Dataset Information

Using Cure Models to Estimate the Serial Interval of Tuberculosis With Limited Follow-up.

ABSTRACT: Serial interval (SI), defined as the time between symptom onset in an infector and infectee pair, is commonly used to understand infectious diseases transmission. Slow progression to active disease, as well as the small percentage of individuals who will eventually develop active disease, complicate the estimation of the SI for tuberculosis (TB). In this paper, we showed via simulation studies that when there is credible information on the percentage of those who will develop TB disease following infection, a cure model, first introduced by Boag in 1949, should be used to estimate the SI for TB. This model includes a parameter in the likelihood function to account for the study population being composed of those who will have the event of interest and those who will never have the event. We estimated the SI for TB to be approximately 0.5 years for the United States and Canada (January 2002 to December 2006) and approximately 2.0 years for Brazil (March 2008 to June 2012), which might imply a higher occurrence of reinfection TB in a developing country like Brazil.

SUBMITTER: Ma Y

PROVIDER: S-EPMC7731991 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Using Cure Models to Estimate the Serial Interval of Tuberculosis With Limited Follow-up.

Ma Yicheng Y Jenkins Helen E HE Sebastiani Paola P Ellner Jerrold J JJ Jones-López Edward C EC Dietze Reynaldo R Horsburgh Charles R CR White Laura F LF

American journal of epidemiology 20201101 11

Serial interval (SI), defined as the time between symptom onset in an infector and infectee pair, is commonly used to understand infectious diseases transmission. Slow progression to active disease, as well as the small percentage of individuals who will eventually develop active disease, complicate the estimation of the SI for tuberculosis (TB). In this paper, we showed via simulation studies that when there is credible information on the percentage of those who will develop TB disease followin ...[more]

PMID: 32458995

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Project description:BackgroundThe estimation of healthy life years (HLY) by socio-economic status (SES) requires two types of data: the prevalence of activity limitation by SES generally extracted from surveys and mortality rates by SES generally derived from a linkage between the SES information in population databases (census, register) and mortality records. In some situations, no population-wide databases are available to produce mortality rates by SES, and therefore some alternatives must be explored. This paper assesses the validity of calculating HLY by SES using mortality rates derived from a linkage between surveys and mortality records.MethodsTWO SURVEYS WERE CHOSEN TO EXPLORE THE VALIDITY OF THE PROPOSED APPROACH: The Belgian Health Interview Survey (HIS) and the Belgian Survey on Income and Living Conditions (SILC). The mortality follow-up of these surveys were used to calculate HLY by educational level at age 25. These HLY were compared with HLY estimates calculated using the mortality follow-up of the 2001 census. The validity of this approach was evaluated against two criteria. First, the HLY calculated using the census and those calculated using the surveys must not be significantly different. Second, survey-based HLY must show significant social inequalities since such inequalities have been consistently reported with census-based HLY.ResultsBoth criteria were met. First, for each educational category, no statistically significant difference was found when comparing census-based and survey-based HLY estimates. For instance, men in the lowest educational category have shown a HLY of 34 years according to the HIS, and while this figure was 35.5 years according to the census, this difference was not statistically significant. Second, the survey-based HLY have shown a significant social gradient. For instance, men in the highest educational category are expected to live 9.5 more HLY than their counterparts in the lowest educational category based on the HIS estimates, compared with 7.3 HLY based on the census estimates.ConclusionsThis article suggests that using the mortality follow-up of a nationally representative cross-sectional survey is a valid approach to monitor social inequalities in HLY in the absence of population-wide data.

Dataset Information

Using Cure Models to Estimate the Serial Interval of Tuberculosis With Limited Follow-up.

Publications

Using Cure Models to Estimate the Serial Interval of Tuberculosis With Limited Follow-up.

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