Data Collection

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

Abbott, S, Bennett, C, Hickson, J, Allen, J, Sherratt, K and Funk, S (2020). Collated Results of the National and Subnational Estimates of the Covid 19 Reproduction Number (R) for the United Kingdom Based on Tests, Hospital Admissions and Deaths. [Data Collection]. Harvard Dataverse. https://doi.org/10.7910/DVN/4L3OKY

Abbott, S, Bennett, C, Hickson, J, Allen, J, Sherratt, K and Funk, S (2021). Continent Summary Reproduction Number (R) Based on Reported Cases. [Data Collection]. Harvard Dataverse. https://doi.org/10.7910/DVN/F9HVNL

Abbott, S, Bennett, C, Hickson, J, Allen, J, Sherratt, K and Funk, S (2020). Continent Summary Reproduction Number (R) Based on Reported Deaths. [Data Collection]. Harvard Dataverse. https://doi.org/10.7910/DVN/A12ADQ

Abbott, S, Bennett, C, Hickson, J, Allen, J, Sherratt, K and Funk, S (2021). Local Estimates of the Covid 19 Reproduction Number (R) for the United Kingdom Based on Admissions. [Data Collection]. Harvard Dataverse. https://doi.org/10.7910/DVN/0NYGXE

Abbott, S, Bennett, C, Hickson, J, Allen, J, Sherratt, K and Funk, S (2021). Local Estimates of the Covid 19 Reproduction Number (R) for the United Kingdom Based on Deaths. [Data Collection]. Harvard Dataverse. https://doi.org/10.7910/DVN/UIM3MB

Abbott, S, Bennett, C, Hickson, J, Allen, J, Sherratt, K and Funk, S (2020). Local Estimates of the Covid 19 Reproduction Number (R) for the United Kingdom Based on Test Results. [Data Collection]. Harvard Dataverse. https://doi.org/10.7910/DVN/ISLFJB

Abbott, S, Bennett, C, Hickson, J, Allen, J, Sherratt, K and Funk, S (2020). National Reproduction Number (R) Based on Reported Cases. [Data Collection]. Harvard Dataverse. https://doi.org/10.7910/DVN/TTLQRN

Abbott, S, Bennett, C, Hickson, J, Allen, J, Sherratt, K and Funk, S (2020). National Reproduction Number (R) Estimates Based on Reported Deaths. [Data Collection]. Harvard Dataverse. https://doi.org/10.7910/DVN/RBZVJE

Abbott, S, Bennett, C, Hickson, J, Allen, J, Sherratt, K and Funk, S (2021). National and Subnational Estimates of the Covid 19 Reproduction Number (R) for Belgium Based on Test Results. [Data Collection]. Harvard Dataverse. https://doi.org/10.7910/DVN/NALGQJ

Abbott, S, Bennett, C, Hickson, J, Allen, J, Sherratt, K and Funk, S (2020). National and Subnational Estimates of the Covid 19 Reproduction Number (R) for Brazil Based on Test Results. [Data Collection]. Harvard Dataverse. https://doi.org/10.7910/DVN/METDW2

Abbott, S, Bennett, C, Hickson, J, Allen, J, Sherratt, K and Funk, S (2021). National and Subnational Estimates of the Covid 19 Reproduction Number (R) for Canada Based on Test Results. [Data Collection]. Harvard Dataverse. https://doi.org/10.7910/DVN/2CNKZJ

Abbott, S, Bennett, C, Hickson, J, Allen, J, Sherratt, K and Funk, S (2021). National and Subnational Estimates of the Covid 19 Reproduction Number (R) for Colombia Based on Test Results. [Data Collection]. Harvard Dataverse. https://doi.org/10.7910/DVN/GI8EVP

Abbott, S, Bennett, C, Hickson, J, Allen, J, Sherratt, K and Funk, S (2020). National and Subnational Estimates of the Covid 19 Reproduction Number (R) for Germany Based on Test Results. [Data Collection]. Harvard Dataverse. https://doi.org/10.7910/DVN/LNMJYJ

Abbott, S, Bennett, C, Hickson, J, Allen, J, Sherratt, K and Funk, S (2020). National and Subnational Estimates of the Covid 19 Reproduction Number (R) for India Based on Test Results. [Data Collection]. Harvard Dataverse. https://doi.org/10.7910/DVN/PRP6CY

Abbott, S, Bennett, C, Hickson, J, Allen, J, Sherratt, K and Funk, S (2020). National and Subnational Estimates of the Covid 19 Reproduction Number (R) for Italy Based on Test Results. [Data Collection]. Harvard Dataverse. https://doi.org/10.7910/DVN/8DUSHZ

Abbott, S, Bennett, C, Hickson, J, Allen, J, Sherratt, K and Funk, S (2021). National and Subnational Estimates of the Covid 19 Reproduction Number (R) for South Africa Based on Test Results. [Data Collection]. Harvard Dataverse. https://doi.org/10.7910/DVN/17XS9I

Abbott, S, Bennett, C, Hickson, J, Allen, J, Sherratt, K and Funk, S (2020). National and Subnational Estimates of the Covid 19 Reproduction Number (R) for the United Kingdom Based on Deaths. [Data Collection]. Harvard Dataverse. https://doi.org/10.7910/DVN/QVWUJ5

Abbott, S, Bennett, C, Hickson, J, Allen, J, Sherratt, K and Funk, S (2020). National and Subnational Estimates of the Covid 19 Reproduction Number (R) for the United Kingdom Based on Hospital Admissions. [Data Collection]. Harvard Dataverse. https://doi.org/10.7910/DVN/CCE4XT

Abbott, S, Bennett, C, Hickson, J, Allen, J, Sherratt, K and Funk, S (2020). National and Subnational Estimates of the Covid 19 Reproduction Number (R) for the United Kingdom Based on Test Results. [Data Collection]. Harvard Dataverse. https://doi.org/10.7910/DVN/S07EZB

Abbott, S, Bennett, C, Hickson, J, Allen, J, Sherratt, K and Funk, S (2020). National and Subnational Estimates of the Covid 19 Reproduction Number (R) for the United States of America Based on Test Results. [Data Collection]. Harvard Dataverse. https://doi.org/10.7910/DVN/BZ7FPH

Abbott, S, Bosse, N, DeWitt, M, Rau, A, Chateigner, A, Mareschal, S and Hellewell, J (2020). epiforecasts/EpiSoon. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.3746394

Abbott, S and Funk, S (2021). epiforecasts/covid19.sgene.utla.rt. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.5236661

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

Abbott, S, Gaythorpe, KA, Imai, N and Liu, Y (2020). seabbs/CovidInterventionReview: CC0 license. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.3728162

Abbott, S, Hickson, J, Badr, HS, Funk, S, Monticone, P, Ellis, P, Munday, JD, Allen, J, Pearson, CAB, DeWitt, M, Bosse, N and Meakin, S (2021). epiforecasts/EpiNow2. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.3957489

Abbott, S and Meakin, S (2021). epiforecasts/covid19.nhs.data: Initial release. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.4447465

Abbott, S and Sherratt, K (2022). seabbs/ecdc-weekly-growth-forecasts. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.7189620

Abbott, S, Sherratt, K and Funk, S (2021). Real-time estimation of the time-varying transmission advantage of Omicron in England using S-Gene Target Status as a Proxy. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.5799135

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

Abbott, S, Sherratt, K, Gibbs, H, Finger, F, Campbell, P, Hellewell, J, Barks, P, Meakin, S and Lee, H (2020). epiforecasts/NCoVUtils. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.3635417

Aburto, JM, Schöley, J, Kashnitsky, I, Knowles, I, Zhang, L, Rahal, C, Missov, TI, Dowd, JB, Mills, MC and Kashyap, R (2021). Code to replicate "Quantifying impacts of the COVID-19 pandemic through life expectancy losses". [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.4556982

Adetifa, IMO, Uyoga, S, Gitonga, JN, Mugo, D, Otiende, M, Nyagwange, J, Karanja, HK, Tuju, J, Wanjiku, P, Aman, R, Mwangangi, M, Amoth, P, Kasera, K, Ng’ang’a, W, Rombo, C, Yegon, C, Kithi, K, Odhiambo, E, Rotich, T, Orgut, I, Kihara, S, Bottomley, C, Kagucia, EW, Gallagher, KE, Etyang, A, Voller, S, Lambe, T, Wright, D, Barasa, E, Tsofa, B, Bejon, P, Ochola-Oyier, LI, Agweyu, A, Scott, JAG and Warimwe, GM (2021). Replication Data for: Temporal trends of SARS-CoV-2 seroprevalence in transfusion blood donors during the first wave of the COVID-19 epidemic in Kenya. [Data Collection]. Harvard Dataverse. https://doi.org/10.7910/DVN/FQUNVD

Aldridge, RW, Lewer, D, Beale, S, Johnson, AM, Zambon, M, Hayward, AC and Fragaszy, E (2020). Dataset: Seasonality and immunity to laboratory-confirmed seasonal coronaviruses (HCoV-NL63, HCoV-OC43, and HCoV-229E): results from the Flu Watch cohort study. [Data Collection]. UCL Institute of Health Informatics, London, United Kingdom. https://doi.org/10.14324/000.ds.10093909

Asi, YM, Bebasari, P, Hardy, E, Lokot, M, Meagher, K, Ogbe, E, Parray, AA, Sharma, V, Standley, CJ and Vahedi, L (2022). Additional file 1 of Assessing gender responsiveness of COVID-19 response plans for populations in conflict-affected humanitarian emergencies. [Data Collection]. Figshare. https://doi.org/10.6084/m9.figshare.19174573.v1

Assefa, N, Demissie, L, Teklemarriam, Z, Oundo, JO, Madrid, L, Dessie, Y and Scott, JAG (2021). Replication Data for: Seroprevalence of anti–SARS-CoV-2 antibodies in women attending antenatal care in eastern Ethiopia. [Data Collection]. Harvard Dataverse. https://doi.org/10.7910/DVN/XIWCXN

Barnard, RC (2022). rosannaclairebarnard/covidm-mtd-Omi. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.6806636

Bell, S, Clarke, R, Mounier-Jack, S and Paterson, P (2020). Parents’ and guardians’ views and experiences of accessing routine childhood vaccinations in England during the coronavirus (COVID-19) pandemic: cross-sectional survey and qualitative interview data. [Data Collection]. London School of Hygiene & Tropical Medicine, London, United Kingdom. https://doi.org/10.17037/DATA.00001861.

Bell, S, Clarke, R, Mounier-Jack, S and Paterson, P (2020). Parents’ and guardians’ views on the acceptability of a future COVID-19 vaccine for themselves and their children: cross-sectional survey and qualitative interview data. [Data Collection]. London School of Hygiene & Tropical Medicine, London, United Kingdom. https://doi.org/10.17037/DATA.00001862.

Besançon, L, Deforet, M, Leyrat, C, Segalas, C, Jiang, H and Masuzzo, P (2020). Open Science during the pandemic. [Data Collection]. OSF. https://osf.io/renxy/

Bhaskaran, K and Inglesby, P (2021). opensafely/covid-vs-noncovid-deaths-research. [Data Collection]. Github. https://github.com/opensafely/covid-vs-noncovid-deaths-research

Bottomley, C (2021). christian-bottomley/mixture_model_sarscov2. [Data Collection]. Github. https://github.com/christian-bottomley/mixture_model_sarscov2

Bracher, J, Wolffram, D, Deuschel, J, Görgen, K, Ketterer, J, Ullrich, A, Abbott, S, Barbarossa, M, Bertsimas, D, Bhatia, S, Bodych, M, Bosse, NI, Burgard, J, Castro, L, Fairchild, G, Fuhrmann, J, Funk, S, Gogolewski, K, Gu, Q, Heyder, S, Hotz, T, Kheifetz, Y, Kirsten, H, Krueger, T, Krymova, E, Li, M, Meinke, J, Michaud, I, Niedzielewski, K, Ożański, T, Rakowski, F, Scholz, M, Soni, S, Srivastava, A, Zieliński, J, Zou, D, Gneiting, T and Schienle, M (2021). KITmetricslab/covid19-forecast-hub-de. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.4439666

Brand, S and Ojal, J (2021). ojal/KenyaSerology. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.4705243

Burke, R (2021). rachaelmburke/tbcovidblantyre. [Data Collection]. Github. https://github.com/rachaelmburke/tbcovidblantyre

Candido, DS, Claro, IM, de Jesus, JG, Souza, WM, Moreira, FRR, Dellicour, S, Mellan, TA, du Plessis, L, Pereira, RHM, Sales, FCS, Manuli, ER, Thézé, J, Almeida, L, Menezes, MT, Voloch, CM, Fumagalli, MJ, Coletti, TM, da Silva, CAM, Ramundo, MS, Amorim, MR, Hoeltgebaum, HH, Mishra, S, Gill, MS, Carvalho, LM, Buss, LF, Prete, CA, Ashworth, J, Nakaya, HI, Peixoto, PS, Brady, OJ, Nicholls, SM, Tanuri, A, Rossi, Átila D., Braga, CK, Gerber, AL, de C. Guimarães, AP, Gaburo, N, Alencar, CS, Ferreira, AC, Lima, CX, Levi, JE, Granato, C, Ferreira, GM, Francisco, RS, Granja, F, Garcia, MT, Moretti, ML, Perroud, MW, Castiñeiras, Terezinha M. P. P., Lazari, CS, Hill, SC, de Souza Santos, AA, Simeoni, CL, Forato, J, Sposito, AC, Schreiber, AZ, Santos, MNN, de Sá, CZ, Souza, RP, Resende-Moreira, LC, Teixeira, MM, Hubner, J, Leme, PAF, Moreira, RG, Nogueira, ML, Ferguson, NM, Costa, SF, Proenca-Modena, JL, Vasconcelos, ATR, Bhatt, S, Lemey, P, Wu, C, Rambaut, A, Loman, NJ, Aguiar, RS, Pybus, OG, Sabino, EC and Faria, NR (2020). Data from: Evolution and epidemic spread of SARS-CoV-2 in Brazil. [Data Collection]. Dryad. http://doi.org/10.5061/dryad.rxwdbrv5z

Candido, DS, Claro, IM, de Jesus, JG, Souza, WM, Moreira, FRR, Dellicour, S, Mellan, TA, du Plessis, L, Pereira, RHM, Sales, FCS, Manuli, ER, Thézé, J, Almeida, L, Menezes, MT, Voloch, CM, Fumagalli, MJ, Coletti, TM, da Silva, CAM, Ramundo, MS, Amorim, MR, Hoeltgebaum, HH, Mishra, S, Gill, MS, Carvalho, LM, Buss, LF, Prete, CA, Ashworth, J, Nakaya, HI, Peixoto, PS, Brady, OJ, Nicholls, SM, Tanuri, A, Rossi, Átila D., Braga, CK, Gerber, AL, de C. Guimarães, AP, Gaburo, N, Alencar, CS, Ferreira, AC, Lima, CX, Levi, JE, Granato, C, Ferreira, GM, Francisco, RS, Granja, F, Garcia, MT, Moretti, ML, Perroud, MW, Castiñeiras, Terezinha M. P. P., Lazari, CS, Hill, SC, de Souza Santos, AA, Simeoni, CL, Forato, J, Sposito, AC, Schreiber, AZ, Santos, MNN, de Sá, CZ, Souza, RP, Resende-Moreira, LC, Teixeira, MM, Hubner, J, Leme, PAF, Moreira, RG, Nogueira, ML, Ferguson, NM, Costa, SF, Proenca-Modena, JL, Vasconcelos, ATR, Bhatt, S, Lemey, P, Wu, C, Rambaut, A, Loman, NJ, Aguiar, RS, Pybus, OG, Sabino, EC and Faria, NR (2020). Evolution and epidemic spread of SARS-CoV-2 in Brazil. [Data Collection]. Science. https://doi.org/10.1126/science.abd2161

Chapman, LAC, Barnard, RC, Russell, TW, Abbott, S, Van Zandvoort, K, Davies, NG and Kucharski, AJ (2021). Unexposed populations and potential COVID-19 burden in European countries as of 21st November 2021. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.5772162

Checchi, F (2020). francescochecchi/aden_covid. [Data Collection]. London School of Hygiene & Tropical Medicine, London, United Kingdom. https://github.com/francescochecchi/aden_covid

Clifford, S and Quilty, B (2020). cmmid/pcr_test_trace. [Data Collection]. Github. https://github.com/cmmid/pcr_test_trace

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

Clifford, S, Quilty, B, CMMID nCoV working group, Pearson, C, Flasche, S and Eggo, RM (2020). Effectiveness of airport-based interventions at detecting travellers and delaying an outbreak of COVID-19 (formerly 2019-nCoV). [Data Collection]. Github. https://github.com/cmmid/screening_outbreak_delay

Coletti, P, Wambua, J, Gimma, A, Willem, L, Vercruysse, S, Vanhoutte, B, Jarvis, CI, Van Zandvoort, K, Edmunds, J, Beutels, P and Hens, N (2020). Social contact data from CoMix survey (Belgium). [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.4035001

Davidson, J (2022). Clinical codelist - CPRD Aurum - COVID-19. [Data Collection]. London School of Hygiene & Tropical Medicine, London, United Kingdom. https://doi.org/10.17037/DATA.00002801.

Davidson, J (2022). Clinical codelist - HES - COVID-19. [Data Collection]. London School of Hygiene & Tropical Medicine, London, United Kingdom. https://doi.org/10.17037/DATA.00002800.

Davies, NG (2021). CSV-format data for: Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.5105920

Davies, NG (2020). cmmid/covid-age. [Data Collection]. Github. https://github.com/cmmid/covid-age

Davies, NG, Abbott, S, Barnard, RC, Jarvis, CI, Kucharski, AJ, Munday, J, Pearson, CAB, Russell, TW, Tully, DC, Washburne, AD, Wenseleers, T, Gimma, A, Waites, W, Wong, KL, van Zandvoort, K, Silverman, JD, Diaz-Ordaz, K, Keogh, R, Eggo, RM, Funk, S, Jit, M, Atkins, KE and Edmunds, WJ (2021). Analysis data and code for "Estimated transmissibility and impact of SARS-CoV-2 Variant of Concern 202012/01 in England". [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.4549674

Davies, NG, Abbott, S, Barnard, RC, Jarvis, CI, Kucharski, AJ, Munday, J, Pearson, CAB, Russell, TW, Tully, DC, Washburne, AD, Wenseleers, T, Gimma, A, Waites, W, Wong, KL, van Zandvoort, K, Silverman, JD, Diaz-Ordaz, K, Keogh, R, Eggo, RM, Funk, S, Jit, M, Atkins, KE and Edmunds, WJ (2021). Analysis data and code for "Estimated transmissibility and impact of SARS-CoV-2 lineage B.1.1.7 in England". [Data Collection]. Zenodo. http://doi.org/10.5281/zenodo.4562961

Davies, NG, Jarvis, CI, CMMID COVID-19 Working Group, Edmunds, WJ, Jewell, NP, Diaz-Ordaz, K and Keogh, RH (2021). Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.4579856

Davies, NG, Kucharski, AJ, Eggo, RM, Gimma, A, COVID-19 Working Group and Edmunds, WJ (2020). cmmid/covid-uk. [Data Collection]. Github. https://github.com/cmmid/covid-uk

De Figueiredo, A (2021). Global intent to accept COVID-19 vaccines. [Data Collection]. OSF. https://osf.io/8vezs

De figueiredo, A (2021). Impact of vaccine passports on inclination to accept COVID-19 vaccinations in the UK. [Data Collection]. OSF. https://osf.io/xh9p7/

Endo, A (2022). akira-endo/reanalysis_Fukumoto2021: 'Not finding causal effect' is not 'finding no causal effect' of school closure on COVID-19. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.6457915

Endo, A, Abbott, S, Kucharski, AJ and Funk, S (2020). Extended data: Estimating the overdispersion in COVID-19 transmission using outbreak sizes outside China. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.3740348

Endo, A, Abbott, S, Kucharski, AJ and Funk, S (2020). akira-endo/COVID19_clustersize: Estimating the amount of superspreading using outbreak sizes of COVID-19 outside China. [Data Collection]. Zenodo. http://doi.org/10.5281/zenodo.3741744

Endo, A and Kucharski, AJ (2020). akira-endo/COVID19_backwardtracing. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.4050267

Enria, L, Waterlow, N, Rogers, N, Brindle, H, Lal, S, Eggo, RM, Lees, S and Roberts, C (2020). Trust and Transparency in times of Crisis: Results from an Online Survey During the First Wave (April 2020) of the COVID-19 Epidemic in the UK - Qualitative Data. [Data Collection]. London School of Hygiene & Tropical Medicine, London, United Kingdom. https://doi.org/10.17037/DATA.00001859.

Enria, L, Waterlow, N, Rogers, N, Brindle, H, Lal, S, Eggo, RM, Lees, S and Roberts, C (2021). Trust and Transparency in times of Crisis: Results from an Online Survey During the First Wave (April 2020) of the COVID-19 Epidemic in the UK - Quantitative Data. [Data Collection]. London School of Hygiene & Tropical Medicine, London, United Kingdom. https://doi.org/10.17037/DATA.00002015.

Fernández-Niño, JA, Rojas Botero, ML, Arregoces, L and Ruiz, F (2022). Dataset of Study: Estimated number of deaths directly avoided because of COVID-19 vaccination among older adults in Colombia. [Data Collection]. Zenodo. https://doi.org/10.6084/m9.figshare.19122530.v1

Funk, S (2022). epiforecasts/ons_severity_estimates. [Data Collection]. Github. https://github.com/epiforecasts/ons_severity_estimates

Gaskell, KM, Johnson, M, Gould, V, Hunt, A, Stone, NR, Waites, W, Kasstan, B, Chantler, T, Lal, S, Roberts, Ch, Goldblatt, D, Eggo, RM and Marks, M (2021). Extremely high SARS-CoV-2 seroprevalence in a strictly-Orthodox Jewish community in the UK. [Data Collection]. London School of Hygiene & Tropical Medicine, London, United Kingdom. https://doi.org/10.17037/DATA.00002084.

Gibbs, H (2021). cmmid/uk_movement_communities_covid. [Data Collection]. Github. https://github.com/cmmid/uk_movement_communities_covid

Gibbs, H, CMMID nCov Working Group, Eggo, RM, Grundy, C and Kucharski, AJ (2020). UK Colocation Dashboard. [Data Collection]. Github. https://cmmid.github.io/colocation_dashboard_cmmid/

Gibbs, H, Waterlow, NR, Cheshire, J, Danon, L, Liu, Y, Grundy, C, Kucharski, AJ and Eggo, RM (2021). Population disruption: estimating changes in population distribution in the UK during the COVID-19 pandemic - Estimates for Local Authority Districts. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.5013619

Gibbs, H, Waterlow, NR, Cheshire, J, Danon, L, Liu, Y, Grundy, C, Kucharski, AJ and Eggo, RM (2022). hamishgibbs/facebook_population_2020_2021. [Data Collection]. Github. https://github.com/hamishgibbs/facebook_population_2020_2021

Gimma, A, Munday, JD, Wong, KLM, Coletti, P, Van Zandvoort, K, Prem, K, Klepac, P, Rubin, GJ, Funk, S, Edmunds, WJ and Jarvis, CI (2022). Mean contacts by age and date. [Data Collection]. PLOS Medicine. https://doi.org/10.1371/journal.pmed.1003907.s015

Gimma, A, Wong, KL, Coletti, P and Jarvis, CI (2021). CoMix social contact data (Austria). [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.4775972

Gimma, A, Wong, KL, Coletti, P and Jarvis, CI (2021). CoMix social contact data (France). [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.5040870

Gimma, A, Wong, KL, Coletti, P and Jarvis, CI (2021). CoMix social contact data (Italy). [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.5041112

Gimma, A, Wong, KL, Coletti, P and Jarvis, CI (2021). CoMix social contact data (Poland). [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.5041128

Gimma, A, Wong, KL, Coletti, P and Jarvis, CI (2021). CoMix social contact data (Portugal). [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.5041140

Gimma, A, Wong, KL, Coletti, P and Jarvis, CI (2021). CoMix social contact data (Spain). [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.5040839

Gimma, A, Wong, KL, Coletti, P and Jarvis, CI (2021). CoMix social contact data (Denmark). [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.5040530

Gimma, A, Wong, KL, Coletti, P and Jarvis, CI (2022). CoMix social contact data (Estonia). [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.6535312

Glazik, R (2021). Data supporting "A Snapshot of the Practicality of, and Barriers to, Implementation of COVID-19 Interventions: Public Health and Healthcare Workers' Perceptions". [Data Collection]. London School of Hygiene and Tropical Medicine, London, United Kingdom. https://doi.org/10.17037/DATA.00002321.

Ha, BTT, Ngoc Quang, L, Quoc Thanh, P, Duc, DM, Mirzoev, T and Bui, TMA (2021). Community engagement in the prevention and control of COVID-19: Insights from Vietnam. Qualitative transcripts. [Data Collection]. PLOS One. https://doi.org/10.1371/journal.pone.0254432.s002

Hellewell, J (2020). cmmid/ringbp. [Data Collection]. Github. https://github.com/cmmid/ringbp

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/

Hellewell, J, Lucas, T, Davis, E, Abbott, S, Gimma, A and Thompson, R (2020). timcdlucas/ringbp: Code as used in the paper "Engagement and adherence trade-offs for SARS-CoV-2 contact tracing". [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.4221774

Hodgson, D and Abbott, S (2022). dchodge/hero-study: Version submitted with WOR reviewers comments. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.5215671

Jarvis, C (2021). jarvisc1/comix_uk_covid_restrictions. [Data Collection]. Github. https://github.com/jarvisc1/comix_uk_covid_restrictions

Jarvis, C, Van zandvoort, K, Gimma, A, Prem, K, CMMID, Cwg, Klepac, P, Rubin, GJ and Edmunds, WJ (2020). Contact survey during COVID-19. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.3741391

Jombart, T, Abbott, S, Gimma, A, Van zandvoort, K and Jarvis, C (2020). Inferring COVID-19 cases from recent death. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.3733046

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

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

Jung, S, Endo, A, Kinoshita, R and Nishiura, H (2021). SungmokJung/Projection_Japan_COVID19 v1.0.0. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.4576936

Kayiga, H, Genevive, DA, Amuge, PM, Ssemata, AS, Nanzira, RS and Nakimuli, A (2021). Lived experiences of frontline healthcare providers offering maternal and newborn services amidst the novel corona virus disease 19 pandemic in Uganda: A qualitative study. S1 Dataset. [Data Collection]. PLOS ONE. https://doi.org/10.1371/journal.pone.0259835.s001

Kitonsa, J, Kamacooko, O, Bahemuka, UM, Kibengo, F, Kakande, A, Wajja, A, Basajja, V, Lumala, A, Ssemwanga, E, Asaba, R, Mugisha, J, Pierce, BF, Shattock, R, Kaleebu, P and Ruzagira, E (2021). Survey data on willingness to participate in COVID-19 vaccine trials among healthcare workers in three Ugandan hospitals. [Data Collection]. London School of Hygiene & Tropical Medicine, London, United Kingdom. https://doi.org/10.17037/DATA.00002168.

Koltai, M (2021). mbkoltai/covid_lmic_model: Model fitting excess mortality data in Mogadishu v1.0. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.5534762

Kucharski, AJ (2021). adamkucharski/covid-import-model. [Data Collection]. Github. https://github.com/adamkucharski/covid-import-model

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

Laban, N (2021). Comparable exposure to SARS-CoV-2 in young children and healthcare workers in Zambia. [Data Collection]. Figshare. https://doi.org/10.6084/m9.figshare.14237285.v2

Leclerc, QJ, Fuller, NM, Knight, LE, Funk, S and Knight, GM (2020). COVID19 settings of transmission - collected reports database. [Data Collection]. Figshare. https://doi.org/10.6084/m9.figshare.12173343.v5

Leclerc, QJ, Nightingale, E and Abbott, S (2020). qleclerc/nhs_pathways_report. [Data Collection]. Github. https://github.com/qleclerc/nhs_pathways_report

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

Lindsey, BB, Villabona-Arenas, CJ, Atkins, KE and Campbell, F (2021). Chjulian/sheffield_HT: Characterising within-hospital SARS-CoV-2 transmission events. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.5769865

Liu, Y (2020). yangclaraliu/COVID19_NPIs_vs_Rt. [Data Collection]. Github. https://github.com/yangclaraliu/COVID19_NPIs_vs_Rt

Liu, Y (2022). yangclaraliu/COVID_Vac_Delay. [Data Collection]. Github. https://github.com/yangclaraliu/COVID_Vac_Delay

Liu, Y, Funk, S and Flasche, S (2020). yangclaraliu/2019nCoV_proportion_asym: WOR Submission. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.3709941

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

Liu, Y, Sandmann, FG, Barnard, RC, Pearson, CA, CMMID Working-19 Working Group, Pastore, R, Pebody, R, Flasche, S and Jit, M (2021). Optimising health and economic impacts of COVID-19 vaccine rollout strategies in the WHO European Region. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.4964148

Lovell-Read, FA, Funk, S, Obolski, U, Donnelly, CA and Thompson, RN (2021). Supplementary material from "Interventions targeting non-symptomatic cases can be important to prevent local outbreaks: SARS-CoV-2 as a case study". [Data Collection]. The Royal Society. https://doi.org/10.6084/m9.figshare.c.5416023.v1

Marshall, G, Skeva, R, Jay, C and Fearon, E (2022). Interview summary data supporting "Public involvement in pandemic modelling: a qualitative study of Test, Trace and Isolate practices in the UK and implications for modelling". [Data Collection]. Zenodo. https://doi.org/10.6084/m9.figshare.15067119.v2

Mccreesh, N, Dlamini, V, Edwards, A, Olivier, S, Dayi, N, Dikgale, K, Nxumalo, S, Dreyer, J, Baisley, K, Siedner, MJ, White, RG, Herbst, K, Grant, AD and Harling, G (2021). Social contact information from PIPSA residents in uMkhanyakude before and during the Covid-19 pandemic – data from the Umoya Omuhle and Covid Social Contacts studies. [Data Collection]. AHRI Data Repository. https://doi.org/10.23664/AHRI.UOANDCSC.DATASET.2021

Mee, P, Alexander, N and Colón-González, FJ (2021). Paul-Mee/clic_brazil. [Data Collection]. Github. https://github.com/Paul-Mee/clic_brazil

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

Munday, JD and Jarvis, CI (2021). jdmunday/CoMix_schools_reopening. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.5172069

Munday, JD, Jarvis, CI, Gimma, A, Wong, KL, van Zandvoort, K, Funk, S and Edmunds, WJ (2021). CoMix - Age structured contact matrices for 9 key periods of the COVID-19 epidemic in England. [Data Collection]. Zenodo. http://doi.org/10.5281/zenodo.4677018

Nightingale, E (2022). esnightingale/covid_deaths_spatial. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.5763663

Nightingale, E, Waterlow, N, Clifford, S and Rees, E (2020). COVID-19 length of hospital stay. [Data Collection]. Github. https://github.com/esnightingale/los_review

Otieno, GP, Murunga, N, Agoti, CN, Gallagher, KE, Awori, JO and Nokes, DJ (2020). Replication Data for: Surveillance of endemic human coronaviruses (HCoV-NL63, OC43 and 229E) associated with pneumonia in Kilifi, Kenya. [Data Collection]. Harvard Dataverse. https://doi.org/10.7910/DVN/ZQ1DJY

Palmer, J, Sherratt, K, Martin-Nielsen, R, Bevan, J, Gibbs, H, CMMID COVID-19 Working Group, Funk, S and Abbott, S (2021). covidregionaldata: Subnational data for COVID-19 epidemiology. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.3957539

Parker, E (2020). Covid 2019 tracker. [Data Collection]. London School of Hygiene & Tropical Medicine, London, United Kingdom. https://vac-lshtm.shinyapps.io/ncov_tracker/

Parker, E (2021). vac-lshtm/VaC_tracker. [Data Collection]. Github. https://github.com/vac-lshtm/VaC_tracker

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Pavelka, M, van Zandvoort, K, Abbott, S, Sherratt, K, Majdan, M, Jarcuska, P, Krajci, M, Flasche, S and Funk, S (2021). Data and R code accompanying the manuscript "The impact of population-wide rapid antigen testing on SARS-CoV-2 prevalence in Slovakia". [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.4570938

Pearce, N (2021). PROTECT initiative extended Covid-19 occupational questionnaire. [Data Collection]. OSF. https://doi.org/10.17605/OSF.IO/HDC8S

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

Pearson, CAB (2021). cmmid/covidTestVac. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.4725814

Pearson, CAB, Russell, TW and Kucharski, AJ (2021). cmmid/SA2UK. [Data Collection]. Github. https://github.com/cmmid/SA2UK

Pearson, CAB, Russell, TW and Kucharski, AJ (2022). cmmid/SA2UK: CEA submission. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.6979557

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.

Phelan, J and Deelder, W (2020). COVID-Profiler. [Data Collection]. Github. https://github.com/jodyphelan/covid-profiler

Pillai, AN, Hladish, T, Pearson, CAB, Toh, B, Noah4944 and Stoltzfus, A (2023). tjhladish/covid-abm: Active Vaccination Experiment 2023-02-02. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.7601663

Prem, K (2021). kieshaprem/synthetic-contact-matrices. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.4889499

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

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

Pung, R (2021). rachaelpung/serial_interval_covid_b.1.617.2. [Data Collection]. Github. https://github.com/rachaelpung/serial_interval_covid_b.1.617.2

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

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

Quilty, BJ, Hellewell, J, Clifford, S and CMMID COVID-19 working group (2021). R code for: "Confirmatory testing with a second lateral flow test may mitigate false positives at low levels of SARS-CoV-2 prevalence in English schools". [Data Collection]. London School of Hygiene & Tropical Medicine, London, United Kingdom. https://doi.org/10.17037/DATA.00002074.

Rasoanaivo, TF, Bourner, J, Randriamparany, RN, Gamana, TM, Andrianaivoarimanana, V, Raherivelo, MH, Randriamampionona, H, Rajerison, M, Raberahona, M, Salam, AP, Edwards, T, Olliaro, PL and Randremanana, RV (2021). Data for: "The impact of COVID-19 on clinical research for Neglected Tropical Diseases (NTDs): A case study of bubonic plague". [Data Collection]. PLOS Neglected Tropical Diseases. https://doi.org/10.1371/journal.pntd.0010064.s001

Roberts, C, Brindle, H, Rogers, N, Eggo, RM, Enria, L and Lees, S (2021). Data for: "Vaccine Confidence and Hesitancy at the start of COVID-19 vaccine deployment in the UK: An embedded mixed-methods study". [Data Collection]. London School of Hygiene & Tropical Medicine, London, United Kingdom. https://doi.org/10.17037/DATA.00002337.

Rosello, A, Abbott, S and Barnard, RC (2021). rmjlros/COVID19_care_home_NPIs. [Data Collection]. Github. https://github.com/rmjlros/COVID19_care_home_NPIs

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

Russell, TW, Hellewell, J, Abbott, S, Jarvis, C, Zandvoort, Kv, Ratnayake, R, CMMID nCov working group, Flasche, S, Eggo, RM, Edmunds, WJ and Kucharski, AJ (2020). thimotei/CFR_calculation. [Data Collection]. Github. https://github.com/thimotei/CFR_calculation

Russell, TW, Hellewell, J, Jarvis, CI, Van-Zandvoort, K, Abbott, S, Ratnayake, R, Flasche, S, Eggo, RM and Kucharski, AJ (2020). Estimating the infection and case fatality ratio for COVID-19 using age-adjusted data from the outbreak on the Diamond Princess cruise ship. [Data Collection]. Github. https://github.com/thimotei/cCFRDiamondPrincess

Russell, TW, Wu, JT, Clifford, S, CMMID COVID-19 working group, Edmunds, WJ, Kucharski, AJ and Jit, M (2020). thimotei/covid_travel_restrictions. [Data Collection]. Github. https://github.com/thimotei/covid_travel_restrictions

Sera, F, Abbott, S and Roye, D (2021). fsera/COVIDWeather. [Data Collection]. London School of Hygiene & Tropical Medicine, London, United Kingdom. https://doi.org/10.5281/zenodo.5215841

Sherratt, K (2020). epiforecasts/rt-comparison-uk-public: v1.0.0. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.4029074

Sherratt, K and Funk, S (2022). covid19-forecast-hub-europe/euro-hub-ensemble: Zenodo release. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.6895699

Simons, D, Shahab, L, Brown, J and Perski, O (2021). The association of smoking status with SARS-CoV-2 infection, hospitalisation and mortality from COVID-19: A living rapid evidence review and Bayesian meta-analyses (version 11) - Data. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.4002046

Strongman, H and Carreira, H (2021). STATA Do files for "Factors associated with excess mortality in the first wave of COVID-19 pandemic in the UK: a cohort analysis using the Clinical Practice Research Databank". [Data Collection]. London School of Hygiene & Tropical Medicine, London, United Kingdom. https://doi.org/10.17037/DATA.00002560.

Tazare, J (2020). johntaz/COVID-Collateral. [Data Collection]. Github. https://github.com/johntaz/COVID-Collateral

Tazare, J and Walker, A (2022). opensafely/post-covid-outcomes-research. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.6475807

Thomas, S (2020). COVID-19 risk group - Neurological disease codelist. [Data Collection]. London School of Hygiene & Tropical Medicine, London, United Kingdom. https://doi.org/10.17037/DATA.00001704.

Tomlinson, LA, Iwagami, M, Bidulka, P and Wong, AY (2020). Supplementary data for “Comparisons of Staphylococcus aureus infection and other outcomes between users of angiotensin-converting-enzyme inhibitors and angiotensin II receptor blockers: lessons for COVID-19 from a nationwide cohort study”. [Data Collection]. London School of Hygiene & Tropical Medicine, London, United Kingdom. https://doi.org/10.17037/PUBS.04656578.

University of Glasgow, MRC/CSO Social and Public Health Sciences, University College London and London School of Hygiene and Tropical Medicine (2021). National Survey of Sexual Attitudes and Lifestyles COVID-19 Study, 2020. [Data Collection]. UK Data Service. http://doi.org/10.5255/UKDA-SN-8865-1

Uyoga, S, Adetifa, IM, Otiende, M, Gitonga, JN, Mugo, D, Nyagwange, J, Karanja, HK, Tuju, J, Makale, J, Aman, R, Mwangangi, M, Amoth, P, Kasera, K, Ng’ang’a, W, Chege, E, Yegon, C, Kithi, K, Odhiambo, E, Rotich, T, Orgut, I, Kihara, S, Bottomley, C, Kagucia, EW, Gallagher, KE, Etyang, A, Voller, S, Lambe, T, Wright, D, Barasa, E, Tsofa, B, Mwangangi, J, Bejon, P, Ochola-Oyier, LI, Warimwe, GM, Agweyu, A and Scott, JAG (2021). Replication Data for: Prevalence of SARS-CoV-2 Antibodies from a one-year National Serosurveillance of Kenyan Blood Transfusion Donors. [Data Collection]. Harvard Dataverse. https://doi.org/10.7910/DVN/3E1YSQ

Vaccine Centre (2020). COVID-19 vaccine development pipeline. [Data Collection]. London School of Hygiene & Tropical Medicine, London, United Kingdom. https://vac-lshtm.shinyapps.io/ncov_vaccine_landscape/

Walker, J, Grint, D, Strongman, H, Eggo, RM, Peppa, M, Minassian, C, Mansfield, KE, Rentsch, C, Douglas, IJ, Mathur, R, Wong, A, Quint, JK, Andrews, N, Lopez-bernal, J, Scott, A, Ramsay, M, Smeeth, L and McDonald, H (2020). UK prevalence of risk factors for severe COVID-19 disease, by age and region: point prevalence estimates in 2019 and 2014, using electronic health records. [Data Collection]. London School of Hygiene & Tropical Medicine, London, United Kingdom. https://doi.org/10.17037/DATA.00001833.

Wang, SY, Stark, A, Evan Ray, Bosse, N, Reich, NG, Sherratt, K, Shah, A, Wattanachit, N, Khoale1096, Huang, YD, Gerding, A, Gruson, H, Cramer, E, Shandross, L, Abbott, S and Funk, S (2021). reichlab/covidHubUtils. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.5207939

Waterlow, NR, Van Leeuwen, E, Davies, N, Flasche, S and Eggo, RM (2021). cmmid/coronavirus_immunity. [Data Collection]. Github. https://github.com/cmmid/coronavirus_immunity

Williamson, E, Walker, AJ, Bhaskaran, KJ, Bacon, S, Bates, C, Morton, CE, Curtis, HJ, Mehrkar, A, Evans, D, Inglesby, P, Cockburn, J, Mcdonald, HI, MacKenna, B, Tomlinson, L, Douglas, IJ, Rentsch, CT, Mathur, R, Wong, A, Grieve, R, Harrison, D, Forbes, H, Schultze, A, Croker, RT, Parry, J, Hester, F, Harper, S, Perera, R, Evans, S, Smeeth, L and Goldacre, B (2020). opensafely/risk-factors-research. [Data Collection]. Github. https://github.com/ebmdatalab/opensafely-risk-factors-research

Wong, A, Bacon, S, Walker, A, Davy, S, Inglesby, P and MacKenna, B (2021). opensafely/anticoagulants-research. [Data Collection]. Github. https://github.com/opensafely/anticoagulants-research

Wu, JT, Mei, S, Luo, S, Leung, K, Liu, D, Lv, Q, Liu, J, Li, Y, Prem, K, Jit, M, Weng, J, Feng, T, Zheng, X and Leung, GM (2021). Table S4 from A global assessment of the impact of school closure in reducing COVID-19 spread. [Data Collection]. Figshare. https://doi.org/10.6084/m9.figshare.16851696.v1

Yakob, L (2021). lwyakob/COVIDquarantine. [Data Collection]. Github. https://github.com/lwyakob/COVIDquarantine

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

actions-user, Sherratt, K, Gruson, H, Funk, S, Bracher, J, BIOCOM-SC, Walraven, R, miraanto, h-veronika, Rodiah, I, gr3gr3, Kraus, D, hgurung-iem, epiforecasts-bot, Xu, FT, Heyder, S, aniruddhadiga, Abbott, S, Sun, T, Mingio, M, Deuschel, J, pmontman, janezz25, neele-itwm, Gibson, G, EpiGraph, Tarantino, B, Karlen, D, Bhatia, S and borjarv (2022). covid19-forecast-hub-europe/covid19-forecast-hub-europe. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.6401421