Tuberculosis
- Compute % individuals in each category of induration mm
- Bayesian meta-regression to pool RR per mm of induration
- Compute risk weighted prevalence of latent TB infection (LTBI)
- DisMod-MR 2.2
- Inflate prevalence for extra-pulmonary TB
- Divide by risk-weighted LTBI prevalence
- Predict MI ratio-based incidence (
- Divide incidence by risk-weighted LTBI prevalence
- Divide CSMR by risk-weighted LTBI prevalence
- Compute EMR priors based on CSMR, incidence & prevalence
- Calculate prevalence and incidence among the entire population
- Mixed effects regression to predict location-year specific %HIVTB among TB cases
- Apply %HIVTB to TB all forms by location/year
- Age split HIVTB prevalent & incident cases by HIV prevalence
- Calculate proportions of MDR-TB in HIV-TB cases
- Apply MDR-HIV-TB proportions to HIV-TB cases
- Apply super-region level proportions of XDR-TB in MDR-TB cases to all MDR-HIV-TB cases
- Subtract XDR-HIV-TB from MDR-HIV-TB
- Subtract MDR HIVTB from HIVTB
- Subtract HIVTB from TB all forms
- Space-time Gaussian Process Regression
- Calculate proportions of MDR-TB in TB no-HIV cases
- Apply MDR-TB proportions
- Subtract MDRTB no-HIV from TB no-HIV
- Calculate super-region level proportions of XDR- TB among MDR-TB cases
- Apply super-region level proportions of XDR-TB among MDR-TB cases to all MDR-TB cases
- Subtract XDR-TB no-HIV from MDR-TB no-HIV
- Comorbidity correction (COMO)
Turner syndrome
- Comorbidity correction (COMO)
- Dismod-MR 2.1 of total prevalence (incidence = 0, remission = 0)
- Dismod-MR 2.1: estimating birth prevalence
- Meta-analysis of % of conditions with Turner syndrome
- Severity splits
Typhoid & Paratyphoid
- Comorbidity correction (COMO)
- Diagnostic sensitivity adjustment
- DisMod model of incidence
- DisMod model of proportion
- Incidence split
- Metaanalysis of blood culture sensitivity
- Rescaling to sum to 1
- Severity splits
Upper Respiratory Infections
- % mild, moderate, severe
- Age sex splitting
- Comorbidity correction (COMO)
- Converting period to point prevalence
- DisMod-MR 2.1
- Severity splits
Urticaria
- Age-sex splitting
- Comorbidity correction (COMO)
- Dismod-MR 2.1
- Meta-analysis of % mild and severe Urticaria
- Severity splits
Uterine fibroids
- Adjustment from primary code to all code based on Claims data
- Comorbidity correction (COMO)
- Dismod-MR 2.1
- Meta-analysis of % mild, moderate, severe uterine fibroids
- Severity splits
Varicella and herpes zoster
- Assume all varicella cases are mild
- Comorbidity correction (COMO)
- DisMod-MR 2.1
- Incidence data age sex splitting
- Population incidence rate calculation
- Prevalence calculation
- Seroprevalence age sex splitting
Vascular intestinal disorders
- Adjustment from primary code to all code based on Claims data
- Comorbidity correction (COMO)
- Computing excess mortality from available incidence & CSMR data
- DisMod-MR 2.1
Viral skin diseases
- Adjustment from primary code to all code based on Claims data
- Age-sex splitting
- Comorbidity correction (COMO)
- Dismod-MR 2.1
- Meta-analysis of % mild and severe Viral skin diseases
- Severity splits
Visceral leishmaniasis
- Comorbidity correction (COMO)
- ST-GPR
- Age-sex splitting
- Presence and underreporting adjustment
- Sequela split
Vision Impairment
- Comorbidity correction (COMO)
- Crosswalk data points that span multiple vision loss categories
- Crosswalk best-corrected data points from soruces not reporting presenting vision impairment
- Linear regression of prevalence with fixed effects on best-corrected vision impairment, SDI, HAQI, and superregion random effects
- Age-split data points spanning >20 years using superregion pattern
- Dismod-MR 2.1
- Proportionally squeeze sum of causes to fit each severity envelope
Vitamin A deficiency
- DisMod-MR 2.1 (Vit A supplementation coverage)
- DisMod-MR 2.1 (Vit A deficiency)
- DisMod-MR 2.1 (Prevalence of vision loss due to Vit A deficiency)
- Vision loss envelope
- Severity splits
- Subtract from Vit A deficiency (total)
- Comorbidity correction (COMO)
Whooping Cough
- Age-sex splitting
- Assume all whooping cough cases are moderate
- Comorbidity correction (COMO)
- Mixed effects regression
- Prevalence = incidence * duration
Yellow fever
- Asymptomatic estimation
- Comorbidity correction (COMO)
- Mixed effects negative binomial model
- Severity split
- Underreporting correction
Zika
