 2,4, Peter Winskill 2, Giovanni Charles 2, Gregory [...]

Published
2023
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36. Onset and window of SARS-CoV-2 infectiousness and temporal correlation with symptom onset: a prospective, longitudinal, community cohort study

Author

Badhan, Anjna, Varro, Robert, Luca, Constanta, Quinn, Valerie, Cutajar, Jessica, Nichols, Niamh, Russell, Jessica, Grey, Holly, Ketkar, Anjeli, Miserocchi, Giulia, Tejpal, Chitra, Catchpole, Harriet, Nixon, Koji, Di Biase, Berenice, Hopewell, Tamara, Narean, Janakan Sam, Samuel, Jada, Timcang, Kristel, McDermott, Eimear, Bremang, Samuel, Hammett, Sarah, Evetts, Samuel, Kondratiuk, Alexandra, Hakki, Seran, Zhou, Jie, Jonnerby, Jakob, Singanayagam, Anika, Barnett, Jack L, Madon, Kieran J, Koycheva, Aleksandra, Kelly, Christine, Houston, Hamish, Nevin, Sean, Fenn, Joe, Kundu, Rhia, Crone, Michael A, Pillay, Timesh D, Ahmad, Shazaad, Derqui-Fernandez, Nieves, Conibear, Emily, Freemont, Paul S, Taylor, Graham P, Ferguson, Neil, Zambon, Maria, Barclay, Wendy S, Dunning, Jake, and Lalvani, Ajit

Published
2022
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38. Safety, tolerability and viral kinetics during SARS-CoV-2 human challenge in young adults

Author

Killingley, Ben, Mann, Alex J., Kalinova, Mariya, Boyers, Alison, Goonawardane, Niluka, Zhou, Jie, Lindsell, Kate, Hare, Samanjit S., Brown, Jonathan, Frise, Rebecca, Smith, Emma, Hopkins, Claire, Noulin, Nicolas, Löndt, Brandon, Wilkinson, Tom, Harden, Stephen, McShane, Helen, Baillet, Mark, Gilbert, Anthony, Jacobs, Michael, Charman, Christine, Mande, Priya, Nguyen-Van-Tam, Jonathan S., Semple, Malcolm G., Read, Robert C., Ferguson, Neil M., Openshaw, Peter J., Rapeport, Garth, Barclay, Wendy S., Catchpole, Andrew P., and Chiu, Christopher

Published
2022
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42. Estimating the COVID-19 infection fatality ratio accounting for seroreversion using statistical modelling

Author

Brazeau, Nicholas F., Verity, Robert, Jenks, Sara, Fu, Han, Whittaker, Charles, Winskill, Peter, Dorigatti, Ilaria, Walker, Patrick G. T., Riley, Steven, Schnekenberg, Ricardo P., Hoeltgebaum, Henrique, Mellan, Thomas A., Mishra, Swapnil, Unwin, H. Juliette T., Watson, Oliver J., Cucunubá, Zulma M., Baguelin, Marc, Whittles, Lilith, Bhatt, Samir, Ghani, Azra C., Ferguson, Neil M., and Okell, Lucy C.

Published
2022
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45. Comparative analysis of the risks of hospitalisation and death associated with SARS-CoV-2 omicron (B.1.1.529) and delta (B.1.617.2) variants in England: a cohort study

Author

Nyberg, Tommy, Ferguson, Neil M, Nash, Sophie G, Webster, Harriet H, Flaxman, Seth, Andrews, Nick, Hinsley, Wes, Lopez Bernal, Jamie, Kall, Meaghan, Bhatt, Samir, Blomquist, Paula, Zaidi, Asad, Volz, Erik, Abdul Aziz, Nurin, Harman, Katie, Funk, Sebastian, Abbott, Sam, Hope, Russell, Charlett, Andre, Chand, Meera, Ghani, Azra C, Seaman, Shaun R, Dabrera, Gavin, De Angelis, Daniela, Presanis, Anne M, Thelwall, Simon, Bernal, Jamie Lopez, and Aziz, Nurin Abdul

Published
2022
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46. Climate change, malaria and neglected tropical diseases: a scoping review.

Author

Klepac, Petra, Hsieh, Jennifer L, Ducker, Camilla L, Assoum, Mohamad, Booth, Mark, Byrne, Isabel, Dodson, Sarity, Martin, Diana L, Turner, C Michael R, Daalen, Kim R van, Abela, Bernadette, Akamboe, Jennifer, Alves, Fabiana, Brooker, Simon J, Ciceri-Reynolds, Karen, Cole, Jeremy, Desjardins, Aidan, Drakeley, Chris, Ediriweera, Dileepa S, and Ferguson, Neil M

Subjects
CLIMATE change, CHIKUNGUNYA, DENGUE, MALARIA, HEALTH services accessibility
Abstract

To explore the effects of climate change on malaria and 20 neglected tropical diseases (NTDs), and potential effect amelioration through mitigation and adaptation, we searched for papers published from January 2010 to October 2023. We descriptively synthesised extracted data. We analysed numbers of papers meeting our inclusion criteria by country and national disease burden, healthcare access and quality index (HAQI), as well as by climate vulnerability score. From 42 693 retrieved records, 1543 full-text papers were assessed. Of 511 papers meeting the inclusion criteria, 185 studied malaria, 181 dengue and chikungunya and 53 leishmaniasis; other NTDs were relatively understudied. Mitigation was considered in 174 papers (34%) and adaption strategies in 24 (5%). Amplitude and direction of effects of climate change on malaria and NTDs are likely to vary by disease and location, be non-linear and evolve over time. Available analyses do not allow confident prediction of the overall global impact of climate change on these diseases. For dengue and chikungunya and the group of non-vector-borne NTDs, the literature privileged consideration of current low-burden countries with a high HAQI. No leishmaniasis papers considered outcomes in East Africa. Comprehensive, collaborative and standardised modelling efforts are needed to better understand how climate change will directly and indirectly affect malaria and NTDs. [ABSTRACT FROM AUTHOR]

Published
2024
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47. Community transmission and viral load kinetics of the SARS-CoV-2 delta (B.1.617.2) variant in vaccinated and unvaccinated individuals in the UK: a prospective, longitudinal, cohort study

Author

Badhan, Anjna, Dustan, Simon, Tejpal, Chitra, Ketkar, Anjeli V, Narean, Janakan Sam, Hammett, Sarah, McDermott, Eimear, Pillay, Timesh, Houston, Hamish, Luca, Constanta, Samuel, Jada, Bremang, Samuel, Evetts, Samuel, Poh, John, Anderson, Charlotte, Jackson, David, Miah, Shahjahan, Ellis, Joanna, Lackenby, Angie, Singanayagam, Anika, Hakki, Seran, Dunning, Jake, Madon, Kieran J, Crone, Michael A, Koycheva, Aleksandra, Derqui-Fernandez, Nieves, Barnett, Jack L, Whitfield, Michael G, Varro, Robert, Charlett, Andre, Kundu, Rhia, Fenn, Joe, Cutajar, Jessica, Quinn, Valerie, Conibear, Emily, Barclay, Wendy, Freemont, Paul S, Taylor, Graham P, Ahmad, Shazaad, Zambon, Maria, Ferguson, Neil M, and Lalvani, Ajit

Published
2022
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48. Mathematical models of human mobility of relevance to malaria transmission in Africa.

Author

Marshall, John, Wu, Sean, Sanchez C, Hector, Kiware, Samson, Ndhlovu, Micky, Ouédraogo, André, Touré, Mahamoudou, Sturrock, Hugh, Ghani, Azra, and Ferguson, Neil

Subjects
Adolescent, Adult, Africa, Child, Child, Preschool, Female, Humans, Infant, Malaria, Male, Models, Theoretical, Prevalence, Spatial Analysis, Travel, Young Adult
Abstract

As Africa-wide malaria prevalence declines, an understanding of human movement patterns is essential to inform how best to target interventions. We fitted movement models to trip data from surveys conducted at 3-5 sites throughout each of Mali, Burkina Faso, Zambia and Tanzania. Two models were compared in terms of their ability to predict the observed movement patterns - a gravity model, in which movement rates between pairs of locations increase with population size and decrease with distance, and a radiation model, in which travelers are cumulatively absorbed as they move outwards from their origin of travel. The gravity model provided a better fit to the data overall and for travel to large populations, while the radiation model provided a better fit for nearby populations. One strength of the data set was that trips could be categorized according to traveler group - namely, women traveling with children in all survey countries and youth workers in Mali. For gravity models fitted to data specific to these groups, youth workers were found to have a higher travel frequency to large population centers, and women traveling with children a lower frequency. These models may help predict the spatial transmission of malaria parasites and inform strategies to control their spread.

Published
2018

49. Infectious virus in exhaled breath of symptomatic seasonal influenza cases from a college community

Author

Yan, Jing, Grantham, Michael, Pantelic, Jovan, de Mesquita, P Jacob Bueno, Albert, Barbara, Liu, Fengjie, Ehrman, Sheryl, Milton, Donald K, Adamson, Walt, Beato-Arribas, Blanca, Bischoff, Werner, Booth, William, Cauchemez, Simon, Enstone, Joanne, Ferguson, Neil, Forni, John, Gilbert, Anthony, Grohskopf, Lisa, Hayward, Andrew, Hewitt, Michael, Kang, Ashley, Killingley, Ben, Lambkin-Williams, Robert, Mann, Alex, Milton, Donald, Nguyen-Van-Tam, Jonathan, Noakes, Catherine, Oxford, John, Palmarini, Massimo, Wang, Jennifer, Bennett, Allan, Cowling, Ben, Monto, Arnold, and Tellier, Raymond

Subjects
Prevention, Emerging Infectious Diseases, Lung, Biodefense, Influenza, Pneumonia & Influenza, Infectious Diseases, Vaccine Related, Clinical Research, Infection, Good Health and Well Being, Aerosols, Air Microbiology, Body Mass Index, Cough, Exhalation, Female, Humans, Influenza, Human, Male, Models, Theoretical, Prevalence, RNA, Viral, Respiratory System, Respiratory Tract Infections, Seasons, Students, Temperature, Universities, Vaccination, Young Adult, influenza virus, aerosol, airborne infection, vaccination effects, viral shedding, EMIT Consortium
Abstract

Little is known about the amount and infectiousness of influenza virus shed into exhaled breath. This contributes to uncertainty about the importance of airborne influenza transmission. We screened 355 symptomatic volunteers with acute respiratory illness and report 142 cases with confirmed influenza infection who provided 218 paired nasopharyngeal (NP) and 30-minute breath samples (coarse >5-µm and fine ≤5-µm fractions) on days 1-3 after symptom onset. We assessed viral RNA copy number for all samples and cultured NP swabs and fine aerosols. We recovered infectious virus from 52 (39%) of the fine aerosols and 150 (89%) of the NP swabs with valid cultures. The geometric mean RNA copy numbers were 3.8 × 104/30-minutes fine-, 1.2 × 104/30-minutes coarse-aerosol sample, and 8.2 × 108 per NP swab. Fine- and coarse-aerosol viral RNA were positively associated with body mass index and number of coughs and negatively associated with increasing days since symptom onset in adjusted models. Fine-aerosol viral RNA was also positively associated with having influenza vaccination for both the current and prior season. NP swab viral RNA was positively associated with upper respiratory symptoms and negatively associated with age but was not significantly associated with fine- or coarse-aerosol viral RNA or their predictors. Sneezing was rare, and sneezing and coughing were not necessary for infectious aerosol generation. Our observations suggest that influenza infection in the upper and lower airways are compartmentalized and independent.

Published
2018

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