Akira Endo, MD PhD

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Infectious disease modeller at London School of Hygiene & Tropical Medicine.
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Research interests

Compared with other types of diseases, infectious diseases are unique in that protecting an individual from a disease also means protecting other people by reducing their risk of exposure to the pathogen. This “interdependency” makes the control of infectious disease outbreaks an important social agenda. My current research interests include disease spread within and across households/schools/workplaces, improving vaccine evaluation methodologies and optimal control strategies.

Work

Education

Preprints

  1. Endo A. ‘Not finding causal effect’ is not ‘finding no causal effect’ of school closure on COVID-19 [version 1; peer review: 1 approved, 1 approved with reservations]. F1000Research. 2022;11:456 doi: 10.12688/f1000research.111915.1
  2. Abbott S, Hellewell J, Thompson RN, Sherratt K, Gibbs HP, Bosse NI, Munday JD, Meakin S, Doughty EL, Chun JY, Chan YD, Finger F, Campbell P, Endo A, Pearson CAB, Gimma A, Russell T, CMMID COVID modelling group, Flasche S, Kucharski AJ, Eggo RM, Funk S. Estimating the time-varying reproduction number of SARS-CoV-2 using national and subnational case counts [version 1; peer review: awaiting peer review]. Wellcome Open Res. 2020, 5:112 doi:10.12688/wellcomeopenres.16006.1

Publications

  1. Endo A, Murayama H, Abbott S, Ratnayake R, Pearson CAB, Edmunds WJ, Fearon E, Funk S. Heavy-tailed sexual contact networks and the epidemiology of monkeypox outbreak in the global outbreak, 2022. Science. 2022:eadd4507. doi: 10.1126/science.add4507
  2. Endo A, Asai Y, Tajima T, Endo M, Akiyama T, Matsunaga N, Ishioka H, Tsuzuki S, Ohmagari N. Temporal trends in microbial detection during the COVID-19 pandemic: analysis of the Japan Surveillance for Infection Prevention and Healthcare Epidemiology (J-SIPHE) database. J Infect Chemother. 2022. doi:10.1016/j.jiac.2022.08.028
  3. Endo A; CMMID COVID-19 Working Group, Uchida M, Liu Y, Atkins KE, Kucharski AJ, Funk S. Simulating respiratory disease transmission within and between classrooms to assess pandemic management strategies at schools. Proc Natl Acad Sci U S A. 2022;119(37):e2203019119. doi:10.1073/pnas.2203019119
  4. Hart WS, Abbott S, Endo A, Hellewell J, Miller E, Andrews N, Maini PK, Funk S, Thompson RN. Inference of the SARS-CoV-2 generation time using UK household data. Elife. 2022;11:e70767. doi: 10.7554/eLife.70767.
  5. Endo A, Uchida M, Hayashi N, Liu Y, Atkins KE, Kucharski AJ, Funk S. Within and between classroom transmission patterns of seasonal influenza among primary school students in Matsumoto city, Japan. Proc Natl Acad Sci U S A. 2021;118(46):e2112605118. doi:10.1073/pnas.2112605118
  6. Jung S, Endo A, Akhmetzhanov AR, Nishiura H. Predicting the effective reproduction number of COVID-19: Inference using human mobility, temperature, and risk awareness. Int J Infect Dis. 2021. doi:10.1016/j.ijid.2021.10.007
  7. Clifford S, Quilty BJ, Russell TW, Liu Y, Chan YD, Pearson CAB, Eggo RM, Endo A; CMMID COVID-19 Working Group, Flasche S, Edmunds WJ. Strategies to reduce the risk of SARS-CoV-2 importation from international travellers: modelling estimations for the United Kingdom, July 2020. Euro Surveill. 2021;26(39):2001440. doi:10.2807/1560-7917.ES.2021.26.39.2001440
  8. Endo A†, Jung S†, Kinoshita R, Nishiura H. Projecting a second wave of COVID-19 in Japan with variable interventions in high-risk settings. R Soc Open Sci. 2021;8:202169. doi:10.1098/rsos.202169
  9. Munday JD, Sherratt K, Meakin S, Endo A, Pearson CAB, Hellewell J, Abbott S, Bosse N; CMMID COVID-19 Working Group, Atkins KE, Wallinga J, Edmunds WJ, van Hoek AJ, Funk S. Implications of the school-household network structure on SARS-CoV-2 transmission under different school reopening strategies in England. Nat Commun. 2021;12:1942. doi:10.1038/s41467-021-22213-0
  10. Endo A; Centre for the Mathematical Modelling of Infectious Diseases (CMMID) COVID-19 Working Group, Leclerc QJ, Knight GM, Medley GF, Atkins KE, Funk S, Kucharski AJ. Implication of backward contact tracing in the presence of overdispersed transmission in COVID-19 outbreak. Wellcome Open Res. 2020;5:239. doi:10.12688/wellcomeopenres.16344.1
  11. Nishi A, Endo A†, Dewey G†, Neman S, Iwamoto SK, Ni MY, Tsugawa Y, Iosifidis G, Smith JD, Young S. Network Interventions for Managing the COVID-19 Pandemic and Sustaining Economy. Proc Natl Acad Sci U S A. 2020;117(48):30285-30294. doi:10.1073/pnas.2014297117
  12. Endo A, Funk S, Kucharski AJ. Bias correction methods for test-negative designs in the presence of misclassification. Epidemiology and Infection. 2020;148:E216. doi:10.1017/S0950268820002058
  13. Jit M, Jombart T, Nightingale ES, Endo A, Abbott S; LSHTM Centre for Mathematical Modelling of Infectious Diseases COVID-19 Working Group, Edmunds WJ. Estimating number of cases and spread of coronavirus disease (COVID-19) using critical care admissions, United Kingdom, February to March 2020. Euro Surveill. 2020;25(18):2000632. doi:10.2807/1560-7917.ES.2020.25.18.2000632
  14. Endo A; Centre for the Mathematical Modelling of Infectious Diseases COVID-19 Working Group, Abbott S, Kucharski AJ, Funk S. Estimating the overdispersion in COVID-19 transmission using outbreak sizes outside China. Wellcome Open Res. 2020;5:67. doi:10.12688/wellcomeopenres.15842.3
  15. Endo A, Nishiura H. Age and geographic dependence of Zika virus infection during the outbreak on Yap island, 2007. Math Biosci Eng. 2020;17(4):4115-4126. doi:10.3934/mbe.2020228
  16. Endo A, Uchida M, Kucharski AJ, Funk S. Fine-scale family structure shapes influenza transmission risk in households: Insights from primary schools in Matsumoto city, 2014/15. PLoS Comput Biol. 2019;15(12):e1007589. doi:10.1371/journal.pcbi.1007589
  17. Endo A, van Leeuwen E, Baguelin M. Introduction to particle Markov-chain Monte Carlo for disease dynamics modellers. Epidemics. 2019;29:100363. doi:10.1016/j.epidem.2019.100363
  18. Matsuyama R, Akhmetzhanov AR, Endo A, Lee H, Yamaguchi T, Tsuzuki S, Nishiura H. Uncertainty and sensitivity analysis of the basic reproduction number of diphtheria: a case study of a Rohingya refugee camp in Bangladesh, November-December 2017. PeerJ. 2018;6:e4583. doi:10.7717/peerj.4583
  19. Endo A, Ejima K, Nishiura H. Capturing the transmission dynamics of the 2009 Japanese pandemic influenza H1N1 in the presence of heterogeneous immunity. Ann Epidemiol. 2018;28(5):293-300.e1. doi:10.1016/j.annepidem.2018.02.011
  20. Nishiura H, Lee H, Yuan B, Endo A, Akhmetzhanov AR, Chowell G. Infectious disease risks among refugees from North Korea. Int J Infect Dis. 2018;66:22-25. doi:10.1016/j.ijid.2017.10.021
  21. Endo A, Nishiura H. The Role of Migration in Maintaining the Transmission of Avian Influenza in Waterfowl: A Multisite Multispecies Transmission Model along East Asian-Australian Flyway. Can J Infect Dis Med Microbiol. 2018;2018:3420535. doi:10.1155/2018/3420535
  22. Nishiura H, Endo A, Saitoh M, et al. Identifying determinants of heterogeneous transmission dynamics of the Middle East respiratory syndrome (MERS) outbreak in the Republic of Korea, 2015: a retrospective epidemiological analysis. BMJ Open. 2016;6(2):e009936. doi:10.1136/bmjopen-2015-009936
  23. Mizumoto K, Endo A, Chowell G, Miyamatsu Y, Saitoh M, Nishiura H. Real-time characterization of risks of death associated with the Middle East respiratory syndrome (MERS) in the Republic of Korea, 2015. BMC Med. 2015;13:228. doi:10.1186/s12916-015-0468-3
  24. Endo A, Nishiura H. Transmission dynamics of vivax malaria in the republic of Korea: Effectiveness of anti-malarial mass chemoprophylaxis. J Theor Biol. 2015;380:499-505. doi:10.1016/j.jtbi.2015.06.024

(†Equal contribution)

Publications (consortium)

  1. Jarvis CI, Gimma A, van Zandvoort K, Wong KLM; CMMID COVID-19 working group, Edmunds WJ. The impact of local and national restrictions in response to COVID-19 on social contacts in England: a longitudinal natural experiment. BMC Med. 2021;19(1):52. doi: 10.1186/s12916-021-01924-7
  2. Meakin S, Abbott S, Bosse N, Munday J, Gruson H, Hellewell J, Sherratt K; CMMID COVID-19 Working Group, Funk S. Comparative assessment of methods for short-term forecasts of COVID-19 hospital admissions in England at the local level. BMC Med. 2022;20(1):86. doi: 10.1186/s12916-022-02271-x
  3. Koltai M, Warsame A, Bashiir F, Freemantle T, Reeve C, Williams C, Jit M, Flasche S, Davies NG; CMMID COVID-19 working group, Aweis A, Ahmed M, Dalmar A, Checchi F. Date of introduction and epidemiologic patterns of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Mogadishu, Somalia: estimates from transmission modelling of satellite-based excess mortality data in 2020. Wellcome Open Res. 2022;6:255. doi: 10.12688/wellcomeopenres.17247.2
  4. Liu Y, Sandmann FG, Barnard RC, Pearson CAB, Pastore R, Pebody R, Flasche S, Jit M. Optimising health and economic impacts of COVID-19 vaccine prioritisation strategies in the WHO European Region: a mathematical modelling study. Lancet Reg Health Eur. 2022;12:100267. doi: 10.1016/j.lanepe.2021.100267
  5. Nightingale ES, Brady OJ; CMMID Covid-19 working group, Yakob L. The importance of saturating density dependence for population-level predictions of SARS-CoV-2 resurgence compared with density-independent or linearly density-dependent models, England, 23 March to 31 July 2020. Euro Surveill. 2021;26(49):2001809. doi: 10.2807/1560-7917.ES.2021.26.49.2001809
  6. Gibbs H, Nightingale E, Liu Y, Cheshire J, Danon L, Smeeth L, Pearson CAB, Grundy C; LSHTM CMMID COVID-19 working group, Kucharski AJ, Eggo RM. Detecting behavioural changes in human movement to inform the spatial scale of interventions against COVID-19. PLoS Comput Biol. 2021;17(7):e1009162. doi: 10.1371/journal.pcbi.1009162
  7. Pearson CAB, Bozzani F, Procter SR, Davies NG, Huda M, Jensen HT, Keogh-Brown M, Khalid M, Sweeney S, Torres-Rueda S; CHiL COVID-19 Working Group; CMMID COVID-19 Working Group, Eggo RM, Vassall A, Jit M. COVID-19 vaccination in Sindh Province, Pakistan: A modelling study of health impact and cost-effectiveness. PLoS Med. 2021;18(10):e1003815. doi: 10.1371/journal.pmed.1003815. Erratum in: PLoS Med. 2022;19(5):e1003990.
  8. Sherratt K, Abbott S, Meakin SR, Hellewell J, Munday JD, Bosse N; CMMID COVID-19 Working Group, Jit M, Funk S. Exploring surveillance data biases when estimating the reproduction number: with insights into subpopulation transmission of COVID-19 in England. Philos Trans R Soc Lond B Biol Sci. 2021;376(1829):20200283. doi: 10.1098/rstb.2020.0283
  9. McCarthy CV, Sandmann FG; CMMID COVID-19 Working Group, Jit M. Global and national estimates of the number of healthcare workers at high risk of SARS-CoV-2 infection. J Hosp Infect. 2021;111:205-207. doi: 10.1016/j.jhin.2021.02.012.
  10. Munday JD, Jarvis CI, Gimma A, Wong KLM, van Zandvoort K; CMMID COVID-19 Working Group, Funk S, Edmunds WJ. Estimating the impact of reopening schools on the reproduction number of SARS-CoV-2 in England, using weekly contact survey data. BMC Med. 2021;19(1):233. doi: 10.1186/s12916-021-02107-0
  11. Prem K, Zandvoort KV, Klepac P, Eggo RM, Davies NG; Centre for the Mathematical Modelling of Infectious Diseases COVID-19 Working Group, Cook AR, Jit M. Projecting contact matrices in 177 geographical regions: An update and comparison with empirical data for the COVID-19 era. PLoS Comput Biol. 2021;17(7):e1009098. doi: 10.1371/journal.pcbi.1009098
  12. Procter SR, Abbas K, Flasche S, Griffiths U, Hagedorn B, O’Reilly KM; CMMID COVID-19 Working Group, Jit M. SARS-CoV-2 infection risk during delivery of childhood vaccination campaigns: a modelling study. BMC Med. 2021;19(1):198. doi: 10.1186/s12916-021-02072-8
  13. Hellewell J, Russell TW; SAFER Investigators and Field Study Team; Crick COVID-19 Consortium; CMMID COVID-19 working group, Beale R, Kelly G, Houlihan C, Nastouli E, Kucharski AJ. Estimating the effectiveness of routine asymptomatic PCR testing at different frequencies for the detection of SARS-CoV-2 infections. BMC Med. 2021;19(1):106. doi: 10.1186/s12916-021-01982-x
  14. Leng T, White C, Hilton J, Kucharski A, Pellis L, Stage H, Davies NG; Centre for Mathematical Modelling of Infectious Disease 2019 nCoV Working Group, Keeling MJ, Flasche S. The effectiveness of social bubbles as part of a Covid-19 lockdown exit strategy, a modelling study. Wellcome Open Res. 2021;5:213. doi: 10.12688/wellcomeopenres.16164.2
  15. Pavelka M, Van-Zandvoort K, Abbott S, Sherratt K, Majdan M; CMMID COVID-19 working group; Inštitút Zdravotných Analýz, Jarčuška P, Krajčí M, Flasche S, Funk S. The impact of population-wide rapid antigen testing on SARS-CoV-2 prevalence in Slovakia. Science. 2021;372(6542):635-641. doi: 10.1126/science.abf9648.
  16. Leclerc QJ, Fuller NM, Keogh RH, Diaz-Ordaz K, Sekula R, Semple MG; ISARIC4C Investigators; CMMID COVID-19 Working Group, Atkins KE, Procter SR, Knight GM. Importance of patient bed pathways and length of stay differences in predicting COVID-19 hospital bed occupancy in England. BMC Health Serv Res. 2021;21(1):566. doi: 10.1186/s12913-021-06509-x
  17. Davies NG, Jarvis CI; CMMID COVID-19 Working Group, Edmunds WJ, Jewell NP, Diaz-Ordaz K, Keogh RH. Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7. Nature. 2021. doi:10.1038/s41586-021-03426-1
  18. Sandmann FG, Davies NG, Vassall A, Edmunds WJ, Jit M; Centre for the Mathematical Modelling of Infectious Diseases COVID-19 working group. The potential health and economic value of SARS-CoV-2 vaccination alongside physical distancing in the UK: a transmission model-based future scenario analysis and economic evaluation. Lancet Infect Dis. 2021;21(7):962-974. doi: 10.1016/S1473-3099(21)00079-7. Erratum in: Lancet Infect Dis. 2021;21(10):e302.
  19. Mburu CN, Ojal J, Chebet R, Akech D, Karia B, Tuju J, Sigilai A, Abbas K, Jit M, Funk S, Smits G, van Gageldonk PGM, van der Klis FRM, Tabu C, Nokes DJ; LSHTM CMMID COVID-19 Working Group, Scott J, Flasche S, Adetifa I. The importance of supplementary immunisation activities to prevent measles outbreaks during the COVID-19 pandemic in Kenya. BMC Med. 2021;19(1):35. doi: 10.1186/s12916-021-01906-9
  20. Davies NG, Abbott S, Barnard RC, Jarvis CI, Kucharski AJ, Munday JD, Pearson CAB, Russell TW, Tully DC, Washburne AD, Wenseleers T, Gimma A, Waites W, Wong KLM, van Zandvoort K, Silverman JD; CMMID COVID-19 Working Group; COVID-19 Genomics UK (COG-UK) Consortium, Diaz-Ordaz K, Keogh R, Eggo RM, Funk S, Jit M, Atkins KE, Edmunds WJ. Estimated transmissibility and impact of SARS-CoV-2 lineage B.1.1.7 in England. Science. 2021:eabg3055. doi:10.1126/science.abg3055
  21. Liu Y, Morgenstern C, Kelly J, Lowe R; CMMID COVID-19 Working Group, Jit M. The impact of non-pharmaceutical interventions on SARS-CoV-2 transmission across 130 countries and territories. BMC Med. 2021;19(1):40. doi:10.1186/s12916-020-01872-8
  22. Jarvis CI, Gimma A, van Zandvoort K, Wong KLM; CMMID COVID-19 working group, Edmunds WJ. The impact of local and national restrictions in response to COVID-19 on social contacts in England: a longitudinal natural experiment. BMC Med. 2021;19(1):52. doi:10.1186/s12916-021-01924-7
  23. Leclerc QJ, Nightingale ES, Abbott S; CMMID COVID-19 Working Group, Jombart T. Analysis of temporal trends in potential COVID-19 cases reported through NHS Pathways England. Sci Rep. 2021;11:7106. doi:10.1038/s41598-021-86266-3
  24. Davies NG, Barnard RC, Jarvis CI, Russell TW, Semple MG, Jit M, Edmunds WJ; Centre for Mathematical Modelling of Infectious Diseases COVID-19 Working Group; ISARIC4C investigators. Association of tiered restrictions and a second lockdown with COVID-19 deaths and hospital admissions in England: a modelling study. Lancet Infect Dis. 2020;S1473-3099(20)30984-1. doi:10.1016/S1473-3099(20)30984-1
  25. Quilty BJ, Clifford S, Hellewell J, Russell TW, Kucharski AJ, Flasche S, Edmunds WJ; Centre for the Mathematical Modelling of Infectious Diseases COVID-19 working group. Quarantine and testing strategies in contact tracing for SARS-CoV-2: a modelling study. Lancet Public Health. 2021;S2468-2667(20)30308-X. doi: 10.1016/S2468-2667(20)30308-X
  26. Russell TW, Wu JT, Clifford S, Edmunds WJ, Kucharski AJ, Jit M; Centre for the Mathematical Modelling of Infectious Diseases COVID-19 working group. Effect of internationally imported cases on internal spread of COVID-19: a mathematical modelling study. Lancet Public Health. 2021;6(1):e12-e20. doi: 10.1016/S2468-2667(20)30263-2
  27. Quaife M, van Zandvoort K, Gimma A, Shah K, McCreesh N, Prem K, Barasa E, Mwanga D, Kangwana B, Pinchoff J; CMMID COVID-19 Working Group, Edmunds WJ, Jarvis CI, Austrian K. The impact of COVID-19 control measures on social contacts and transmission in Kenyan informal settlements. BMC Med. 2020;18(1):316. doi: 10.1186/s12916-020-01779-4
  28. van Zandvoort K, Jarvis CI, Pearson CAB, Davies NG; CMMID COVID-19 working group, Ratnayake R, Russell TW, Kucharski AJ, Jit M, Flasche S, Eggo RM, Checchi F. Response strategies for COVID-19 epidemics in African settings: a mathematical modelling study. BMC Med. 2020;18(1):324. doi: 10.1186/s12916-020-01789-2
  29. Davies NG, Kucharski AJ, Eggo RM, Gimma A, Edmunds WJ; Centre for the Mathematical Modelling of Infectious Diseases COVID-19 working group. Effects of non-pharmaceutical interventions on COVID-19 cases, deaths, and demand for hospital services in the UK: a modelling study. Lancet Public Health. 2020;5(7):e375-e385. doi: 10.1016/S2468-2667(20)30133-X
  30. Rees EM, Nightingale ES, Jafari Y, Waterlow NR, Clifford S, Pearson CAB, CMMID Working Group, Jombart T, Procter SR, Knight GM. COVID-19 length of hospital stay: a systematic review and data synthesis. BMC Med. 2020;18:270. doi:10.1186/s12916-020-01726-3
  31. Emery JC, Russell TW, Liu Y, Hellewell J, Pearson CA; CMMID COVID-19 Working Group, Knight GM, Eggo RM, Kucharski AJ, Funk S, Flasche S, Houben RMGJ. The contribution of asymptomatic SARS-CoV-2 infections to transmission on the Diamond Princess cruise ship. Elife. 2020;9:e58699. doi:10.7554/eLife.58699
  32. Firth JA, Hellewell J, Klepac P, Kissler S; CMMID COVID-19 Working Group, Kucharski AJ, Spurgin LG. Using a real-world network to model localized COVID-19 control strategies. Nat Med. 2020;10.1038/s41591-020-1036-8. doi:10.1038/s41591-020-1036-8
  33. Abbas K, Procter SR, van Zandvoort K, Clark A, Funk S, Mengistu T, Hogan D, Dansereau E, Jit M, Flasche S; LSHTM CMMID COVID-19 Working Group. Routine childhood immunisation during the COVID-19 pandemic in Africa: a benefit-risk analysis of health benefits versus excess risk of SARS-CoV-2 infection. Lancet Glob Health. 2020;S2214-109X(20)30308-9. doi:10.1016/S2214-109X(20)30308-9
  34. Leclerc QJ, Fuller NM, Knight LE; CMMID COVID-19 Working Group, Funk S, Knight GM. What settings have been linked to SARS-CoV-2 transmission clusters?. Wellcome Open Res. 2020;5:83. doi:10.12688/wellcomeopenres.15889.2
  35. Jarvis CI, Van Zandvoort K, Gimma A, Prem K; CMMID COVID-19 working group, Klepac P, Rubin GJ, Edmunds WJ. Quantifying the impact of physical distance measures on the transmission of COVID-19 in the UK. BMC Med. 2020;18(1):124. doi: 10.1186/s12916-020-01597-8
  36. Clark A, Jit M, Warren-Gash C, Guthrie B, Wang HHX, Mercer SW, Sanderson C, McKee M, Troeger C, Ong KL, Checchi F, Perel P, Joseph S, Gibbs HP, Banerjee A, Eggo RM; Centre for the Mathematical Modelling of Infectious Diseases COVID-19 working group. Global, regional, and national estimates of the population at increased risk of severe COVID-19 due to underlying health conditions in 2020: a modelling study. Lancet Glob Health. 2020;8(8):e1003-e1017. doi: 10.1016/S2214-109X(20)30264-3
  37. Pearson CA, Van Schalkwyk C, Foss AM, O’Reilly KM; SACEMA Modelling and Analysis Response Team; CMMID COVID-19 working group, Pulliam JR. Projected early spread of COVID-19 in Africa through 1 June 2020. Euro Surveill. 2020;25(18):2000543. doi:10.2807/1560-7917.ES.2020.25.18.2000543
  38. Jarvis CI, Van Zandvoort K, Gimma A, Prem K; CMMID COVID-19 working group, Klepac P, Rubin GJ, Edmunds WJ. Quantifying the impact of physical distance measures on the transmission of COVID-19 in the UK. BMC Med. 2020 May 7;18(1):124. doi:10.1186/s12916-020-01597-8
  39. Oshitani H; Experts Members of The National COVID-19 Cluster Taskforce at Ministry of Health, Labour and Welfare, Japan. Cluster-based approach to Coronavirus Disease 2019 (COVID-19) response in Japan-February-April 2020. Jpn J Infect Dis. 2020;10.7883/yoken.JJID.2020.363. doi:10.7883/yoken.JJID.2020.363
  40. Clifford S, Pearson CAB, Klepac P, Van Zandvoort K, Quilty BJ; CMMID COVID-19 working group, Eggo RM, Flasche S. Effectiveness of interventions targeting air travellers for delaying local outbreaks of SARS-CoV-2. J Travel Med. 2020;taaa068. doi:10.1093/jtm/taaa068
  41. Kucharski AJ, Klepac P, Conlan AJK, Kissler SM, Tang ML, Fry H, Gog JR, Edmunds WJ; CMMID COVID-19 working group. Effectiveness of isolation, testing, contact tracing, and physical distancing on reducing transmission of SARS-CoV-2 in different settings: a mathematical modelling study. Lancet Infect Dis. 2020;S1473-3099(20)30457-6. doi:10.1016/S1473-3099(20)30457-6.
  42. Davies NG, Kucharski AJ, Eggo RM, Gimma A, Edmunds WJ; Centre for the Mathematical Modelling of Infectious Diseases COVID-19 working group. Effects of non-pharmaceutical interventions on COVID-19 cases, deaths, and demand for hospital services in the UK: a modelling study. Lancet Public Health. 2020;5(7):e375-e385. doi:10.1016/S2468-2667(20)30133-X

Journal correspondence

  1. Endo A. Estimated sensitivity values of SARS-CoV-2 tests from cross-sectional data warrant caution due to unvalidated model assumptions. Clin Infect Dis. 2020;ciaa1656, doi:10.1093/cid/ciaa1656

Conferences

  1. Endo A, Uchida M, Hayashi N, Liu Y, Atkins KE, Kucharski AJ, Funk S. Within and between classroom transmission patterns of seasonal influenza among primary school students in Matsumoto city, Japan. Epidemics 8 Conference, online, Dec. 2021. (Poster)
  2. Endo A, Uchida M, Kucharski AJ, Funk S. Social structure shapes transmission patterns of influenza in schools and households: insights from Matsumoto city, Japan, 2014/15. The 30th Annual Scientific Meeting of the Japan Epidemiological Association, Tokyo, Feb. 2020. (Poster)
  3. Endo A, Uchida M, Kucharski AJ, Funk S. Fine-scale family structure shapes influenza transmission risk in households: Insights from primary schools in Matsumoto city, 2014/15. Epidemics 7 Conference, Charleston, Dec, 2019. (Oral)
  4. Endo A, Funk S, Kucharski AJ. Bias correction methods for test-negatvie design in thepresence of misclassification” The 29th Annual Scientific Meeting of the Japan Epidemiological Association, Feb. 2019. (Oral)
  5. Endo A, Nishiura H. The role of migration in maintaining the transmission ofavian influenza in waterfowl: a multi-site multi-species transmission model along East Asian-Australian Flyway” Epidemics 6 Conference, Sitges, Nov. 2017.15. (Poster)
  6. Endo A, Lessler J, Nishiura H. Multiexponential fitting to coarsely-reported case in-cidence: analysis of heterogeneous transmission in pH1N1 epidemic in Gifu, Japan. Innovative Mathematical Modeling for the Analysis of Infectious Disease Data, Kobe, Oct. 2016. (Oral)
  7. Endo A, Funk S, Kucharski AJ, Nishiura H. Detecting evolution in zoonotic pathogen during the course of an outbreak: a mathematical model based on contact history with wildlife. International Society for Environmental Epidemiology and International Society of Exposure Science Asia Chapter Conference, Sapporo, June 2016. (Oral)
  8. Endo A, Nishiura H. A method for calculating the lifetime risk reduction of infection induced by newly implemented vaccination program. International Conference on Emerging Infectious Diseases, Atlanta, Sept. 2015. (Poster)
  9. Endo A, Nishiura H. Transmission dynamics of vivax malaria in the republic of Korea: effectiveness of anti-malarial mass chemoprophylaxis. Challenges in Malaria Research, Oxford, Sept. 2014. (Poster)

Grants, Awards and Scholarships

  1. Japan Science and Technology Agency: Precursory Research for Embryonic Science and Technology grant (2022)
  2. Japan Society for Mathematical Biology: Early Career Award (2022)
  3. Japan Society for the Promotion of Science: Grants-in-Aid for Scientific Research (KAKENHI) (2022)
  4. Foundation for the Fusion Of Science and Technology: Research Subsidy (2022)
  5. UCLA Asia Pacific Center Faculty Grant Wagatsuma Fellowship Award (co-PI) (2021)
  6. Japan Society for the Promotion of Science Overseas Research Fellowship (2021)
  7. Lnest Grant Taisho Pharmaceutical Award (2020)
  8. The Alan Turing Institute Enrichment Student (2019)
  9. British Council Japan Association Scholar Award (2017)
  10. The Nakajima Foundation Overseas Scholarship (2017)
  11. The Social Medicine Promotion Foundation Araki Award for Student (2016)
  12. The Social Medicine Promotion Foundation Araki Award for Student (2015)
  13. Kyoya Scholars (2011)