Browse by Data capture method

Up a level
Export as [feed] Atom [feed] RSS
Group by: Date | Item Type | No Grouping
Number of items: 74.

Data Collection

Abbott, S, Hellewell, J, Lucas, T, Funk, S and Gimma, A (2023). epiforecasts/ringbp. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.3749529

Suárez-Idueta, L, Ohuma, EO, Chang, C, Hazel, EA, Yargawa, J, Okwaraji, YB, Bradley, E, Gordon, A, Sexton, J, Lawford, H, Paixao cruz, ES, Falcão, IR, Lisonkova, S, Wen, Q, Velebil, P, Jírová, J, Horváth-Puhó, E, Sørensen, HT, Sakkeus, L, Abuladze, L, Yunis, KA, Bizri, AA, Alvarez Lopez, S, Broeders, L, van Dijk, AE, Alyafei, F, AlQubaisi, M, Razaz, N, Söderling, J, Smith, LK, Matthews, R, Lowry, E, Rowland, N, Wood, R, Monteath, K, Pereyra, I, Pravia, G, Lawn, JE and Blencowe, H (2023). Data for: "Neonatal mortality risk of large for gestational age and macrosomic live births in 15 countries including 115.6 million nationwide linked records, 2000–2020". [Data Collection]. London School of Hygiene & Tropical Medicine, London, United Kingdom. https://doi.org/10.17037/DATA.00003666.

Churcher, T, Stopard, I, Hamlet, A, Dee, D, Sanou, A, Rowland, M, Guelbeogo, M, Emidi, B, Mosha, J, Challenger, J, Denz, A, Charles, G, Russell, E, Fitzjohn, R, Winskill, P, Fornadel, C, Mclean, T, Digre, P, Wagman, J, Mosha, F, Cook, J, Akogbéto, M, Djogbenou, L, Ranson, H, Manjurano, A, N'fale, S, Protopopoff, N, Accrombessi, M, Ngufor, C, Foster, G and Sherrard-Smith, E (2023). MINT-data-v20230208. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.8344311

Pung, R (2023). rachaelpung/covid_missed_infections. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.7538046

Keddie, S, Bärenbold, O, Keogh, R and Bradley, J (2022). Stan models for diagnostic tests accuracy simulation; Accompaniment for Journal Article. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.6616490

Woodhouse, M, Aspinall, W, Sparks, R, Brooks-Pollock, E and Relton, CL (2022). Alternative Covid-19 mitigation measures in school classrooms: Analysis using an agent-based model of SARS-CoV-2 transmission. [Data Collection]. Dryad. https://doi.org/10.5061/dryad.pk0p2ngr3

Briggs, A (2022). Decision Modelling for Health Economic Evaluation - Exercises. [Data Collection]. London School of Hygiene & Tropical Medicine, London, United Kingdom. https://doi.org/10.17037/DATA.00002980.

Greener, R, Lewis, D, Reades, J, Miles, S and Cummins, S (2022). Software and results for: Incorporating social norms into a configurable agent-based model of commuting behaviour. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.4916753

Greener, R, Lewis, D, Reades, J, Miles, S and Cummins, S (2021). Software and results for: An agent-based model for simulating the impact of social norms on active commuting interventions. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.4916753

Pearson, CAB, Bozzani, F, Procter, SR, Davies, NG, Huda, M, Jensen, HT, Keogh-Brown, M, Khalid, M, Sweeney, S, Torres-Rueda, S, Eggo, RM, Vassall, A and Jit, M (2021). Simulation results for "COVID-19 vaccination in Sindh Province, Pakistan: a modelling study of health impact and cost-effectiveness". [Data Collection]. Zenodo. http://doi.org/10.5281/zenodo.5070957

Quilty, B (2021). cmmid/covid_quar_test_import_risk. [Data Collection]. Github. https://github.com/cmmid/covid_quar_test_import_risk

Timaeus, I (2021). BugBunny/oRphanhood. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.4889479

Vicedo-Cabrera, AM, Gasparrini, A and Royé, D (2021). anavica/mcc_ccattr_NCC. [Data Collection]. Github. https://github.com/anavica/mcc_ccattr_NCC

Quilty, B (2021). cmmid/quar_test_contact_tracing. [Data Collection]. Github. https://github.com/cmmid/quar_test_contact_tracing

Munday, JD (2021). jdmunday/SchoolHouseholdNetworksCOVID: Initial release. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.4552421

Chapman, LAC (2021). LloydChapman/COVID_homeless_modelling. [Data Collection]. Github. https://github.com/LloydChapman/COVID_homeless_modelling

Fernandez, MAL, Zivich, P and Smith, MJ (2020). migariane/TutorialCausalInferenceEstimators: Computational Causal Inference for Applied Researchers. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.4424912

Gasparrini, A (2020). gasparrini/2019_vicedo-cabrera_Epidem_Rcodedata. [Data Collection]. Github. https://github.com/gasparrini/2019_vicedo-cabrera_Epidem_Rcodedata

Thompson, J (2020). Comparison of small-sample standard-error corrections for generalised estimating equations in stepped wedge cluster randomised trials with a binary outcome: A simulation study. [Data Collection]. Zenodo. https://zenodo.org/10.5281/zenodo.4049828

Harris, F (2020). Interstate trade of cereals in India. [Data Collection]. London School of Hygiene & Tropical Medicine, London, United Kingdom. https://doi.org/10.17037/DATA.00001870.

Nash, S, Thompson, J and Leurent, B (2020). CLAN: Stata module to perform cluster-level analysis of cluster randomised trials. [Data Collection]. Statistical Software Components S458844, Boston College Department of Economics. https://ideas.repec.org/c/boc/bocode/s458844.html

Yakob, L and Nightingale, E (2020). lwyakob/COVIDsaturates. [Data Collection]. Github. https://github.com/lwyakob/COVIDsaturates

Liu, Y, Gong, W, Clifford, S, Sundaram, ME, CMMID COVID-19 Working Group, Jit, M, Flasche, S and Klepac, P (2020). yangclaraliu/covid_surveillance_strategy: WOR Submission. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.4017353

Leng, T and Flasche, S (2020). tsleng93/SocialBubble: Social Bubble (including density dependence). [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.3982789

Gibbs, H, Abbott, S and Funk, S (2020). RtD3. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.4011841

Greener, R (2020). Machine learning methods to investigate segments of the British consumer food market and to predict weight status: Source code. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.3992349

Clifford, S, Quilty, BJ, Russell, TW, Liu, Y, Chan, YD, Pearson, CAB, Eggo, RM, Endo, A, CMMID COVID-19 Working Group, Flasche, S and Edmunds, WJ (2020). cmmid/travel_screening_strategies. [Data Collection]. Github. https://github.com/cmmid/travel_screening_strategies

Russell, TW, Golding, N, Hellewell, J, Abbott, S, Pearson, CAB, Van zandvoort, K, Jarvis, CI, Gibbs, H, Liu, Y, Eggo, RM, Edmunds, WJ, Kucharski, AJ and CMMID COVID-19 working group (2020). Reconstructing the global dynamics of unreported COVID-19 cases and infections. [Data Collection]. Github. https://github.com/thimotei/covid_underreporting

Pearson, CAB, Van zandvoort, K, Jarvis, CI, Davies, NG, Thompson, S, Checchi, F, Jit, M, Eggo, RM and LSHTM CMMID COVID-19 Working Group (2020). Projections of COVID-19 epidemics in LMIC countries. [Data Collection]. London School of Hygiene & Tropical Medicine, London, United Kingdom. https://doi.org/10.17037/DATA.00001564.

Abbas, KM (2020). vaccine-impact/epi_covid. [Data Collection]. Github. https://github.com/vaccine-impact/epi_covid

Jombart, T and Schumacher, D (2020). trendbreaker 0.1.0: Detect Changes in Temporal Trends. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.3888493

Quaife, M (2020). mquaife/kenya_mixing. [Data Collection]. Github. https://github.com/mquaife/kenya_mixing

Abbott, S, Sherratt, K, Funk, S and Hellewell, J (2020). epiforecasts/covid: Submission release. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.3746396

Kissler, SM, Klepac, P, Tang, M, Conlan, AJ and Gog, JR (2020). skissler/haslemere. [Data Collection]. Github. https://github.com/skissler/haslemere

Flasche, S (2020). StefanFlasche/Pneumo_Trans_Inf. [Data Collection]. Github. https://github.com/StefanFlasche/Pneumo_Trans_Inf

Jombart, T, Clifford, S, Pearson, Carl A. B. Pearson, Rees, E, Nightingale, E, Procter, S and Knight, G (2020). thibautjombart/covid19_bed_occupancy: Second major release. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.3746662

Prem, K, Liu, Y, Russell, TW, Kucharski, AJ, Eggo, RM, Davies, NG, Jit, M, Klepac, P, Flasche, S, Clifford, S, Pearson, CAB, Munday, JD, Abbott, S, Gibbs, H, Rosello, A, Quilty, BJ, Jombart, T, Sun, F, Diamond, C, Gimma, A, Van zandvoort, K, Funk, S, Jarvis, CI, Edmunds, WJ, Bosse, NI and Hellewell, J (2020). Age-structured SEIR model for COVID-19 outbreak in Wuhan, China. [Data Collection]. Github. https://github.com/kieshaprem/covid19-agestructureSEIR-wuhan-social-distancing

Jombart, T, Abbott, S, Gimma, A, Zandvoort, K, Clifford, S, Jarvis, C, Russell, T, Funk, S, Gibbs, H, Eggo, RM, Kucharski, AJ, CMMID COVID-19 Working Group and Edmunds, WJ (2020). Inferring COVID-19 cases from deaths of confirmed cases. [Data Collection]. CMMID Repository. https://cmmid.github.io/visualisations/inferring-covid19-cases-from-deaths

Hellewell, J, Abbott, S, Gimma, A, Bosse, N, Jarvis, C, Russell, T, Munday, J, Kucharski, A, Edmunds, WJ, Funk, S, Eggo, R, Sun, F, Flasche, S, Quilty, B, Davies, N, Liu, Y, Clifford, S, Klepac, P, Jit, M, Diamond, C, Gibbs, H and Van Zandvoort, K (2020). Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts. [Data Collection]. Github. https://github.com/cmmid/ringbp/

Robert, A (2020). geosocial-outbreaker: Integrating geographical and social contact data to reconstruct transmission chains. [Data Collection]. Github. https://github.com/alxsrobert/o2geosocial

Keogh, R, Seaman, SR, Gran, JM and Vansteelandt, S (2020). Causal Sim code. [Data Collection]. Github. https://github.com/ruthkeogh/causal_sim

Paradis, E, Kamvar, ZN, Jombart, T, Brian, K and Frederic, M (2020). pegas: Population and Evolutionary Genetics Analysis System. [Data Collection]. Zenodo. http://doi.org/10.5281/zenodo.3647668

Kucharski, AJ, Russell, TW, Diamond, C, CMMID nCoV working group, Funk, S and Eggo, RM (2020). Probability of a large 2019-nCoV outbreak following introduction of cases. [Data Collection]. Github. https://cmmid.github.io/visualisations/new-outbreak-probability

Abbott, S, Funk, S, Munday, JD and Hellewell, J (2020). epiforecasts/WuhanSeedingVsTransmission: Resubmission to Wellcome Open Research. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.3630424

Gasparrini, A (2019). gasparrini/2019_sera_StatMed_Rcode. [Data Collection]. Github. https://github.com/gasparrini/2019_sera_StatMed_Rcode

Flasche, S (2019). Denvaxia-in-Phillippines. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.3496819

Keogh, R and Bartlett, J (2019). Measurement error correction methods applied to NHANES data. [Data Collection]. Github. https://github.com/ruthkeogh/meas_error_handbook

Thompson, J (2019). SWPERMUTE: Stata module to compute Permutation tests for Stepped-Wedge Cluster-Randomised Trials. [Data Collection]. Statistical Software Components S458426, Boston College Department of Economics. https://ideas.repec.org/c/boc/bocode/s458426.html

Finger, F, Funk, S, White, K, Siddiqui, MR, Edmunds, WJ and Kucharski, AJ (2019). Real-time analysis of the diphtheria outbreak in forcibly displaced Myanmar nationals in Bangladesh. [Data Collection]. Figshare. https://doi.org/10.6084/m9.figshare.7829816.v1.

Funk, S (2019). R Code accompanying the manuscript "Assessing the performance of real-time epidemic forecasts: A case study of Ebola in the Western Area region of Sierra Leone, 2014-15". [Data Collection]. Zenodo. http://doi.org/10.5281/zenodo.2547701

Sumner, T (2018). Mathematical model projections for: "Application of provincial data in mathematical modelling to inform sub-national tuberculosis program decision-making in South Africa". [Data Collection]. London School of Hygiene & Tropical Medicine, London, United Kingdom. https://doi.org/10.17037/DATA.00000950.

Witmer, K, Sherrard-Smith, E, Straschil, U, Tunnicliff, M, Baum, J and Delves, M (2018). MOESM1 of An inexpensive open source 3D-printed membrane feeder for human malaria transmission studies. [Data Collection]. Figshare. https://doi.org/10.6084/m9.figshare.6933695.v1

Witmer, K, Sherrard-Smith, E, Straschil, U, Tunnicliff, M, Baum, J and Delves, M (2018). MOESM2 of An inexpensive open source 3D-printed membrane feeder for human malaria transmission studies. [Data Collection]. Figshare. https://doi.org/10.6084/m9.figshare.6933704.v1

Keogh, R (2018). MI-TVE. [Data Collection]. Github. https://github.com/ruthkeogh/MI-TVE

Eggo, RM (2018). Computer code of the coinfection model. [Data Collection]. PLOS Pathogens. https://doi.org/10.1371/journal.ppat.1006770.s004.

Langham, S, Wright, A, Kenworthy, J, Grieve, R and Dunlop, WC (2018). Cost-Effectiveness of Take-Home Naloxone for the Prevention of Overdose Fatalities among Heroin Users in the United Kingdom: Supplemental Materials. [Data Collection]. Value in Health. https://doi.org/10.1016/j.jval.2017.07.014

van Kleef, E, Luangasanatip, N, Bonten, MJ and Cooper, BS (2017). R code: why sensitive bacteria are resistant to hospital infection control. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.1045530

Marks, M, Mitja, O, Fitzpatrick, C, Asiedu, K, Solomon, AW, Mabey, D and Funk, S (2017). R files for: Mathematical Modeling of Programmatic Requirements for Yaws Eradication. [Data Collection]. London School of Hygiene & Tropical Medicine, London, United Kingdom. https://doi.org/10.17037/DATA.266.

Rossell, D and Rubio, FJ (2017). Tractable Bayesian variable selection: beyond normality. [Data Collection]. Figshare. https://doi.org/10.6084/m9.figshare.5410747.v1

Choi, YH, Campbell, H, Amirthalingam, G, Van Hoek, AJ and Miller, E (2017). Additional file 3: of Investigating the pertussis resurgence in England and Wales, and options for future control. [Data Collection]. Figshare. https://doi.org/10.6084/m9.figshare.c.3614585_D1.v1

Luque, MA (2017). migariane/meltmle: Ensemble Learning Targeted Maximum Likelihood Estimation for Stata users. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.2560827

Le Rutte, EA, Chapman, LA, Coffeng, LE, Jervis, S, Hasker, EC, Dwivedi, S, Karthick, M, Das, A, Mahapatra, T, Chaudhuri, I, Boelaert, MC, Medley, GF, Srikantiah, S, Hollingsworth, TD and de Vlas, SJ (2017). Elimination of visceral leishmaniasis in the Indian subcontinent: a comparison of predictions from three transmission models. [Data Collection]. Epidemics. http://doi.org/10.1016/j.epidem.2017.01.002

Kessy, A, Lewin, A and Strimmer, K (2017). Optimal Whitening and Decorrelation. [Data Collection]. Figshare. https://doi.org/10.6084/m9.figshare.4568002.v1

Gasparrini, A (2017). R Code for: "Modelling lagged associations in environmental time series data: a simulation study". [Data Collection]. Github. https://github.com/gasparrini/2016_gasparrini_Epidem_Rcode

Marks, M and Roberts, C (2017). Poisson Regression Dataset for "Learning Clinical Epidemiology with R" tutorial. [Data Collection]. London School of Hygiene & Tropical Medicine, London, United Kingdom. https://doi.org/10.17037/DATA.00000609.

Kucharski, AJ, Funk, S, Eggo, RM, Mallet, H, Edmunds, WJ and Nilles, EJ (2016). S1 Dataset for "Transmission Dynamics of Zika Virus in Island Populations: A Modelling Analysis of the 2013–14 French Polynesia Outbreak". [Data Collection]. PLoS Neglected Tropical Diseases. https://doi.org/10.1371/journal.pntd.0004726.s016

Diaz-ordaz, K, Kenward, M, Gomes, M and Grieve, R (2016). Multiple imputation methods for bivariate outcomes in cluster randomised trials: Supporting Information. [Data Collection]. London School of Hygiene & Tropical Medicine, London, United Kingdom. https://doi.org/10.17037/DATA.99.

Sadique, Z, Lopman, B, Cooper, BS and Edmunds, J (2016). Cost-effectiveness of Ward Closure to Control Outbreaks of Norovirus Infection in UK National Health Service Hospitals: Epidemic simulation model. [Data Collection]. Oxford University Press. https://doi.org/10.1093/infdis/jiv410

Jeandron, A, Saidi, JM, Kapama, A, Burhole, M, Birembano, F, Vandevelde, T, Gasparrini, A, Armstrong, B, Cairncross, S and Ensink, J (2015). Water Supply Interruptions and Suspected Cholera Incidence: A Time-Series Regression in the Democratic Republic of the Congo. [Data Collection]. PLOS Medicine. https://doi.org/10.1371/journal.pmed.1001893

Kucharski, A and Edmunds, J (2015). Characterizing the Transmission Potential of Zoonotic Infections from Minor Outbreaks: Simulation and Inference code. [Data Collection]. PLOS Computational Biology. http://doi.org/10.1371/journal.pcbi.1004154.s010

Phillips, A, Cambiano, V, Nakagawa, F, Magubu, T, Miners, A, Ford, D, Pillay, D, De Luca, A, Lundgren, J and Revill, P (2014). Cost-Effectiveness of HIV Drug Resistance Testing to Inform Switching to Second Line Antiretroviral Therapy in Low Income Settings: Supporting material. [Data Collection]. Figshare. https://doi.org/10.6084/m9.figshare.1155223

Pigott, DM, Golding, N, Mylne, A, Huang, Z, Henry, AJ, Weiss, DJ, Brady, OJ, Kraemer, MU, Smith, DL, Moyes, CL, Bhatt, S, Gething, PW, Horby, PW, Bogoch, II, Brownstein, JS, Mekaru, SR, Tatem, AJ, Khan, K and Hay, SI (2014). Source code for analysis of the zoonotic niche of Ebolavirus. [Data Collection]. GitHub, Inc.. https://doi.org/10.7554/eLife.04395.

Okumu, F (2012). Combining insecticide treated bed nets and indoor residual spraying for malaria vector control in Africa. [Data Collection]. London School of Hygiene & Tropical Medicine, London, United Kingdom. https://doi.org/10.17037/DATA.39.

Pocock, S, Bennett, M, Mccormack, V, Gueyffier, F, Boutitie, F, Fagard, RH and Boissel, J (2006). Cardiovascular Risk Score Calculator. [Data Collection]. London School of Hygiene & Tropical Medicine, London, United Kingdom. http://riskscore.lshtm.ac.uk/

This list was generated on Mon Oct 7 02:21:08 2024 BST.