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Volume 32, Number 4—April 2026

Research Letter

Acute Febrile Illness Surveillance for Estimating Population Immunity, Dominican Republic, 2021

Eric J. NillesComments to Author , Cecilia Then Paulino, Marietta Vasquez, William Duke, Petr Jarolim, Ronald Skewes Ramm, Adam Kucharski, and Colleen L. Lau
Author affiliation: Harvard Humanitarian Initiative, Cambridge, Massachusetts, USA (E.J. Nilles); Brigham and Women's Hospital, Boston, Massachusetts, USA (E.J. Nilles, P. Jarolim); Ministry of Public Health and Social Assistance, Santo Domingo, Dominican Republic (C.T. Paulino, R.S. Ramm); Yale School of Medicine, New Haven, Connecticut, USA (M. Vazquez); National University Pedro Henríquez Ureña, Santo Domingo, Dominican Republic (W. Duke); Harvard Medical School, Boston (P. Jarolim); London School of Hygiene & Tropical Medicine, London, UK (A. Kucharski); The University of Queensland, Brisbane, Queensland, Australia (C.L. Lau)

Main Article

Figure

Spike antibody responses by surveillance and population survey sampling methods for study of acute febrile illness surveillance similar to household serosurvey for estimating population immunity, Dominican Republic. The study compared SARS-CoV-2 spike antibody data collected during July–October 2021 in the same provinces from a longitudinal AFI surveillance system embedded in routine healthcare settings (“surveillance”) (4), which included routine blood collection for serologic testing; and a multistage, population-representative household serologic survey (“survey”) (1). Participants were matched by age and number of COVID-19 vaccine doses at a 1:5 ratio (surveillance, n = 115; survey, n = 575). A) Histogram showing number of participants by sampling date. B) Density ridge plots illustrating titer distributions by sampling method. Dashed gray lines indicate previously reported spike antibody thresholds associated with >75% protection against symptomatic infection for Mu (101.23), Delta (101.88), BA.1 (102.80), and BA.4/5 (103.06). Threshold for XBB.1 was inferred based on ≈10-fold lower neutralizing response relative to BA.4/5. C) Dot-whisker plots showing estimated proportion of participants with antibody levels corresponding to >75% protection by variant or subvariant (underlying data in Appendix Table 1). Dots indicate point estimates; whiskers indicate 95% CIs. Protection thresholds taken from previously published variant-specific correlates of protection (5). Estimates show percentages of persons above those thresholds (uncertainty in thresholds [reported 95% CIs] not propagated into percentages).

Figure. Spike antibody responses by surveillance and population survey sampling methods for study of acute febrile illness surveillance similar to household serosurvey for estimating population immunity, Dominican Republic. The study compared SARS-CoV-2 spike antibody data collected during July–October 2021 in the same provinces from a longitudinal AFI surveillance system embedded in routine healthcare settings (“surveillance”) (4), which included routine blood collection for serologic testing; and a multistage, population-representative household serologic survey (“survey”) (1). Participants were matched by age and number of COVID-19 vaccine doses at a 1:5 ratio (surveillance, n = 115; survey, n = 575). A) Histogram showing number of participants by sampling date. B) Density ridge plots illustrating titer distributions by sampling method. Dashed gray lines indicate previously reported spike antibody thresholds associated with >75% protection against symptomatic infection for Mu (101.23), Delta (101.88), BA.1 (102.80), and BA.4/5 (103.06). Threshold for XBB.1 was inferred based on ≈10-fold lower neutralizing response relative to BA.4/5. C) Dot-whisker plots showing estimated proportion of participants with antibody levels corresponding to >75% protection by variant or subvariant (underlying data in Appendix Table 1). Dots indicate point estimates; whiskers indicate 95% CIs. Protection thresholds taken from previously published variant-specific correlates of protection (5). Estimates show percentages of persons above those thresholds (uncertainty in thresholds [reported 95% CIs] not propagated into percentages).

Main Article

References
  1. Nilles  EJ, Paulino  CT, de St. Aubin  M, Restrepo  AC, Mayfield  H, Dumas  D, et al. SARS-CoV-2 seroprevalence, cumulative infections, and immunity to symptomatic infection—a multistage national household survey and modelling study, Dominican Republic, June–October 2021. Lancet Reg Health Am. 2022;16:100390. DOIPubMedGoogle Scholar
  2. Barber  RM, Sorensen  RJD, Pigott  DM, Bisignano  C, Carter  A, Amlag  JO, et al. COVID-19 Cumulative Infection Collaborators. Estimating global, regional, and national daily and cumulative infections with SARS-CoV-2 through Nov 14, 2021: a statistical analysis. Lancet. 2022;399:235180. DOIPubMedGoogle Scholar
  3. Hallal  PC, Hartwig  FP, Horta  BL, Silveira  MF, Struchiner  CJ, Vidaletti  LP, et al. SARS-CoV-2 antibody prevalence in Brazil: results from two successive nationwide serological household surveys. Lancet Glob Health. 2020;8:e13908. DOIPubMedGoogle Scholar
  4. Nilles  EJ, de St. Aubin  M, Dumas  D, Duke  W, Etienne  MC, Abdalla  G, et al. Monitoring temporal changes in SARS-CoV-2 spike antibody levels and variant-specific risk for infection, Dominican Republic, March 2021–August 2022. Emerg Infect Dis. 2023;29:72333. DOIPubMedGoogle Scholar
  5. Nilles  EJ, Paulino  CT, de St. Aubin  M, Duke  W, Jarolim  P, Sanchez  IM, et al. Tracking immune correlates of protection for emerging SARS-CoV-2 variants. Lancet Infect Dis. 2023;394:101. DOIPubMedGoogle Scholar
  6. Nilles  EJ, Roberts  K, de St. Aubin  M, Mayfield  H, Restrepo  AC, Garnier  S, et al. Convergence of SARS-CoV-2 spike antibody levels to a population immune setpoint. EBioMedicine. 2024;108:105319. DOIPubMedGoogle Scholar

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