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Volume 28, Number 4—April 2022

Research

Reassessing Reported Deaths and Estimated Infection Attack Rate during the First 6 Months of the COVID-19 Epidemic, Delhi, India

Margarita Pons-SalortComments to Author , Jacob John, Oliver J. Watson, Nicholas F. Brazeau, Robert Verity, Gagandeep Kang, and Nicholas C. Grassly
Author affiliations: Imperial College London School of Public Health, London, UK (M. Pons-Salort, O.J. Watson, N.F. Brazeau, R. Verity, N.C. Grassly); Christian Medical College, Vellore, India (J. John, G. Kang)

Main Article

Figure 4

Estimated reporting of coronavirus disease deaths, Delhi, India, March 15–September 30, 2020. Violin plots show the posterior distribution of the estimate of death reporting for 3 different values for the assumed age-adjusted IFR, using age-stratified estimates of IFR based on data from mostly high-income countries; 0.21% corresponds to lower bound, 0.39% to the median, and 0.85% to the upper bounds of the IFR based on data documented elsewhere (4). Horizontal black lines indicate the median values of the posterior distributions. IFR, infection-fatality ratio.

Figure 4. Estimated reporting of coronavirus disease deaths, Delhi, India, March 15–September 30, 2020. Violin plots show the posterior distribution of the estimate of death reporting for 3 different values for the assumed age-adjusted IFR, using age-stratified estimates of IFR based on data from mostly high-income countries; 0.21% corresponds to lower bound, 0.39% to the median, and 0.85% to the upper bounds of the IFR based on data documented elsewhere (4). Horizontal black lines indicate the median values of the posterior distributions. IFR, infection-fatality ratio.

Main Article

References
  1. Pulla  P. ‘The epidemic is growing very rapidly’: Indian government adviser fears coronavirus crisis will worsen. Nature. 2020;583:180. DOIPubMedGoogle Scholar
  2. Chatterjee  P. Is India missing COVID-19 deaths? Lancet. 2020;396:657. DOIPubMedGoogle Scholar
  3. Sharma  N, Sharma  P, Basu  S, Saxena  S, Chawla  R, Dushyant  K, et al. The seroprevalence of severe acute respiratory syndrome coronavirus 2 in Delhi, India: a repeated population-based seroepidemiological study. Trans R Soc Trop Med Hyg. 2021;•••:trab109; Epub ahead of print. DOIPubMedGoogle Scholar
  4. Brazeau  NF, Verity  R, Jenks  S, Fu  H, Whittaker  C, Winskill  P, et al. COVID-19 infection fatality ratio: estimates from seroprevalence. London: Imperial College London; 2020 [cited 2021 Mar 23]. https://www.imperial.ac.uk/mrc-global-infectious-disease-analysis/covid-19/report-34-ifr
  5. O’Driscoll  M, Ribeiro Dos Santos  G, Wang  L, Cummings  DAT, Azman  AS, Paireau  J, et al. Age-specific mortality and immunity patterns of SARS-CoV-2. Nature. 2021;590:140–5. DOIPubMedGoogle Scholar
  6. Verity  R, Okell  LC, Dorigatti  I, Winskill  P, Whittaker  C, Imai  N, et al. Estimates of the severity of coronavirus disease 2019: a model-based analysis. [Erratum in Lancet Infect Dis. 2020;20:e116.]. Lancet Infect Dis. 2020;20:669–77. DOIPubMedGoogle Scholar
  7. Levin  AT, Hanage  WP, Owusu-Boaitey  N, Cochran  KB, Walsh  SP, Meyerowitz-Katz  G. Assessing the age specificity of infection fatality rates for COVID-19: systematic review, meta-analysis, and public policy implications. Eur J Epidemiol. 2020;35:1123–38. DOIPubMedGoogle Scholar
  8. COVID19India [cited 2021 Mar 23]. https://www.covid19india.org
  9. Census of India. Population projections for India and states 2011–2036: report of the technical group on population projections. November 2019 [cited 2021 Mar 23]. https://nhm.gov.in/New_Updates_2018/Report_Population_Projection_2019.pdf
  10. Wallinga  J, Lipsitch  M. How generation intervals shape the relationship between growth rates and reproductive numbers. Proc Biol Sci. 2007;274:599–604. DOIPubMedGoogle Scholar
  11. Bi  Q, Wu  Y, Mei  S, Ye  C, Zou  X, Zhang  Z, et al. Epidemiology and transmission of COVID-19 in 391 cases and 1286 of their close contacts in Shenzhen, China: a retrospective cohort study. Lancet Infect Dis. 2020;20:911–9. DOIPubMedGoogle Scholar
  12. Lau  YC, Tsang  TK, Kennedy-Shaffer  L, Kahn  R, Lau  EHY, Chen  D, et al. Joint estimation of generation time and incubation period for coronavirus disease (Covid-19). J Infect Dis. 2021;•••:jiab424; Epub ahead of print. DOIPubMedGoogle Scholar
  13. Nishiura  H, Linton  NM, Akhmetzhanov  AR. Serial interval of novel coronavirus (COVID-19) infections. Int J Infect Dis. 2020;93:284–6. DOIPubMedGoogle Scholar
  14. Xin  H, Li  Y, Wu  P, Li  Z, Lau  EHY, Qin  Y, et al. Estimating the latent period of coronavirus disease 2019 (COVID-19). Clin Infect Dis. 2021;•••:ciab746. DOIPubMedGoogle Scholar
  15. Lauer  SA, Grantz  KH, Bi  Q, Jones  FK, Zheng  Q, Meredith  HR, et al. The incubation period of coronavirus disease 2019 (COVID-19) from publicly reported confirmed cases: estimation and application. Ann Intern Med. 2020;172:577–82. DOIPubMedGoogle Scholar
  16. Xin  H, Wong  JY, Murphy  C, Yeung  A, Taslim Ali  S, Wu  P, et al. The incubation period distribution of coronavirus disease 2019 (COVID-19): a systematic review and meta-analysis. Clin Infect Dis. 2021;73:2344–52. DOIPubMedGoogle Scholar
  17. Oran  DP, Topol  EJ. The proportion of SARS-CoV-2 infections that are asymptomatic : a systematic review. Ann Intern Med. 2021;174:655–62. DOIPubMedGoogle Scholar
  18. Beale  S, Hayward  A, Shallcross  L, Aldridge  RW, Fragaszy  E. A rapid review and meta-analysis of the asymptomatic proportion of PCR-confirmed SARS-CoV-2 infections in community settings. Wellcome Open Res. 2020;5:266. DOIGoogle Scholar
  19. Buitrago-Garcia  D, Egli-Gany  D, Counotte  MJ, Hossmann  S, Imeri  H, Ipekci  AM, et al. Occurrence and transmission potential of asymptomatic and presymptomatic SARS-CoV-2 infections: A living systematic review and meta-analysis. PLoS Med. 2020;17:e1003346. DOIPubMedGoogle Scholar
  20. Gaythorpe  K, Imai  N, Cuomo-Dannenburg  G, Baguelin  M, Bhatia  S, Boonyasiri  A, et al. Symptom progression of COVID-19. Imperial College London. 2020 [cited 2021 Mar 23]. https://www.imperial.ac.uk/mrc-global-infectious-disease-analysis/covid-19/report-8-symptom-progression-covid-19
  21. Knock  ES, Whittles  LK, Lees  JA, Perez-Guzman  PN, Verity  R, FitzJohn  RG, et al. Key epidemiological drivers and impact of interventions in the 2020 SARS-CoV-2 epidemic in England. Sci Transl Med. 2021;13:eabg4262. DOIPubMedGoogle Scholar
  22. Salje  H, Tran Kiem  C, Lefrancq  N, Courtejoie  N, Bosetti  P, Paireau  J, et al. Estimating the burden of SARS-CoV-2 in France. [Erratum in Science. 2020;368:eabd4246]. Science. 2020;369:208–11. DOIPubMedGoogle Scholar
  23. Hay  JA. lazymcmc R package [cited 2021 Mar 23]. https://github.com/jameshay218/lazymcmc
  24. R: a language and environment for statistical computing [cited 2021 Mar 23]. https://www.gbif.org/tool/81287/r-a-language-and-environment-for-statistical-computing
  25. Malani  A, Shah  D, Kang  G, Lobo  GN, Shastri  J, Mohanan  M, et al. Seroprevalence of SARS-CoV-2 in slums versus non-slums in Mumbai, India. Lancet Glob Health. 2021;9:e110–1. DOIPubMedGoogle Scholar
  26. Laxminarayan  R, B  CM, G  VT, Arjun Kumar  KV, Wahl  B, Lewnard  JA. SARS-CoV-2 infection and mortality during the first epidemic wave in Madurai, south India: a prospective, active surveillance study. Lancet Infect Dis. 2021;21:1665–76. DOIPubMedGoogle Scholar
  27. Clark  A, Jit  M, Warren-Gash  C, Guthrie  B, Wang  HHX, Mercer  SW, et al.; 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:e1003–17. DOIPubMedGoogle Scholar
  28. Kumar  P, Chander  B. COVID 19 mortality: Probable role of microbiome to explain disparity. Med Hypotheses. 2020;144:110209. DOIPubMedGoogle Scholar
  29. Walker  PGT, Whittaker  C, Watson  OJ, Baguelin  M, Winskill  P, Hamlet  A, et al. The impact of COVID-19 and strategies for mitigation and suppression in low- and middle-income countries. Science. 2020;369:413–22. DOIPubMedGoogle Scholar
  30. Chandrashekhar  V. Herd immunity? India still has a long way to go, scientists say. Science. 2020;370:513. DOIPubMedGoogle Scholar
  31. Mlcochova  P, Kemp  SA, Dhar  MS, Papa  G, Meng  B, Ferreira  IATM, et al.; Indian SARS-CoV-2 Genomics Consortium (INSACOG); Genotype to Phenotype Japan (G2P-Japan) Consortium; CITIID-NIHR BioResource COVID-19 Collaboration. SARS-CoV-2 B.1.617.2 Delta variant replication and immune evasion. Nature. 2021;599:114–9. DOIPubMedGoogle Scholar

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