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Estimating the population health burden of Lyme disease in Ontario, Canada: a microsimulation modelling approach

Stephen Mac, Gerald A. Evans, Samir N. Patel, Eleanor M. Pullenayegum and Beate Sander
November 16, 2021 9 (4) E1005-E1012; DOI: https://doi.org/10.9778/cmajo.20210024
Stephen Mac
Institute of Health Policy, Management and Evaluation (Mac, Sander), University of Toronto; THETA Collaborative (Mac, Sander), University Health Network, Toronto, Ont.; Department of Medicine (Evans), Queen’s University, Kingston, Ont.; ICES Central (Evans, Sander); Public Health Ontario (Patel, Sander); Department of Laboratory Medicine and Pathobiology (Patel), University of Toronto; The Hospital for Sick Children (SickKids) (Pullenayegum); Dalla Lana School of Public Health (Pullenayegum), University of Toronto, Toronto, Ont.
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Gerald A. Evans
Institute of Health Policy, Management and Evaluation (Mac, Sander), University of Toronto; THETA Collaborative (Mac, Sander), University Health Network, Toronto, Ont.; Department of Medicine (Evans), Queen’s University, Kingston, Ont.; ICES Central (Evans, Sander); Public Health Ontario (Patel, Sander); Department of Laboratory Medicine and Pathobiology (Patel), University of Toronto; The Hospital for Sick Children (SickKids) (Pullenayegum); Dalla Lana School of Public Health (Pullenayegum), University of Toronto, Toronto, Ont.
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Samir N. Patel
Institute of Health Policy, Management and Evaluation (Mac, Sander), University of Toronto; THETA Collaborative (Mac, Sander), University Health Network, Toronto, Ont.; Department of Medicine (Evans), Queen’s University, Kingston, Ont.; ICES Central (Evans, Sander); Public Health Ontario (Patel, Sander); Department of Laboratory Medicine and Pathobiology (Patel), University of Toronto; The Hospital for Sick Children (SickKids) (Pullenayegum); Dalla Lana School of Public Health (Pullenayegum), University of Toronto, Toronto, Ont.
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Eleanor M. Pullenayegum
Institute of Health Policy, Management and Evaluation (Mac, Sander), University of Toronto; THETA Collaborative (Mac, Sander), University Health Network, Toronto, Ont.; Department of Medicine (Evans), Queen’s University, Kingston, Ont.; ICES Central (Evans, Sander); Public Health Ontario (Patel, Sander); Department of Laboratory Medicine and Pathobiology (Patel), University of Toronto; The Hospital for Sick Children (SickKids) (Pullenayegum); Dalla Lana School of Public Health (Pullenayegum), University of Toronto, Toronto, Ont.
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Beate Sander
Institute of Health Policy, Management and Evaluation (Mac, Sander), University of Toronto; THETA Collaborative (Mac, Sander), University Health Network, Toronto, Ont.; Department of Medicine (Evans), Queen’s University, Kingston, Ont.; ICES Central (Evans, Sander); Public Health Ontario (Patel, Sander); Department of Laboratory Medicine and Pathobiology (Patel), University of Toronto; The Hospital for Sick Children (SickKids) (Pullenayegum); Dalla Lana School of Public Health (Pullenayegum), University of Toronto, Toronto, Ont.
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  • Figure 1:
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    Figure 1:

    Model schematic of individual state-transition model. Note: LD = Lyme disease, PTLDS = post-treatment Lyme disease syndrome. Within the states of Lyme disease, individuals can develop sequelae. Individuals can recover to a healthy state from any state of Lyme disease.

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    Figure 2:

    Sensitivity analysis of key parameters on quality-adjusted life-years (QALYs) lost over the lifetime of 100 000 people in Ontario in a seeded deterministic simulation, using a base-case reference of 70.6 QALYs lost because of Lyme disease. Note: AE = adverse event, CI = confidence interval, EM = erythema migrans, IQR = interquartile range, LL = lower limit, PTLDS = post-treatment Lyme disease syndrome, Q1 = quartile 1, Q3 = quartile 3, UL = upper limit. *Lower range is 75% of the recovery parameter (varies by sequelae). †Upper and lower limits of the 95% CI for diagnostic test characteristics (values in Table 1). ‡Q1 values for low values, Q3 values for high values, simultaneously for all sequelae utility values. §Equivalent to having a utility value of a healthy person (varies by age and sex).

Tables

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    Table 1:

    Key parameters and data sources

    ParameterBase case value (range)*Data sources
    Key Lyme disease probability parameters and data sources
    Lyme disease
     Probability of high-risk exposure0.628 (0.471–0.786)†Personal communication, PHO
     LD incidence rates, per 100 000 (varies by age and sex)2.9–13.9 (0.000029–0.000139)‡Nelder et al. 20185
     Probability of clinical diagnosis after EM rash, high-risk exposure area0.583 (0.437–0.729)‡Henry et al. 201215
     Probability of clinical diagnosis after EM rash, low-risk exposure area0.261 (0.196–0.326)†Henry et al. 201215
    Diagnostics
     Sensitivity, early localized0.463 (0.391–0.537)§Waddell et al. 201618
     Sensitivity, early disseminated0.897 (0.783–0.954)§Waddell et al. 201618
     Sensitivity, late disseminated0.994 (0.957–0.999)§Waddell et al. 201618
     Specificity, early localized0.993 (0.983–0.997)§Waddell et al. 201618
     Specificity, early disseminated0.997 (0.984–0.999)§Waddell et al. 201618
     Specificity, late disseminated0.993 (0.985–0.997)§Waddell et al. 201618
     Probability of testing (varies by presence or absence of sequelae)0.402–0.805 (0.30–0.98)†Henry et al. 201215
     Delay in results1–2 wkPHO 201717
    Treatment
     Treatment efficacy
      Erythema migrans0.85 (0.80–1.00)‡Magid et al. 199219
      Arthritic sequelae0.85 (0.40–0.80)‡Liu et al. 198920
      Cardiac sequelae0.90 (0.80–1.00)‡Steere et al. 199321
      Neurologic sequelae0.90 (0.76–0.97)‡Logigian and Steere 199222 Dattwyler et al. 198823 Karlsson et al. 199424
     Oral treatment completion0.90 (0.68–1.00)†Magid et al. 199219
     IV treatment completion0.99 (0.75–1.00)†Magid et al. 199219
     Probability of adverse event, oral0.04 (0.03–0.05)†Shadick et al. 200110
     Probability of adverse event, IV0.06 (0.05–0.08)†Shadick et al. 200110
    Outcomes
     Probability of hospitalization0.05 (0.04–0.06)†Shing et al. 201925
     Length of hospitalization, d7.9 (3.8–12.1)§Shing et al. 201925
     EM rash0.80 (0.60–1.00)†Shadick et al. 200110
     Probability of developing sequelae (varies by LD stage and sex)0.10–0.17 (0.08–0.21)†Unpublished data from cited study26**
     Arthritic sequelae (M, F)0.56–0.63 (0.41–0.76)†Unpublished data from cited study26**
     Cardiac sequelae (F, M)0.43–0.48 (0.29–0.53)†Unpublished data from cited study26**
     Cognitive sequelae (F, M)0.37–0.44 (0.29–0.58)†Unpublished data from cited study26**
     Cranial nerve palsy sequelae (F, M)0.11–0.24 (0.08–0.26)†Unpublished data from cited study26**
     Multiple EM sequelae (M, F)0.22–0.36 (0.16–0.40)†Unpublished data from cited study26**
     Meningitis or polyneuropathy sequelae (F, M)0.06–0.11 (0.12–0.24)†Unpublished data from cited study26**
    Key utility parameters and data sources
    Utilities
     Healthy, stratified by age and sex0.62–0.90 (0.38–0.98)§Guertin et al. 201813
     Arthritic sequelae0.69 (0.51–0.86)¶Shadick et al. 200110
     Cardiac sequelae0.61 (0.38–0.78)¶Shadick et al. 200110
     Cognitive sequelae0.60 (0.37–0.73)¶Shadick et al. 200110
     Erythema migrans0.80 (0.70–0.93)¶Shadick et al. 200110
     Cranial nerve palsy0.61 (0.36–0.81)¶Shadick et al. 200110
     Meningitis or polyneuropathy0.52 (0.27–0.73)¶Shadick et al. 200110
     PTLDS0.54 (0.30–0.70)¶Shadick et al. 200110
     Minor adverse events, disutility0.05 (0.04–0.06)†Eckman et al. 199712
     Major adverse events, disutility0.10 (0.08–0.13)†Eckman et al. 199712
     Oral treatment, disutility0.01 (0.00–0.01)†Eckman et al. 199712
     Intravenous treatment, disutility0.03 (0.02–0.04)†Eckman et al. 199712
    • Note: CI = confidence interval, EM = erythema migrans, F = female, IQR = interquartile range, IV = intravenous, LD = Lyme disease, M = male, PHO = Public Health Ontario, PTLDS = post-treatment Lyme disease syndrome.

    • ↵* Type of range varies by study, as indicated.

    • ↵† Range represents plausible range.

    • ↵‡ Range represents full range.

    • ↵§ Range represents 95% CI.

    • ↵¶ Range represents IQR.

    • ↵** Study authors provided these data.

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    Table 2:

    Base-case results of 100 simulations of 100 000 people in Ontario with lifetime risk of Lyme disease

    OutcomesMean incidence per 100 000 (95% CI)Proportion of mean incidence of total LD infections, %*Median incidence per 100 000 (IQR)Proportion of median incidence of total LD infections, %*
    Total LD infections333 (329–337)334 (320–346)
     Diagnosed cases308 (304–311)92.5308 (294–321)92.2
     Early localized107 (105–109)32.1108 (100–116)32.3
      Clinically diagnosed44 (43–46)13.245 (38–49)13.5
      Laboratory-confirmed63 (62–64)18.963 (58–68)18.9
     Early disseminated (laboratory-confirmed)137 (134–140)41.1137 (129–144)41.0
     Late disseminated (laboratory-confirmed)63 (61–65)18.963 (58–69)18.9
     Undiagnosed cases26 (25–27)7.826 (22–29)7.8
     Reinfections4 (3–4)1.24 (2–5)1.2
    Sequelae
     Early disseminated stage
      Cardiac20 (19–20)6.019 (17–22)5.9
      Cranial nerve palsy8 (7–8)2.49 (6–10)2.7
      Multiple erythema migrans12 (12–13)3.612 (10–15)3.6
      Neurological (meningitis, polyneuropathy)4 (3–4)1.23 (2–5)0.9
     Late disseminated stage
      Arthritic14 (13–15)4.214 (12–16)4.2
      Cognitive9 (9–10)2.79 (7–11)2.7
     All stages
      PTLDS34 (33–35)10.234 (31–37)10.2
    QALYS
     Undiscounted112.6 (109.6–115.4)113.0 (105.7–120.1)
     Discounted (1.5%)84.5 (82.9–86.1)84.6 (78.6–88.8)
    • Note: CI = confidence interval, IQR = interquartile range, LD = Lyme disease, PTLDS = post-treatment Lyme disease syndrome, QALY = quality-adjusted life-year.

    • ↵* Mean and median frequency may not sum up exactly because of rounding.

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Estimating the population health burden of Lyme disease in Ontario, Canada: a microsimulation modelling approach
Stephen Mac, Gerald A. Evans, Samir N. Patel, Eleanor M. Pullenayegum, Beate Sander
Oct 2021, 9 (4) E1005-E1012; DOI: 10.9778/cmajo.20210024

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Estimating the population health burden of Lyme disease in Ontario, Canada: a microsimulation modelling approach
Stephen Mac, Gerald A. Evans, Samir N. Patel, Eleanor M. Pullenayegum, Beate Sander
Oct 2021, 9 (4) E1005-E1012; DOI: 10.9778/cmajo.20210024
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